192 results on '"West TE"'
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2. Distinct classes and subclasses of antibodies to hemolysin co-regulated protein 1 and O-polysaccharide and correlation with clinical characteristics of melioidosis patients
- Author
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Pumpuang, A, Phunpang, R, Ekchariyawat, P, Dulsuk, A, Loupha, S, Kwawong, K, Charoensawat, Y, Thiansukhon, E, Day, NPJ, Burtnick, MN, Brett, PJ, West, TE, and Chantratita, N
- Subjects
Male ,Burkholderia pseudomallei ,lcsh:R ,lcsh:Medicine ,Diagnostic markers ,Antibodies, Bacterial ,Article ,Immunoglobulin A ,Hemolysin Proteins ,Melioidosis ,Polysaccharides ,Immunoglobulin G ,Humans ,Female ,lcsh:Q ,Bacterial infection ,lcsh:Science - Abstract
Melioidosis is a tropical infectious disease caused by Burkholderia pseudomallei that results in high mortality. Hemolysin co-regulated protein 1 (Hcp1) and O-polysaccharide (OPS) are vaccine candidates and potential diagnostic antigens. The correlation of classes/subclasses of antibodies against these antigens with clinical characteristics of melioidosis patients is unknown. Antibodies in plasma samples from melioidosis patients and healthy donors were quantified by ELISA and compared with clinical features. In melioidosis patients, Hcp1 induced high IgG levels. OPS induced high IgG and IgA levels. The area under receiver operating characteristic curve (AUROCC) to discriminate melioidosis cases from healthy donors was highest for anti-Hcp1 IgG (0.92) compared to anti-Hcp1 IgA or IgM. In contrast, AUROCC for anti-OPS for IgG (0.91) and IgA (0.92) were comparable. Anti-Hcp1 IgG1 and anti-OPS IgG2 had the greatest AUROCCs (0.87 and 0.95, respectively) compared to other IgG subclasses for each antigen. Survivors had significantly higher anti-Hcp1 IgG3 levels than non-survivors. Male melioidosis patients with diabetes had higher anti-OPS IgA levels than males without diabetes. Thus, diverse and specific antibody responses are associated with distinct clinical characteristics in melioidosis, confirming the diagnostic utility of these responses and providing new insights into immune mechanisms.
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- 2019
3. Reducing antibiotic treatment duration for ventilator-associated pneumonia (REGARD-VAP): a trial protocol for a randomised clinical trial.
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Mo, Y, West, TE, MacLaren, G, Booraphun, S, Li, AY, Kayastha, G, Lau, YH, Chew, YT, Chetchotisakd, P, Tambyah, PA, Limmathurotsakul, D, Cooper, B, Mo, Y, West, TE, MacLaren, G, Booraphun, S, Li, AY, Kayastha, G, Lau, YH, Chew, YT, Chetchotisakd, P, Tambyah, PA, Limmathurotsakul, D, and Cooper, B
- Abstract
INTRODUCTION: Ventilator-associated pneumonia (VAP) is the most common nosocomial infection in intensive care units (ICUs). Using short-course antibiotics to treat VAP caused by Gram-negative non-fermenting bacteria has been reported to be associated with excess pneumonia recurrences. The "REducinG Antibiotic tReatment Duration for Ventilator-Associated Pneumonia" (REGARD-VAP) trial aims to provide evidence for using a set of reproducible clinical criteria to shorten antibiotic duration for individualised treatment duration of VAP. METHODS AND ANALYSIS: This is a randomised controlled hierarchical non-inferiority-superiority trial being conducted in ICUs across Nepal, Thailand and Singapore. The primary outcome is a composite endpoint of death and pneumonia recurrence at day 60. Secondary outcomes include ventilator-associated events, multidrug-resistant organism infection or colonisation, total duration of antibiotic exposure, mechanical ventilation and hospitalisation. Adult patients who satisfy the US Centers for Disease Control and Prevention National Healthcare Safety Network VAP diagnostic criteria are enrolled. Participants are assessed daily until fever subsides for >48 hours and have stable blood pressure, then randomised to a short duration treatment strategy or a standard-of-care duration arm. Antibiotics may be stopped as early as day 3 if respiratory cultures are negative, and day 5 if respiratory cultures are positive in the short-course arm. Participants receiving standard-of-care will receive antibiotics for at least 8 days. Study participants are followed for 60 days after enrolment. An estimated 460 patients will be required to achieve 80% power to determine non-inferiority with a margin of 12%. All outcomes are compared by absolute risk differences. The conclusion of non-inferiority, and subsequently superiority, will be based on unadjusted and adjusted analyses in both the intention-to-treat and per-protocol populations. ETHICS AND DISSEMINATION
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- 2021
4. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study
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Rudd, KE, Johnson, SC, Agesa, KM, Shackelford, KA, Tsoi, D, Kievlan, DR, Colombara, DV, Ikuta, KS, Kissoon, N, Finfer, S, Fleischmann-Struzek, C, Machado, FR, Reinhart, KK, Rowan, K, Seymour, CW, Watson, RS, West, TE, Marinho, F, Hay, SI, Lozano, R, Lopez, AD, Angus, DC, Murray, CJL, Naghavi, M, Rudd, KE, Johnson, SC, Agesa, KM, Shackelford, KA, Tsoi, D, Kievlan, DR, Colombara, DV, Ikuta, KS, Kissoon, N, Finfer, S, Fleischmann-Struzek, C, Machado, FR, Reinhart, KK, Rowan, K, Seymour, CW, Watson, RS, West, TE, Marinho, F, Hay, SI, Lozano, R, Lopez, AD, Angus, DC, Murray, CJL, and Naghavi, M
- Abstract
BACKGROUND: Sepsis is life-threatening organ dysfunction due to a dysregulated host response to infection. It is considered a major cause of health loss, but data for the global burden of sepsis are limited. As a syndrome caused by underlying infection, sepsis is not part of standard Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimates. Accurate estimates are important to inform and monitor health policy interventions, allocation of resources, and clinical treatment initiatives. We estimated the global, regional, and national incidence of sepsis and mortality from this disorder using data from GBD 2017. METHODS: We used multiple cause-of-death data from 109 million individual death records to calculate mortality related to sepsis among each of the 282 underlying causes of death in GBD 2017. The percentage of sepsis-related deaths by underlying GBD cause in each location worldwide was modelled using mixed-effects linear regression. Sepsis-related mortality for each age group, sex, location, GBD cause, and year (1990-2017) was estimated by applying modelled cause-specific fractions to GBD 2017 cause-of-death estimates. We used data for 8·7 million individual hospital records to calculate in-hospital sepsis-associated case-fatality, stratified by underlying GBD cause. In-hospital sepsis-associated case-fatality was modelled for each location using linear regression, and sepsis incidence was estimated by applying modelled case-fatality to sepsis-related mortality estimates. FINDINGS: In 2017, an estimated 48·9 million (95% uncertainty interval [UI] 38·9-62·9) incident cases of sepsis were recorded worldwide and 11·0 million (10·1-12·0) sepsis-related deaths were reported, representing 19·7% (18·2-21·4) of all global deaths. Age-standardised sepsis incidence fell by 37·0% (95% UI 11·8-54·5) and mortality decreased by 52·8% (47·7-57·5) from 1990 to 2017. Sepsis incidence and mortality varied substantially across regions, with the highest burden in s
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- 2020
5. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Kyu, Hh, Abate, D, Abate, Kh, Abay, Sm, Abbafati, C, Abbasi, N, Abbastabar, H, Abd-Allah, F, Abdela, J, Abdelalim, A, Abdollahpour, I, Abdulkader, Rs, Abebe, M, Abebe, Z, Abil, Oz, Aboyans, V, Abrham, Ar, Abu-Raddad, Lj, Abu-Rmeileh, Nme, Accrombessi, Mmk, Acharya, D, Acharya, P, Ackerman, In, Adamu, Aa, Adebayo, Om, Adekanmbi, V, Ademi, Z, Adetokunboh, Oo, Adib, Mg, Adsuar, Jc, Afanvi, Ka, Afarideh, M, Afshin, A, Agarwal, G, Agesa, Km, Aggarwal, R, Aghayan, Sa, Agrawal, A, Ahmadi, A, Ahmadi, M, Ahmadieh, H, Ahmed, Mb, Ahmed, S, Aichour, An, Aichour, I, Aichour, Mte, Akinyemiju, T, Akseer, N, Al-Aly, Z, Al-Eyadhy, A, Al-Mekhlafi, Hm, Al-Raddadi, Rm, Alahdab, F, Alam, K, Alam, T, Alashi, A, Alavian, Sm, Alene, Ka, Alijanzadeh, M, Alizadeh-Navaei, R, Aljunid, Sm, Alkerwi, A, Alla, F, Allebeck, P, Alonso, J, Alsharif, U, Altirkawi, K, Alvis-Guzman, N, Aminde, Ln, Amini, E, Amiresmaili, M, Ammar, W, Amoako, Ya, Anber, Nh, Andrei, Cl, Androudi, S, Animut, Md, Anjomshoa, M, Ansha, Mg, Antonio, Cat, Anwari, P, Arabloo, J, Aremu, O, Ärnlöv, J, Arora, A, Arora, M, Artaman, A, Aryal, Kk, Asayesh, H, Ataro, Z, Ausloos, M, Avila-Burgos, L, Avokpaho, Efga, Awasthi, A, Ayala, Quintanilla, Ayer, R, Azzopardi, Ps, Babazadeh, A, Badali, H, Balakrishnan, K, Bali, Ag, Banach, M, Banoub, Jam, Barac, A, Barboza, Ma, Barker-Collo, Sl, Bärnighausen, Tw, Barquera, S, Barrero, Lh, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Behzadifar, M, Bekele, Bb, Bekru, Et, Belachew, Ab, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bensenor, Im, Berhane, A, Bernabe, E, Bernstein, Rs, Beuran, M, Beyranvand, T, Bhala, N, Bhatt, S, Bhaumik, S, Bhutta, Za, Biadgo, B, Biehl, Mh, Bijani, A, Bikbov, B, Bilano, V, Bililign, N, Bin, Sayeed, Bisanzio, D, Bjørge, T, Bleyer, A, Bobasa, Em, Bou-Orm, Ir, Boufous, S, Bourne, R, Brady, Oj, Brant, Lc, Brayne, C, Brazinova, A, Breitborde, Njk, Brenner, H, Briant, Ps, Briko, An, Britton, G, Brugha, T, Buchbinder, R, Busse, R, Butt, Za, Cahuana-Hurtado, L, Campuzano, Rincon, Cano, J, Cárdenas, R, Carrero, Jj, Carter, A, Carvalho, F, Castañeda-Orjuela, Ca, Castillo, Rivas, J, Castro, F, Catalá-López, F, Cercy, Km, Cerin, E, Chaiah, Y, Chang, Jc, Charlson, Fj, Chattu, Vk, Chiang, Pp, Chitheer, A, Choi, Jj, Christensen, H, Christopher, Dj, Chung, Sc, Cicuttini, Fm, Cirillo, Massimo, Collado-Mateo, D, Cooper, C, Cortesi, Pa, Cortinovis, M, Cousin, E, Criqui, Mh, Cromwell, Ea, Cross, M, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dandona, L, Dandona, R, Dargan, Pi, Daryani, A, Das, Gupta, Das, R, Neves, J, Dasa, Tt, Davitoiu, Dv, De, La, Hoz, Fp, Leo, De, D, De, Neve, Jw, Steur, De, H, Degefa, Mg, Degenhardt, L, Deiparine, S, Demoz, Gt, Denova-Gutiérrez, E, Deribe, K, Dervenis, N, Des, Jarlais, Dey, S, Dharmaratne, Sd, Dhimal, M, Dinberu, Mt, Dirac, Ma, Djalalinia, S, Doan, L, Dokova, K, Doku, Dt, Dorsey, Er, Doyle, Ke, Driscoll, Tr, Dubey, M, Dubljanin, E, Duken, Ee, Duncan, Bb, Duraes, Ar, Ebrahimi, H, Ebrahimpour, S, Echko, Mm, Edessa, D, Edvardsson, D, Effiong, A, Eggen, Ae, Ehrlich, Jr, Bcheraoui, El, C, El-Khatib, Z, Elyazar, Irf, Enayati, A, Endalifer, Ml, Endries, Ay, Er, B, Erskine, He, Eskandarieh, S, Esteghamati, A, Esteghamati, S, Fakhim, H, Faramarzi, M, Fareed, M, Farhadi, F, Farid, Ta, Farinha, Cses, Farioli, A, Faro, A, Farzadfar, F, Fazaeli, Aa, Feigin, Vl, Fentahun, N, Fereshtehnejad, Sm, Fernandes, E, Fernandes, Jc, Ferrari, Aj, Ferreira, Ml, Filip, I, Fischer, F, Fitzmaurice, C, Foigt, Na, Foreman, Kj, Frank, Td, Fukumoto, T, Fullman, N, Fürst, T, Furtado, Jm, Gakidou, E, Gall, S, Gallus, S, Ganji, M, Garcia-Basteiro, Al, Gardner, Wm, Gebre, Ak, Gebremedhin, At, Gebremichael, Tg, Gelano, Tf, Geleijnse, Jm, Genova-Maleras, R, Geramo, Ycd, Gething, Pw, Gezae, Ke, Ghadami, Mr, Ghadiri, K, Ghasemi-Kasman, M, Ghimire, M, Ghoshal, Ag, Gill, Ps, Gill, Tk, Ginawi, Ia, Giussani, G, Gnedovskaya, Ev, Goldberg, Em, Goli, S, Gómez-Dantés, H, Gona, Pn, Gopalani, Sv, Gorman, Tm, Goulart, Ac, Goulart, Bng, Grada, A, Grosso, G, Gugnani, Hc, Guillemin, F, Guo, Y, Gupta, Pc, Gupta, R, Gupta, T, Gutiérrez, Ra, Gyawali, B, Haagsma, Ja, Hachinski, V, Hafezi-Nejad, N, Haghparast, Bidgoli, Hagos, Tb, Hailegiyorgis, Tt, Haj-Mirzaian, A, Hamadeh, Rr, Hamidi, S, Handal, Aj, Hankey, Gj, Hao, Y, Harb, Hl, Harikrishnan, S, Haririan, H, Haro, Jm, Hassankhani, H, Hassen, Hy, Havmoeller, R, Hay, Rj, Hay, Si, Hedayatizadeh-Omran, A, Heibati, B, Hendrie, D, Henok, A, Heredia-Pi, I, Herteliu, C, Heydarpour, F, Heydarpour, P, Hibstu, Dt, Hoek, Hw, Hoffman, Hj, Hole, Mk, Homaie, Rad, E, Hoogar, P, Hosgood, Hd, Hosseini, Sm, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hotez, Pj, Hoy, Dg, Hsairi, M, Htet, As, Huang, Jj, Iburg, Km, Ikeda, Ct, Ilesanmi, Os, Irvani, Ssn, Irvine, Cms, Islam, Sms, Islami, F, Jacobsen, Kh, Jahangiry, L, Jahanmehr, N, Jain, Sk, Jakovljevic, M, James, Sl, Jayatilleke, Au, Jeemon, P, Jha, Rp, Jha, V, Js, Ji, Johnson, Co, Jonas, Jb, Jonnagaddala, J, Jorjoran, Shushtari, Z, Joshi, A, Jozwiak, Jj, Jungari, Sb, Jürisson, M, Kabir, Z, Kadel, R, Kahsay, A, Kalani, R, Kanchan, T, Kar, C, Karami, M, Karami, Matin, B, Karch, A, Karema, C, Karimi, N, Karimi, Sm, Kasaeian, A, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Kaul, A, Kawakami, N, Kazemi, Z, Karyani, Ak, Keighobadi, Mm, Keiyoro, Pn, Kemmer, L, Kemp, Gr, Kengne, Ap, Keren, A, Khader, Ys, Khafaei, B, Khafaie, Ma, Khajavi, A, Khalid, N, Khalil, Ia, Khan, Ea, Khan, Ms, Khan, Ma, Khang, Yh, Khater, Mm, Khazaei, M, Khoja, At, Khosravi, A, Khosravi, Mh, Kiadaliri, Aa, Kidanemariam, Zt, Kiirithio, Dn, Kim, Ci, Kim, D, Kim, Ye, Kim, Yj, Kimokoti, Rw, Kinfu, Y, Kisa, A, Kissimova-Skarbek, K, Knudsen, Aks, Kocarnik, Jm, Kochhar, S, Kokubo, Y, Kolola, T, Kopec, Ja, Kosen, S, Kotsakis, Ga, Koul, Pa, Koyanagi, A, Krishan, K, Krishnaswami, S, Krohn, Kj, Kuate, Defo, Kucuk, B, Bicer, B, Kumar, Ga, Kumar, M, Kuzin, I, Lad, Dp, Lad, Sd, Lafranconi, A, Lalloo, R, Lallukka, T, Lami, Fh, Lang, Jj, Langan, Sm, Lansingh, Vc, Latifi, A, Lau, Km, Lazarus, Jv, Leasher, Jl, Ledesma, Jr, Lee, Ph, Leigh, J, Leili, M, Leshargie, Ct, Leung, J, Levi, M, Lewycka, S, Li, S, Li, Y, Liang, X, Liao, Y, Liben, Ml, Lim, Ll, Lim, Ss, Limenih, Ma, Linn, S, Liu, S, Looker, Kj, Lopez, Ad, Lorkowski, S, Lotufo, Pa, Lozano, R, Lucas, Tcd, Lunevicius, R, Lyons, Ra, Ma, S, Macarayan, Erk, Mackay, Mt, Maddison, Er, Madotto, F, Maghavani, Dp, Mai, Ht, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malta, Dc, Mamun, Aa, Manda, Al, Manguerra, H, Mansournia, Ma, Mantilla, Herrera, Mantovani, Lg, Maravilla, Jc, Marcenes, W, Marks, A, Martins-Melo, Fr, Martopullo, I, März, W, Marzan, Mb, Massano, J, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mazidi, M, Mcalinden, C, Mcgrath, Jj, Mckee, M, Mcmahon, Bj, Mehata, S, Mehrotra, R, Mehta, Km, Mehta, V, Mejia-Rodriguez, F, Mekonen, T, Melese, A, Melku, M, Memiah, Ptn, Memish, Za, Mendoza, W, Mengistu, G, Mensah, Ga, Mereta, St, Meretoja, A, Meretoja, Tj, Mestrovic, T, Miazgowski, B, Miazgowski, T, Millear, Ai, Miller, Tr, Mini, Gk, Mirarefin, M, Mirica, A, Mirrakhimov, Em, Misganaw, At, Mitchell, Pb, Mitiku, H, Moazen, B, Mohajer, B, Mohammad, Ka, Mohammadi, M, Mohammadifard, N, Mohammadnia-Afrouzi, M, Mohammed, Ma, Mohammed, S, Mohebi, F, Mokdad, Ah, Molokhia, M, Monasta, L, Montañez, Jc, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Lakeh, M, Moradinazar, M, Moraga, P, Morawska, L, Moreno, Velásquez, I, Morgado-Da-Costa, J, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Mruts, Kb, Muche, Aa, Muchie, Kf, Mueller, Uo, Muhammed, Os, Mukhopadhyay, S, Muller, K, Mumford, Je, Murthy, Gvs, Musa, Ki, Mustafa, G, Nabhan, Af, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Nahvijou, A, Naik, G, Najafi, F, Nam, Hs, Nangia, V, Nansseu, Jr, Neamati, N, Negoi, I, Negoi, Ri, Neupane, S, Newton, Crj, Ngunjiri, Jw, Nguyen, Aq, Nguyen, G, Nguyen, Ht, Nguyen, Hlt, Nguyen, Lh, Nguyen, M, Nguyen, Nb, Nguyen, Sh, Nichols, E, Ningrum, Dna, Nixon, Mr, Nomura, S, Noroozi, M, Norrving, B, Noubiap, Jj, Nouri, Hr, Shiadeh, Mn, Nowroozi, Mr, Nsoesie, Eo, Nyasulu, Ps, Odell, Cm, Ofori-Asenso, R, Ogbo, Fa, Ih, Oh, Oladimeji, O, Olagunju, At, Olagunju, To, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Oren, E, Ortiz, A, Ota, E, Otstavnov, Ss, Øverland, S, Owolabi, Mo, P, A, M, Pacella, R, Pakhare, Ap, Pakpour, Ah, Pana, A, Panda-Jonas, S, Park, Ek, Park, J, Parry, Cdh, Parsian, H, Pasdar, Y, Patel, S, Patil, St, Patle, A, Patton, Gc, Paturi, Vr, Paudel, D, Paulson, Kr, Pearce, N, Pereira, A, Pereira, Dm, Perico, N, Pesudovs, K, Petzold, M, Pham, Hq, Phillips, Mr, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pirsaheb, M, Pishgar, F, Plana-Ripoll, O, Polinder, S, Popova, S, Postma, Mj, Pourshams, A, Poustchi, H, Prabhakaran, D, Prakash, S, Prakash, V, Prasad, N, Purcell, Ca, Qorbani, M, Quistberg, Da, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahimi, K, Rahimi, Z, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rahman, Mhu, Rahman, Ma, Rahman, Su, Rai, Rk, Rajati, F, Ranjan, P, Rao, Pc, Rasella, D, Rawaf, Dl, Rawaf, S, Reddy, Ks, Reiner, Rc, Reitsma, Mb, Remuzzi, G, Renzaho, Amn, Resnikoff, S, Rezaei, S, Rezai, Ms, Ribeiro, Alp, Roberts, Nls, Robinson, Sr, Roever, L, Ronfani, L, Roshandel, G, Rostami, A, Roth, Ga, Rothenbacher, D, Rubagotti, E, Sachdev, Ps, Sadat, N, Sadeghi, E, Saeedi, Moghaddam, S, Safari, H, Safari, Y, Safari-Faramani, R, Safdarian, M, Safi, S, Safiri, S, Sagar, R, Sahebkar, A, Sahraian, Ma, Sajadi, Hs, Salam, N, Salama, Js, Salamati, P, Saleem, Z, Salimi, Y, Salimzadeh, H, Salomon, Ja, Salvi, Ss, Salz, I, Samy, Am, Sanabria, J, Sanchez-Niño, Md, Santomauro, Df, Santos, Is, Santos, Jv, Santric, Milicevic, Sao, Mm, Jose, Bp, Sardana, M, Sarker, Ar, Sarmiento-Suárez, R, Sarrafzadegan, N, Sartorius, B, Sarvi, S, Sathian, B, Satpathy, M, Sawant, Ar, Sawhney, M, Saxena, S, Schaeffner, E, Schmidt, Mi, Schneider, Ijc, Schutte, Ae, Schwebel, Dc, Schwendicke, F, Scott, Jg, Sekerija, M, Sepanlou, Sg, Serván-Mori, E, Seyedmousavi, S, Shabaninejad, H, 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Ngunjiri, Josephine W, Nguyen, Anh Quynh, Nguyen, Grant, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Minh, Nguyen, Nam Ba, Nguyen, Son Hoang, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nixon, Molly R, Nomura, Shuhei, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Odell, Christopher M, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L, Ong, Sok King, Oren, Eyal, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, P A, Mahesh, Pacella, Rosana, Pakhare, Abhijit P, Pakpour, Amir H, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Eun-Kee, Park, Jame, Parry, Charles D H, Parsian, Hadi, Pasdar, Yahya, Patel, Shanti, Patil, Snehal T, Patle, Ajay, Patton, George C, Paturi, Vishnupriya Rao, Paudel, Deepak, Paulson, Katherine R, Pearce, Neil, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Pham, Hai Quang, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Piradov, Michael A, Pirsaheb, Meghdad, Pishgar, Farhad, Plana-Ripoll, Oleguer, Polinder, Suzanne, Popova, Svetlana, Postma, Maarten J, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prakash, V., Prasad, Narayan, Purcell, Caroline A, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi, Zohreh, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Ranjan, Prabhat, Rao, Puja C, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Reddy, K Srinath, Reiner, Robert C, Reitsma, Marissa Bettay, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio Luiz P, Roberts, Nicholas L S, Robinson, Stephen R, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A, Rothenbacher, Dietrich, Rubagotti, Enrico, Sachdev, Perminder S, Sadat, Nafi, Sadeghi, Ehsan, Saeedi Moghaddam, Sahar, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saleem, Zikria, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A, Salvi, Sundeep Santosh, Salz, Inbal, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Santomauro, Damian Francesco, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarmiento-Suárez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J C, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A, Shaikh, Masood Ali, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokoohinia, Yalda, Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G, Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Sliwa, Karen, Smith, David L, Smith, Mari, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Sorensen, Reed J D, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Starodubov, Vladimir I, Stein, Dan J, Steiner, Caitlyn, Steiner, Timothy J, Stokes, Mark A, Stovner, Lars Jacob, Subart, Michelle L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Tandon, Nikhil, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Taylor, Hugh R, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekelemedhin, Shishay Wahdey, Tekle, Merhawi Gebremedhin, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Tessema, Belay, Teweldemedhin, Mebrahtu, Thankappan, Kavumpurathu Raman, Theis, Andrew, Thirunavukkarasu, Sathish, Thomas, Nihal, Tilahun, Binyam, To, Quyen G, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E, Tortajada-Girbés, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Troeger, Christopher E, Tsadik, Afewerki Gebremeskel, Tsoi, Derrick, Tudor Car, Lorainne, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Undurraga, Eduardo A, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Williams, Hywel C, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zandian, Hamed, Zar, Heather J, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zipkin, Ben, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna, and Murray, Christopher J L
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Male ,Health Status ,health statu ,HALE ,mortality rate ,communicable disease ,DALYs ,Global Burden of Disease ,Risk Factors ,Prevalence ,Medicine and Health Sciences ,Singapore ,OUTCOMES ,disability-adjusted life year ,international cooperation ,Medicine (all) ,11 Medical And Health Sciences ,Central African Republic ,newborn disease ,IRON-DEFICIENCY ,AIDS ,priority journal ,Bahrain ,disease severity ,Female ,Quality-Adjusted Life Years ,cerebrovascular accident ,Ukraine ,Life Sciences & Biomedicine ,INTERVENTIONS ,Slovakia ,DISORDERS ,Burundi ,WEIGHTS ,GBD 2017 DALYs and HALE Collaborators ,Communicable Diseases ,Article ,STYLE ,Medicine, General & Internal ,Life Expectancy ,General & Internal Medicine ,Humans ,Disabled Persons ,human ,Healthy Lifestyle ,HALE, DALYs, global burden of disease ,Mortality ,Aged ,Science & Technology ,Mortality, Premature ,HIV ,ischemic heart disease ,major clinical study ,PREVENTION ,non communicable disease ,GBD, disability-adjusted life-years ,age ,sex factor ,Socioeconomic Factors ,Algeria ,Federation of Bosnia and Herzegovina ,lower respiratory tract infection ,Wounds and Injuries ,GENDER ,Human medicine ,trend study ,chronic obstructive lung disease - Abstract
Background How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Sociodemographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7.4 years (95% uncertainty interval 74-7.8), from 65.6 years (65.3-65- 8) in 1990 to 73.0 years (72.7-73.3) in 2017. The increase in years of life varied from 5.1 years (5.0-5.3) in high SDI countries to 12.0 years (11.3-12.8) in low SDI countries. Of the additional years of life expected at birth, 26.3% (20.1-33.1) were expected to be spent in poor health in high SDI countries compared with 11.7% (8.8-15.1) in low-middle SDI countries. HALE at birth increased by 6.3 years (5.9-6.7), from 57.0 years (54.6-59.1) in 1990 to 63.3 years (60.5-65.7) in 2017. The increase varied from 3.8 years (3.4-4.1) in high SDI countries to 10.5 years (9.8-11.2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1.0 year (0.4-1.7) in Saint Vincent and the Grenadines (62.4 years [59.9-64.7] in 1990 to 63.5 years [60.9-65.8] in 2017) to 23.7 years (21.9-25.6) in Eritrea (30.7 years [28.9-32.2] in 1990 to 54.4 years [51.5-57.1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1.4 years (0.6-2.3) in Algeria to 11.9 years (10.9-12.9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75.8 years [72.4-78.7]) and males (72.6 years [69 " 8-75.0]) and the lowest estimates were in Central African Republic (47.0 years [43.7-50.2] for females and 42.8 years [40.1-45.6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41.3% (38.8-43.5) for communicable diseases and by 49"8% (47.9-51.6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40.1% (36.8-43.0), although age-standardised DALY rates decreased by 18.1% (16.0-20.2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low S DI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
6. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
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Troeger, C, Blacker, BF, Khalil, IA, Rao, PC, Cao, S, Zimsen, SRM, Albertson, S, Stanaway, JD, Deshpande, A, Farag, T, Forouzanfar, MH, Abebe, Z, Adetifa, IMO, Adhikari, TB, Akibu, M, Lami, FH, Al-Eyadhy, A, Alvis-Guzman, N, Amare, AT, Amoako, YA, Antonio, CAT, Aremu, O, Asfaw, ET, Asgedom, SW, Atey, TM, Attia, EF, Avokpaho, EFGA, Ayele, HT, Ayuk, TB, Balakrishnan, K, Barac, A, Bassat, Q, Behzadifar, M, Bhaumik, S, Bhutta, ZA, Bijani, A, Brauer, M, Brown, A, Camargos, PAM, Castaneda-Orjuela, CA, Colombara, D, Conti, S, Dadi, AF, Dandona, L, Dandona, R, Do, HP, Dubljanin, E, Edessa, D, Elkout, H, Endries, AY, Fijabi, DO, Foreman, KJ, Fullman, N, Garcia-Basteiro, AL, Gessner, BD, Gething, PW, Gupta, R, Gupta, T, Hailu, GB, Hassen, HY, Hedayati, MT, Heidari, M, Hibstu, DT, Horita, N, Ilesanmi, OS, Jakovljevic, MB, Jamal, AA, Kahsay, A, Kasaeian, A, Kassa, DH, Khader, YS, Khan, EA, Khan, MN, Khang, Y-H, Kim, YJ, Kissoon, N, Knibbs, LD, Kochhar, S, Koul, PA, Kumar, GA, Lodha, R, Razek, HM, Malta, DC, Mathew, JL, Mengistu, DT, Mezgebe, HB, Mohammad, KA, Mohammed, AM, Momeniha, F, Murthy, S, Nguyen, CT, Nielsen, KR, Ningrum, DNA, Nirayo, YL, Oren, E, Ortiz, JR, Mahesh, PA, Postma, MJ, Qorbani, M, Quansah, R, Rai, RK, Rana, SM, Ranabhat, CL, Ray, SE, Rezai, MS, Ruhago, GM, Safiri, S, Salomon, JA, Sartorius, B, Savic, M, Sawhney, M, She, J, Sheikh, A, Shiferaw, MS, Shigematsu, M, Singh, JA, Somayaji, R, Sufiyan, MB, Taffere, GR, Temsah, M-H, Thompson, MJ, Tobe-Gai, R, Topor-Madry, R, Tran, BX, Tran, TT, Tuem, KB, Ukwaja, KN, Vollset, SE, Walson, JL, Weldegebreal, F, Werdecker, A, West, TE, Yonemoto, N, Zaki, MES, Zhou, L, Zodpey, S, Vos, T, Lim, SS, Naghavi, M, Murray, CJL, Mokdad, AH, Hay, SI, Jr, RRC, and Infecti, GBDLR
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Adult ,Aged, 80 and over ,Male ,Adolescent ,Incidence ,Infant, Newborn ,Infant ,Respiratory Tract Infections/epidemiology ,Biostatistics ,Middle Aged ,Global Health ,Survival Analysis ,Young Adult ,Cost of Illness ,Risk Factors ,Child, Preschool ,Prevalence ,Humans ,Female ,Topography, Medical ,Virus Diseases/epidemiology ,Child ,Epidemiologic Methods ,Bacterial Infections/epidemiology ,Aged - Abstract
Background Lower respiratory infections are a leading cause of morbidity and mortality around the world. The Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016, provides an up-to-date analysis of the burden of lower respiratory infections in 195 countries. This study assesses cases, deaths, and aetiologies spanning the past 26 years and shows how the burden of lower respiratory infection has changed in people of all ages. Methods We used three separate modelling strategies for lower respiratory infections in GBD 2016: a Bayesian hierarchical ensemble modelling platform (Cause of Death Ensemble model), which uses vital registration, verbal autopsy data, and surveillance system data to predict mortality due to lower respiratory infections; a compartmental meta-regression tool (DisMod-MR), which uses scientific literature, population representative surveys, and healthcare data to predict incidence, prevalence, and mortality; and modelling of counterfactual estimates of the population attributable fraction of lower respiratory infection episodes due to Streptococcus pneumoniae, Haemophilus influenzae type b, influenza, and respiratory syncytial virus. We calculated each modelled estimate for each age, sex, year, and location. We modelled the exposure level in a population for a given risk factor using DisMod-MR and a spatiotemporal Gaussian process regression, and assessed the effectiveness of targeted interventions for each risk factor in children younger than 5 years. We also did a decomposition analysis of the change in LRI deaths from 2000–16 using the risk factors associated with LRI in GBD 2016. Findings In 2016, lower respiratory infections caused 652 572 deaths (95% uncertainty interval [UI] 586 475–720 612) in children younger than 5 years (under-5s), 1 080 958 deaths (943 749–1 170 638) in adults older than 70 years, and 2 377 697 deaths (2 145 584–2 512 809) in people of all ages, worldwide. Streptococcus pneumoniae was the leading cause of lower respiratory infection morbidity and mortality globally, contributing to more deaths than all other aetiologies combined in 2016 (1 189 937 deaths, 95% UI 690 445–1 770 660). Childhood wasting remains the leading risk factor for lower respiratory infection mortality among children younger than 5 years, responsible for 61·4% of lower respiratory infection deaths in 2016 (95% UI 45·7–69·6). Interventions to improve wasting, household air pollution, ambient particulate matter pollution, and expanded antibiotic use could avert one under-5 death due to lower respiratory infection for every 4000 children treated in the countries with the highest lower respiratory infection burden. Interpretation Our findings show substantial progress in the reduction of lower respiratory infection burden, but this progress has not been equal across locations, has been driven by decreases in several primary risk factors, and might require more effort among elderly adults. By highlighting regions and populations with the highest burden, and the risk factors that could have the greatest effect, funders, policy makers, and programme implementers can more effectively reduce lower respiratory infections among the world’s most susceptible populations.
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- 2019
7. OEDGE modeling of far-SOL tungsten impurity sources and screening in WEST
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J.B. Maeker, J.H. Nichols, D.C. Donovan, A. Grosjean, J. Gunn, N. Fedorczak, C. Guillemaut, C.C. Klepper, E.A. Unterberg, D.C. Easley, and WEST Team
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WEST ,Tungsten impurity modeling ,Scrape-off layer ,Impurity screening ,Far-SOL ,Nuclear engineering. Atomic power ,TK9001-9401 - Abstract
The plasma background and impurity transport in the scrape-off layer (SOL) of the WEST tokamak are modeled for three discharges over a Psep power scan ranging between 1.5 and 2.35 MW. An extended modeling grid is used to investigate far-SOL sourcing from the WEST baffle and lower divertor. Divertor Langmuir probe data at the targets and upstream data from reciprocating Langmuir probes and interferometry/reflectometry is used to create a simulated background plasma with the OSM and EIRENE codes. W-I spectroscopic data from WEST at the lower divertor and baffle is used to estimate the sputtered W flux as an input to the impurity transport code DIVIMP. A potential mechanism for far-SOL impurities from the baffle to transport into the near-SOL is proposed and discussed in terms of the model’s force balances. Analysis of simulated impurity transport showed similar impurity density at the separatrix for the mid and high-power cases despite the high-power case having 10% more sputtered W. This is explained by the combination of differing trends in the sourcing and screening with scaling power.
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- 2022
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8. Integrating sepsis management recommendations into clinical care guidelines for district hospitals in resource-limited settings: the necessity to augment new guidelines with future research.
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Jacob, ST, Lim, M, Banura, P, Bhagwanjee, S, Bion, J, Cheng, AC, Cohen, H, Farrar, J, Gove, S, Hopewell, P, Moore, CC, Roth, C, West, TE, Jacob, ST, Lim, M, Banura, P, Bhagwanjee, S, Bion, J, Cheng, AC, Cohen, H, Farrar, J, Gove, S, Hopewell, P, Moore, CC, Roth, C, and West, TE
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Several factors contribute to the high mortality attributed to severe infections in resource-limited settings. While improvements in survival and processes of care have been made in high-income settings among patients with severe conditions, such as sepsis, guidelines necessary for achieving these improvements may lack applicability or have not been tested in resource-limited settings. The World Health Organization's recent publication of the Integrated Management of Adolescent and Adult Illness District Clinician Manual provides details on how to optimize management of severely ill, hospitalized patients in such settings, including specific guidance on the management of patients with septic shock and respiratory failure without shock. This manuscript provides the context, process and underpinnings of these sepsis guidelines. In light of the current deficits in care and the limitations associated with these guidelines, the authors propose implementing these standardized best practice guidelines while using them as a foundation for sepsis research undertaken in, and directly relevant to, resource-limited settings.
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- 2013
9. Strategies to reduce mortality from bacterial sepsis in adults in developing countries.
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Cheng, AC, West, TE, Limmathurotsakul, D, Peacock, SJ, Cheng, AC, West, TE, Limmathurotsakul, D, and Peacock, SJ
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Sharon Peacock and colleagues discuss management of adult patients with sepsis in low- and middle-income settings, with a particular emphasis on tropical regions.
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- 2008
10. Emphysematous Cystitis due to Clostridium perfringens
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Lauer Ad, Holley Hp, and West Te
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medicine.medical_specialty ,Pneumaturia ,medicine.diagnostic_test ,business.industry ,Urinary system ,Urinary incontinence ,General Medicine ,Hematocrit ,Clostridium perfringens ,medicine.disease ,medicine.disease_cause ,Gastroenterology ,Surgery ,Internal medicine ,Emphysematous cystitis ,medicine ,Dysuria ,Anaerobic bacteria ,medicine.symptom ,business - Abstract
ANAEROBIC bacteria are infrequent pathogens of the urinary tract. Emphysematous cystitis results most commonly from infection with a gasforming aerobic organism such as Escherichia coli . 1 We describe a diabetic patient with emphysematous cystitis due to the gas-forming anaerobe Clostridium perfringens . Report of a Case A 72-year-old woman was admitted to the Charleston County Hospital in December 1979 for evaluation of weakness and intermittent, cramping, periumbilical pain of two months' duration. She reported that the pain decreased after voiding and denied any dysuria, urgency, urinary incontinence, or pneumaturia. She was a well-controlled diabetic whose condition was maintained with 20 units of isophane insulin suspension daily. Blood glucose value on admission was 86 mg/dL; hematocrit reading, 31 vol%; and WBC count, 7,700 cells per cubic millimeter, with 41% neutrophils. Findings from urinalysis demonstrated 35 to 45 WBCs per cubic millimeter and were otherwise normal. An abdominal roentgenogram showed an enlarged bladder
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- 1981
11. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
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Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, 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GENDER-DIFFERENCES ,SUICIDE ,Medicine (all) ,Burden of Disease Study 2017 ,SDG ,CONSUMPTION ,11 Medical And Health Sciences ,GBD, Sustainable Development Goals ,PREVENTION ,ALCOHOL-USE ,CARDIOVASCULAR-DISEASE ,SMOKING PREVALENCE ,General & Internal Medicine ,factors risk ,Medicine and Health Sciences ,Human medicine ,CESSATION ,PERSPECTIVE ,TRANSITION - Abstract
Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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12. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Roth, Gregory A., Collaborotors, G. B. 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Miller, Tr, Miller-Petrie, Mk, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Moreno Velásquez, I, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nachega, Jb, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Lh, Nguyen, Th, Ningrum, Dna, Nirayo, Yl, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Orpana, Hm, Ortiz, Jr, Øverland, S, Owolabi, Mo, Özdemir, R, P A, M, Pakhare, Ap, Pakpour, Ah, Pandian, Jd, Park, Ek, Parry, Cdh, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Postma, Mj, Purcell, Ca, Quistberg, Da, Rade, Kw, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahman, Mhu, Rahman, Ma, Rai, Rk, Ranabhat, Cl, Rao, Pc, Rawaf, Dl, Razo-García, C, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Tran, Bx, Tran, Kb, Troeger, Ce, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Updike, Rl, Uthman, Oa, Uzun, Sb, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Wagner, Gr, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weintraub, Rg, Weldegwergs, Kg, Werkneh, Aa, West, Te, Whiteford, Ha, Wilner, Lb, Wolfe, Cda, Wu, Yc, Wyper, Gma, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yentür, Gk, Yimer, Em, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaman, Sb, Zeleke, Aj, Zenebe, Zm, Zhang, Al, Zuhlke, Lj, and Murray, Cjl.
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Adult ,Male ,Adolescent ,national age-sex-specific mortality ,UNITED-STATES ,Global Health ,Socioeconomic Factor ,Global Burden of Disease ,GBD, causes of death ,Young Adult ,Age Distribution ,Life Expectancy ,General & Internal Medicine ,Cause of Death ,PUBLIC-HEALTH PROBLEM ,mortality ,282 causes global burden of disease ,Sex Distribution ,Child ,Aged ,Aged, 80 and over ,BARRIERS ,DEMENTIA ,Medicine (all) ,Infant, Newborn ,Infant ,11 Medical And Health Sciences ,Middle Aged ,TRENDS ,PREVENTION ,PREVALENCE ,ALZHEIMERS-DISEASE ,INDIVIDUALS ,3121 General medicine, internal medicine and other clinical medicine ,Child, Preschool ,REGISTRATION ,Female ,Human medicine ,Human - Abstract
Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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13. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Kalayu Brhane, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada, Mukhopadhyay, Satinath, Muller, Kate, Mumford, John Everett, Murhekar, Manoj, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Nabhan, Ashraf F, Nagata, Chie, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramo, Natarajan, Gopalakrishnan, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Suba, Newton, Charles Richard Jame, Ngunjiri, Josephine W, Nguyen, Anh Quynh, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Minh, Nguyen, Nam Ba, Nguyen, Son Hoang, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Shuhei, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nsoesie, 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Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saleem, Komal, Saleem, Zikria, Salimi, Yahya, Salomon, Joshua A, Salvi, Sundeep Santosh, Salz, Inbal, Samy, Abdallah M, Sanabria, Juan, Sang, Yingying, Santomauro, Damian Francesco, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Saylan, Mete, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A, Shaikh, Masood Ali, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Sharafi, Heidar, 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Eduardo A, Unutzer, Jurgen, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wu, Shouling, Wu, Yun-Chun, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeleke, Ayalew Jejaw, Zenebe, Zerihun Menlkalew, Zhang, Kai, Zhao, Zheng, Zhou, Maigeng, Zodpey, Sanjay, Zucker, Inbar, Vos, Theo, and Murray, Christopher J L
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YLDs ,global burden of disease ,General & Internal Medicine ,Medicine (all) ,prevalence ,incidence ,Human medicine ,global burden of disease, YLDs, incidence, prevalence ,GBD, years lived with disability - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 39% (95% uncertainty interval [UI] 3.1-4. 6) from 1990 to 2017; however, the all-age YLD rate increased by 7.2% (6.0-8.4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7.9% (6 6-9. 2) for males and 6.5% (5.4-7.7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-hatin and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
14. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
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Ray, Dos Santos, Kadine Priscila Bender, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duncan, Bruce Bartholow, Echko, Michelle, Edessa, Dumessa, Edvardsson, David, Ehrlich, Joshua R., Eldrenkamp, Erika, El-Khatib, Ziad, Endres, Matthia, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Fakhar, Mahdi, Farag, Tamer, Faramarzi, Mahbobeh, Faraon, Emerito Jose Aquino, Faro, André, Farzadfar, Farshad, Fatusi, Adesegun, Fazeli, Mir Sohail, Feigin, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Fijabi, Daniel Obadare, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Flor, Luisa Sorio, Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fürst, Thoma, Futran, Neal D., Gakidou, Emmanuela, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Ganji, Morsaleh, Gebre, Abadi Kahsu, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M., Geremew, Demeke, Gething, Peter W., Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Gill, Paramjit Singh, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Goli, Sriniva, Gomez-Dantes, Hector, Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Grada, Ayman, Griswold, Max, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Haagsma, Juanita A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hankey, Graeme J., Harb, Hilda L., Harewood, Heather C., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassen, Hamid Yimam, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., He, Jiawei, Hearps, Stephen J.C., Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henry, Nathaniel J., Herrera Ballesteros, Victor Hugo, Herteliu, Claudiu, Hibstu, Desalegn Tsegaw, Hiluf, Molla Kahssay, Hoek, Hans W., Homaie Rad, Enayatollah, Horita, Nobuyuki, Hosgood, H. Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. Venkat, Nascimento, Bruno Ramo, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R., Ngunjiri, Josephine Wanjiku, Nguyen, Grant, Nguyen, Long, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nolte, Ellen, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Nyandwi, Alypio, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., De Oliveira, Patricia Pereira Vasconcelo, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortega-Altamirano, Doris V., Ortiz, Alberto, Ozdemir, Raziye, Pa, Mahesh, Pain, Amanda W., Palone, Marcos Roberto Tovani, Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Park, Eun-Kee, Parsian, Hadi, Patel, Teja, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paturi, Vishnupriya Rao, Paudel, Deepak, De Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, Maria Jesu, Rivera, Juan A., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nobhojit, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S., Sadat, Nafi, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salama, Joseph, Salamati, Payman, De Freitas Saldanha, Raphael, Salimzadeh, Hamideh, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sancheti, Parag K., Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Schaeffner, Elke, Schmidhuber, Josef, Schmidt, Maria Inê, Schneider, Ione J.C., Schumacher, Austin E., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shafieesabet, Azadeh, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Shams-Beyranvand, Mehran, Sharafi, Heidar, Sharif-Alhoseini, Mahdi, Shariful Islam, Sheikh Mohammed, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shfare, Mebrahtu Teweldemedhin, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shinohara, Yukito, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shrime, Mark G., Shukla, Sharvari Rahul, Siabani, Soraya, Sigfusdottir, Inga Dora, Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Lavanya, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sinke, Abiy Hiruye, Sisay, Mekonnen, Skirbekk, Vegard, Sliwa, Karen, Smith, Alison, Soares Filho, Adauto Martin, Sobaih, Badr H.A., Somai, Melek, Soneji, Samir, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J., Stokes, Mark Andrew, Sturua, Lela, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sunguya, Bruno F., Sur, Patrick J., Sykes, Bryan L., Sylaja, P.N., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tadesse, Andualem Henok, Taffere, Getachew Redae, Tandon, Nikhil, Tariku, Amare Tariku, Taveira, Nuno, Tehrani-Banihashemi, Arash, Temam Shifa, Girma, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tesema, Azeb Gebresilassie, Tesfaye, Dawit Jember, Tessema, Belay, Thakur, J.S., Thomas, Nihal, Thompson, Matthew J., Tillmann, Taavi, To, Quyen G., Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Avnish, Tripathy, Srikanth Prasad, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tudor Car, Lorainne, Tuem, Kald Beshir, Tyrovolas, Stefano, Uchendu, Uche S., Ukwaja, Kingsley Nnanna, Ullah, Irfan, Updike, Rachel, Uthman, Olalekan A., Uzochukwu, Benjamin S. Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. 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Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, 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Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
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Peformance ,Coverage ,Dánartíðni ,Lífslíkur ,Life expectancy ,GBD ,Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best) ,universal health coverage ,Article ,access quality health care ,health care access and quality index ,Nations ,Healthcare Acce ,Cause-specific mortality ,Psychology ,Healthcare Access and Quality Index ,Mælitæki ,States ,Medicine (all) ,Health care ,Þjóðir ,Public Health, Global Health, Social Medicine and Epidemiology ,Quality ,Heilbrigðisþjónusta ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Sálfræði ,Indicator ,Amenable mortality ,Transition ,we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations ,Trends ,Inequalities - Abstract
Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.
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- 2018
15. Long COVID and recovery from Long COVID: quality of life impairments and subjective cognitive decline at a median of 2 years after initial infection.
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Szewczyk W, Fitzpatrick AL, Fossou H, Gentile NL, Sotoodehnia N, Vora SB, West TE, Bertolli J, Cope JR, Lin JS, Unger ER, and Vu QM
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- Humans, Female, Male, Middle Aged, Aged, Adult, Surveys and Questionnaires, COVID-19 psychology, COVID-19 complications, COVID-19 epidemiology, Quality of Life, Cognitive Dysfunction epidemiology, SARS-CoV-2, Post-Acute COVID-19 Syndrome
- Abstract
Background: Recovery from SARS CoV-2 infection is expected within 3 months. Long COVID occurs after SARS-CoV-2 when symptoms are present for more than 3 months that are continuous, relapsing and remitting, or progressive. Better understanding of Long COVID illness trajectories could strengthen patient care and support., Methods: We characterized functional impairments, quality of life (QoL), and cognition among patients who recovered from SARS-CoV-2 infection within 3 months (without Long COVID), after 3 months (Recovered Long COVID), or remained symptomatic (Long COVID). Among 7305 patients identified with previous SARS-CoV-2 infection between March 2020 and December 2021, confirmed in the medical record with laboratory test or physician diagnosis, 435 (6%) completed a single self-administered survey between March 2022 and September 2022. Multi-domain QoL and cognitive concerns were evaluated using PROMIS-29 and the Cognitive Change Index-12., Results: Nearly half the participants (47.7%) were surveyed more than 2 years from initial infection (median = 23.3 months; IQR = 18.6, 26.7) and 86.7% were surveyed more than 1 year from infection. A significantly greater proportion of the Long COVID (n = 215) group, (Current and Recovered combined), had moderate-to-severe impairment in all health domains assessed compared to those Without Long COVID (n = 220; all p < 0.05). The Recovered Long COVID group (n = 34) had significantly lower prevalence of fatigue, pain, depression, and physical and social function impairment compared to those with Current Long COVID (n = 181; all p < 0.05). However, compared to patients Without Long COVID, the Recovered Long COVID group had greater prevalences of fatigue, pain (p ≤ 0.06) and subjective cognitive decline (61.8% vs 29.1%; p < 0.01). Multivariate relative risk (RR) regression indicated Long COVID risk was greater for older age groups (RR range 1.46-1.52; all p ≤ 0.05), those without a bachelor's degree (RR = 1.33; 95% CI = 1.03-1.71; p = 0.03), and those with 3 or more comorbidities prior to SARS-CoV-2 infection (RR = 1.45; 95% CI = 1.11-1.90; p < 0.01)., Conclusions: Long COVID is associated with long-term subjective cognitive decline and diminished quality of life. Clinically significant cognitive complaints, fatigue, and pain were present even in those who reported they had recovered from Long COVID. These findings have implications for the sustainability of participation in work, education, and social activities., (© 2024. The Author(s).)
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- 2024
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16. γδ T Cells Mediate Protection against Neutrophil-associated Lung Inflammation in Pulmonary Melioidosis.
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Wright SW, Sengyee S, Ekchariyawat P, Phunpang R, Dulsuk A, Rerolle G, Bashmail A, Chantratita N, Gharib SA, and West TE
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- Animals, Humans, Lung immunology, Lung pathology, Lung microbiology, Mice, Inbred C57BL, Burkholderia pseudomallei immunology, Female, Mice, Receptors, Antigen, T-Cell, gamma-delta metabolism, Receptors, Antigen, T-Cell, gamma-delta immunology, Pneumonia immunology, Pneumonia microbiology, Pneumonia pathology, Male, Disease Models, Animal, Pneumonia, Bacterial immunology, Pneumonia, Bacterial microbiology, Pneumonia, Bacterial pathology, Neutrophil Infiltration, T-Lymphocytes immunology, Intraepithelial Lymphocytes immunology, Melioidosis immunology, Melioidosis pathology, Melioidosis microbiology, Neutrophils immunology, Neutrophils metabolism
- Abstract
Pulmonary melioidosis is a severe tropical infection caused by Burkholderia pseudomallei and is associated with high mortality, despite early antibiotic treatment. γδ T cells have been increasingly implicated as drivers of the host neutrophil response during bacterial pneumonia, but their role in pulmonary melioidosis is unknown. Here, we report that in patients with melioidosis, a lower peripheral blood γδ T-cell concentration is associated with higher mortality, even when adjusting for severity of illness. γδ T cells were also enriched in the lung and protected against mortality in a mouse model of pulmonary melioidosis. γδ T-cell deficiency in infected mice induced an early recruitment of neutrophils to the lung, independent of bacterial burden. Subsequently, γδ T-cell deficiency resulted in increased neutrophil-associated inflammation in the lung as well as impaired bacterial clearance. In addition, γδ T cells influenced neutrophil function and subset diversity in the lung after infection. Our results indicate that γδ T cells serve a novel protective role in the lung during severe bacterial pneumonia by regulating excessive neutrophil-associated inflammation.
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- 2024
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17. Genetic variation, structural analysis, and virulence implications of BimA and BimC in clinical isolates of Burkholderia pseudomallei in Thailand.
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Cagape CMS, Seng R, Saiprom N, Tandhavanant S, Chewapreecha C, Boonyuen U, West TE, and Chantratita N
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- Humans, Thailand epidemiology, Virulence genetics, Bacterial Proteins genetics, Bacterial Proteins metabolism, A549 Cells, Genome, Bacterial, Phylogeny, Microfilament Proteins, Burkholderia pseudomallei genetics, Burkholderia pseudomallei pathogenicity, Burkholderia pseudomallei metabolism, Burkholderia pseudomallei isolation & purification, Melioidosis microbiology, Genetic Variation
- Abstract
Melioidosis is a life-threatening tropical disease caused by an intracellular gram-negative bacterium Burkholderia pseudomallei. B. pseudomallei polymerizes the host cell actin through autotransporters, BimA, and BimC, to facilitate intracellular motility. Two variations of BimA in B. pseudomallei have been reported previously: BimA
Bp and BimA B. mallei-like (BimABm ). However, little is known about genetic sequence variations within BimA and BimC, and their potential effect on the virulence of B. pseudomallei. This study analyzed 1,294 genomes from clinical isolates of patients admitted to nine hospitals in northeast Thailand between 2015 and 2018 and performed 3D structural analysis and plaque-forming efficiency assay. The genomic analysis identified 10 BimABp and 5 major BimC types, in the dominant and non-dominant lineages of the B. pseudomallei population structure. Our protein prediction analysis of all BimABp and major BimC variants revealed that their 3D structures were conserved compared to those of B. pseudomallei K96243. Sixteen representative strains of the most distant BimABp types were tested for plaque formation and the development of polar actin tails in A549 epithelial cells. We found that all isolates retained these functions. These findings enhance our understanding of the prevalence of BimABp and BimC variants and their implications for B. pseudomallei virulence., (© 2024. The Author(s).)- Published
- 2024
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18. Dysfunctional host cellular immune responses are associated with mortality in melioidosis.
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Wright SW, Ekchariyawat P, Sengyee S, Phunpang R, Dulsuk A, Saiprom N, Thiansukhon E, Pattanapanyasat K, Korbsrisate S, West TE, and Chantratita N
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- Humans, Male, Female, Middle Aged, Aged, Adult, Immunity, Cellular, Interleukin-17 immunology, CD4-Positive T-Lymphocytes immunology, Cytokines blood, Cytokines immunology, Prospective Studies, Melioidosis immunology, Melioidosis mortality, Melioidosis microbiology, Burkholderia pseudomallei immunology, CD8-Positive T-Lymphocytes immunology, Th17 Cells immunology
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Melioidosis is a tropical infection caused by the intracellular pathogen Burkholderia pseudomallei , an underreported and emerging global threat. As melioidosis-associated mortality is frequently high despite antibiotics, novel management strategies are critically needed. Therefore, we sought to determine whether functional changes in the host innate and adaptive immune responses are induced during acute melioidosis and are associated with outcome. Using a unique whole blood stimulation assay developed for use in resource-limited settings, we examined induced cellular functional and phenotypic changes in a cohort of patients with bacteremic melioidosis prospectively enrolled within 24 h of positive blood culture and followed for 28 days. Compared to healthy controls, melioidosis survivors generated an IL-17 response mediated by Th17 cells and terminally-differentiated effector memory CD8
+ T cells ( P < .05, both), persisting to 28 days after enrolment. Furthermore, melioidosis survivors developed polyfunctional cytokine production in CD8+ T cells ( P < .01). Conversely, a reduction in CCR6+ CD4+ T cells was associated with higher mortality, even after adjustments for severity of illness ( P = 0.004). Acute melioidosis was also associated with a profound acute impairment in monocyte function as stimulated cytokine responses were reduced in classical, intermediate and non-classical monocytes. Impaired monocyte cytokine function improved by 28-days after enrolment. These data suggest that IL-17 mediated cellular responses may be contributors to host defense during acute melioidosis, and that innate immune function may be impaired. These insights could provide novel targets for the development of therapies and vaccine targets in this frequently lethal disease.- Published
- 2024
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19. Dysregulated immunologic landscape of the early host response in melioidosis.
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Rongkard P, Xia L, Kronsteiner B, Yimthin T, Phunpang R, Dulsuk A, Hantrakun V, Wongsuvan G, Chamnan P, Lovelace-Macon L, Marchi E, Day NP, Shojaie A, Limmathurotsakul D, Chantratita N, Klenerman P, Dunachie SJ, West TE, and Gharib SA
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- Humans, Male, Female, Middle Aged, Adult, Aged, Thailand epidemiology, Immunity, Innate, Transcriptome, Adaptive Immunity, Interferons metabolism, Interferons immunology, Melioidosis immunology, Melioidosis mortality, Melioidosis microbiology, Burkholderia pseudomallei immunology
- Abstract
Melioidosis, a neglected tropical infection caused by Burkholderia pseudomallei, commonly presents as pneumonia or sepsis with mortality rates up to 50% despite appropriate treatment. A better understanding of the early host immune response to melioidosis may lead to new therapeutic interventions and prognostication strategies to reduce disease burden. Whole blood transcriptomic signatures in 164 patients with melioidosis and in 70 patients with other infections hospitalized in northeastern Thailand enrolled within 24 hours following hospital admission were studied. Key findings were validated in an independent melioidosis cohort. Melioidosis was characterized by upregulation of interferon (IFN) signaling responses compared with other infections. Mortality in melioidosis was associated with excessive inflammation, enrichment of type 2 immune responses, and a dramatic decrease in T cell-mediated immunity compared with survivors. We identified and independently confirmed a 5-gene predictive set classifying fatal melioidosis (validation cohort area under the receiver operating characteristic curve 0.83; 95% CI, 0.67-0.99). This study highlights the intricate balance between innate and adaptive immunity during fatal melioidosis and can inform future precision medicine strategies for targeted therapies and prognostication in this severe infection.
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- 2024
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20. Genetic diversity, determinants, and dissemination of Burkholderia pseudomallei lineages implicated in melioidosis in Northeast Thailand.
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Seng R, Chomkatekaew C, Tandhavanant S, Saiprom N, Phunpang R, Thaipadungpanit J, Batty EM, Day NPJ, Chantratita W, West TE, Thomson NR, Parkhill J, Chewapreecha C, and Chantratita N
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- Thailand epidemiology, Humans, Phylogeny, Gene Flow, Genome, Bacterial genetics, Burkholderia pseudomallei genetics, Burkholderia pseudomallei isolation & purification, Burkholderia pseudomallei classification, Melioidosis microbiology, Melioidosis epidemiology, Genetic Variation
- Abstract
Melioidosis is an often-fatal neglected tropical disease caused by an environmental bacterium Burkholderia pseudomallei. However, our understanding of the disease-causing bacterial lineages, their dissemination, and adaptive mechanisms remains limited. To address this, we conduct a comprehensive genomic analysis of 1,391 B. pseudomallei isolates collected from nine hospitals in northeast Thailand between 2015 and 2018, and contemporaneous isolates from neighbouring countries, representing the most densely sampled collection to date. Our study identifies three dominant lineages, each with unique gene sets potentially enhancing bacterial fitness in the environment. We find that recombination drives lineage-specific gene flow. Transcriptome analyses of representative clinical isolates from each dominant lineage reveal increased expression of lineage-specific genes under environmental conditions in two out of three lineages. This underscores the potential importance of environmental persistence for these dominant lineages. The study also highlights the influence of environmental factors such as terrain slope, altitude, and river direction on the geographical dispersal of B. pseudomallei. Collectively, our findings suggest that environmental persistence may play a role in facilitating the spread of B. pseudomallei, and as a prerequisite for exposure and infection, thereby providing useful insights for informing melioidosis prevention and control strategies., (© 2024. The Author(s).)
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- 2024
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21. Severity of Inhalation Injury and Risk of Nosocomial Pneumonia: A Retrospective Cohort Study.
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Coston TD, Gaskins D, Bailey A, Minus E, Arbabi S, West TE, and Stewart BT
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Background: The impact of inhalation injury on risk of nosocomial pneumonia (NP), an important complication in patients with burns, is not well established., Research Question: Is more severe inhalation injury associated with increased risk of NP?, Study Design and Methods: We performed a retrospective cohort study of patients with suspected inhalation injury admitted to a regional burn center from 2011 to 2022 who underwent diagnostic bronchoscopy within 48 h of admission. We estimated the association of high-grade inhalation injury (Abbreviated Injury Scale grade 3 and 4) vs low-grade inhalation injury (Abbreviated Injury Scale grade 1 and 2) with NP adjusted for age, burn size, and comorbid obstructive lung disease. Death and hospital discharge were considered competing risks., Results: Of the 245 patients analyzed, 51 (21%) had high-grade injury, 180 (73%) had low-grade injury, and 14 (6%) had no inhalation injury. Among the 236 patients hospitalized for ≥ 48 h, NP occurred in 24 of 50 patients (48%) in the high-grade group, 54 of 172 patients (31%) in the low-grade group, and two of 14 patients (14%) in the no inhalation injury group. High-grade (vs low-grade) inhalation injury was associated with higher hazard of NP in both the proportional cause-specific hazard model (cause-specific hazard ratio, 2.04; 95% CI, 1.26-3.30; P = .004) and Fine-Gray subdistribution hazard model (subdistribution hazard ratio for NP, 2.24; 95% CI, 1.38-3.64; P = .001)., Interpretation: In this study, among patients with inhalation injury, more severe injury was associated with higher hazard of NP in competing risk analysis. Additional research is needed to investigate mechanisms that may explain the relationship between inhalation injury and NP and to identify more effective risk reduction strategies., Competing Interests: Financial/Nonfinancial Disclosures None declared., (Copyright © 2024 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)
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- 2024
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22. Flagellin-modulated inflammasome pathways characterize the human alveolar macrophage response to Burkholderia pseudomallei , a lung-tropic pathogen.
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Lovelace-Macon L, Baker SM, Ducken D, Seal S, Rerolle G, Tomita D, Smith KD, Schwarz S, and West TE
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- Humans, Melioidosis immunology, Melioidosis microbiology, Cells, Cultured, Macrophages, Alveolar immunology, Macrophages, Alveolar microbiology, Inflammasomes immunology, Inflammasomes metabolism, Burkholderia pseudomallei immunology, Flagellin immunology, Flagellin metabolism, Host-Pathogen Interactions immunology
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Melioidosis is an emerging tropical infection caused by inhalation, inoculation, or ingestion of the flagellated, facultatively intracellular pathogen Burkholderia pseudomallei . The melioidosis case fatality rate is often high, and pneumonia, the most common presentation, doubles the risk of death. The alveolar macrophage is a sentinel pulmonary host defense cell, but the human alveolar macrophage in B. pseudomallei infection has never been studied. The objective of this study was to investigate the host-pathogen interaction of B. pseudomallei infection with the human alveolar macrophage and to determine the role of flagellin in modulating inflammasome-mediated pathways. We found that B. pseudomallei infects primary human alveolar macrophages but is gradually restricted in the setting of concurrent cell death. Electron microscopy revealed cytosolic bacteria undergoing division, indicating that B. pseudomallei likely escapes the alveolar macrophage phagosome and may replicate in the cytosol, where it triggers immune responses. In paired human blood monocytes, uptake and intracellular restriction of B. pseudomallei are similar to those observed in alveolar macrophages, but cell death is reduced. The alveolar macrophage cytokine response to B. pseudomallei is characterized by marked interleukin (IL)-18 secretion compared to monocytes. Both cytotoxicity and IL-18 secretion in alveolar macrophages are partially flagellin dependent. However, the proportion of IL-18 release that is driven by flagellin is greater in alveolar macrophages than in monocytes. These findings suggest differential flagellin-mediated inflammasome pathway activation in the human alveolar macrophage response to B. pseudomallei infection and expand our understanding of intracellular pathogen recognition by this unique innate immune lung cell., Competing Interests: The authors declare no conflict of interest.
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- 2024
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23. Prognostic Accuracy of Screening Tools for Clinical Deterioration in Adults With Suspected Sepsis in Northeastern Thailand: A Cohort Validation Study.
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Wixon-Genack J, Wright SW, Cobb Ortega NL, Hantrakun V, Rudd KE, Teparrukkul P, Limmathurotsakul D, and West TE
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Background: We sought to assess the performance of commonly used clinical scoring systems to predict imminent clinical deterioration in patients hospitalized with suspected infection in rural Thailand., Methods: Patients with suspected infection were prospectively enrolled within 24 hours of admission to a referral hospital in northeastern Thailand between 2013 and 2017. In patients not requiring intensive medical interventions, multiple enrollment scores were calculated including the National Early Warning Score (NEWS), the Modified Early Warning Score, Between the Flags, and the quick Sequential Organ Failure Assessment score. Scores were tested for predictive accuracy of clinical deterioration, defined as a new requirement of mechanical ventilation, vasoactive medications, intensive care unit admission, and/or death approximately 1 day after enrollment. The association of each score with clinical deterioration was evaluated by means of logistic regression, and discrimination was assessed by generating area under the receiver operating characteristic curve., Results: Of 4989 enrolled patients, 2680 met criteria for secondary analysis, and 100 of 2680 (4%) experienced clinical deterioration within 1 day after enrollment. NEWS had the highest discrimination for predicting clinical deterioration (area under the receiver operating characteristic curve, 0.78 [95% confidence interval, .74-.83]) compared with the Modified Early Warning Score (0.67 [.63-.73]; P < .001), quick Sequential Organ Failure Assessment (0.65 [.60-.70]; P < .001), and Between the Flags (0.69 [.64-.75]; P < .001). NEWS ≥5 yielded optimal sensitivity and specificity for clinical deterioration prediction., Conclusions: In patients hospitalized with suspected infection in a resource-limited setting in Southeast Asia, NEWS can identify patients at risk of imminent clinical deterioration with greater accuracy than other clinical scoring systems., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)
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- 2024
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24. Correction: Clinical epidemiology and outcomes of community acquired infection and sepsis among hospitalized patients in a resource limited setting in Northeast Thailand: A prospective observational study (Ubon-sepsis).
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Hantrakun V, Somayaji R, Teparrukkul P, Boonsri C, Rudd K, Day NPJ, West TE, and Limmathurotsakul D
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[This corrects the article DOI: 10.1371/journal.pone.0204509.]., (Copyright: © 2024 Hantrakun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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25. Lack of Association of TLR1 and TLR5 Coding Variants with Mortality in a Large Multicenter Cohort of Melioidosis Patients.
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Yimthin T, Phunpang R, Wright SW, Thiansukhon E, Chaisuksant S, Chetchotisakd P, Tanwisaid K, Chuananont S, Morakot C, Sangsa N, Silakun W, Chayangsu S, Buasi N, Lertmemongkolchai G, Chantratita N, and West TE
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- Humans, Male, Female, Thailand epidemiology, Middle Aged, Adult, Cohort Studies, Polymorphism, Single Nucleotide, Genotype, Burkholderia pseudomallei genetics, Prospective Studies, Aged, Genetic Predisposition to Disease, Melioidosis mortality, Melioidosis genetics, Melioidosis microbiology, Toll-Like Receptor 1 genetics, Bacteremia mortality, Bacteremia microbiology, Bacteremia genetics, Toll-Like Receptor 5 genetics
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Melioidosis, infection caused by Burkholderia pseudomallei, is characterized by robust innate immune responses. We have previously reported associations of TLR1 single nucleotide missense variant rs76600635 with mortality and of TLR5 nonsense variant rs5744168 with both bacteremia and mortality in single-center studies of patients with melioidosis in northeastern Thailand. The objective of this study was to externally validate the associations of rs76600635 and rs5744168 with bacteremia and mortality in a large multicenter cohort of melioidosis patients. We genotyped rs76600635 and rs5744168 in 1,338 melioidosis patients enrolled in a prospective parent cohort study conducted at nine hospitals in northeastern Thailand. The genotype frequencies of rs76600635 did not differ by bacteremia status (P = 0.27) or 28-day mortality (P = 0.84). The genotype frequencies of rs5744168 did not differ by either bacteremia status (P = 0.46) or 28-day mortality (P = 0.10). Assuming a dominant genetic model, there was no association of the rs76600635 variant with bacteremia (adjusted odds ratio [OR], 0.75; 95% CI, 0.54-1.04, P = 0.08) or 28-day mortality (adjusted OR, 0.96; 95% CI, 0.71-1.28, P = 0.77). There was no association of the rs5744168 variant with bacteremia (adjusted OR, 1.24; 95% CI, 0.76-2.03, P = 0.39) or 28-day mortality (adjusted OR, 1.22; 95% CI, 0.83-1.79, P = 0.21). There was also no association of either variant with 1-year mortality. We conclude that in a large multicenter cohort of patients hospitalized with melioidosis in northeastern Thailand, neither TLR1 missense variant rs76600635 nor TLR5 nonsense variant rs5744168 is associated with bacteremia or mortality.
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- 2024
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26. Estimates of Incidence and Predictors of Fatiguing Illness after SARS-CoV-2 Infection.
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Vu QM, Fitzpatrick AL, Cope JR, Bertolli J, Sotoodehnia N, West TE, Gentile N, and Unger ER
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- Humans, Incidence, Muscle Fatigue, SARS-CoV-2, COVID-19 epidemiology, Fatigue Syndrome, Chronic
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This study aimed to estimate the incidence rates of post-COVID-19 fatigue and chronic fatigue and to quantify the additional incident fatigue caused by COVID-19. We analyzed electronic health records data of 4,589 patients with confirmed COVID-19 during February 2020-February 2021 who were followed for a median of 11.4 (interquartile range 7.8-15.5) months and compared them to data from 9,022 propensity score-matched non-COVID-19 controls. Among COVID-19 patients (15% hospitalized for acute COVID-19), the incidence rate of fatigue was 10.2/100 person-years and the rate of chronic fatigue was 1.8/100 person-years. Compared with non-COVID-19 controls, the hazard ratios were 1.68 (95% CI 1.48-1.92) for fatigue and 4.32 (95% CI 2.90-6.43) for chronic fatigue. The observed association between COVID-19 and the significant increase in the incidence of fatigue and chronic fatigue reinforces the need for public health actions to prevent SARS-CoV-2 infections.
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- 2024
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27. Statin Use and Reduced Risk of Pneumonia in Patients with Melioidosis: A Lung-Specific Statin Association.
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Coston TD, Wright SW, Phunpang R, Dulsuk A, Thiansukhon E, Chaisuksant S, Tanwisaid K, Chuananont S, Morakot C, Sangsa N, Chayangsu S, Silakun W, Buasi N, Chetchotisakd P, Day NPJ, Lertmemongkolchai G, Chantratita N, and West TE
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- Humans, Cohort Studies, Prospective Studies, Lung, Melioidosis drug therapy, Melioidosis epidemiology, Melioidosis chemically induced, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Pneumonia complications
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Rationale: 3-Hydroxy-3-methylglutaryl coenzyme A reductase inhibitor (statin) use is associated with a lower risk of incident pneumonia and, less robustly, with nonpulmonary infections. Whether statin use is associated with a lower risk of pneumonia than other clinical presentations of infection with the same pathogen is unknown. Objectives: To assess whether preadmission statin use is associated with a lower risk of pneumonia than nonpneumonia presentations among patients hospitalized with Burkholderia pseudomallei infection (melioidosis). Methods: We performed a secondary analysis of a prospective multicenter cohort study of patients hospitalized with culture-confirmed B. pseudomallei infection (melioidosis). We used Poisson regression with robust standard errors to test for an association between statin use and pneumonia. We then performed several sensitivity analyses that addressed healthy user effect and indication bias. Results: Of 1,372 patients with melioidosis enrolled in the parent cohort, 1,121 were analyzed. Nine hundred eighty (87%) of 1,121 were statin nonusers, and 141 (13%) of 1,121 were statin users. Forty-six (33%) of 141 statin users presented with pneumonia compared with 432 (44%) of 980 statin nonusers. Statin use was associated with a lower risk of pneumonia in unadjusted analysis (relative risk, 0.74; 95% confidence interval, 0.58-0.95; P = 0.02) and, after adjustment for demographic variables, comorbidities, environmental exposures, and symptom duration (relative risk, 0.73; 95% confidence interval, 0.57-0.94; P = 0.02). The results of sensitivity analyses, including active comparator analysis and inverse probability of treatment weighting, were consistent with the primary analysis. Conclusions: In hospitalized patients with melioidosis, preadmission statin use was associated with a lower risk of pneumonia than other clinical presentations of melioidosis, suggesting a lung-specific protective effect of statins.
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- 2024
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28. Plasma Metabolomics Reveals Distinct Biological and Diagnostic Signatures for Melioidosis.
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Xia L, Hantrakun V, Teparrukkul P, Wongsuvan G, Kaewarpai T, Dulsuk A, Day NPJ, Lemaitre RN, Chantratita N, Limmathurotsakul D, Shojaie A, Gharib SA, and West TE
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- Humans, Prospective Studies, Metabolomics, Melioidosis diagnosis, Melioidosis microbiology, Burkholderia pseudomallei, Sepsis
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Rationale: The global burden of sepsis is greatest in low-resource settings. Melioidosis, infection with the gram-negative bacterium Burkholderia pseudomallei , is a frequent cause of fatal sepsis in endemic tropical regions such as Southeast Asia. Objectives: To investigate whether plasma metabolomics would identify biological pathways specific to melioidosis and yield clinically meaningful biomarkers. Methods: Using a comprehensive approach, differential enrichment of plasma metabolites and pathways was systematically evaluated in individuals selected from a prospective cohort of patients hospitalized in rural Thailand with infection. Statistical and bioinformatics methods were used to distinguish metabolomic features and processes specific to patients with melioidosis and between fatal and nonfatal cases. Measurements and Main Results: Metabolomic profiling and pathway enrichment analysis of plasma samples from patients with melioidosis ( n = 175) and nonmelioidosis infections ( n = 75) revealed a distinct immuno-metabolic state among patients with melioidosis, as suggested by excessive tryptophan catabolism in the kynurenine pathway and significantly increased levels of sphingomyelins and ceramide species. We derived a 12-metabolite classifier to distinguish melioidosis from other infections, yielding an area under the receiver operating characteristic curve of 0.87 in a second validation set of patients. Melioidosis nonsurvivors ( n = 94) had a significantly disturbed metabolome compared with survivors ( n = 81), with increased leucine, isoleucine, and valine metabolism, and elevated circulating free fatty acids and acylcarnitines. A limited eight-metabolite panel showed promise as an early prognosticator of mortality in melioidosis. Conclusions: Melioidosis induces a distinct metabolomic state that can be examined to distinguish underlying pathophysiological mechanisms associated with death. A 12-metabolite signature accurately differentiates melioidosis from other infections and may have diagnostic applications.
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- 2024
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29. Genetic diversity, determinants, and dissemination of Burkholderia pseudomallei lineages implicated in melioidosis in northeast Thailand.
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Seng R, Chomkatekaew C, Tandhavanant S, Saiprom N, Phunpang R, Thaipadungpanit J, Batty EM, Day NP, Chantratita W, West TE, Thomson NR, Parkhill J, Chewapreecha C, and Chantratita N
- Abstract
Melioidosis is an often-fatal neglected tropical disease caused by an environmental bacterium Burkholderia pseudomallei . However, our understanding of the disease-causing bacterial lineages, their dissemination, and adaptive mechanisms remains limited. To address this, we conducted a comprehensive genomic analysis of 1,391 B. pseudomallei isolates collected from nine hospitals in northeast Thailand between 2015 and 2018, and contemporaneous isolates from neighbouring countries, representing the most densely sampled collection to date. Our study identified three dominant lineages with unique gene sets enhancing bacterial fitness, indicating lineage-specific adaptation strategies. Crucially, recombination was found to drive lineage-specific gene flow. Transcriptome analyses of representative clinical isolates from each dominant lineage revealed heightened expression of lineage-specific genes in environmental versus infection conditions, notably under nutrient depletion, highlighting environmental persistence as a key factor in the success of dominant lineages. The study also revealed the role of environmental factors - slope of terrain, altitude, direction of rivers, and the northeast monsoons - in shaping B. pseudomallei geographical dispersal. Collectively, our findings highlight persistence in the environment as a pivotal element facilitating B. pseudomallei spread, and as a prelude to exposure and infection, thereby providing useful insights for informing melioidosis prevention and control strategies.
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- 2023
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30. IL-1R2-based biomarker models predict melioidosis mortality independent of clinical data.
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Kaewarpai T, Wright SW, Yimthin T, Phunpang R, Dulsuk A, Lovelace-Macon L, Rerolle GF, Dow DB, Hantrakun V, Day NPJ, Lertmemongkolchai G, Limmathurotsakul D, West TE, and Chantratita N
- Abstract
Introduction: Melioidosis is an often-fatal tropical infectious disease caused by the Gram-negative bacillus Burkholderia pseudomallei , but few studies have identified promising biomarker candidates to predict outcome., Methods: In 78 prospectively enrolled patients hospitalized with melioidosis, six candidate protein biomarkers, identified from the literature, were measured in plasma at enrollment. A multi-biomarker model was developed using least absolute shrinkage and selection operator (LASSO) regression, and mortality discrimination was compared to a clinical variable model by receiver operating characteristic curve analysis. Mortality prediction was confirmed in an external validation set of 191 prospectively enrolled patients hospitalized with melioidosis., Results: LASSO regression selected IL-1R2 and soluble triggering receptor on myeloid cells 1 (sTREM-1) for inclusion in the candidate biomarker model. The areas under the receiver operating characteristic curve (AUC) for mortality discrimination for the IL-1R2 + sTREM-1 model (AUC 0.81, 95% CI 0.72-0.91) as well as for an IL-1R2-only model (AUC 0.78, 95% CI 0.68-0.88) were higher than for a model based on a modified Sequential Organ Failure Assessment (SOFA) score (AUC 0.69, 95% CI 0.56-0.81, p < 0.01, p = 0.03, respectively). In the external validation set, the IL-1R2 + sTREM-1 model (AUC 0.86, 95% CI 0.81-0.92) had superior 28-day mortality discrimination compared to a modified SOFA model (AUC 0.80, 95% CI 0.74-0.86, p < 0.01) and was similar to a model containing IL-1R2 alone (AUC 0.82, 95% CI 0.76-0.88, p = 0.33)., Conclusion: Biomarker models containing IL-1R2 had improved 28-day mortality prediction compared to clinical variable models in melioidosis and may be targets for future, rapid test development., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kaewarpai, Wright, Yimthin, Phunpang, Dulsuk, Lovelace-Macon, Rerolle, Dow, Hantrakun, Day, Lertmemongkolchai, Limmathurotsakul, West and Chantratita.)
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- 2023
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31. Antibiotic susceptibility of clinical Burkholderia pseudomallei isolates in northeast Thailand during 2015-2018 and the genomic characterization of β-lactam-resistant isolates.
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Fen SHY, Tandhavanant S, Phunpang R, Ekchariyawat P, Saiprom N, Chewapreecha C, Seng R, Thiansukhon E, Morakot C, Sangsa N, Chayangsu S, Chuananont S, Tanwisaid K, Silakun W, Buasi N, Chaisuksant S, Hompleum T, Chetchotisakd P, Day NPJ, Chantratita W, Lertmemongkolchai G, West TE, and Chantratita N
- Abstract
Melioidosis is an often fatal infection in tropical regions caused by an environmental bacterium, Burkholderia pseudomallei Current recommended melioidosis treatment requires intravenous β-lactam antibiotics such as ceftazidime (CAZ), meropenem (MEM) or amoxicillin-clavulanic acid (AMC) and oral trimethoprim-sulfamethoxazole. Emerging antibiotic resistance could lead to therapy failure and high mortality. We performed a prospective multicentre study in northeast Thailand during 2015-2018 to evaluate antibiotic susceptibility and characterize β-lactam resistance in clinical B. pseudomallei isolates. Collection of 1,317 B. pseudomallei isolates from patients with primary and relapse infections were evaluated for susceptibility to CAZ, imipenem (IPM), MEM and AMC. β-lactam resistant isolates were confirmed by broth microdilution method and characterized by whole genome sequence analysis, penA expression and β-lactamase activity. The resistant phenotype was verified via penA mutagenesis. All primary isolates were IPM-susceptible but we observed two CAZ-resistant and one CAZ-intermediate resistant isolates, two MEM-less susceptible isolates, one AMC-resistant and two AMC-intermediate resistant isolates. One of 13 relapse isolates was resistant to both CAZ and AMC. Two isolates were MEM-less susceptible. Strains DR10212A (primary) and DR50054E (relapse) were multi-drug resistant. Genomic and mutagenesis analyses supplemented with gene expression and β-lactamase analyses demonstrated that CAZ-resistant phenotype was caused by PenA variants: P167S (N=2) and penA amplification (N=1). Despite the high mortality rate in melioidosis, our study revealed that B. pseudomallei isolates had a low frequency of β-lactam resistance caused by penA alterations. Clinical data suggest that resistant variants may emerge in patients during antibiotic therapy and be associated with poor response to treatment., (Copyright © 2021 Fen et al.)
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- 2023
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32. Prospective Analysis of Antibody Diagnostic Tests and TTS1 Real-Time PCR for Diagnosis of Melioidosis in Areas Where It Is Endemic.
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Noparatvarakorn C, Sengyee S, Yarasai A, Phunpang R, Dulsuk A, Ottiwet O, Janon R, Morakot C, Burtnick MN, Brett PJ, West TE, and Chantratita N
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- Humans, Real-Time Polymerase Chain Reaction, Antibodies, Bacterial, Sensitivity and Specificity, Hemolysin Proteins genetics, Diagnostic Tests, Routine, Melioidosis diagnosis, Melioidosis microbiology, Burkholderia pseudomallei genetics
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Melioidosis is a tropical infectious disease caused by Burkholderia pseudomallei. Melioidosis is associated with diverse clinical manifestations and high mortality. Early diagnosis is needed for appropriate treatment, but it takes several days to obtain bacterial culture results. We previously developed a rapid immunochromatography test (ICT) based on hemolysin coregulated protein 1 (Hcp1) and two enzyme-linked immunosorbent assays (ELISAs) based on Hcp1 (Hcp1-ELISA) and O-polysaccharide (OPS-ELISA) for serodiagnosis of melioidosis. This study prospectively validated the diagnostic accuracy of the Hcp1-ICT in suspected melioidosis cases and determined its potential use for identifying occult melioidosis cases. Patients were enrolled and grouped by culture results, including 55 melioidosis cases, 49 other infection patients, and 69 patients with no pathogen detected. The results of the Hcp1-ICT were compared with culture, a real-time PCR test based on type 3 secretion system 1 genes (TTS1-PCR), and ELISAs. Patients in the no-pathogen-detected group were followed for subsequent culture results. Using bacterial culture as a gold standard, the sensitivity and specificity of Hcp1-ICT were 74.5% and 89.8%, respectively. The sensitivity and specificity of TTS1-PCR were 78.2% and 100%, respectively. The diagnostic accuracy was markedly improved if the Hcp1-ICT results were combined with TTS1-PCR results (sensitivity and specificity were 98.2% and 89.8%, respectively). Among patients with initially negative cultures, Hcp1-ICT was positive in 16/73 (21.9%). Five of the 16 patients (31.3%) were subsequently confirmed to have melioidosis by repeat culture. The combined Hcp1-ICT and TTS1-PCR test results are useful for diagnosis, and Hcp1-ICT may help identify occult cases of melioidosis.
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- 2023
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33. Abundance of ACVR1B transcript is elevated during septic conditions: Perspectives obtained from a hands-on reductionist investigation.
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Preechanukul A, Yimthin T, Tandhavanant S, Brummaier T, Chomkatekaew C, Das S, Syed Ahamed Kabeer B, Toufiq M, Rinchai D, West TE, Chaussabel D, Chantratita N, and Garand M
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- Humans, Transforming Growth Factor beta metabolism, Activin Receptors, Type I metabolism, Melioidosis, Sepsis
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Sepsis is a complex heterogeneous condition, and the current lack of effective risk and outcome predictors hinders the improvement of its management. Using a reductionist approach leveraging publicly available transcriptomic data, we describe a knowledge gap for the role of ACVR1B (activin A receptor type 1B) in sepsis. ACVR1B, a member of the transforming growth factor-beta (TGF-beta) superfamily, was selected based on the following: 1) induction upon in vitro exposure of neutrophils from healthy subjects with the serum of septic patients (GSE49755), and 2) absence or minimal overlap between ACVR1B, sepsis, inflammation, or neutrophil in published literature. Moreover, ACVR1B expression is upregulated in septic melioidosis, a widespread cause of fatal sepsis in the tropics. Key biological concepts extracted from a series of PubMed queries established indirect links between ACVR1B and "cancer", "TGF-beta superfamily", "cell proliferation", "inhibitors of activin", and "apoptosis". We confirmed our observations by measuring ACVR1B transcript abundance in buffy coat samples obtained from healthy individuals ( n =3) exposed to septic plasma (n = 26 melioidosis sepsis cases) ex vivo . Based on our re-investigation of publicly available transcriptomic data and newly generated ex vivo data, we provide perspective on the role of ACVR1B during sepsis. Additional experiments for addressing this knowledge gap are discussed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Preechanukul, Yimthin, Tandhavanant, Brummaier, Chomkatekaew, Das, Syed Ahamed Kabeer, Toufiq, Rinchai, West, Chaussabel, Chantratita and Garand.)
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- 2023
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34. Phenotypic and genetic alterations of Burkholderia pseudomallei in patients during relapse and persistent infections.
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Seng R, Phunpang R, Saiprom N, Dulsuk A, Chewapreecha C, Thaipadungpanit J, Batty EM, Chantratita W, West TE, and Chantratita N
- Abstract
The bacterium Burkholderia pseudomallei is the causative agent of melioidosis, a severe tropical disease associated with high mortality and relapse and persistent infections. Treatment of melioidosis requires prolonged antibiotic therapy; however, little is known about relapse and persistent infections, particularly the phenotypic and genetic alterations of B. pseudomallei in patients. In this study, we performed pulsed-field gel electrophoresis (PFGE) to compare the bacterial genotype between the initial isolate and the subsequent isolate from each of 23 suspected recurrent and persistent melioidosis patients in Northeast Thailand. We used whole-genome sequencing (WGS) to investigate multilocus sequence types and genetic alterations of within-host strain pairs. We also investigated the bacterial phenotypes associated with relapse and persistent infections, including multinucleated giant cell (MNGC) formation efficiency and intracellular multiplication. We first identified 13 (1.2%) relapse, 7 (0.7%) persistent, and 3 (0.3%) reinfection patients from 1,046 survivors. Each of the 20 within-host strain pairs from patients with relapse and persistent infections shared the same genotype, suggesting that the subsequent isolates arise from the infecting isolate. Logistic regression analysis of clinical data revealed regimen and duration of oral antibiotic therapies as risk factors associated with relapse and persistent infections. WGS analysis demonstrated 17 within-host genetic alteration events in 6 of 20 paired isolates, including a relatively large deletion and 16 single-nucleotide polymorphism (stocktickerSNP) mutations distributed across 12 genes. In 1 of 20 paired isolates, we observed significantly increased cell-to-cell fusion and intracellular replication in the second isolate compared with the initial isolate from a patient with persistent infection. WGS analysis suggested that a non-synonymous mutation in the tssB-5 gene, which encoded an essential component of the type VI secretion system, may be associated with the increased intracellular replication and MNGC formation efficiency of the second isolate of the patient. This information provides insights into genetic and phenotypic alterations in B. pseudomallei in human melioidosis, which may represent a bacterial strategy for persistent and relapse infections., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Seng, Phunpang, Saiprom, Dulsuk, Chewapreecha, Thaipadungpanit, Batty, Chantratita, West and Chantratita.)
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- 2023
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35. Characteristics and One Year Outcomes of Melioidosis Patients in Northeastern Thailand: A Prospective, Multicenter Cohort Study.
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Chantratita N, Phunpang R, Yarasai A, Dulsuk A, Yimthin T, Onofrey LA, Coston TD, Thiansukhon E, Chaisuksant S, Tanwisaid K, Chuananont S, Morakot C, Sangsa N, Chayangsu S, Silakun W, Buasi N, Chetchotisakd P, Day NP, Lertmemongkolchai G, and West TE
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Background: Melioidosis is a neglected tropical infection caused by the environmental saprophyte Burkholderia pseudomallei ., Methods: We conducted a prospective, observational study at nine hospitals in northeastern Thailand, a hyperendemic melioidosis zone, to define current characteristics of melioidosis patients and quantify outcomes over one year., Findings: 2574 individuals hospitalised with culture-confirmed melioidosis were screened and 1352 patients were analysed. The median age was 55 years, 975 (72%) were male, and 951 (70%) had diabetes. 565 (42%) patients presented with lung infection, 1042 (77%) were bacteremic, 442 (33%) received vasopressors/inotropes and 547 (40%) received mechanical ventilation. 1307 (97%) received an intravenous antibiotic against B. pseudomallei . 335/1345 (25%) patients died within one month and 448/1322 (34%) of patients died within one year. Most patients had risk factors for melioidosis, but patients without identified risk factors did not have a reduced risk of death. Of patients discharged alive, most received oral trimethoprim-sulfamethoxazole, which was associated with decreased risk of post-discharge death; 235/970 (24%) were readmitted, and 874/1015 (86%) survived to one year. Recurrent infection was detected in 17/994 patients (2%). Patients with risk factors other than diabetes had increased risk of death and increased risk of hospital readmission., Interpretation: In northeastern Thailand patients with melioidosis experience high rates of bacteremia, organ failure and death. Most patients discharged alive survive one year although all-cause readmission is common. Recurrent disease is rare. Strategies that emphasize prevention, rapid diagnosis and intensification of early clinical management are likely to have greatest impact in this and other resource-restricted regions., Funding: US NIH/NIAID U01AI115520., Competing Interests: Conflicts of interests We declare that we have no competing interests.
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- 2023
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36. Dorsal Root Ganglion Stimulation for Lower Extremity Neuropathic Pain Syndromes: An Evidence-Based Literature Review.
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D'Souza RS, Kubrova E, Her YF, Barman RA, Smith BJ, Alvarez GM, West TE, and Abd-Elsayed A
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- Ganglia, Spinal physiology, Humans, Lower Extremity, Chronic Pain, Complex Regional Pain Syndromes therapy, Neuralgia therapy
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Dorsal root ganglion stimulation (DRG-S) is a form of selective neuromodulation therapy that targets the dorsal root ganglion. DRG-S offers analgesia in a variety of chronic pain conditions and is approved for treatment of complex regional pain syndrome (CRPS) by the US Food and Drug Administration (FDA). There has been increasing utilization of DRG-S to treat various neuropathic pain syndromes of the lower extremity, although evidence remains limited to one randomized controlled trial and 39 observational studies. In this review, we appraised the current evidence for DRG-S in the treatment of lower extremity neuropathic pain using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. The primary outcome was change in pain intensity after DRG-S compared to baseline. We stratified presentation of results based of type of neuropathy (CRPS, painful diabetic neuropathy, mononeuropathy, polyneuropathy) as well as location of neuropathy (hip, knee, foot). Future powered randomized controlled trials with homogeneous participants are warranted., (© 2022. The Author(s).)
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- 2022
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37. Enhanced bedside mortality prediction combining point-of-care lactate and the quick Sequential Organ Failure Assessment (qSOFA) score in patients hospitalised with suspected infection in southeast Asia: a cohort study.
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Wright SW, Hantrakun V, Rudd KE, Lau CY, Lie KC, Chau NVV, Teparrukkul P, West TE, and Limmathurotsakul D
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- Adult, Cohort Studies, Hospital Mortality, Humans, Intensive Care Units, Lactic Acid analysis, Point-of-Care Systems, Prognosis, Retrospective Studies, Thailand, Organ Dysfunction Scores, Sepsis diagnosis
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Background: Simple, bedside prediction of infection-related mortality in low-resource settings is crucial for triage and resource-utilisation decisions. We aimed to evaluate mortality prediction by combining point-of-care venous lactate with the quick Sequential Organ Failure Assessment (qSOFA) score in adult patients admitted to hospital with suspected infection in southeast Asia., Methods: We performed a cohort study by prospectively enrolling patients aged 18 years or older who had been admitted to hospital within the previous 24 h for suspected infection (with at least three documented systemic manifestations of infection according to the 2012 Surviving Sepsis Campaign) at Sunpasitthiprasong Hospital in Ubon Ratchathani, Thailand (derivation cohort). Venous lactate concentration was determined by a point-of-care device and multiple scores were developed. We then evaluated candidate 28-day mortality prediction models combining qSOFA and the lactate scores. A final model was compared with the qSOFA score, a lactate score, and a modified Sequential Organ Failure Assessment (SOFA) score for mortality discrimination using the area under the receiver operating characteristic curve (AUROC). Mortality discrimination of the qSOFA-lactate score was then verified in an external, prospectively enrolled, multinational cohort in southeast Asia., Findings: Between March 1, 2013, and Jan 26, 2017, 5001 patients were enrolled in the derivation cohort; 4980 had point-of-care lactate data available and were eligible for analysis, and 816 died within 28 days of enrolment. The discrimination for 28-day mortality prediction of a qSOFA-lactate score combining the qSOFA score and a lactate score was superior to that of the qSOFA score alone (AUROC 0·78 [95% CI 0·76-0·80] vs 0·68 [0·67-0·70]; p<0·0001) and similar to a modified SOFA score (0·77 [0·75-0·78]; p=0·088). A lactate score alone had superior discrimination compared with the qSOFA score (AUROC 0·76 [95% CI 0·74-0·78]; p<0·0001). 815 patients were enrolled in the external validation cohort and 792 had point-of-care lactate data and were included in the analysis; the qSOFA-lactate score (AUROC 0·77 [95% CI 0·73-0·82]) showed significantly improved 28-day mortality discrimination compared with the qSOFA score alone (0·69 [0·63-0·74]; p<0·0001)., Interpretation: In southeast Asia, rapid, bedside assessments based on point-of-care lactate concentration combined with the qSOFA score can identify patients at risk of sepsis-related mortality with greater accuracy than the qSOFA score alone, and with similar accuracy to a modified SOFA score., Funding: National Institutes of Health, Wellcome Trust., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
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- 2022
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38. Sensitivity and specificity of DPP® Fever Panel II Asia in the diagnosis of malaria, dengue and melioidosis.
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Amornchai P, Hantrakun V, Wongsuvan G, Boonsri C, Yoosuk S, Nilsakul J, Blacksell SD, West TE, Lubell Y, and Limmathurotsakul D
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- Case-Control Studies, Fever diagnosis, Humans, Immunoglobulin M, Sensitivity and Specificity, Thailand epidemiology, Dengue diagnosis, Malaria diagnosis, Melioidosis diagnosis, Sepsis
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Introduction. Rapid diagnostic tests (RDTs) that can facilitate the diagnosis of a panel of tropical infectious diseases are critically needed. DPP® Fever Panel II Asia is a multiplex lateral flow immunoassay comprising antigen and IgM panels for the diagnosis of pathogens that commonly cause febrile illness in Southeast Asia. Hypothesis/Gap Statement. Accuracy of DPP® Fever Panel II Asia has not been evaluated in clinical studies. Aim. To evaluate the sensitivity and specificity of DPP® Fever Panel II Asia for malaria, dengue and melioidosis. Methodology. We conducted a cohort-based case-control study. Both cases and controls were derived from a prospective observational study of patients presenting with community-acquired infections and sepsis in northeast Thailand (Ubon sepsis). We included 143 and 98 patients diagnosed with malaria or dengue based on a positive PCR assay and 177 patients with melioidosis based on a culture positive for Burkholderia pseudomallei . Controls included 200 patients who were blood culture-positive for Staphylococcus aureus , Escherichia coli or Klebsiella pneumoniae , and cases of the other diseases. Serum samples collected from all patients within 24 h of admission were stored and tested using the DPP® Fever Panel II Asia antigen and IgM multiplex assays. We selected cutoff values for each individual assay corresponding to a specificity of ≥95 %. When assessing diagnostic tests in combination, results were considered positive if either individual test was positive. Results. Within the DPP® Fever Panel II Asia antigen assay, a combination of pLDH and HRPII for malaria had a sensitivity of 91 % and a specificity of 97 %. The combination of dengue NS1 antigen and dengue antibody tests had a sensitivity of 61 % and a specificity of 91 %. The B. pseudomallei CPS antigen test had a sensitivity of 27 % and a specificity of 97 %. An odds ratio of 2.34 (95 % CI 1.16-4.72, P =0.02) was observed for the association between CPS positivity and mortality among melioidosis patients. Conclusion. The performance of the DPP® Fever Panel II Asia for diagnosis of malaria was high and that for dengue and melioidosis was relatively limited. For all three diseases, performance was comparable to that of other established RDTs. The potential operational advantages of a multiplex and quantitative point-of-care assay are substantial and warrant further investigation.
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- 2022
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39. Global influenza surveillance systems to detect the spread of influenza-negative influenza-like illness during the COVID-19 pandemic: Time series outlier analyses from 2015-2020.
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Cobb NL, Collier S, Attia EF, Augusto O, West TE, and Wagenaar BH
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- Humans, Pandemics, Population Surveillance methods, SARS-CoV-2, Time Factors, COVID-19 epidemiology, Influenza, Human diagnosis, Influenza, Human epidemiology, Virus Diseases
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Background: Surveillance systems are important in detecting changes in disease patterns and can act as early warning systems for emerging disease outbreaks. We hypothesized that analysis of data from existing global influenza surveillance networks early in the COVID-19 pandemic could identify outliers in influenza-negative influenza-like illness (ILI). We used data-driven methods to detect outliers in ILI that preceded the first reported peaks of COVID-19., Methods and Findings: We used data from the World Health Organization's Global Influenza Surveillance and Response System to evaluate time series outliers in influenza-negative ILI. Using automated autoregressive integrated moving average (ARIMA) time series outlier detection models and baseline influenza-negative ILI training data from 2015-2019, we analyzed 8,792 country-weeks across 28 countries to identify the first week in 2020 with a positive outlier in influenza-negative ILI. We present the difference in weeks between identified outliers and the first reported COVID-19 peaks in these 28 countries with high levels of data completeness for influenza surveillance data and the highest number of reported COVID-19 cases globally in 2020. To account for missing data, we also performed a sensitivity analysis using linear interpolation for missing observations of influenza-negative ILI. In 16 of the 28 countries (57%) included in this study, we identified positive outliers in cases of influenza-negative ILI that predated the first reported COVID-19 peak in each country; the average lag between the first positive ILI outlier and the reported COVID-19 peak was 13.3 weeks (standard deviation 6.8). In our primary analysis, the earliest outliers occurred during the week of January 13, 2020, in Peru, the Philippines, Poland, and Spain. Using linear interpolation for missing data, the earliest outliers were detected during the weeks beginning December 30, 2019, and January 20, 2020, in Poland and Peru, respectively. This contrasts with the reported COVID-19 peaks, which occurred on April 6 in Poland and June 1 in Peru. In many low- and middle-income countries in particular, the lag between detected outliers and COVID-19 peaks exceeded 12 weeks. These outliers may represent undetected spread of SARS-CoV-2, although a limitation of this study is that we could not evaluate SARS-CoV-2 positivity., Conclusions: Using an automated system of influenza-negative ILI outlier monitoring may have informed countries of the spread of COVID-19 more than 13 weeks before the first reported COVID-19 peaks. This proof-of-concept paper suggests that a system of influenza-negative ILI outlier monitoring could have informed national and global responses to SARS-CoV-2 during the rapid spread of this novel pathogen in early 2020., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: TEW: Funding for studies of respiratory infection from NIH and CDC. The other Authors have declared no competing interests.
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- 2022
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40. Chemokines, soluble PD-L1, and immune cell hyporesponsiveness are distinct features of SARS-CoV-2 critical illness.
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Morrell ED, Bhatraju PK, Sathe NA, Lawson J, Mabrey L, Holton SE, Presnell SR, Wiedeman A, Acosta-Vega C, Mitchem MA, Liu T, Chai XY, Sahi S, Brager C, Orlov M, Sakr SS, Sader A, Lum DM, Koetje N, Garay A, Barnes E, Cromer G, Bray MK, Pipavath S, Fink SL, Evans L, Long SA, West TE, Wurfel MM, and Mikacenic C
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- B7-H1 Antigen, Chemokines, Critical Illness, Humans, Prospective Studies, SARS-CoV-2, Tumor Necrosis Factor-alpha, COVID-19, Respiratory Insufficiency
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Critically ill patients manifest many of the same immune features seen in coronavirus disease 2019 (COVID-19), including both "cytokine storm" and "immune suppression." However, direct comparisons of molecular and cellular profiles between contemporaneously enrolled critically ill patients with and without severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are limited. We sought to identify immune signatures specifically enriched in critically ill patients with COVID-19 compared with patients without COVID-19. We enrolled a multisite prospective cohort of patients admitted under suspicion for COVID-19, who were then determined to be SARS-CoV-2-positive ( n = 204) or -negative ( n = 122). SARS-CoV-2-positive patients had higher plasma levels of CXCL10, sPD-L1, IFN-γ, CCL26, C-reactive protein (CRP), and TNF-α relative to SARS-CoV-2-negative patients adjusting for demographics and severity of illness (Bonferroni P value < 0.05). In contrast, the levels of IL-6, IL-8, IL-10, and IL-17A were not significantly different between the two groups. In SARS-CoV-2-positive patients, higher plasma levels of sPD-L1 and TNF-α were associated with fewer ventilator-free days (VFDs) and higher mortality rates (Bonferroni P value < 0.05). Lymphocyte chemoattractants such as CCL17 were associated with more severe respiratory failure in SARS-CoV-2-positive patients, but less severe respiratory failure in SARS-CoV-2-negative patients ( P value for interaction < 0.01). Circulating T cells and monocytes from SARS-CoV-2-positive subjects were hyporesponsive to in vitro stimulation compared with SARS-CoV-2-negative subjects. Critically ill SARS-CoV-2-positive patients exhibit an immune signature of high interferon-induced lymphocyte chemoattractants (e.g., CXCL10 and CCL17) and immune cell hyporesponsiveness when directly compared with SARS-CoV-2-negative patients. This suggests a specific role for T-cell migration coupled with an immune-checkpoint regulatory response in COVID-19-related critical illness.
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- 2022
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41. Plasma Soluble CD14 Subtype Levels Are Associated With Clinical Outcomes in Critically Ill Subjects With Coronavirus Disease 2019.
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Mabrey FL, Morrell ED, Bhatraju PK, Sathe NA, Sakr SS, Sahi SK, West TE, Mikacenic C, and Wurfel MM
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Importance: In bacterial sepsis, CD14 and its N-terminal fragment (soluble CD14 subtype, "Presepsin") have been characterized as markers of innate immune responses and emerging evidence has linked both to coronavirus disease 2019 pathophysiology., Objectives: Our aim was to determine the relationship between the soluble form of CD14 and soluble CD14 subtype plasma levels, coronavirus disease 2019 status, and coronavirus disease 2019-related outcomes., Design: A prospective cohort study., Setting: ICUs in three tertiary hospitals in Seattle, WA., Participants: Two-hundred four critically ill patients under investigation for coronavirus disease 2019., Main Outcomes and Measures: We measured plasma soluble CD14 and soluble CD14 subtype levels in samples collected upon admission. We tested for associations between biomarker levels and coronavirus disease 2019 status. We stratified by coronavirus disease 2019 status and tested for associations between biomarker levels and outcomes., Results: Among 204 patients, 102 patients had coronavirus disease 2019 and 102 patients did not. In both groups, the most common ICU admission diagnosis was respiratory failure or pneumonia and proportions receiving respiratory support at admission were similar. In regression analyses adjusting for age, sex, race/ethnicity, steroid therapy, comorbidities, and severity of illness, soluble CD14 subtype was 54% lower in coronavirus disease 2019 than noncoronavirus disease 2019 patients (fold difference, 0.46; 95% CI, 0.28-0.77; p = 0.003). In contrast to soluble CD14 subtype, soluble CD14 levels did not differ between coronavirus disease 2019 and noncoronavirus disease 2019 patients. In both coronavirus disease 2019 and noncoronavirus disease 2019, in analyses adjusting for age, sex, race/ethnicity, steroid therapy, and comorbidities, higher soluble CD14 subtype levels were associated with death (coronavirus disease 2019: adjusted relative risk, 1.21; 95% CI, 1.06-1.39; p = 0.006 and noncoronavirus disease 2019: adjusted relative risk, 1.19; 95% CI, 1.03-1.38; p = 0.017), shock, and fewer ventilator-free days. In coronavirus disease 2019 only, an increase in soluble CD14 subtype was associated with severe acute kidney injury (adjusted relative risk, 1.23; 95% CI, 1.05-1.44; p = 0.013)., Conclusions: Higher plasma soluble CD14 subtype is associated with worse clinical outcomes in critically ill patients irrespective of coronavirus disease 2019 status though soluble CD14 subtype levels were lower in coronavirus disease 2019 patients than noncoronavirus disease 2019 patients. Soluble CD14 subtype levels may have prognostic utility in coronavirus disease 2019., Competing Interests: The authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)
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- 2021
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42. Progressive Pulmonary Fibrosis After Non-Critical COVID-19: A Case Report.
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Doane JJ, Hirsch KS, Baldwin JO, Wurfel MM, Pipavath SN, and West TE
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- Adult, Humans, Male, Pandemics, SARS-CoV-2, COVID-19, Pulmonary Fibrosis etiology, Respiratory Distress Syndrome etiology
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BACKGROUND The COVID-19 global pandemic is ongoing, and despite vaccination efforts, SARS-CoV-2 continues to circulate worldwide. The spectrum of COVID-19 illness is broad, from asymptomatic infection to respiratory failure and acute respiratory distress syndrome (ARDS), and the long-term sequelae of infection are unclear. COVID-19-related pulmonary fibrosis has been previously described in the setting of critical illness and ARDS but has not been well described in cases requiring minimal supplemental oxygen. CASE REPORT We present the case of a 42-year-old man hospitalized with coronavirus disease 2019 (COVID-19) who initially required minimal supplemental oxygen but weeks later developed progressive pulmonary fibrosis requiring high-flow nasal cannula and ICU admission. Using novel computed tomography (CT) imaging processing techniques, we demonstrate progression from initial ground-glass opacities to pulmonary fibrosis and traction bronchiectasis over several months. Additionally, we describe clinical responsiveness to an extended course of corticosteroids. CONCLUSIONS Although pulmonary fibrosis is a known complication of severe COVID-19-related ARDS requiring mechanical ventilation, our report suggests that patients with milder forms of COVID-19 infection may develop post-acute pulmonary fibrosis.
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- 2021
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43. Evaluation of antigen-detecting and antibody-detecting diagnostic test combinations for diagnosing melioidosis.
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Amornchai P, Hantrakun V, Wongsuvan G, Wuthiekanun V, Wongratanacheewin S, Teparrakkul P, West TE, AuCoin DP, Day NPJ, Brett PJ, Burtnick MN, Chantratitra N, and Limmathurotsakul D
- Subjects
- Antibodies, Bacterial immunology, Antigens, Bacterial immunology, Burkholderia pseudomallei immunology, Burkholderia pseudomallei isolation & purification, Case-Control Studies, Humans, Melioidosis microbiology, Prospective Studies, Antibodies, Bacterial analysis, Antigens, Bacterial analysis, Diagnostic Tests, Routine methods, Enzyme-Linked Immunosorbent Assay methods, Melioidosis diagnosis
- Abstract
Background: Melioidosis, an infectious disease caused by Burkholderia pseudomallei, is endemic in many tropical developing countries and has a high mortality. Here we evaluated combinations of a lateral flow immunoassay (LFI) detecting B. pseudomallei capsular polysaccharide (CPS) and enzyme-linked immunosorbent assays (ELISA) detecting antibodies against hemolysin co-regulated protein (Hcp1) or O-polysaccharide (OPS) for diagnosing melioidosis., Methodology/principal Findings: We conducted a cohort-based case-control study. Both cases and controls were derived from a prospective observational study of patients presenting with community-acquired infections and sepsis in northeast Thailand (Ubon-sepsis). Cases included 192 patients with a clinical specimen culture positive for B. pseudomallei. Controls included 502 patients who were blood culture positive for Staphylococcus aureus, Escherichia coli or Klebsiella pneumoniae or were polymerase chain reaction assay positive for malaria or dengue. Serum samples collected within 24 hours of admission were stored and tested using a CPS-LFI, Hcp1-ELISA and OPS-ELISA. When assessing diagnostic tests in combination, results were considered positive if either test was positive. We selected ELISA cut-offs corresponding to a specificity of 95%. Using a positive cut-off OD of 2.912 for Hcp1-ELISA, the combination of the CPS-LFI and Hcp1-ELISA had a sensitivity of 67.7% (130/192 case patients) and a specificity of 95.0% (477/502 control patients). The sensitivity of the combination (67.7%) was higher than that of the CPS-LFI alone (31.3%, p<0.001) and that of Hcp1-ELISA alone (53.6%, p<0.001). A similar phenomenon was also observed for the combination of CPS-LFI and OPS-ELISA. In case patients, positivity of the CPS-LFI was associated with a short duration of symptoms, high modified Sequential (sepsis-related) Organ Failure Assessment (SOFA) score, bacteraemia and mortality outcome, while positivity of Hcp1-ELISA was associated with a longer duration of symptoms, low modified SOFA score, non-bacteraemia and survival outcome., Conclusions/significance: A combination of antigen-antibody diagnostic tests increased the sensitivity of melioidosis diagnosis over individual tests while preserving high specificity. Point-of-care tests for melioidosis based on the use of combination assays should be further developed and evaluated., Competing Interests: The authors have declared that no competing interests exist.
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- 2021
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44. Comparative clinical characteristics and outcomes of patients with community acquired bacteremia caused by Escherichia coli, Burkholderia pseudomallei and Staphylococcus aureus: A prospective observational study (Ubon-sepsis).
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Somayaji R, Hantrakun V, Teparrukkul P, Wongsuvan G, Rudd KE, Day NPJ, West TE, and Limmathurotsakul D
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- Adult, Aged, Aged, 80 and over, Anti-Bacterial Agents therapeutic use, Bacteremia drug therapy, Bacteremia epidemiology, Bacteremia mortality, Blood microbiology, Burkholderia pseudomallei drug effects, Burkholderia pseudomallei genetics, Burkholderia pseudomallei isolation & purification, Community-Acquired Infections drug therapy, Community-Acquired Infections epidemiology, Community-Acquired Infections mortality, Escherichia coli drug effects, Escherichia coli genetics, Escherichia coli isolation & purification, Female, Humans, Male, Middle Aged, Prospective Studies, Staphylococcus aureus drug effects, Staphylococcus aureus genetics, Staphylococcus aureus isolation & purification, Thailand epidemiology, Young Adult, Bacteremia microbiology, Burkholderia pseudomallei physiology, Community-Acquired Infections microbiology, Escherichia coli physiology, Staphylococcus aureus physiology
- Abstract
Background: Community acquired bacteremia (CAB) is a common cause of sepsis in low and middle-income countries (LMICs). However, knowledge about factors associated with outcomes of CAB in LMICs is limited., Methodology/principal Findings: A prospective observational study (Ubon-sepsis) of adults admitted to a referral hospital with community-acquired infection in Northeastern Thailand was conducted between March 1, 2013 and February 1, 2017. In the present analysis, patients with a blood culture collected within 24 hours of admission that was positive for one of the three most common pathogens were studied. Clinical features, management, and outcomes of patients with each cause of CAB were compared. Of 3,806 patients presenting with community-acquired sepsis, 155, 131 and 37 patients had a blood culture positive for Escherichia coli, Burkholderia pseudomallei and Staphylococcus aureus, respectively. Of these 323 CAB patients, 284 (89%) were transferred from other hospitals. 28-day mortality was highest in patients with B. pseudomallei bactaeremia (66%), followed by those with S. aureus bacteraemia (43%) and E. coli (19%) bacteraemia. In the multivariable Cox proportional hazards model adjusted for age, sex, transfer from another hospital, empirical antibiotics prior to or during the transfer, and presence of organ dysfunction on admission, B. pseudomallei (aHR 3.78; 95%CI 2.31-6.21) and S. aureus (aHR 2.72; 95%CI 1.40-5.28) bacteraemias were associated with higher mortality compared to E. coli bacteraemia. Receiving empirical antibiotics recommended for CAB caused by the etiologic organism prior to or during transfer was associated with survival (aHR 0.58; 95%CI 0.38-0.88)., Conclusions/significance: Mortality of patients with CAB caused by B. pseudomallei was higher than those caused by S. aureus and E. coli, even after adjusting for presence of organ dysfunction on admission and effectiveness of empirical antibiotics received. Improving algorithms or rapid diagnostic tests to guide early empirical antibiotic may be key to improving CAB outcomes in LMICs., Competing Interests: The authors have declared that no competing interests exist.
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- 2021
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45. Melioidosis Patient Survival Correlates With Strong IFN-γ Secreting T Cell Responses Against Hcp1 and TssM.
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Sengyee S, Yarasai A, Janon R, Morakot C, Ottiwet O, Schmidt LK, West TE, Burtnick MN, Chantratita N, and Brett PJ
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- Adult, Burkholderia pseudomallei immunology, Female, Humans, Male, Middle Aged, Thailand, Bacterial Proteins immunology, CD4-Positive T-Lymphocytes immunology, Interferon-gamma immunology, Melioidosis immunology, Melioidosis mortality, Virulence Factors immunology
- Abstract
Melioidosis, caused by the Gram-negative bacterium Burkholderia pseudomallei , is a serious infectious disease with diverse clinical manifestations. The morbidity and mortality of melioidosis is high in Southeast Asia and no licensed vaccines currently exist. This study was aimed at evaluating human cellular and humoral immune responses in Thai adults against four melioidosis vaccine candidate antigens. Blood samples from 91 melioidosis patients and 100 healthy donors from northeast Thailand were examined for immune responses against B. pseudomallei Hcp1, AhpC, TssM and LolC using a variety of cellular and humoral immune assays including IFN-γ ELISpot assays, flow cytometry and ELISA. PHA and a CPI peptide pool were also used as control stimuli in the ELISpot assays. Hcp1 and TssM stimulated strong IFN-γ secreting T cell responses in acute melioidosis patients which correlated with survival. High IFN-γ secreting CD4
+ T cell responses were observed during acute melioidosis. Interestingly, while T cell responses of melioidosis patients against the CPI peptide pool were low at the time of enrollment, the levels increased to the same as in healthy donors by day 28. Although high IgG levels against Hcp1 and AhpC were detected in acute melioidosis patients, no significant differences between survivors and non-survivors were observed. Collectively, these studies help to further our understanding of immunity against disease following natural exposure of humans to B. pseudomallei as well as provide important insights for the selection of candidate antigens for use in the development of safe and effective melioidosis subunit vaccines., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sengyee, Yarasai, Janon, Morakot, Ottiwet, Schmidt, West, Burtnick, Chantratita and Brett.)- Published
- 2021
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46. Reducing antibiotic treatment duration for ventilator-associated pneumonia (REGARD-VAP): a trial protocol for a randomised clinical trial.
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Mo Y, West TE, MacLaren G, Booraphun S, Li AY, Kayastha G, Lau YH, Chew YT, Chetchotisakd P, Tambyah PA, Limmathurotsakul D, and Cooper B
- Subjects
- Adult, Anti-Bacterial Agents therapeutic use, Duration of Therapy, Humans, Nepal, Randomized Controlled Trials as Topic, Singapore, Thailand, Pneumonia, Ventilator-Associated drug therapy
- Abstract
Introduction: Ventilator-associated pneumonia (VAP) is the most common nosocomial infection in intensive care units (ICUs). Using short-course antibiotics to treat VAP caused by Gram-negative non-fermenting bacteria has been reported to be associated with excess pneumonia recurrences. The "REducinG Antibiotic tReatment Duration for Ventilator-Associated Pneumonia" (REGARD-VAP) trial aims to provide evidence for using a set of reproducible clinical criteria to shorten antibiotic duration for individualised treatment duration of VAP., Methods and Analysis: This is a randomised controlled hierarchical non-inferiority-superiority trial being conducted in ICUs across Nepal, Thailand and Singapore. The primary outcome is a composite endpoint of death and pneumonia recurrence at day 60. Secondary outcomes include ventilator-associated events, multidrug-resistant organism infection or colonisation, total duration of antibiotic exposure, mechanical ventilation and hospitalisation. Adult patients who satisfy the US Centers for Disease Control and Prevention National Healthcare Safety Network VAP diagnostic criteria are enrolled. Participants are assessed daily until fever subsides for >48 hours and have stable blood pressure, then randomised to a short duration treatment strategy or a standard-of-care duration arm. Antibiotics may be stopped as early as day 3 if respiratory cultures are negative, and day 5 if respiratory cultures are positive in the short-course arm. Participants receiving standard-of-care will receive antibiotics for at least 8 days. Study participants are followed for 60 days after enrolment. An estimated 460 patients will be required to achieve 80% power to determine non-inferiority with a margin of 12%. All outcomes are compared by absolute risk differences. The conclusion of non-inferiority, and subsequently superiority, will be based on unadjusted and adjusted analyses in both the intention-to-treat and per-protocol populations., Ethics and Dissemination: The study has received approvals from the Oxford Tropical Research Ethics Committee and the respective study sites. Results will be disseminated to patients, their caregivers, physicians, the funders, the critical care societies and other researchers., Trial Registration Number: NCT03382548., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)
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- 2021
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47. Comparison of host endothelial, epithelial and inflammatory response in ICU patients with and without COVID-19: a prospective observational cohort study.
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Bhatraju PK, Morrell ED, Zelnick L, Sathe NA, Chai XY, Sakr SS, Sahi SK, Sader A, Lum DM, Liu T, Koetje N, Garay A, Barnes E, Lawson J, Cromer G, Bray MK, Pipavath S, Kestenbaum BR, Liles WC, Fink SL, West TE, Evans L, Mikacenic C, and Wurfel MM
- Subjects
- Adult, Aged, Biomarkers blood, COVID-19 epidemiology, COVID-19 therapy, Case-Control Studies, Female, Humans, Inflammation blood, Intensive Care Units, Male, Middle Aged, Prospective Studies, COVID-19 blood, Endothelial Cells virology, Epithelial Cells virology, Host Microbial Interactions, Inflammation virology
- Abstract
Background: Analyses of blood biomarkers involved in the host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral infection can reveal distinct biological pathways and inform development and testing of therapeutics for COVID-19. Our objective was to evaluate host endothelial, epithelial and inflammatory biomarkers in COVID-19., Methods: We prospectively enrolled 171 ICU patients, including 78 (46%) patients positive and 93 (54%) negative for SARS-CoV-2 infection from April to September, 2020. We compared 22 plasma biomarkers in blood collected within 24 h and 3 days after ICU admission., Results: In critically ill COVID-19 and non-COVID-19 patients, the most common ICU admission diagnoses were respiratory failure or pneumonia, followed by sepsis and other diagnoses. Similar proportions of patients in both groups received invasive mechanical ventilation at the time of study enrollment. COVID-19 and non-COVID-19 patients had similar rates of acute respiratory distress syndrome, severe acute kidney injury, and in-hospital mortality. While concentrations of interleukin 6 and 8 were not different between groups, markers of epithelial cell injury (soluble receptor for advanced glycation end products, sRAGE) and acute phase proteins (serum amyloid A, SAA) were significantly higher in COVID-19 compared to non-COVID-19, adjusting for demographics and APACHE III scores. In contrast, angiopoietin 2:1 (Ang-2:1 ratio) and soluble tumor necrosis factor receptor 1 (sTNFR-1), markers of endothelial dysfunction and inflammation, were significantly lower in COVID-19 (p < 0.002). Ang-2:1 ratio and SAA were associated with mortality only in non-COVID-19 patients., Conclusions: These studies demonstrate that, unlike other well-studied causes of critical illness, endothelial dysfunction may not be characteristic of severe COVID-19 early after ICU admission. Pathways resulting in elaboration of acute phase proteins and inducing epithelial cell injury may be promising targets for therapeutics in COVID-19.
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- 2021
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48. Comparison of Clinical Features and Outcomes in Critically Ill Patients Hospitalized with COVID-19 versus Influenza.
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Cobb NL, Sathe NA, Duan KI, Seitz KP, Thau MR, Sung CC, Morrell ED, Mikacenic C, Kim HN, Liles WC, Luks AM, Town J, Pipavath S, Wurfel MM, Hough CL, West TE, and Bhatraju PK
- Subjects
- Adult, Aged, COVID-19 diagnosis, Critical Care, Critical Illness, Female, Hospital Mortality, Hospitalization, Humans, Influenza, Human diagnosis, Male, Middle Aged, Respiration, Artificial, Retrospective Studies, United States, COVID-19 mortality, COVID-19 therapy, Influenza, Human mortality, Influenza, Human therapy
- Abstract
Rationale: No direct comparisons of clinical features, laboratory values, and outcomes between critically ill patients with coronavirus disease (COVID-19) and patients with influenza in the United States have been reported. Objectives: To evaluate the risk of mortality comparing critically ill patients with COVID-19 with patients with seasonal influenza. Methods: We retrospectively identified patients admitted to the intensive care units (ICUs) at two academic medical centers with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or influenza A or B infections between January 1, 2019, and April 15, 2020. The clinical data were obtained by medical record review. All patients except one had follow-up to hospital discharge or death. We used relative risk regression adjusting for age, sex, number of comorbidities, and maximum sequential organ failure scores on Day 1 in the ICU to determine the risk of hospital mortality and organ dysfunction in patients with COVID-19 compared with patients with influenza. Results: We identified 65 critically ill patients with COVID-19 and 74 patients with influenza. The mean (±standard deviation) age in each group was 60.4 ± 15.7 and 56.8 ± 17.6 years, respectively. Patients with COVID-19 were more likely to be male, have a higher body mass index, and have higher rates of chronic kidney disease and diabetes. Of the patients with COVID-19, 37% identified as Hispanic, whereas 10% of the patients with influenza identified as Hispanic. A similar proportion of patients had fevers (∼40%) and lymphopenia (∼80%) on hospital presentation. The rates of acute kidney injury and shock requiring vasopressors were similar between the groups. Although the need for invasive mechanical ventilation was also similar in both groups, patients with COVID-19 had slower improvements in oxygenation, longer durations of mechanical ventilation, and lower rates of extubation than patients with influenza. The hospital mortality was 40% in patients with COVID-19 and 19% in patients with influenza (adjusted relative risk, 2.13; 95% confidence interval, 1.24-3.63; P = 0.006). Conclusions: The need for invasive mechanical ventilation was common in patients in the ICU for COVID-19 and influenza. Compared with those with influenza, patients in the ICU with COVID-19 had worse respiratory outcomes, including longer duration of mechanical ventilation. In addition, patients with COVID-19 were at greater risk for in-hospital mortality, independent of age, sex, comorbidities, and ICU severity of illness.
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- 2021
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49. A 2-Biomarker Model Augments Clinical Prediction of Mortality in Melioidosis.
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Wright SW, Kaewarpai T, Lovelace-Macon L, Ducken D, Hantrakun V, Rudd KE, Teparrukkul P, Phunpang R, Ekchariyawat P, Dulsuk A, Moonmueangsan B, Morakot C, Thiansukhon E, Limmathurotsakul D, Chantratita N, and West TE
- Subjects
- Adult, Biomarkers blood, Burkholderia pseudomallei, Humans, Thailand, Cytokines blood, Melioidosis diagnosis, Melioidosis mortality
- Abstract
Background: Melioidosis, infection caused by Burkholderia pseudomallei, is a common cause of sepsis with high associated mortality in Southeast Asia. Identification of patients at high likelihood of clinical deterioration is important for guiding decisions about resource allocation and management. We sought to develop a biomarker-based model for 28-day mortality prediction in melioidosis., Methods: In a derivation set (N = 113) of prospectively enrolled, hospitalized Thai patients with melioidosis, we measured concentrations of interferon-γ, interleukin-1β, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-ɑ, granulocyte-colony stimulating factor, and interleukin-17A. We used least absolute shrinkage and selection operator (LASSO) regression to identify a subset of predictive biomarkers and performed logistic regression and receiver operating characteristic curve analysis to evaluate biomarker-based prediction of 28-day mortality compared with clinical variables. We repeated select analyses in an internal validation set (N = 78) and in a prospectively enrolled external validation set (N = 161) of hospitalized adults with melioidosis., Results: All 8 cytokines were positively associated with 28-day mortality. Of these, interleukin-6 and interleukin-8 were selected by LASSO regression. A model consisting of interleukin-6, interleukin-8, and clinical variables significantly improved 28-day mortality prediction over a model of only clinical variables [AUC (95% confidence interval [CI]): 0.86 (.79-.92) vs 0.78 (.69-.87); P = .01]. In both the internal validation set (0.91 [0.84-0.97]) and the external validation set (0.81 [0.74-0.88]), the combined model including biomarkers significantly improved 28-day mortality prediction over a model limited to clinical variables., Conclusions: A 2-biomarker model augments clinical prediction of 28-day mortality in melioidosis., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.)
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- 2021
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50. Effectiveness of a sepsis programme in a resource-limited setting: a retrospective analysis of data of a prospective observational study (Ubon-sepsis).
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Booraphun S, Hantrakun V, Siriboon S, Boonsri C, Poomthong P, Singkaew BO, Wasombat O, Chamnan P, Champunot R, Rudd K, Day NPJ, Dondorp AM, Teparrukkul P, West TE, and Limmathurotsakul D
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- Hospital Mortality, Humans, Intensive Care Units, Prospective Studies, Retrospective Studies, Thailand, Organ Dysfunction Scores, Sepsis therapy
- Abstract
Objective: To evaluate the effectiveness of a Sepsis Fast Track (SFT) programme initiated at a regional referral hospital in Thailand in January 2015., Design: A retrospective analysis using the data of a prospective observational study (Ubon-sepsis) from March 2013 to January 2017., Setting: General medical wards and medical intensive care units (ICUs) of a study hospital., Participants: Patients with community-acquired sepsis observed under the Ubon-sepsis cohort. Sepsis was defined as modified Sequential Organ Failure Assessment (SOFA) Score ≥2., Main Exposure: The SFT programme was a protocol to identify and initiate sepsis care on hospital admission, implemented at the study hospital in 2015. Patients in the SFT programme were admitted directly to the ICUs when available. The non-exposed group comprised of patients who received standard of care., Main Outcome: The primary outcome was 28-day mortality. The secondary outcomes were measured sepsis management interventions., Results: Of 3806 sepsis patients, 903 (24%) were detected and enrolled in the SFT programme of the study hospital (SFT group) and 2903 received standard of care (non-exposed group). Patients in the SFT group had more organ dysfunction, were more likely to receive measured sepsis management and to be admitted directly to the ICU (19% vs 4%). Patients in the SFT group were more likely to survive (adjusted HR 0.72, 95% CI 0.58 to 0.88, p=0.001) adjusted for admission year, gender, age, comorbidities, modified SOFA Score and direct admission to the ICUs., Conclusions: The SFT programme is associated with improved sepsis care and lower risk of death in sepsis patients in rural Thailand, where some critical care resources are limited. The survival benefit is observed even when all patients enrolled in the programme could not be admitted directly into the ICUs., Trial Registration Number: NCT02217592., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)
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- 2021
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