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1. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Author

Schumacher, AE, Kyu, HH, Antony, CM, Aravkin, AY, Azhar, GS, Bisignano, C, Burkart, K, Cercy, KM, Chung, E, Coberly, K, Comfort, H, Cousin, E, Culbreth, GT, Cunningham, M, Weaver, ND, Degenhardt, L ; https://orcid.org/0000-0002-8513-2218, Deitesfeld, L, Dirac, MA, Estep, K, Feigin, VL, Flaxman, AD, Flor, LS, Force, LM, Fuller, JE, Gakidou, E, Hay, SI, Ikuta, KS, Jones, DP, Kassebaum, NJ, Kassel, MB, Keller, C, Kinzel, KE, Krohn, KJ, Lozano, R, May, EA, McKowen, ALW, McLaughlin, SA, Mehlman, ML, Mestrovic, T, Mokdad, AH, Mosser, JF, Mougin, V, Naghavi, M, Nesbit, OD, Novotney, A, Ozten, Y, Pease, SA, Pigott, DM, Reiner, RC, Robinson-Oden, HE, Shaw, DH, Slepak, ELN, Sorensen, RJD, Verghese, NA, Vollset, SE, Vongpradith, A, Vos, T, Wang, D, Watson, S, Weaver, MR, Wells, KM, Wilson, S, Wool, EE, Zheng, P, Lim, SS, Murray, CJL, Boyko, EJ, Chahine, Y, Kalani, R, Krishnamoorthy, V, Khalil, IA, Minja, NW, Morrison, SD, Nafukho, FM, Olivas-Martinez, A, Orellana, ER, Tram, KH, Aali, A, Rahnavard, N, Ahmadzade, AM, Mohammad-Pour, S, Morovatdar, N, Pourali, G, Zafari, N, Abbafati, C, Cattaruzza, MS, Abbas, J, Phillips, MR, Abbasgholizadeh, R, Emamverdi, M, Friedman, J, Abbasi, MA, Daneshvar, S, Dashti, M, Ghasemzadeh, A, Mirza-Aghazadeh-Attari, M, Doshmangir, L, Ghafourifard, M, Lotfi, M, Hosseini, MS, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Addo, Isaac, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Aboagye, Richard ; https://orcid.org/0000-0002-3498-2909, Huda, Md Nazmul ; https://orcid.org/0000-0001-7048-1266, Cullen, Patricia ; https://orcid.org/0000-0003-4652-0936, Sitas, Freddy ; https://orcid.org/0000-0001-9679-1481, Si, Yafei ; https://orcid.org/0000-0001-9334-8230, Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692, Schumacher, AE, Kyu, HH, Antony, CM, Aravkin, AY, Azhar, GS, Bisignano, C, Burkart, K, Cercy, KM, Chung, E, Coberly, K, Comfort, H, Cousin, E, Culbreth, GT, Cunningham, M, Weaver, ND, Degenhardt, L ; https://orcid.org/0000-0002-8513-2218, Deitesfeld, L, Dirac, MA, Estep, K, Feigin, VL, Flaxman, AD, Flor, LS, Force, LM, Fuller, JE, Gakidou, E, Hay, SI, Ikuta, KS, Jones, DP, Kassebaum, NJ, Kassel, MB, Keller, C, Kinzel, KE, Krohn, KJ, Lozano, R, May, EA, McKowen, ALW, McLaughlin, SA, Mehlman, ML, Mestrovic, T, Mokdad, AH, Mosser, JF, Mougin, V, Naghavi, M, Nesbit, OD, Novotney, A, Ozten, Y, Pease, SA, Pigott, DM, Reiner, RC, Robinson-Oden, HE, Shaw, DH, Slepak, ELN, Sorensen, RJD, Verghese, NA, Vollset, SE, Vongpradith, A, Vos, T, Wang, D, Watson, S, Weaver, MR, Wells, KM, Wilson, S, Wool, EE, Zheng, P, Lim, SS, Murray, CJL, Boyko, EJ, Chahine, Y, Kalani, R, Krishnamoorthy, V, Khalil, IA, Minja, NW, Morrison, SD, Nafukho, FM, Olivas-Martinez, A, Orellana, ER, Tram, KH, Aali, A, Rahnavard, N, Ahmadzade, AM, Mohammad-Pour, S, Morovatdar, N, Pourali, G, Zafari, N, Abbafati, C, Cattaruzza, MS, Abbas, J, Phillips, MR, Abbasgholizadeh, R, Emamverdi, M, Friedman, J, Abbasi, MA, Daneshvar, S, Dashti, M, Ghasemzadeh, A, Mirza-Aghazadeh-Attari, M, Doshmangir, L, Ghafourifard, M, Lotfi, M, Hosseini, MS, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Sharma, Saurab ; https://orcid.org/0000-0002-9817-5372, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Addo, Isaac, Biswas, Raaj Kishore ; https://orcid.org/0000-0003-4294-6323, Okeke, Sylvester ; https://orcid.org/0000-0001-9211-1813, Aboagye, Richard ; https://orcid.org/0000-0002-3498-2909, Huda, Md Nazmul ; https://orcid.org/0000-0001-7048-1266, Cullen, Patricia ; https://orcid.org/0000-0003-4652-0936, Sitas, Freddy ; https://orcid.org/0000-0001-9679-1481, Si, Yafei ; https://orcid.org/0000-0001-9334-8230, and Dai-Keller, Zhaoli ; https://orcid.org/0000-0003-0809-5692

Abstract

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, ant

Published
2024

2. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Author

Ong, KL, Stafford, LK, McLaughlin, SA, Boyko, EJ, Vollset, SE, Smith, AE, Dalton, BE, Duprey, J, Cruz, JA, Hagins, H, Lindstedt, PA, Aali, A, Abate, YH, Abate, MD, Abbasian, M, Abbasi-Kangevari, Z, Abbasi-Kangevari, M, ElHafeez, SA, Abd-Rabu, R, Abdulah, DM, Abdullah, AYM, Abedi, V, Abidi, H, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, Abolhassani, H, Abu-Gharbieh, E, Abu-Zaid, A, Adane, TD, Adane, DE, Addo, IY, Adegboye, OA, Adekanmbi, V, Adepoju, AV, Adnani, QES, Afolabi, RF, Agarwal, G, Aghdam, ZB, Agudelo-Botero, M, Arriagada, CEA, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, D, Ahmad, R, Ahmad, S, Ahmad, A, Ahmadi, A, Ahmadi, K, Ahmed, A, Ahmed, LA, Ahmed, SA, Ajami, M, Akinyemi, RO, Al Hamad, H, Al Hasan, SM, AL-Ahdal, TMA, Alalwan, TA, Al-Aly, Z, AlBataineh, MT, Alcalde-Rabanal, JE, Alemi, S, Ali, H, Alinia, T, Aljunid, SM, Almustanyir, S, Al-Raddadi, RM, Alvis-Guzman, N, Amare, F, Ameyaw, EK, Amiri, S, Amusa, GA, Andrei, CL, Anjana, RM, Ansar, A, Ansari, G, Ansari-Moghaddam, A, Anyasodor, AE, Arabloo, J, Aravkin, AY, Areda, D, Arifin, H, Arkew, M, Armocida, B, Arnlov, J, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Aryan, Z, Asemu, MT, Asghari-Jafarabadi, M, Askari, E, Asmelash, D, Astell-Burt, T, Athar, M, Athari, SS, Atout, MMDW, Avila-Burgos, L, Awaisu, A, Azadnajafabad, S, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Bhaskar, Sonu, Sundstorm, Johan ; https://orcid.org/0000-0003-2247-8454, Feng, Xiaoqi ; https://orcid.org/0000-0002-3421-220X, Huda, Md Nazmul ; https://orcid.org/0000-0001-7048-1266, Ong, KL, Stafford, LK, McLaughlin, SA, Boyko, EJ, Vollset, SE, Smith, AE, Dalton, BE, Duprey, J, Cruz, JA, Hagins, H, Lindstedt, PA, Aali, A, Abate, YH, Abate, MD, Abbasian, M, Abbasi-Kangevari, Z, Abbasi-Kangevari, M, ElHafeez, SA, Abd-Rabu, R, Abdulah, DM, Abdullah, AYM, Abedi, V, Abidi, H, Aboagye, RG ; https://orcid.org/0000-0002-3498-2909, Abolhassani, H, Abu-Gharbieh, E, Abu-Zaid, A, Adane, TD, Adane, DE, Addo, IY, Adegboye, OA, Adekanmbi, V, Adepoju, AV, Adnani, QES, Afolabi, RF, Agarwal, G, Aghdam, ZB, Agudelo-Botero, M, Arriagada, CEA, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, D, Ahmad, R, Ahmad, S, Ahmad, A, Ahmadi, A, Ahmadi, K, Ahmed, A, Ahmed, LA, Ahmed, SA, Ajami, M, Akinyemi, RO, Al Hamad, H, Al Hasan, SM, AL-Ahdal, TMA, Alalwan, TA, Al-Aly, Z, AlBataineh, MT, Alcalde-Rabanal, JE, Alemi, S, Ali, H, Alinia, T, Aljunid, SM, Almustanyir, S, Al-Raddadi, RM, Alvis-Guzman, N, Amare, F, Ameyaw, EK, Amiri, S, Amusa, GA, Andrei, CL, Anjana, RM, Ansar, A, Ansari, G, Ansari-Moghaddam, A, Anyasodor, AE, Arabloo, J, Aravkin, AY, Areda, D, Arifin, H, Arkew, M, Armocida, B, Arnlov, J, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Aryan, Z, Asemu, MT, Asghari-Jafarabadi, M, Askari, E, Asmelash, D, Astell-Burt, T, Athar, M, Athari, SS, Atout, MMDW, Avila-Burgos, L, Awaisu, A, Azadnajafabad, S, Xu, Luna ; https://orcid.org/0000-0003-4787-6547, Bhaskar, Sonu, Sundstorm, Johan ; https://orcid.org/0000-0003-2247-8454, Feng, Xiaoqi ; https://orcid.org/0000-0002-3421-220X, and Huda, Md Nazmul ; https://orcid.org/0000-0001-7048-1266

Abstract

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparativ

Published
2023

3. Evaluating acute nipple inversion, imaging findings and outcomes.

Author

Hatcher KM, Leon A, Cornell LF, Jakub JW, McLaughlin SA, and Maimone S

Subjects
Humans, Female, Retrospective Studies, Middle Aged, Adult, Aged, Mammography methods, Sensitivity and Specificity, Aged, 80 and over, Young Adult, Nipples diagnostic imaging, Nipples pathology, Breast Neoplasms diagnostic imaging, Magnetic Resonance Imaging methods, Ultrasonography, Mammary methods
Abstract

Purpose: Acute nipple inversion can be unsettling for patients and is sometimes associated with an underlying breast malignancy. It also poses a diagnostic challenge with lack of consensus management guidelines. This study reviewed institutional experience with new nipple inversion, including malignant association, imaging utilization, and outcomes, in an effort to improve management., Methods: A multisite institutional retrospective review was conducted of all breast imaging reports from 1/2010 to 6/2022 mentioning nipple inversion as an indication or finding. Patients with new nipple inversion, defined as arising since the time of last breast imaging exam or if reported as new by the patient/provider, were included for analysis. Retroareolar imaging findings, BI-RADS assessments/recommendations, pathology obtained from percutaneous or excisional biopsies, and follow-up imaging and clinical exams were collated. Cases of chronic or stable nipple inversion were excluded. Descriptive statistics were performed., Results: A total of 414 patients had new nipple inversion, 387/414 (93.5 %) with benign or negative results at initial imaging and 27/414 (6.5 %) with malignant lesions. Diagnostic mammography/ultrasound detected 25/27 (92.6 %) cancers (sensitivity 92.6 %, specificity 75.5 %, PPV 20.8 %, NPV 99.3 %). Of 62 breast MRI exams performed in patients with negative mammogram/ultrasound, no cancers were detected in the retroareolar space with 2 incidental malignant lesions discovered distant from the nipple., Conclusion: Diagnostic mammography/ultrasound is reliable in workups of acute nipple inversion, with a high sensitivity and NPV for excluding malignancy. Breast MRI and surgical referral should be reserved for patients with suspicious associated symptoms or clinical findings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Published
2024
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4. The impact of COVID-19 on health care-associated infections in intensive care units in low- and middle-income countries: International Nosocomial Infection Control Consortium (INICC) findings.

Author

Rosenthal VD, Myatra SN, Divatia JV, Biswas S, Shrivastava A, Al-Ruzzieh MA, Ayaad O, Bat-Erdene A, Bat-Erdene I, Narankhuu B, Gupta D, Mandal S, Sengupta S, Joudi H, Omeis I, Agha HM, Fathallala A, Mohahmed EH, Yesiler I, Oral M, Ozcelik M, Mehta Y, Sarma S, Chatterjee S, Belkebir S, Kanaa A, Jeetawi R, Mclaughlin SA, Shultz JM, Bearman G, Jin Z, and Yin R

Subjects
Delivery of Health Care, Developing Countries, Female, Humans, Intensive Care Units, Male, Pandemics, Prospective Studies, COVID-19 epidemiology, Cross Infection epidemiology, Cross Infection prevention & control, Pneumonia, Ventilator-Associated epidemiology, Urinary Tract Infections epidemiology
Abstract

Background: This study examines the impact of the COVID-19 pandemic on health care-associated infection (HAI) incidence in low- and middle-income countries (LMICs)., Methods: Patients from 7 LMICs were followed up during hospital intensive care unit (ICU) stays from January 2019 to May 2020. HAI rates were calculated using the International Nosocomial Infection Control Consortium (INICC) Surveillance Online System applying the Centers for Disease Control and Prevention's National Healthcare Safety Network (CDC-NHSN) criteria. Pre-COVID-19 rates for 2019 were compared with COVID-19 era rates for 2020 for central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated events (VAEs), mortality, and length of stay (LOS)., Results: A total of 7,775 patients were followed up for 49,506 bed days. The 2019 to 2020 rate comparisons were 2.54 and 4.73 CLABSIs per 1,000 central line days (risk ratio [RR] = 1.85, p = .0006), 9.71 and 12.58 VAEs per 1,000 mechanical ventilator days (RR = 1.29, p = .10), and 1.64 and 1.43 CAUTIs per 1,000 urinary catheter days (RR = 1.14; p = .69). Mortality rates were 15.2% and 23.2% for 2019 and 2020 (RR = 1.42; p < .0001), respectively. Mean LOS for 2019 and 2020 were 6.02 and 7.54 days (RR = 1.21, p < .0001), respectively., Discussion: This study documents an increase in HAI rates in 7 LMICs during the first 5 months of the COVID-19 pandemic and highlights the need to reprioritize and return to conventional infection prevention practices., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Published
2022
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5. Recalibrating the decision for MRI-directed breast ultrasound in patients with newly diagnosed breast cancer, factors predicting sonographic success.

Author

Maimone S, Morozov AP, Li Z, Craver EC, Elder EA, and McLaughlin SA

Subjects
Breast diagnostic imaging, Female, Humans, Magnetic Resonance Imaging, Retrospective Studies, Ultrasonography, Mammary, Breast Neoplasms diagnostic imaging
Abstract

Objective: Evaluate utilization of MRI-directed breast ultrasound (US) in patients with newly diagnosed breast cancer and refine practices to increase success of sonographic lesion detection., Methods: This retrospective single-institution review was restricted to women with breast cancer who underwent MRI from November 2006 to January 2017. Enhancing breast lesions, separate from the index tumor, recommended for MRI-directed US were assessed to see which were detected and which characteristics predicted success in detection. Univariate mixed-effects logistic modeling predicted likelihood of finding breast lesions with US, with odds ratios reported. All tests were two-sided with p < 0.05 considered significant., Results: A total of 275 patients underwent MRI-directed US for 361 breast lesions, of which 187 (51.8%) were found on US. Of those detected, 171 (91.4%) were masses and 16 (8.6%) were nonmass enhancement (NME), with masses 14 times more likely to be seen (p < 0.001). Size alone was not a significant predictor but achieved significance when associated with lesion type (mass size, p < 0.001). Masses with irregular shapes or margins and invasive carcinomas were more frequently detected. Patient age, internal enhancement pattern, and distribution of NME were not significant predictors in sonographic detection. A presumed sonographic correlate for NME was found for 16 (16.2%) of 99 attempted lesions., Conclusion: As MRI access expands, utilization of MRI-directed US should be scrutinized to avoid downstream practice inefficiencies. Sonographic detection rates for NME remain low for women undergoing MRI for disease extent, with NME often better suited for MRI-guided biopsy., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Published
2021
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