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148 results on '"Nazarzadeh, M."'

6. The Blood Pressure Lowering Treatment Trialists’ Collaboration: methodological clarifications of recent reports

Author

Nazarzadeh, M, Canoy, D, Bidel, Z, Copland, E, Rahimi, K, Teo, K, Davis, BR, Chalmers, J, Pepine, CJ, and Woodward, M

Subjects
Cognition, Cardiovascular Diseases, Systole, Physiology, Data Collection, Internal Medicine, Humans, Blood Pressure, Cardiology and Cardiovascular Medicine, Randomized Controlled Trials as Topic
Abstract

Epidemiological evidence has consistently shown that people with higher systolic or diastolic blood pressure are at greater risk of cardiovascular diseases. However, there has been limited randomized evidence to determine the role of blood pressure level at treatment initiation in the reduction of cardiovascular diseases risk. The extent to which other characteristics of individuals, such as prior disease history, age or sex, should be taken into account has also been controversial. Furthermore, effects on less commonly reported efficacy and safety outcomes remain underexplored. The Blood Pressure Lowering Treatment Trialists' Collaboration has collected individual-level participant data from 52 randomized clinical trials, with more than 360 000 participants, and is now the largest source of individual-level data from randomized clinical trials of blood pressure-lowering treatment. This resource provides an unprecedented opportunity to address major areas of uncertainty relating to stratified efficacy and safety of antihypertensive therapy. Recent reports have demonstrated the power of pooled analyses of the Blood Pressure Lowering Treatment Trialists' Collaboration dataset in filling long-standing gaps in our knowledge. However, there have been some misconceptions regarding the methods underpinning the recent reports, which we clarify in this article.

Published
2022

7. Systolic Blood Pressure and Cardiovascular Risk in Patients With Diabetes: A Prospective Cohort Study

Author

Rao, S, Li, Y, Nazarzadeh, M, Canoy, D, Mamouei, M, Hassaine, A, Salimi-Khorshidi, G, and Rahimi, K

Subjects
Internal Medicine
Abstract

Background: Whether the association between systolic blood pressure (SBP) and risk of cardiovascular disease is monotonic or whether there is a nadir of optimal blood pressure remains controversial. We investigated the association between SBP and cardiovascular events in patients with diabetes across the full spectrum of SBP. Methods: A cohort of 49 000 individuals with diabetes aged 50 to 90 years between 1990 and 2005 was identified from linked electronic health records in the United Kingdom. Associations between SBP and cardiovascular outcomes (ischemic heart disease, heart failure, stroke, and cardiovascular death) were analyzed using a deep learning approach. Results: Over a median follow-up of 7.3 years, 16 378 cardiovascular events were observed. The relationship between SBP and cardiovascular events followed a monotonic pattern, with the group with the lowest baseline SBP of Conclusions: Using deep learning modeling, we found a monotonic relationship between SBP and risk of cardiovascular outcomes in patients with diabetes, without evidence of a J-shaped relationship.

Published
2022

8. Blood pressure and risk of venous thromboembolism: a cohort analysis of 5.5 million UK adults and Mendelian randomization studies

Author

Nazarzadeh, M, Bidel, Z, Mohseni, H, Canoy, D, Pinho-Gomes, AC, Hassaine, A, Dehghan, A, Tregouet, DA, Smith, NL, Rahimi, K, and Consortium, INVENT

Subjects
Physiology, Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Evidence for the effect of elevated blood pressure on the risk of venous thromboembolism (VTE) has been conflicting. We sought to assess the association between systolic blood pressure and the risk of VTE.Three complementary studies comprising an observational cohort analysis, a one-sample and two-sample Mendelian randomization were conducted using data from 5,588,280 patients registered in the Clinical Practice Research Datalink (CPRD) dataset and 432,173 UK Biobank participants with valid genetic data. Summary statistics of International Network on Venous Thrombosis (INVENT) genome-wide association meta-analysis was used for two-sample Mendelian randomization. The primary outcome was the first occurrence of VTE event, identified from hospital discharge reports, death registers, and/or primary care records. In the CPRD cohort, 104,017 (1.9%) patients had a first diagnosis of VTE during the 9.6-year follow-up. Each 20 mmHg increase in systolic blood pressure was associated with a 7% lower risk of VTE (hazard ratio 0.93, 95% CI [0.92 to 0.94]). Statistically significant interactions were found for sex and body mass index, but not for age and subtype of VTE (pulmonary embolism and deep venous thrombosis). Mendelian randomization studies provided strong evidence for the association between systolic blood pressure and VTE, both in the one-sample (odds ratio [OR]: 0.69 [95% CI 0.57 to 0.83] and two-sample analyses (OR 0.80, 95% CI [0.70 to 0.92]).We found an increased risk of VTE with lower blood pressure and this association was independently confirmed in two Mendelian randomization analyses. The benefits of blood pressure reduction are likely to outweigh the harms in most patient groups, but in people with predisposing factors for VTE, further blood pressure reduction should be made cautiously.In a large-scale population cohort, with over 100,000 first episodes of VTE and a median follow-up of about 10 years, we found a 7% higher risk of VTE for each 20 mmHg lower systolic blood pressure. The association was comparable when we examined pulmonary embolism and deep venous thrombosis separately, and persisted after taking into account age and other factors, including anticoagulant treatment during follow-up. These results were confirmed using two independent Mendelian randomization studies. Although the beneficial effects of blood pressure-lowering are likely to outweigh any harms in most patient groups, clinicians should be aware of the potential risk of VTE from antihypertensive therapy, in particular in people who have predisposing factors for VTE.

Published
2022

9. Age-stratified and blood-pressure-stratified effects of blood-pressure-lowering pharmacotherapy for the prevention of cardiovascular disease and death: an individual participant-level data meta-analysis

Author

Rahimi, K, Bidel, Z, Nazarzadeh, M, Copland, E, Canoy, D, Wamil, M, Majert, J, Mcmanus, R, Adler, A, Agodoa, L, Algra, A, Asselbergs, F, Beckett, N, Berge, E, Black, H, Boersma, E, Brouwers, F, Brown, M, Brugts, J, Bulpitt, C, Byington, R, Cushman, W, Cutler, J, Devereaux, R, Dwyer, J, Estacio, R, Fagard, R, Fox, K, Fukui, T, Gupta, A, Holman, R, Imai, Y, Ishii, M, Julius, S, Kanno, Y, Kjeldsen, S, Kostis, J, Kuramoto, K, Lanke, J, Lewis, E, Lewis, J, Lievre, M, Lindholm, L, Lueders, S, Macmahon, S, Mancia, G, Matsuzaki, M, Mehlum, M, Nissen, S, Ogawa, H, Ogihara, T, Ohkubo, T, Palmer, C, Patel, A, Pfeffer, M, Pitt, B, Poulter, N, Rakugi, H, Reboldi, G, Reid, C, Remuzzi, G, Ruggenenti, P, Saruta, T, Schrader, J, Schrier, R, Sever, P, Sleight, P, Staessen, J, Suzuki, H, Thijs, L, Ueshima, K, Umemoto, S, van Gilst, W, Verdecchia, P, Wachtell, K, Whelton, P, Wing, L, Woodward, M, Yui, Y, Yusuf, S, Zanchetti, A, Zhang, Z, Anderson, C, Baigent, C, Brenner, B, Collins, R, de Zeeuw, D, Lubsen, J, Malacco, E, Neal, B, Perkovic, V, Rodgers, A, Rothwell, P, Salimi-Khorshidi, G, Sundstrom, J, Turnbull, F, Viberti, G, Wang, J, Chalmers, J, Davis, B, Pepine, C, Teo, K, Rahimi K., Bidel Z., Nazarzadeh M., Copland E., Canoy D., Wamil M., Majert J., McManus R., Adler A., Agodoa L., Algra A., Asselbergs F. W., Beckett N. S., Berge E., Black H., Boersma E., Brouwers F. P. J., Brown M., Brugts J. J., Bulpitt C. J., Byington R. P., Cushman W. C., Cutler J., Devereaux R. B., Dwyer J. P., Estacio R., Fagard R., Fox K., Fukui T., Gupta A. K., Holman R. R., Imai Y., Ishii M., Julius S., Kanno Y., Kjeldsen S. E., Kostis J., Kuramoto K., Lanke J., Lewis E., Lewis J. B., Lievre M., Lindholm L. H., Lueders S., MacMahon S., Mancia G., Matsuzaki M., Mehlum M. H., Nissen S., Ogawa H., Ogihara T., Ohkubo T., Palmer C. R., Patel A., Pfeffer M. A., Pitt B., Poulter N. R., Rakugi H., Reboldi G., Reid C., Remuzzi G., Ruggenenti P., Saruta T., Schrader J., Schrier R., Sever P., Sleight P., Staessen J. A., Suzuki H., Thijs L., Ueshima K., Umemoto S., van Gilst W. H., Verdecchia P., Wachtell K., Whelton P., Wing L., Woodward M., Yui Y., Yusuf S., Zanchetti A., Zhang Z. -Y., Anderson C., Baigent C., Brenner B. M., Collins R., de Zeeuw D., Lubsen J., Malacco E., Neal B., Perkovic V., Rodgers A., Rothwell P., Salimi-Khorshidi G., Sundstrom J., Turnbull F., Viberti G., Wang J., Chalmers J., Davis B. R., Pepine C. J., Teo K. K., Rahimi, K, Bidel, Z, Nazarzadeh, M, Copland, E, Canoy, D, Wamil, M, Majert, J, Mcmanus, R, Adler, A, Agodoa, L, Algra, A, Asselbergs, F, Beckett, N, Berge, E, Black, H, Boersma, E, Brouwers, F, Brown, M, Brugts, J, Bulpitt, C, Byington, R, Cushman, W, Cutler, J, Devereaux, R, Dwyer, J, Estacio, R, Fagard, R, Fox, K, Fukui, T, Gupta, A, Holman, R, Imai, Y, Ishii, M, Julius, S, Kanno, Y, Kjeldsen, S, Kostis, J, Kuramoto, K, Lanke, J, Lewis, E, Lewis, J, Lievre, M, Lindholm, L, Lueders, S, Macmahon, S, Mancia, G, Matsuzaki, M, Mehlum, M, Nissen, S, Ogawa, H, Ogihara, T, Ohkubo, T, Palmer, C, Patel, A, Pfeffer, M, Pitt, B, Poulter, N, Rakugi, H, Reboldi, G, Reid, C, Remuzzi, G, Ruggenenti, P, Saruta, T, Schrader, J, Schrier, R, Sever, P, Sleight, P, Staessen, J, Suzuki, H, Thijs, L, Ueshima, K, Umemoto, S, van Gilst, W, Verdecchia, P, Wachtell, K, Whelton, P, Wing, L, Woodward, M, Yui, Y, Yusuf, S, Zanchetti, A, Zhang, Z, Anderson, C, Baigent, C, Brenner, B, Collins, R, de Zeeuw, D, Lubsen, J, Malacco, E, Neal, B, Perkovic, V, Rodgers, A, Rothwell, P, Salimi-Khorshidi, G, Sundstrom, J, Turnbull, F, Viberti, G, Wang, J, Chalmers, J, Davis, B, Pepine, C, Teo, K, Rahimi K., Bidel Z., Nazarzadeh M., Copland E., Canoy D., Wamil M., Majert J., McManus R., Adler A., Agodoa L., Algra A., Asselbergs F. W., Beckett N. S., Berge E., Black H., Boersma E., Brouwers F. P. J., Brown M., Brugts J. J., Bulpitt C. J., Byington R. P., Cushman W. C., Cutler J., Devereaux R. B., Dwyer J. P., Estacio R., Fagard R., Fox K., Fukui T., Gupta A. K., Holman R. R., Imai Y., Ishii M., Julius S., Kanno Y., Kjeldsen S. E., Kostis J., Kuramoto K., Lanke J., Lewis E., Lewis J. B., Lievre M., Lindholm L. H., Lueders S., MacMahon S., Mancia G., Matsuzaki M., Mehlum M. H., Nissen S., Ogawa H., Ogihara T., Ohkubo T., Palmer C. R., Patel A., Pfeffer M. A., Pitt B., Poulter N. R., Rakugi H., Reboldi G., Reid C., Remuzzi G., Ruggenenti P., Saruta T., Schrader J., Schrier R., Sever P., Sleight P., Staessen J. A., Suzuki H., Thijs L., Ueshima K., Umemoto S., van Gilst W. H., Verdecchia P., Wachtell K., Whelton P., Wing L., Woodward M., Yui Y., Yusuf S., Zanchetti A., Zhang Z. -Y., Anderson C., Baigent C., Brenner B. M., Collins R., de Zeeuw D., Lubsen J., Malacco E., Neal B., Perkovic V., Rodgers A., Rothwell P., Salimi-Khorshidi G., Sundstrom J., Turnbull F., Viberti G., Wang J., Chalmers J., Davis B. R., Pepine C. J., and Teo K. K.

Abstract

Background: The effects of pharmacological blood-pressure-lowering on cardiovascular outcomes in individuals aged 70 years and older, particularly when blood pressure is not substantially increased, is uncertain. We compared the effects of blood-pressure-lowering treatment on the risk of major cardiovascular events in groups of patients stratified by age and blood pressure at baseline. Methods: We did a meta-analysis using individual participant-level data from randomised controlled trials of pharmacological blood-pressure-lowering versus placebo or other classes of blood-pressure-lowering medications, or between more versus less intensive treatment strategies, which had at least 1000 persons-years of follow-up in each treatment group. Participants with previous history of heart failure were excluded. Data were obtained from the Blood Pressure Lowering Treatment Triallists' Collaboration. We pooled the data and categorised participants into baseline age groups (<55 years, 55–64 years, 65–74 years, 75–84 years, and ≥85 years) and blood pressure categories (in 10 mm Hg increments from <120 mm Hg to ≥170 mm Hg systolic blood pressure and from <70 mm Hg to ≥110 mm Hg diastolic). We used a fixed effects one-stage approach and applied Cox proportional hazard models, stratified by trial, to analyse the data. The primary outcome was defined as either a composite of fatal or non-fatal stroke, fatal or non-fatal myocardial infarction or ischaemic heart disease, or heart failure causing death or requiring hospital admission. Findings: We included data from 358 707 participants from 51 randomised clinical trials. The age of participants at randomisation ranged from 21 years to 105 years (median 65 years [IQR 59–75]), with 42 960 (12·0%) participants younger than 55 years, 128 437 (35·8%) aged 55–64 years, 128 506 (35·8%) 65–74 years, 54 016 (15·1%) 75–84 years, and 4788 (1·3%) 85 years and older. The hazard ratios for the risk of major cardiovascular events per 5 mm Hg

Published
2021

10. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study

Author

Roth, G, Mensah, G, Johnson, C, Addolorato, G, Ammirati, E, Baddour, L, Barengo, N, Beaton, A, Benjamin, E, Benziger, C, Bonny, A, Brauer, M, Brodmann, M, Cahill, T, Carapetis, J, Catapano, A, Chugh, S, Cooper, L, Coresh, J, Criqui, M, Decleene, N, Eagle, K, Emmons-Bell, S, Feigin, V, Fernandez-Sola, J, Fowkes, G, Gakidou, E, Grundy, S, He, F, Howard, G, Hu, F, Inker, L, Karthikeyan, G, Kassebaum, N, Koroshetz, W, Lavie, C, Lloyd-Jones, D, Lu, H, Mirijello, A, Temesgen, A, Mokdad, A, Moran, A, Muntner, P, Narula, J, Neal, B, Ntsekhe, M, Moraes de Oliveira, G, Otto, C, Owolabi, M, Pratt, M, Rajagopalan, S, Reitsma, M, Ribeiro, A, Rigotti, N, Rodgers, A, Sable, C, Shakil, S, Sliwa-Hahnle, K, Stark, B, Sundstrom, J, Timpel, P, Tleyjeh, I, Valgimigli, M, Vos, T, Whelton, P, Yacoub, M, Zuhlke, L, Murray, C, Fuster, V, Fowkes, F, Misganaw, A, Oliveira, G, Sliwa, K, Abbasi-Kangevari, M, Abdi, A, Abedi, A, Aboyans, V, Abrha, W, Abu-Gharbieh, E, Abushouk, A, Acharya, D, Adair, T, Adebayo, O, Ademi, Z, Advani, S, Afshari, K, Afshin, A, Agarwal, G, Agasthi, P, Ahmad, S, Ahmadi, S, Ahmed, M, Aji, B, Akalu, Y, Akande-Sholabi, W, Aklilu, A, Akunna, C, Alahdab, F, Al-Eyadhy, A, Alhabib, K, Alif, S, Alipour, V, Aljunid, S, Alla, F, Almasi-Hashiani, A, Almustanyir, S, Al-Raddadi, R, Amegah, A, Amini, S, Aminorroaya, A, Amu, H, Amugsi, D, Ancuceanu, R, Anderlini, D, Andrei, T, Andrei, C, Ansari-Moghaddam, A, Anteneh, Z, Antonazzo, I, Antony, B, Anwer, R, Appiah, L, Arabloo, J, Arnlov, J, Artanti, K, Ataro, Z, Ausloos, M, Avila-Burgos, L, Awan, A, Awoke, M, Ayele, H, Ayza, M, Azari, S, B, D, Baheiraei, N, Baig, A, Bakhtiari, A, Banach, M, Banik, P, Baptista, E, Barboza, M, Barua, L, Basu, S, Bedi, N, Bejot, Y, Bennett, D, Bensenor, I, Berman, A, Bezabih, Y, Bhagavathula, A, Bhaskar, S, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, M, Boloor, A, Brant, L, Brenner, H, Briko, N, Butt, Z, Caetano dos Santos, F, Cahill, L, Cahuana-Hurtado, L, Camera, L, Campos-Nonato, I, Cantu-Brito, C, Car, J, Carrero, J, Carvalho, F, Castaneda-Orjuela, C, Catala-Lopez, F, Cerin, E, Charan, J, Chattu, V, Chen, S, Chin, K, Choi, J, Chu, D, Chung, S, Cirillo, M, Coffey, S, Conti, S, Costa, V, Cundiff, D, Dadras, O, Dagnew, B, Dai, X, Damasceno, A, Dandona, L, Dandona, R, Davletov, K, De la Cruz-Gongora, V, De la Hoz, F, De Neve, J, Denova-Gutierrez, E, Derbew Molla, M, Derseh, B, Desai, R, Deuschl, G, Dharmaratne, S, Dhimal, M, Dhungana, R, Dianatinasab, M, Diaz, D, Djalalinia, S, Dokova, K, Douiri, A, Duncan, B, Duraes, A, Eagan, A, Ebtehaj, S, Eftekhari, A, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, I, Elhadi, M, El-Jaafary, S, Esteghamati, S, Etisso, A, Eyawo, O, Fadhil, I, Faraon, E, Faris, P, Farwati, M, Farzadfar, F, Fernandes, E, Fernandez Prendes, C, Ferrara, P, Filip, I, Fischer, F, Flood, D, Fukumoto, T, Gad, M, Gaidhane, S, Ganji, M, Garg, J, Gebre, A, Gebregiorgis, B, Gebregzabiher, K, Gebremeskel, G, Getacher, L, Obsa, A, Ghajar, A, Ghashghaee, A, Ghith, N, Giampaoli, S, Gilani, S, Gill, P, Gillum, R, Glushkova, E, Gnedovskaya, E, Golechha, M, Gonfa, K, Goudarzian, A, Goulart, A, Guadamuz, J, Guha, A, Guo, Y, Gupta, R, Hachinski, V, Hafezi-Nejad, N, Haile, T, Hamadeh, R, Hamidi, S, Hankey, G, Hargono, A, Hartono, R, Hashemian, M, Hashi, A, Hassan, S, Hassen, H, Havmoeller, R, Hay, S, Hayat, K, Heidari, G, Herteliu, C, Holla, R, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Iavicoli, I, Ibeneme, C, Ibitoye, S, Ilesanmi, O, Ilic, I, Ilic, M, Iqbal, U, Irvani, S, Islam, S, Islam, R, Iso, H, Iwagami, M, Jain, V, Javaheri, T, Jayapal, S, Jayaram, S, Jayawardena, R, Jeemon, P, Jha, R, Jonas, J, Jonnagaddala, J, Joukar, F, Jozwiak, J, Jurisson, M, Kabir, A, Kahlon, T, Kalani, R, Kalhor, R, Kamath, A, Kamel, I, Kandel, H, Kandel, A, Karch, A, Kasa, A, Katoto, P, Kayode, G, Khader, Y, Khammarnia, M, Khan, M, Khan, E, Khatab, K, Kibria, G, Kim, Y, Kim, G, Kimokoti, R, Kisa, S, Kisa, A, Kivimaki, M, Kolte, D, Koolivand, A, Korshunov, V, Koulmane Laxminarayana, S, Koyanagi, A, Krishan, K, Krishnamoorthy, V, Kuate Defo, B, Kucuk Bicer, B, Kulkarni, V, Kumar, G, Kumar, N, Kurmi, O, Kusuma, D, Kwan, G, La Vecchia, C, Lacey, B, Lallukka, T, Lan, Q, Lasrado, S, Lassi, Z, Lauriola, P, Lawrence, W, Laxmaiah, A, Legrand, K, Li, M, Li, B, Li, S, Lim, S, Lim, L, Lin, H, Lin, Z, Lin, R, Liu, X, Lopez, A, Lorkowski, S, Lotufo, P, Lugo, A, M, N, Madotto, F, Mahmoudi, M, Majeed, A, Malekzadeh, R, Malik, A, Mamun, A, Manafi, N, Mansournia, M, Mantovani, L, Martini, S, Mathur, M, Mazzaglia, G, Mehata, S, Mehndiratta, M, Meier, T, Menezes, R, Meretoja, A, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, I, Miller, T, Mirrakhimov, E, Mirzaei, H, Moazen, B, Moghadaszadeh, M, Mohammad, Y, Mohammad, D, Mohammed, S, Mohammed, M, Mokhayeri, Y, Molokhia, M, Montasir, A, Moradi, G, Moradzadeh, R, Moraga, P, Morawska, L, Moreno Velasquez, I, Morze, J, Mubarik, S, Muruet, W, Musa, K, Nagarajan, A, Nalini, M, Nangia, V, Naqvi, A, Narasimha Swamy, S, Nascimento, B, Nayak, V, Nazari, J, Nazarzadeh, M, Negoi, R, Neupane Kandel, S, Nguyen, H, Nixon, M, Norrving, B, Noubiap, J, Nouthe, B, Nowak, C, Odukoya, O, Ogbo, F, Olagunju, A, Orru, H, Ortiz, A, Ostroff, S, Padubidri, J, Palladino, R, Pana, A, Panda-Jonas, S, Parekh, U, Park, E, Parvizi, M, Pashazadeh Kan, F, Patel, U, Pathak, M, Paudel, R, Pepito, V, Perianayagam, A, Perico, N, Pham, H, Pilgrim, T, Piradov, M, Pishgar, F, Podder, V, Polibin, R, Pourshams, A, Pribadi, D, Rabiee, N, Rabiee, M, Radfar, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Ur Rahman, M, Rahman, M, Rahmani, A, Rakovac, I, Ram, P, Ramalingam, S, Rana, J, Ranasinghe, P, Rao, S, Rathi, P, Rawal, L, Rawasia, W, Rawassizadeh, R, Remuzzi, G, Renzaho, A, Rezapour, A, Riahi, S, Roberts-Thomson, R, Roever, L, Rohloff, P, Romoli, M, Roshandel, G, Rwegerera, G, Saadatagah, S, Saber-Ayad, M, Sabour, S, Sacco, S, Sadeghi, M, Saeedi Moghaddam, S, Safari, S, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, A, Santos, I, Santric-Milicevic, M, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sawhney, M, Saylan, M, Schmidt, M, Schutte, A, Senthilkumaran, S, Sepanlou, S, Sha, F, Shahabi, S, Shahid, I, Shaikh, M, Shamali, M, Shamsizadeh, M, Shawon, M, Sheikh, A, Shigematsu, M, Shin, M, Shin, J, Shiri, R, Shiue, I, Shuval, K, Siabani, S, Siddiqi, T, Silva, D, Singh, J, Mtech, A, Skryabin, V, Skryabina, A, Soheili, A, Spurlock, E, Stockfelt, L, Stortecky, S, Stranges, S, Suliankatchi Abdulkader, R, Tadbiri, H, Tadesse, E, Tadesse, D, Tajdini, M, Tariqujjaman, M, Teklehaimanot, B, Temsah, M, Tesema, A, Thakur, B, Thankappan, K, Thapar, R, Thrift, A, Timalsina, B, Tonelli, M, Touvier, M, Tovani-Palone, M, Tripathi, A, Tripathy, J, Truelsen, T, Tsegay, G, Tsegaye, G, Tsilimparis, N, Tusa, B, Tyrovolas, S, Umapathi, K, Unim, B, Unnikrishnan, B, Usman, M, Vaduganathan, M, Valdez, P, Vasankari, T, Velazquez, D, Venketasubramanian, N, Vu, G, Vujcic, I, Waheed, Y, Wang, Y, Wang, F, Wei, J, Weintraub, R, Weldemariam, A, Westerman, R, Winkler, A, Wiysonge, C, Wolfe, C, Wubishet, B, Xu, G, Yadollahpour, A, Yamagishi, K, Yan, L, Yandrapalli, S, Yano, Y, Yatsuya, H, Yeheyis, T, Yeshaw, Y, Yilgwan, C, Yonemoto, N, Yu, C, Yusefzadeh, H, Zachariah, G, Zaman, S, Zaman, M, Zamanian, M, Zand, R, Zandifar, A, Zarghi, A, Zastrozhin, M, Zastrozhina, A, Zhang, Z, Zhang, Y, Zhang, W, Zhong, C, Zou, Z, Zuniga, Y, Roth G. A., Mensah G. A., Johnson C. O., Addolorato G., Ammirati E., Baddour L. M., Barengo N. C., Beaton A. Z., Benjamin E. J., Benziger C. P., Bonny A., Brauer M., Brodmann M., Cahill T. J., Carapetis J., Catapano A. L., Chugh S. S., Cooper L. T., Coresh J., Criqui M., DeCleene N., Eagle K. A., Emmons-Bell S., Feigin V. L., Fernandez-Sola J., Fowkes G., Gakidou E., Grundy S. M., He F. J., Howard G., Hu F., Inker L., Karthikeyan G., Kassebaum N., Koroshetz W., Lavie C., Lloyd-Jones D., Lu H. S., Mirijello A., Temesgen A. M., Mokdad A., Moran A. E., Muntner P., Narula J., Neal B., Ntsekhe M., Moraes de Oliveira G., Otto C., Owolabi M., Pratt M., Rajagopalan S., Reitsma M., Ribeiro A. L. P., Rigotti N., Rodgers A., Sable C., Shakil S., Sliwa-Hahnle K., Stark B., Sundstrom J., Timpel P., Tleyjeh I. M., Valgimigli M., Vos T., Whelton P. K., Yacoub M., Zuhlke L., Murray C., Fuster V., Beaton A., Carapetis J. R., Chugh S., Criqui M. H., DeCleene N. K., Fowkes F. G. R., Kassebaum N. J., Koroshetz W. J., Misganaw A. T., Mokdad A. H., Oliveira G. M. M., Otto C. M., Owolabi M. O., Reitsma M. B., Rigotti N. A., Sable C. A., Shakil S. S., Sliwa K., Stark B. A., Tleyjeh I. I., Zuhlke L. J., Abbasi-Kangevari M., Abdi A., Abedi A., Aboyans V., Abrha W. A., Abu-Gharbieh E., Abushouk A. I., Acharya D., Adair T., Adebayo O. M., Ademi Z., Advani S. M., Afshari K., Afshin A., Agarwal G., Agasthi P., Ahmad S., Ahmadi S., Ahmed M. B., Aji B., Akalu Y., Akande-Sholabi W., Aklilu A., Akunna C. J., Alahdab F., Al-Eyadhy A., Alhabib K. F., Alif S. M., Alipour V., Aljunid S. M., Alla F., Almasi-Hashiani A., Almustanyir S., Al-Raddadi R. M., Amegah A. K., Amini S., Aminorroaya A., Amu H., Amugsi D. A., Ancuceanu R., Anderlini D., Andrei T., Andrei C. L., Ansari-Moghaddam A., Anteneh Z. A., Antonazzo I. C., Antony B., Anwer R., Appiah L. T., Arabloo J., Arnlov J., Artanti K. D., Ataro Z., Ausloos M., Avila-Burgos L., Awan A. T., Awoke M. A., Ayele H. T., Ayza M. A., Azari S., B D. B., Baheiraei N., Baig A. A., Bakhtiari A., Banach M., Banik P. C., Baptista E. A., Barboza M. A., Barua L., Basu S., Bedi N., Bejot Y., Bennett D. A., Bensenor I. M., Berman A. E., Bezabih Y. M., Bhagavathula A. S., Bhaskar S., Bhattacharyya K., Bijani A., Bikbov B., Birhanu M. M., Boloor A., Brant L. C., Brenner H., Briko N. I., Butt Z. A., Caetano dos Santos F. L., Cahill L. E., Cahuana-Hurtado L., Camera L. A., Campos-Nonato I. R., Cantu-Brito C., Car J., Carrero J. J., Carvalho F., Castaneda-Orjuela C. A., Catala-Lopez F., Cerin E., Charan J., Chattu V. K., Chen S., Chin K. L., Choi J. -Y. J., Chu D. -T., Chung S. -C., Cirillo M., Coffey S., Conti S., Costa V. M., Cundiff D. K., Dadras O., Dagnew B., Dai X., Damasceno A. A. M., Dandona L., Dandona R., Davletov K., De la Cruz-Gongora V., De la Hoz F. P., De Neve J. -W., Denova-Gutierrez E., Derbew Molla M., Derseh B. T., Desai R., Deuschl G., Dharmaratne S. D., Dhimal M., Dhungana R. R., Dianatinasab M., Diaz D., Djalalinia S., Dokova K., Douiri A., Duncan B. B., Duraes A. R., Eagan A. W., Ebtehaj S., Eftekhari A., Eftekharzadeh S., Ekholuenetale M., El Nahas N., Elgendy I. Y., Elhadi M., El-Jaafary S. I., Esteghamati S., Etisso A. E., Eyawo O., Fadhil I., Faraon E. J. A., Faris P. S., Farwati M., Farzadfar F., Fernandes E., Fernandez Prendes C., Ferrara P., Filip I., Fischer F., Flood D., Fukumoto T., Gad M. M., Gaidhane S., Ganji M., Garg J., Gebre A. K., Gebregiorgis B. G., Gebregzabiher K. Z., Gebremeskel G. G., Getacher L., Obsa A. G., Ghajar A., Ghashghaee A., Ghith N., Giampaoli S., Gilani S. A., Gill P. S., Gillum R. F., Glushkova E. V., Gnedovskaya E. V., Golechha M., Gonfa K. B., Goudarzian A. H., Goulart A. C., Guadamuz J. S., Guha A., Guo Y., Gupta R., Hachinski V., Hafezi-Nejad N., Haile T. G., Hamadeh R. R., Hamidi S., Hankey G. J., Hargono A., Hartono R. K., Hashemian M., Hashi A., Hassan S., Hassen H. Y., Havmoeller R. J., Hay S. I., Hayat K., Heidari G., Herteliu C., Holla R., Hosseini M., Hosseinzadeh M., Hostiuc M., Hostiuc S., Househ M., Huang J., Humayun A., Iavicoli I., Ibeneme C. U., Ibitoye S. E., Ilesanmi O. S., Ilic I. M., Ilic M. D., Iqbal U., Irvani S. S. N., Islam S. M. S., Islam R. M., Iso H., Iwagami M., Jain V., Javaheri T., Jayapal S. K., Jayaram S., Jayawardena R., Jeemon P., Jha R. P., Jonas J. B., Jonnagaddala J., Joukar F., Jozwiak J. J., Jurisson M., Kabir A., Kahlon T., Kalani R., Kalhor R., Kamath A., Kamel I., Kandel H., Kandel A., Karch A., Kasa A. S., Katoto P. D. M. C., Kayode G. A., Khader Y. S., Khammarnia M., Khan M. S., Khan M. N., Khan M., Khan E. A., Khatab K., Kibria G. M. A., Kim Y. J., Kim G. R., Kimokoti R. W., Kisa S., Kisa A., Kivimaki M., Kolte D., Koolivand A., Korshunov V. A., Koulmane Laxminarayana S. L., Koyanagi A., Krishan K., Krishnamoorthy V., Kuate Defo B., Kucuk Bicer B., Kulkarni V., Kumar G. A., Kumar N., Kurmi O. P., Kusuma D., Kwan G. F., La Vecchia C., Lacey B., Lallukka T., Lan Q., Lasrado S., Lassi Z. S., Lauriola P., Lawrence W. R., Laxmaiah A., LeGrand K. E., Li M. -C., Li B., Li S., Lim S. S., Lim L. -L., Lin H., Lin Z., Lin R. -T., Liu X., Lopez A. D., Lorkowski S., Lotufo P. A., Lugo A., M N. K., Madotto F., Mahmoudi M., Majeed A., Malekzadeh R., Malik A. A., Mamun A. A., Manafi N., Mansournia M. A., Mantovani L. G., Martini S., Mathur M. R., Mazzaglia G., Mehata S., Mehndiratta M. M., Meier T., Menezes R. G., Meretoja A., Mestrovic T., Miazgowski B., Miazgowski T., Michalek I. M., Miller T. R., Mirrakhimov E. M., Mirzaei H., Moazen B., Moghadaszadeh M., Mohammad Y., Mohammad D. K., Mohammed S., Mohammed M. A., Mokhayeri Y., Molokhia M., Montasir A. A., Moradi G., Moradzadeh R., Moraga P., Morawska L., Moreno Velasquez I., Morze J., Mubarik S., Muruet W., Musa K. I., Nagarajan A. J., Nalini M., Nangia V., Naqvi A. A., Narasimha Swamy S., Nascimento B. R., Nayak V. C., Nazari J., Nazarzadeh M., Negoi R. 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M., Sabour S., Sacco S., Sadeghi M., Saeedi Moghaddam S., Safari S., Sahebkar A., Salehi S., Salimzadeh H., Samaei M., Samy A. M., Santos I. S., Santric-Milicevic M. M., Sarrafzadegan N., Sarveazad A., Sathish T., Sawhney M., Saylan M., Schmidt M. I., Schutte A. E., Senthilkumaran S., Sepanlou S. G., Sha F., Shahabi S., Shahid I., Shaikh M. A., Shamali M., Shamsizadeh M., Shawon M. S. R., Sheikh A., Shigematsu M., Shin M. -J., Shin J. I., Shiri R., Shiue I., Shuval K., Siabani S., Siddiqi T. J., Silva D. A. S., Singh J. A., Mtech A. S., Skryabin V. Y., Skryabina A. A., Soheili A., Spurlock E. E., Stockfelt L., Stortecky S., Stranges S., Suliankatchi Abdulkader R., Tadbiri H., Tadesse E. G., Tadesse D. B., Tajdini M., Tariqujjaman M., Teklehaimanot B. F., Temsah M. -H., Tesema A. K., Thakur B., Thankappan K. R., Thapar R., Thrift A. G., Timalsina B., Tonelli M., Touvier M., Tovani-Palone M. R., Tripathi A., Tripathy J. P., Truelsen T. C., Tsegay G. M., Tsegaye G. W., Tsilimparis N., Tusa B. S., Tyrovolas S., Umapathi K. K., Unim B., Unnikrishnan B., Usman M. S., Vaduganathan M., Valdez P. R., Vasankari T. J., Velazquez D. Z., Venketasubramanian N., Vu G. T., Vujcic I. S., Waheed Y., Wang Y., Wang F., Wei J., Weintraub R. G., Weldemariam A. H., Westerman R., Winkler A. S., Wiysonge C. S., Wolfe C. D. A., Wubishet B. L., Xu G., Yadollahpour A., Yamagishi K., Yan L. L., Yandrapalli S., Yano Y., Yatsuya H., Yeheyis T. Y., Yeshaw Y., Yilgwan C. S., Yonemoto N., Yu C., Yusefzadeh H., Zachariah G., Zaman S. B., Zaman M. S., Zamanian M., Zand R., Zandifar A., Zarghi A., Zastrozhin M. S., Zastrozhina A., Zhang Z. -J., Zhang Y., Zhang W., Zhong C., Zou Z., Zuniga Y. M. H., Murray C. J. 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Abstract

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside

Published
2020

12. Elevated blood pressure, antihypertensive medications and bone health in the population:revisiting old hypotheses and exploring future research directions

Author

Canoy, D. (Dexter), Harvey, N.C. (Nicholas), Prieto-Alhambra, D. (Daniel), Cooper, C. (Cyrus), Meyer, H.E. (Haakon), Åsvold, B. O., Nazarzadeh, M., Rahimi, K., Canoy, D. (Dexter), Harvey, N.C. (Nicholas), Prieto-Alhambra, D. (Daniel), Cooper, C. (Cyrus), Meyer, H.E. (Haakon), Åsvold, B. O., Nazarzadeh, M., and Rahimi, K.

Abstract

Blood pressure and bone metabolism appear to share commonalities in their physiologic regulation. Specific antihypertensive drug classes may also influence bone mineral density. However, current evidence from existing observational studies and randomised trials is insufficient to establish causal associations for blood pressure and use of blood pressure–lowering drugs with bone health outcomes, particularly with the risks of osteoporosis and fractures. The availability and access to relevant large-scale biomedical data sources as well as developments in study designs and analytical approaches provide opportunities to examine the nature of the association between blood pressure and bone health more reliably and in greater detail than has ever been possible. It is unlikely that a single source of data or study design can provide a definitive answer. However, with appropriate considerations of the strengths and limitations of the different data sources and analytical techniques, we should be able to advance our understanding of the role of raised blood pressure and its drug treatment on the risks of low bone mineral density and fractures. As elevated blood pressure is highly prevalent and blood pressure–lowering drugs are widely prescribed, even small effects of these exposures on bone health outcomes could be important at a population level.

Published
2022

14. Investigating the association of environmental exposures and all-cause mortality in the UK Biobank using sparse principal component analysis

Author

Mamouei, M, Zhu, Y, Nazarzadeh, M, Rahimi, K, Hassaine, A, Salimi-Khorshidi, G, and Cai, Y

Subjects
Principal Component Analysis, Multidisciplinary, Humans, Environmental Exposure, Environmental Health, United Kingdom, Biological Specimen Banks
Abstract

Multicollinearity refers to the presence of collinearity between multiple variables and renders the results of statistical inference erroneous (Type II error). This is particularly important in environmental health research where multicollinearity can hinder inference. To address this, correlated variables are often excluded from the analysis, limiting the discovery of new associations. An alternative approach to address this problem is the use of principal component analysis. This method, combines and projects a group of correlated variables onto a new orthogonal space. While this resolves the multicollinearity problem, it poses another challenge in relation to interpretability of results. Standard hypothesis testing methods can be used to evaluate the association of projected predictors, called principal components, with the outcomes of interest, however, there is no established way to trace the significance of principal components back to individual variables. To address this problem, we investigated the use of sparse principal component analysis which enforces a parsimonious projection. We hypothesise that this parsimony could facilitate the interpretability of findings. To this end, we investigated the association of 20 environmental predictors with all-cause mortality adjusting for demographic, socioeconomic, physiological, and behavioural factors. The study was conducted in a cohort of 379,690 individuals in the UK. During an average follow-up of 8.05 years (3,055,166 total person-years), 14,996 deaths were observed. We used Cox regression models to estimate the hazard ratio (HR) and 95% confidence intervals (CI). The Cox models were fitted to the standardised environmental predictors (a) without any transformation (b) transformed with PCA, and (c) transformed with SPCA. The comparison of findings underlined the potential of SPCA for conducting inference in scenarios where multicollinearity can increase the risk of Type II error. Our analysis unravelled a significant association between average noise pollution and increased risk of all-cause mortality. Specifically, those in the upper deciles of noise exposure have between 5 and 10% increased risk of all-cause mortality compared to the lowest decile.

Published
2022

16. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

Author

Roth, GA, Mensah, GA, Johnson, CO, Addolorato, G, Ammirati, E, Baddour, LM, Barengo, NC, Beaton, AZ, Benjamin, EJ, Benziger, CP, Bonny, A, Brauer, M, Brodmann, M, Cahill, TJ, Carapetis, J, Catapano, AL, Chugh, SS, Cooper, LT, Coresh, J, Criqui, M, DeCleene, N, Eagle, KA, Emmons-Bell, S, Feigin, VL, Fernández-Solà, J, Fowkes, G, Gakidou, E, Grundy, SM, He, FJ, Howard, G, Hu, F, Inker, L, Karthikeyan, G, Kassebaum, N, Koroshetz, W, Lavie, C, Lloyd-Jones, D, Lu, HS, Mirijello, A, Temesgen, AM, Mokdad, A, Moran, AE, Muntner, P, Narula, J, Neal, B, Ntsekhe, M, Moraes de Oliveira, G, Otto, C, Owolabi, M, Pratt, M, Rajagopalan, S, Reitsma, M, Ribeiro, ALP, Rigotti, N, Rodgers, A, Sable, C, Shakil, S, Sliwa-Hahnle, K, Stark, B, Sundström, J, Timpel, P, Tleyjeh, IM, Valgimigli, M, Vos, T, Whelton, PK, Yacoub, M, Zuhlke, L, Murray, C, Fuster, V, Beaton, A, Carapetis, JR, Chugh, S, Criqui, MH, DeCleene, NK, Fernández-Sola, J, Fowkes, FGR, Kassebaum, NJ, Koroshetz, WJ, Misganaw, AT, Mokdad, AH, Oliveira, GMM, Otto, CM, Owolabi, MO, Reitsma, MB, Rigotti, NA, Sable, CA, Shakil, SS, Sliwa, K, Stark, BA, Tleyjeh, II, Zuhlke, LJ, Abbasi-Kangevari, M, Abdi, A, Abedi, A, Aboyans, V, Abrha, WA, Abu-Gharbieh, E, Abushouk, AI, Acharya, D, Adair, T, Adebayo, OM, Ademi, Z, Advani, SM, Afshari, K, Afshin, A, Agarwal, G, Agasthi, P, Ahmad, S, Ahmadi, S, Ahmed, MB, Aji, B, Akalu, Y, Akande-Sholabi, W, Aklilu, A, Akunna, CJ, Alahdab, F, Al-Eyadhy, A, Alhabib, KF, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Almasi-Hashiani, A, Almustanyir, S, Al-Raddadi, RM, Amegah, AK, Amini, S, Aminorroaya, A, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Andrei, T, Andrei, CL, Ansari-Moghaddam, A, Anteneh, ZA, Antonazzo, IC, Antony, B, Anwer, R, Appiah, LT, Arabloo, J, Ärnlöv, J, Artanti, KD, Ataro, Z, Ausloos, M, Avila-Burgos, L, Awan, AT, Awoke, MA, Ayele, HT, Ayza, MA, Azari, S, B, DB, Baheiraei, N, Baig, AA, Bakhtiari, A, Banach, M, Banik, PC, Baptista, EA, Barboza, MA, Barua, L, Basu, S, Bedi, N, Béjot, Y, Bennett, DA, Bensenor, IM, Berman, AE, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, MM, Boloor, A, Brant, LC, Brenner, H, Briko, NI, Butt, ZA, Caetano dos Santos, FL, Cahill, LE, Cahuana-Hurtado, L, Cámera, LA, Campos-Nonato, IR, Cantu-Brito, C, Car, J, Carrero, JJ, Carvalho, F, Castañeda-Orjuela, CA, Catalá-López, F, Cerin, E, Charan, J, Chattu, VK, Chen, S, Chin, KL, Choi, J-YJ, Chu, D-T, Chung, S-C, Cirillo, M, Coffey, S, Conti, S, Costa, VM, Cundiff, DK, Dadras, O, Dagnew, B, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davletov, K, De la Cruz-Góngora, V, De la Hoz, FP, De Neve, J-W, Denova-Gutiérrez, E, Derbew Molla, M, Derseh, BT, Desai, R, Deuschl, G, Dharmaratne, SD, Dhimal, M, Dhungana, RR, Dianatinasab, M, Diaz, D, Djalalinia, S, Dokova, K, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Ebtehaj, S, Eftekhari, A, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, IY, Elhadi, M, El-Jaafary, SI, Esteghamati, S, Etisso, AE, Eyawo, O, Fadhil, I, Faraon, EJA, Faris, PS, Farwati, M, Farzadfar, F, Fernandes, E, Fernandez Prendes, C, Ferrara, P, Filip, I, Fischer, F, Flood, D, Fukumoto, T, Gad, MM, Gaidhane, S, Ganji, M, Garg, J, Gebre, AK, Gebregiorgis, BG, Gebregzabiher, KZ, Gebremeskel, GG, Getacher, L, Obsa, AG, Ghajar, A, Ghashghaee, A, Ghith, N, Giampaoli, S, Gilani, SA, Gill, PS, Gillum, RF, Glushkova, EV, Gnedovskaya, EV, Golechha, M, Gonfa, KB, Goudarzian, AH, Goulart, AC, Guadamuz, JS, Guha, A, Guo, Y, Gupta, R, Hachinski, V, Hafezi-Nejad, N, Haile, TG, Hamadeh, RR, Hamidi, S, Hankey, GJ, Hargono, A, Hartono, RK, Hashemian, M, Hashi, A, Hassan, S, Hassen, HY, Havmoeller, RJ, Hay, SI, Hayat, K, Heidari, G, Herteliu, C, Holla, R, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Iavicoli, I, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Iqbal, U, Irvani, SSN, Shariful Islam, Sheikh, Islam, RM, Iso, H, Iwagami, M, Jain, V, Javaheri, T, Jayapal, SK, Jayaram, S, Jayawardena, R, Jeemon, P, Jha, RP, Jonas, JB, Jonnagaddala, J, Joukar, F, Jozwiak, JJ, Jürisson, M, Kabir, A, Kahlon, T, Kalani, R, Kalhor, R, Kamath, A, Kamel, I, Kandel, H, Kandel, A, Karch, A, Kasa, AS, Katoto, PDMC, Kayode, GA, Khader, YS, Khammarnia, M, Khan, MS, Khan, MN, Khan, M, Khan, EA, Khatab, K, Kibria, GMA, Kim, YJ, Kim, GR, Kimokoti, RW, Kisa, S, Kisa, A, Kivimäki, M, Kolte, D, Koolivand, A, Korshunov, VA, Koulmane Laxminarayana, SL, Koyanagi, A, Krishan, K, Krishnamoorthy, V, Kuate Defo, B, Kucuk Bicer, B, Kulkarni, V, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Kwan, GF, La Vecchia, C, Lacey, B, Lallukka, T, Lan, Q, Lasrado, S, Lassi, ZS, Lauriola, P, Lawrence, WR, Laxmaiah, A, LeGrand, KE, Li, M-C, Li, B, Li, S, Lim, SS, Lim, L-L, Lin, H, Lin, Z, Lin, R-T, Liu, X, Lopez, AD, Lorkowski, S, Lotufo, PA, Lugo, A, M, NK, Madotto, F, Mahmoudi, M, Majeed, A, Malekzadeh, R, Malik, AA, Mamun, AA, Manafi, N, Mansournia, MA, Mantovani, LG, Martini, S, Mathur, MR, Mazzaglia, G, Mehata, S, Mehndiratta, MM, Meier, T, Menezes, RG, Meretoja, A, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Moazen, B, Moghadaszadeh, M, Mohammad, Y, Mohammad, DK, Mohammed, S, Mohammed, MA, Mokhayeri, Y, Molokhia, M, Montasir, AA, Moradi, G, Moradzadeh, R, Moraga, P, Morawska, L, Moreno Velásquez, I, Morze, J, Mubarik, S, Muruet, W, Musa, KI, Nagarajan, AJ, Nalini, M, Nangia, V, Naqvi, AA, Narasimha Swamy, S, Nascimento, BR, Nayak, VC, Nazari, J, Nazarzadeh, M, Negoi, RI, Neupane Kandel, S, Nguyen, HLT, Nixon, MR, Norrving, B, Noubiap, JJ, Nouthe, BE, Nowak, C, Odukoya, OO, Ogbo, FA, Olagunju, AT, Orru, H, Ortiz, A, Ostroff, SM, Padubidri, JR, Palladino, R, Pana, A, Panda-Jonas, S, Parekh, U, Park, E-C, Parvizi, M, Pashazadeh Kan, F, Patel, UK, Pathak, M, Paudel, R, Pepito, VCF, Perianayagam, A, Perico, N, Pham, HQ, Pilgrim, T, Piradov, MA, Pishgar, F, Podder, V, Polibin, RV, Pourshams, A, Pribadi, DRA, Rabiee, N, Rabiee, M, Radfar, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Ur Rahman, MH, Rahman, Muhammad, Rahmani, AM, Rakovac, I, Ram, P, Ramalingam, S, Rana, J, Ranasinghe, P, Rao, SJ, Rathi, P, Rawal, L, Rawasia, WF, Rawassizadeh, R, Remuzzi, G, Renzaho, AMN, Rezapour, A, Riahi, SM, Roberts-Thomson, RL, Roever, L, Rohloff, P, Romoli, M, Roshandel, G, Rwegerera, GM, Saadatagah, S, Saber-Ayad, MM, Sabour, S, Sacco, S, Sadeghi, M, Saeedi Moghaddam, S, Safari, S, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sawhney, M, Saylan, M, Schmidt, MI, Schutte, AE, Senthilkumaran, S, Sepanlou, SG, Sha, F, Shahabi, S, Shahid, I, Shaikh, MA, Shamali, M, Shamsizadeh, M, Shawon, MSR, Sheikh, A, Shigematsu, M, Shin, M-J, Shin, JI, Shiri, R, Shiue, I, Shuval, K, Siabani, S, Siddiqi, TJ, Silva, DAS, Singh, JA, Mtech, AS, Skryabin, VY, Skryabina, AA, Soheili, A, Spurlock, EE, Stockfelt, L, Stortecky, S, Stranges, S, Suliankatchi Abdulkader, R, Tadbiri, H, Tadesse, EG, Tadesse, DB, Tajdini, M, Tariqujjaman, M, Teklehaimanot, BF, Temsah, M-H, Tesema, AK, Thakur, B, Thankappan, KR, Thapar, R, Thrift, AG, Timalsina, B, Tonelli, M, Touvier, M, Tovani-Palone, MR, Tripathi, A, Tripathy, JP, Truelsen, TC, Tsegay, GM, Tsegaye, GW, Tsilimparis, N, Tusa, BS, Tyrovolas, S, Umapathi, KK, Unim, B, Unnikrishnan, B, Usman, MS, Vaduganathan, M, Valdez, PR, Vasankari, TJ, Velazquez, DZ, Venketasubramanian, N, Vu, GT, Vujcic, IS, Waheed, Y, Wang, Y, Wang, F, Wei, J, Weintraub, RG, Weldemariam, AH, Westerman, R, Winkler, AS, Wiysonge, CS, Wolfe, CDA, Wubishet, BL, Xu, G, Yadollahpour, A, Yamagishi, K, Yan, LL, Yandrapalli, S, Yano, Y, Yatsuya, H, Yeheyis, TY, Yeshaw, Y, Yilgwan, CS, Yonemoto, N, Yu, C, Yusefzadeh, H, Zachariah, G, Zaman, SB, Zaman, MS, Zamanian, M, Zand, R, Zandifar, A, Zarghi, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhang, Y, Zhang, W, Zhong, C, Zou, Z, Zuniga, YMH, Murray, CJL, Roth, GA, Mensah, GA, Johnson, CO, Addolorato, G, Ammirati, E, Baddour, LM, Barengo, NC, Beaton, AZ, Benjamin, EJ, Benziger, CP, Bonny, A, Brauer, M, Brodmann, M, Cahill, TJ, Carapetis, J, Catapano, AL, Chugh, SS, Cooper, LT, Coresh, J, Criqui, M, DeCleene, N, Eagle, KA, Emmons-Bell, S, Feigin, VL, Fernández-Solà, J, Fowkes, G, Gakidou, E, Grundy, SM, He, FJ, Howard, G, Hu, F, Inker, L, Karthikeyan, G, Kassebaum, N, Koroshetz, W, Lavie, C, Lloyd-Jones, D, Lu, HS, Mirijello, A, Temesgen, AM, Mokdad, A, Moran, AE, Muntner, P, Narula, J, Neal, B, Ntsekhe, M, Moraes de Oliveira, G, Otto, C, Owolabi, M, Pratt, M, Rajagopalan, S, Reitsma, M, Ribeiro, ALP, Rigotti, N, Rodgers, A, Sable, C, Shakil, S, Sliwa-Hahnle, K, Stark, B, Sundström, J, Timpel, P, Tleyjeh, IM, Valgimigli, M, Vos, T, Whelton, PK, Yacoub, M, Zuhlke, L, Murray, C, Fuster, V, Beaton, A, Carapetis, JR, Chugh, S, Criqui, MH, DeCleene, NK, Fernández-Sola, J, Fowkes, FGR, Kassebaum, NJ, Koroshetz, WJ, Misganaw, AT, Mokdad, AH, Oliveira, GMM, Otto, CM, Owolabi, MO, Reitsma, MB, Rigotti, NA, Sable, CA, Shakil, SS, Sliwa, K, Stark, BA, Tleyjeh, II, Zuhlke, LJ, Abbasi-Kangevari, M, Abdi, A, Abedi, A, Aboyans, V, Abrha, WA, Abu-Gharbieh, E, Abushouk, AI, Acharya, D, Adair, T, Adebayo, OM, Ademi, Z, Advani, SM, Afshari, K, Afshin, A, Agarwal, G, Agasthi, P, Ahmad, S, Ahmadi, S, Ahmed, MB, Aji, B, Akalu, Y, Akande-Sholabi, W, Aklilu, A, Akunna, CJ, Alahdab, F, Al-Eyadhy, A, Alhabib, KF, Alif, SM, Alipour, V, Aljunid, SM, Alla, F, Almasi-Hashiani, A, Almustanyir, S, Al-Raddadi, RM, Amegah, AK, Amini, S, Aminorroaya, A, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Andrei, T, Andrei, CL, Ansari-Moghaddam, A, Anteneh, ZA, Antonazzo, IC, Antony, B, Anwer, R, Appiah, LT, Arabloo, J, Ärnlöv, J, Artanti, KD, Ataro, Z, Ausloos, M, Avila-Burgos, L, Awan, AT, Awoke, MA, Ayele, HT, Ayza, MA, Azari, S, B, DB, Baheiraei, N, Baig, AA, Bakhtiari, A, Banach, M, Banik, PC, Baptista, EA, Barboza, MA, Barua, L, Basu, S, Bedi, N, Béjot, Y, Bennett, DA, Bensenor, IM, Berman, AE, Bezabih, YM, Bhagavathula, AS, Bhaskar, S, Bhattacharyya, K, Bijani, A, Bikbov, B, Birhanu, MM, Boloor, A, Brant, LC, Brenner, H, Briko, NI, Butt, ZA, Caetano dos Santos, FL, Cahill, LE, Cahuana-Hurtado, L, Cámera, LA, Campos-Nonato, IR, Cantu-Brito, C, Car, J, Carrero, JJ, Carvalho, F, Castañeda-Orjuela, CA, Catalá-López, F, Cerin, E, Charan, J, Chattu, VK, Chen, S, Chin, KL, Choi, J-YJ, Chu, D-T, Chung, S-C, Cirillo, M, Coffey, S, Conti, S, Costa, VM, Cundiff, DK, Dadras, O, Dagnew, B, Dai, X, Damasceno, AAM, Dandona, L, Dandona, R, Davletov, K, De la Cruz-Góngora, V, De la Hoz, FP, De Neve, J-W, Denova-Gutiérrez, E, Derbew Molla, M, Derseh, BT, Desai, R, Deuschl, G, Dharmaratne, SD, Dhimal, M, Dhungana, RR, Dianatinasab, M, Diaz, D, Djalalinia, S, Dokova, K, Douiri, A, Duncan, BB, Duraes, AR, Eagan, AW, Ebtehaj, S, Eftekhari, A, Eftekharzadeh, S, Ekholuenetale, M, El Nahas, N, Elgendy, IY, Elhadi, M, El-Jaafary, SI, Esteghamati, S, Etisso, AE, Eyawo, O, Fadhil, I, Faraon, EJA, Faris, PS, Farwati, M, Farzadfar, F, Fernandes, E, Fernandez Prendes, C, Ferrara, P, Filip, I, Fischer, F, Flood, D, Fukumoto, T, Gad, MM, Gaidhane, S, Ganji, M, Garg, J, Gebre, AK, Gebregiorgis, BG, Gebregzabiher, KZ, Gebremeskel, GG, Getacher, L, Obsa, AG, Ghajar, A, Ghashghaee, A, Ghith, N, Giampaoli, S, Gilani, SA, Gill, PS, Gillum, RF, Glushkova, EV, Gnedovskaya, EV, Golechha, M, Gonfa, KB, Goudarzian, AH, Goulart, AC, Guadamuz, JS, Guha, A, Guo, Y, Gupta, R, Hachinski, V, Hafezi-Nejad, N, Haile, TG, Hamadeh, RR, Hamidi, S, Hankey, GJ, Hargono, A, Hartono, RK, Hashemian, M, Hashi, A, Hassan, S, Hassen, HY, Havmoeller, RJ, Hay, SI, Hayat, K, Heidari, G, Herteliu, C, Holla, R, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Huang, J, Humayun, A, Iavicoli, I, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Iqbal, U, Irvani, SSN, Shariful Islam, Sheikh, Islam, RM, Iso, H, Iwagami, M, Jain, V, Javaheri, T, Jayapal, SK, Jayaram, S, Jayawardena, R, Jeemon, P, Jha, RP, Jonas, JB, Jonnagaddala, J, Joukar, F, Jozwiak, JJ, Jürisson, M, Kabir, A, Kahlon, T, Kalani, R, Kalhor, R, Kamath, A, Kamel, I, Kandel, H, Kandel, A, Karch, A, Kasa, AS, Katoto, PDMC, Kayode, GA, Khader, YS, Khammarnia, M, Khan, MS, Khan, MN, Khan, M, Khan, EA, Khatab, K, Kibria, GMA, Kim, YJ, Kim, GR, Kimokoti, RW, Kisa, S, Kisa, A, Kivimäki, M, Kolte, D, Koolivand, A, Korshunov, VA, Koulmane Laxminarayana, SL, Koyanagi, A, Krishan, K, Krishnamoorthy, V, Kuate Defo, B, Kucuk Bicer, B, Kulkarni, V, Kumar, GA, Kumar, N, Kurmi, OP, Kusuma, D, Kwan, GF, La Vecchia, C, Lacey, B, Lallukka, T, Lan, Q, Lasrado, S, Lassi, ZS, Lauriola, P, Lawrence, WR, Laxmaiah, A, LeGrand, KE, Li, M-C, Li, B, Li, S, Lim, SS, Lim, L-L, Lin, H, Lin, Z, Lin, R-T, Liu, X, Lopez, AD, Lorkowski, S, Lotufo, PA, Lugo, A, M, NK, Madotto, F, Mahmoudi, M, Majeed, A, Malekzadeh, R, Malik, AA, Mamun, AA, Manafi, N, Mansournia, MA, Mantovani, LG, Martini, S, Mathur, MR, Mazzaglia, G, Mehata, S, Mehndiratta, MM, Meier, T, Menezes, RG, Meretoja, A, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, IM, Miller, TR, Mirrakhimov, EM, Mirzaei, H, Moazen, B, Moghadaszadeh, M, Mohammad, Y, Mohammad, DK, Mohammed, S, Mohammed, MA, Mokhayeri, Y, Molokhia, M, Montasir, AA, Moradi, G, Moradzadeh, R, Moraga, P, Morawska, L, Moreno Velásquez, I, Morze, J, Mubarik, S, Muruet, W, Musa, KI, Nagarajan, AJ, Nalini, M, Nangia, V, Naqvi, AA, Narasimha Swamy, S, Nascimento, BR, Nayak, VC, Nazari, J, Nazarzadeh, M, Negoi, RI, Neupane Kandel, S, Nguyen, HLT, Nixon, MR, Norrving, B, Noubiap, JJ, Nouthe, BE, Nowak, C, Odukoya, OO, Ogbo, FA, Olagunju, AT, Orru, H, Ortiz, A, Ostroff, SM, Padubidri, JR, Palladino, R, Pana, A, Panda-Jonas, S, Parekh, U, Park, E-C, Parvizi, M, Pashazadeh Kan, F, Patel, UK, Pathak, M, Paudel, R, Pepito, VCF, Perianayagam, A, Perico, N, Pham, HQ, Pilgrim, T, Piradov, MA, Pishgar, F, Podder, V, Polibin, RV, Pourshams, A, Pribadi, DRA, Rabiee, N, Rabiee, M, Radfar, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Ur Rahman, MH, Rahman, Muhammad, Rahmani, AM, Rakovac, I, Ram, P, Ramalingam, S, Rana, J, Ranasinghe, P, Rao, SJ, Rathi, P, Rawal, L, Rawasia, WF, Rawassizadeh, R, Remuzzi, G, Renzaho, AMN, Rezapour, A, Riahi, SM, Roberts-Thomson, RL, Roever, L, Rohloff, P, Romoli, M, Roshandel, G, Rwegerera, GM, Saadatagah, S, Saber-Ayad, MM, Sabour, S, Sacco, S, Sadeghi, M, Saeedi Moghaddam, S, Safari, S, Sahebkar, A, Salehi, S, Salimzadeh, H, Samaei, M, Samy, AM, Santos, IS, Santric-Milicevic, MM, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sawhney, M, Saylan, M, Schmidt, MI, Schutte, AE, Senthilkumaran, S, Sepanlou, SG, Sha, F, Shahabi, S, Shahid, I, Shaikh, MA, Shamali, M, Shamsizadeh, M, Shawon, MSR, Sheikh, A, Shigematsu, M, Shin, M-J, Shin, JI, Shiri, R, Shiue, I, Shuval, K, Siabani, S, Siddiqi, TJ, Silva, DAS, Singh, JA, Mtech, AS, Skryabin, VY, Skryabina, AA, Soheili, A, Spurlock, EE, Stockfelt, L, Stortecky, S, Stranges, S, Suliankatchi Abdulkader, R, Tadbiri, H, Tadesse, EG, Tadesse, DB, Tajdini, M, Tariqujjaman, M, Teklehaimanot, BF, Temsah, M-H, Tesema, AK, Thakur, B, Thankappan, KR, Thapar, R, Thrift, AG, Timalsina, B, Tonelli, M, Touvier, M, Tovani-Palone, MR, Tripathi, A, Tripathy, JP, Truelsen, TC, Tsegay, GM, Tsegaye, GW, Tsilimparis, N, Tusa, BS, Tyrovolas, S, Umapathi, KK, Unim, B, Unnikrishnan, B, Usman, MS, Vaduganathan, M, Valdez, PR, Vasankari, TJ, Velazquez, DZ, Venketasubramanian, N, Vu, GT, Vujcic, IS, Waheed, Y, Wang, Y, Wang, F, Wei, J, Weintraub, RG, Weldemariam, AH, Westerman, R, Winkler, AS, Wiysonge, CS, Wolfe, CDA, Wubishet, BL, Xu, G, Yadollahpour, A, Yamagishi, K, Yan, LL, Yandrapalli, S, Yano, Y, Yatsuya, H, Yeheyis, TY, Yeshaw, Y, Yilgwan, CS, Yonemoto, N, Yu, C, Yusefzadeh, H, Zachariah, G, Zaman, SB, Zaman, MS, Zamanian, M, Zand, R, Zandifar, A, Zarghi, A, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Zhang, Y, Zhang, W, Zhong, C, Zou, Z, Zuniga, YMH, and Murray, CJL

Abstract

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019.Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019.Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside hi

Published
2020

25. Stratified effects of blood pressure-lowering treatment on long-term blood pressure: an individual patient-level meta-analysis involving 50 randomised trials and 334,219 participants

Author

Canoy, D, primary, Copland, E, additional, Ramakrishnan, R, additional, Pinho-Gomes, A.C, additional, Nazarzadeh, M, additional, Bidel, Z, additional, Salimi-Khorshidi, G, additional, Woodward, M, additional, Davis, B.R, additional, Pepine, C.J, additional, Chalmers, J, additional, Teo, K, additional, and Rahimi, K, additional

Published
2020
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28. Inkjet-Printing of Phosphorus and Boron Dopant Sources for Tunnel Oxide Passivating Contacts

Author

Kiaee, Z., Reichel, C., Keding, R., Nazarzadeh, M., Lohmann, R., Feldmann, F., Jahn, M., Huyeng, J.D., Hermle, M., and Clement, F.

Subjects
Homojunction Solar Cells, Silicon Materials and Cells
Abstract

36th European Photovoltaic Solar Energy Conference and Exhibition; 187-191, This paper presents inkjet-printing of phosphorus and boron dopant inks for the formation of tunnel oxide passivating contacts (TOPCon) for back-contact back-junction (BC-BJ) silicon solar cells. The successful realization of passivating contacts utilizing printing technologies is a crucial prerequisite to simplify the fabrication process of BC-BJ cells while approaching the theoretical efficiency limit of silicon solar cells. In this work, the focus is set on developing inkjet printing processes for the application of dopant sources towards higher precision, homogeneity of printed lines and lifetime, in order to establish high passivation quality for TOPCon. Excellent passivation quality is achieved for inkjetprinted n-type (phosphorus) poly-Si surfaces with an implied open-circuit voltage iVOC of up to 733 mV and an implied fill factor iFF of up to 86.4%. For p-type (boron) poly-Si, iVOC of up to 682 mV and iFF of 80.6% were achieved. Similar results were realized by ion-implanted poly-Si surfaces, herein used as the reference, underlining the high potential of the investigated printing processes

Published
2019
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29. Long-Term Exposure to Elevated Systolic Blood Pressure in Predicting Incident Cardiovascular Disease: Evidence From Large-Scale Routine Electronic Health Records

Author

Ayala Solares, JR, Canoy, D, Raimondi, FED, Zhu, Y, Hassaine, A, Salimi-Khorshidi, G, Tran, J, Copland, E, Zottoli, M, Pinho-Gomes, AC, Nazarzadeh, M, Rahimi, K, Ayala Solares, JR, Canoy, D, Raimondi, FED, Zhu, Y, Hassaine, A, Salimi-Khorshidi, G, Tran, J, Copland, E, Zottoli, M, Pinho-Gomes, AC, Nazarzadeh, M, and Rahimi, K

Abstract

Background: How measures of long-term exposure to elevated blood pressure might add to the performance of “current” blood pressure in predicting future cardiovascular disease is unclear. We compared incident cardiovascular disease risk prediction using past, current, and usual systolic blood pressure alone or in combination. Methods and Results: Using data from UK primary care linked electronic health records, we applied a landmark cohort study design and identified 80 964 people, aged 50 years (derivation cohort=64 772; validation cohort=16 192), who, at study entry, had recorded blood pressure, no prior cardiovascular disease, and no previous antihypertensive or lipid-lowering prescriptions. We used systolic blood pressure recorded up to 10 years before baseline to estimate past systolic blood pressure (mean, time-weighted mean, and variability) and usual systolic blood pressure (correcting current values for past time-dependent blood pressure fluctuations) and examined their prospective relation with incident cardiovascular disease (first hospitalization for or death from coronary heart disease or stroke/transient ischemic attack). We used Cox regression to estimate hazard ratios and applied Bayesian analysis within a machine learning framework in model development and validation. Predictive performance of models was assessed using discrimination (area under the receiver operating characteristic curve) and calibration metrics. We found that elevated past, current, and usual systolic blood pressure values were separately and independently associated with increased incident cardiovascular disease risk. When used alone, the hazard ratio (95% credible interval) per 20–mm Hg increase in current systolic blood pressure was 1.22 (1.18–1.30), but associations were stronger for past systolic blood pressure (mean and time-weighted mean) and usual systolic blood pressure (hazard ratio ranging from 1.39–1.45). The area under the receiver operating characteristic curve for a

Published
2019

30. Effects of blood pressure-lowering drugs in heart failure: A systematic review andmeta-analysis of randomized controlled trials

Author

Pinho-Gomes, AC, Azevedo, L, Bidel, Z, Nazarzadeh, M, Canoy, D, Copland, E, Salam, A, Rodgers, A, Kotecha, D, Rahimi, K, Pinho-Gomes, AC, Azevedo, L, Bidel, Z, Nazarzadeh, M, Canoy, D, Copland, E, Salam, A, Rodgers, A, Kotecha, D, and Rahimi, K

Abstract

We aimed to combine evidence from all heart failure trials that have investigated the effects of drugs with blood pressure (BP)-lowering properties to assess the extent to which such drugs reduce BP in heart failure, the association between the net change in BP between treatment arms and cause-specific outcomes and whether treatment effects (efficacy and safety) vary according to baseline BP. We conducted a systematic review and metaanalysis including randomized clinical trials of drugs with BP-lowering properties in patients with chronic heart failure with at least 300 patient-years follow-up. We included a total of 37 trials (91 950 patients) and showed that treatment with drugs with BP-lowering properties resulted in a small but significant decrease in SBP in patients with heart failure with no evidence that the efficacy and safety of those drugs varied according to baseline BP.

Published
2019

31. Investigating the stratified efficacy and safety of pharmacological blood pressure-lowering: An overall protocol for individual patient-level data meta-analyses of over 300 000 randomised participants in the new phase of the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC)

Author

Rahimi, K, Canoy, D, Nazarzadeh, M, Salimi-Khorshidi, G, Woodward, M, Teo, K, Davis, BR, Chalmers, J, Pepine, CJ, Rahimi, K, Canoy, D, Nazarzadeh, M, Salimi-Khorshidi, G, Woodward, M, Teo, K, Davis, BR, Chalmers, J, and Pepine, CJ

Abstract

Introduction Previous research from the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC) and others has shown that pharmacological blood pressure (BP)- lowering substantially reduces the risk of major cardiovascular events, including ischaemic heart disease, heart failure and stroke. In this new phase, the aim is to conduct individual patient-level data (IPD) meta-analyses involving eligible BP-lowering randomised controlled trials (RCTs) to address uncertainties relating to efficacy and safety of BP-lowering treatment. Methods and analysis RCTs investigating the effect of pharmacological BP-lowering, with a minimum of 1000 patient-years of follow-up in each trial arm, are eligible. Our systematic review identified 100 potentially eligible trials. We requested their investigators/sponsors to contribute baseline, follow-up and outcomes data. As of June 2018, the collaboration has obtained data from 49 trials (n=315 046 participants), with additional data currently in the process of being transferred from four RCTs (n=34 642 participants). In addition, data harmonisation has commenced. Scientific activities of the collaboration are overseen by the Steering Committee with input from all collaborators. Detailed protocols for individual meta-analyses will be developed and registered on public platforms. Ethics and dissemination Ethics approval has been obtained for this new and extended phase of the BPLTTC, the largest collaboration of de-identified IPD from RCTs. It offers an efficient and ethical manner of re-purposing existing data to answer clinically important questions relating to BP treatment as well as methodological questions relating to IPD meta-analyses. Among the immediate impacts will include reliable quantification of effects of treatment modifiers, such as baseline BP, age and prior disease, on both vascular and non-vascular outcomes. Analyses will further assess the impact of BP-lowering on important, but less well understood, outcomes

Published
2019

33. P1548Long-term past, current and usual systolic blood pressure and incident cardiovascular disease: risk prediction using large-scale, routinely recorded clinical data

Author

Ayala Solares, J R, primary, Canoy, D, additional, Raimondi, F E D, additional, Zhu, Y, additional, Hassaine, A, additional, Salimi-Khorshidi, G, additional, Tran, J, additional, Copland, E, additional, Zottoli, M, additional, Pinho-Gomes, A C, additional, Nazarzadeh, M, additional, and Rahimi, K, additional

Published
2019
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34. BLOOD PRESSURE AND RISK OF VENOUS THROMBOEMBOLISM

Author

Nazarzadeh, M., primary, Pinho-Gomes, A.C., additional, Mohseni, H., additional, Byrne, K.S., additional, Bidel, Z., additional, Dehghan, A., additional, Canoy, D., additional, Tran, J., additional, Raimondi, F., additional, Solares, R.A., additional, Zhu, Y., additional, Salimi-Khorshi, G., additional, Tregouet, D.A., additional, and Rahimi, K., additional

Published
2019
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35. Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records

Author

Rahimian, F, Salimi-Khorshidi, G, Payberah, AH, Tran, J, Ayala Solares, R, Raimondi, F, Nazarzadeh, M, Canoy, D, Rahimi, K, Rahimian, F, Salimi-Khorshidi, G, Payberah, AH, Tran, J, Ayala Solares, R, Raimondi, F, Nazarzadeh, M, Canoy, D, and Rahimi, K

Abstract

Background: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of capturing complex interactions that are likely to be present when predicting less specific outcomes, such as this one. Methods and findings: We used longitudinal data from linked electronic health records of 4.6 million patients aged 18–100 years from 389 practices across England between 1985 to 2015. The population was divided into a derivation cohort (80%, 3.75 million patients from 300 general practices) and a validation cohort (20%, 0.88 million patients from 89 general practices) from geographically distinct regions with different risk levels. We first replicated a previously reported Cox proportional hazards (CPH) model for prediction of the risk of the first emergency admission up to 24 months after baseline. This reference model was then compared with 2 machine learning models, random forest (RF) and gradient boosting classifier (GBC). The initial set of predictors for all models included 43 variables, including patient demographics, lifestyle factors, laboratory tests, currently prescribed medications, selected morbidities, and previous emergency admissions. We then added 13 more variables (marital status, prior general practice visits, and 11 additional morbidities), and also enriched all variables by incorporating temporal information whenever possible (e.g., time since first diagnosis). We also varied the prediction windows to 12, 36, 48, and 60 months after baseline and compared model performances. For internal validation, we used 5-fold cross-validation. When the initial set of variables was used, GBC outperformed RF and CPH, with an area under the receiver operating characteristic curve (AUC) of 0.779 (95% CI 0.777, 0.781), compared to 0.752 (95% CI 0.751, 0.753) and 0.740 (95% CI 0.739, 0.741), respectively

Published
2018

36. Elevated blood pressure and risk of aortic valve disease: A cohort analysis of 5.4 million UK adults

Author

Rahimi, K, Mohseni, H, Kiran, A, Tran, J, Nazarzadeh, M, Rahimian, F, Woodward, M, Dwyer, T, Macmahon, S, Otto, CM, Rahimi, K, Mohseni, H, Kiran, A, Tran, J, Nazarzadeh, M, Rahimian, F, Woodward, M, Dwyer, T, Macmahon, S, and Otto, CM

Abstract

© The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Cardiology. Aims To test two related hypotheses that elevated blood pressure (BP) is a risk factor for aortic valve stenosis (AS) or regurgitation (AR). Methods and results In this cohort study of 5.4 million UK patients with no known cardiovascular disease or aortic valve disease at baseline, we investigated the relationship between BP and risk of incident AS and AR using multivariable-adjusted Cox regression models. Over a median follow-up of 9.2 years, 20 680 patients (0.38%) were diagnosed with AS and 6440 (0.12%) patients with AR. Systolic BP (SBP) was continuously related to the risk of AS and AR with no evidence of a nadir down to 115 mmHg. Each 20 mmHg increment in SBP was associated with a 41% higher risk of AS (hazard ratio 1.41, 95% confidence interval 1.38-1.45) and a 38% higher risk of AR (1.38, 1.31-1.45). Associations were stronger in younger patients but with no strong evidence for interaction by gender or body mass index. Each 10 mmHg increment in diastolic BP was associated with a 24% higher risk of AS (1.24, 1.19-1.29) but not AR (1.04, 0.97-1.11). Each 15 mmHg increment in pulse pressure was associated with a 46% greater risk of AS (1.46, 1.42-1.50) and a 53% higher risk of AR (1.53, 1.45-1.62). Conclusion Long-term exposure to elevated BP across its whole spectrum was associated with increased risk of AS and AR. The possible causal nature of the observed associations warrants further investigation.

Published
2018

37. Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study

Author

Tran, J, Norton, R, Conrad, N, Rahimian, F, Canoy, D, Nazarzadeh, M, Rahimi, K, Tran, J, Norton, R, Conrad, N, Rahimian, F, Canoy, D, Nazarzadeh, M, and Rahimi, K

Abstract

Background: Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES). Methods and findings: We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%–17.0%) in 2000 to 24.3% (22.1%–34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%–31.4%]), depression (23.0% [21.3%–26.0%]), arthritis (20.9% [19.5%–23.5%]), asthma (17.7% [15.8%–20.8%]), and anxiety (15.0% [13.7%–17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30–59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%–22.7%) in women and 12.5% (12.0%–13.9%) in men, and wom

Published
2018

39. Elevated blood pressure and risk of mitral regurgitation: A longitudinal cohort study of 5.5 million United Kingdom adults

Author

Rahimi, K, Mohseni, H, Otto, CM, Conrad, N, Tran, J, Nazarzadeh, M, Woodward, M, Dwyer, T, MacMahon, S, Rahimi, K, Mohseni, H, Otto, CM, Conrad, N, Tran, J, Nazarzadeh, M, Woodward, M, Dwyer, T, and MacMahon, S

Abstract

© 2017 Rahimi et al. Background: Mitral regurgitation in people without prior cardiac disease is considered a degenerative disease with no established risk factors for its prevention. We aimed to test the hypothesis that elevated systolic blood pressure (SBP) across its usual spectrum is associated with higher risk of mitral regurgitation. Methods and findings: We used linked electronic health records from the United Kingdom Clinical Practice Research Datalink (CPRD) from 1 January 1990 to 31 December 2015. CPRD covers approximately 7% of the current UK population and is broadly representative of the population by age, sex, and ethnicity. About 5.5 million UK patients with no known cardiovascular or valve disease at baseline were included in this cohort study. We investigated the relationship between blood pressure (BP) and risk of mitral regurgitation using Cox regression models. Our primary exposure variable was SBP and our primary outcome was incident reports of mitral regurgitation, which were identified from hospital discharge reports or primary care records. Of the 5,553,984 patients in the CPRD that met our inclusion criteria, during the 10-year follow-up period, 28,655 (0.52%) were diagnosed with mitral regurgitation and a further 1,262 (0.02%) were diagnosed with mitral stenosis. SBP was continuously related to the risk of mitral regurgitation with no evidence of a nadir down to 115 mmHg (p < 0.001). Each 20 mmHg increment in SBP was associated with a 26% higher risk of mitral regurgitation (hazard ratio [HR] 1.26; CI 1.23, 1.29). The observed association was partially mediated by diseases affecting the left ventricle during follow-up (myocardial infarction [MI], ischaemic heart disease [IHD], cardiomyopathy, and heart failure). However, the percentage of excess risk mediated (PERM) by these proximate causes of secondary mitral regurgitation was only 13% (CI 6.1%, 20%), and accounting for them had little effect on the long-term association between SBP and m

Published
2017

40. Elevated blood pressure and risk of mitral regurgitation: A longitudinal cohort study of 5.5 million United Kingdom adults.

Author

Sheikh, A, Rahimi, K, Mohseni, H, Otto, CM, Conrad, N, Tran, J, Nazarzadeh, M, Woodward, M, Dwyer, T, MacMahon, S, Sheikh, A, Rahimi, K, Mohseni, H, Otto, CM, Conrad, N, Tran, J, Nazarzadeh, M, Woodward, M, Dwyer, T, and MacMahon, S

Abstract

BACKGROUND: Mitral regurgitation in people without prior cardiac disease is considered a degenerative disease with no established risk factors for its prevention. We aimed to test the hypothesis that elevated systolic blood pressure (SBP) across its usual spectrum is associated with higher risk of mitral regurgitation. METHODS AND FINDINGS: We used linked electronic health records from the United Kingdom Clinical Practice Research Datalink (CPRD) from 1 January 1990 to 31 December 2015. CPRD covers approximately 7% of the current UK population and is broadly representative of the population by age, sex, and ethnicity. About 5.5 million UK patients with no known cardiovascular or valve disease at baseline were included in this cohort study. We investigated the relationship between blood pressure (BP) and risk of mitral regurgitation using Cox regression models. Our primary exposure variable was SBP and our primary outcome was incident reports of mitral regurgitation, which were identified from hospital discharge reports or primary care records. Of the 5,553,984 patients in the CPRD that met our inclusion criteria, during the 10-year follow-up period, 28,655 (0.52%) were diagnosed with mitral regurgitation and a further 1,262 (0.02%) were diagnosed with mitral stenosis. SBP was continuously related to the risk of mitral regurgitation with no evidence of a nadir down to 115 mmHg (p < 0.001). Each 20 mmHg increment in SBP was associated with a 26% higher risk of mitral regurgitation (hazard ratio [HR] 1.26; CI 1.23, 1.29). The observed association was partially mediated by diseases affecting the left ventricle during follow-up (myocardial infarction [MI], ischaemic heart disease [IHD], cardiomyopathy, and heart failure). However, the percentage of excess risk mediated (PERM) by these proximate causes of secondary mitral regurgitation was only 13% (CI 6.1%, 20%), and accounting for them had little effect on the long-term association between SBP and mitral regurgitation (

Published
2017

41. The effect of Ni and Fe doping on Hall anomaly in vortex state of doped YBCO samples

Author

Nazarzadeh, M., Saeb, F., and Vahid Daadmehr

Subjects
Hall anomaly sign reversal, vortex state, Y based superconductors, lcsh:Physics, lcsh:QC1-999
Abstract

We have investigated hall effect on YBa2Cu3-xMxO7-δ (M=Ni, Fe) bulk samples, with dopant amount 0 ≤ x ≤ 0.045 for Ni and 0 ≤ x ≤ 0.03 for Fe, with magnetic field (H=2.52, 4.61, 6.27 kOe) perpendicular to sample’s surface with constant current 100 mA. Our study shows that as both dopants increases, TC decreases and it decreases faster by Ni . In these ranges of dopant and magnetic field the Hall sign reversal has been observed in all samples once and also ∆max has occurred in lower temperatures, its magnitude increases by Ni, and in Fe doped samples except in sample with dopant amount x=0.03, which almost decreases, that it can show effect of magnetic doping on hall effect.

Published
2010

50. Prevalence of important poisoning methods used in Iranian suicides: A systematic review and meta-analysis

Author

Bidel, Z., Nazarzadeh, M., Ayubi, E., and Kourosh Sayehmiri

Subjects
Suicide, Suicide Method, Meta-analysis, lcsh:R5-920, Poisoning, lcsh:R, lcsh:Medicine, lcsh:Medicine (General)
Abstract

Introduction: One of the most important subjects in the study of suicide is the methods of suicide. There is not accurate information relating to employed poisoning methods for suicide in Iran. Studies conducted in different provinces provided different results. This study aimed to estimate the prevalence of poisoning methods used in attempted suicides in Iran.Materials and Methods: Domestic scientific databases, PubMed, Science direct/ISI and Scopus searched without any time limitation. Searching was updated by March 20, 2012. Initially, 1398 articles were retrieved. After review of titles, 34 studies included for review of full text. Finally, 19 articles entered in meta-analysis. Random effects model of Mantel-Haenzel employed for estimation of pooled prevalence. Meta-regression and Subgroup analyses were employed to assess the cause of heterogeneity among the selected studies.Results: This meta-analysis included 8494 males and 13503 females. Heterogeneity measure for drug poisoning and agricultural poisoning was 99.3% and 98.1%, respectively. The prevalence of drug poisoning was 75% (CI 95%: 68 to 82%) and the prevalence of agricultural poisoning was 13% (CI 95%: 10 to 16%). The lowest prevalence of drug poisoning and agricultural poisoning was in Ilam and Khorasan Razavi provinces and highest in Golestan and Ilam provinces, respectively.Conclusion: Drug poisoning was the most prevalent method for suicide. Therefore, training for no storage of drugs at home and impose more strict instructions for medications prescription are recommended.

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