88 results on '"Erqou, S"'
Search Results
2. Racial differences in the burden of coronary artery calcium and carotid intima media thickness between Blacks and Whites
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Erqou, S., Kip, K. E., Mulukutla, S. R., Aiyer, A. N., and Reis, S. E.
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- 2015
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3. Association between glycated haemoglobin and the risk of lower extremity amputation in patients with diabetes mellitus—review and meta-analysis
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Adler, A. I., Erqou, S., Lima, T. A. S., and Robinson, A. H. N.
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- 2010
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4. Association of C-reactive protein with type 2 diabetes: prospective analysis and meta-analysis
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Lee, C. C., Adler, A. I., Sandhu, M. S., Sharp, S. J., Forouhi, N. G., Erqou, S., Luben, R., Bingham, S., Khaw, K. T., and Wareham, N. J.
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- 2009
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5. Major lipids, apolipoproteins, and risk of vascular disease
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Emerging Risk Factors Collaboration, Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, Wood AM, Lewington S, Sattar N, Packard CJ, Collins R, Thompson SG, Tipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy RP, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Verschure WM, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson J, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Stampfer M, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marin Ibañez A, Feskens EJ, Kromhout D, Walker M, Watson S, Erqou S, Orfei L, Pennells L, Perry PL, Alexander M, Wensley F, White IR, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Epidemiology and Data Science, General practice, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Sarwar, N, Perry, P, Kaptoge, S, Ray, Kk, Thompson, A, Wood, Am, Lewington, S, Sattar, N, Packard, Cj, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Verschure, Wm, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marin Ibañez, A, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Erqou, S, Orfei, L, Pennells, L, Perry, Pl, Alexander, M, Wensley, F, White, Ir, and Danesh, J.
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medicine.medical_specialty ,Apolipoprotein B ,biology ,Triglyceride ,business.industry ,Vascular disease ,Cholesterol ,Proportional hazards model ,Hazard ratio ,Context (language use) ,General Medicine ,11 Medical And Health Sciences ,medicine.disease ,Gastroenterology ,Article ,chemistry.chemical_compound ,Endocrinology ,chemistry ,Internal medicine ,General & Internal Medicine ,biology.protein ,Medicine ,lipids (amino acids, peptides, and proteins) ,Myocardial infarction ,business - Abstract
Udgivelsesdato: 2009-Nov-11 CONTEXT: Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. OBJECTIVE: To assess major lipids and apolipoproteins in vascular risk. DESIGN, SETTING, AND PARTICIPANTS: Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. MAIN OUTCOME MEASURES: Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. RESULTS: The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. CONCLUSION: Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.
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- 2016
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6. Can estrogen receptor status predict for shorter duration of adjuvant trastuzumab in early-stage breast cancer?
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Mathew, A., primary and Erqou, S., additional
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- 2018
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7. P1025Wearable cardioverter-defibrillator therapy for the prevention of sudden cardiac death: a systematic review and meta-analysis
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Masri, A, primary, Altibi, A, additional, Erqou, S, additional, Zmaili, M, additional, Saleh, A, additional, Al-Adham, R, additional, Ayoub, K, additional, Barakat, A, additional, Jain, S, additional, Saba, S, additional, and Adelstein, E, additional
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- 2018
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8. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis
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Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, Danesh JTipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless L, Ballantyne CM, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman MW, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Mayr A, Schett G, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Zacho J, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Benjamin EJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Laukkanen JA, Deeg DJ, Bremmer MA, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Davidson K, Kirkland S, Shaffer J, Korin MR, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Packard CJ, Sattar N, Westendorp RG, Buckley BM, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt RR, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Basu S, Cederholm T, Byberg L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot IM, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe S, Ford I, Robertson M, He Y, Ibañez AM, Feskens EJ, Walker M, Watson S, Erqou S, Lewington S, Pennells L, Perry PL, Ray KK, Sarwar N, Alexander M, Thompson A, White IR, Wood AM, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, General practice, EMGO - Lifestyle, overweight and diabetes, Psychiatry, EMGO - Mental health, Emerging Risk Factors, Collaboration, Kaptoge, S, Di Angelantonio, E, Lowe, G, Pepys, Mb, Thompson, Sg, Collins, R, Danesh JTipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Ballantyne, Cm, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, Mw, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Mayr, A, Schett, G, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Zacho, J, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Benjamin, Ej, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Laukkanen, Ja, Deeg, Dj, Bremmer, Ma, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Davidson, K, Kirkland, S, Shaffer, J, Korin, Mr, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, Rr, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Basu, S, Cederholm, T, Byberg, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, Im, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, S, Ford, I, Robertson, M, He, Y, Ibañez, Am, Feskens, Ej, Walker, M, Watson, S, Erqou, S, Lewington, S, Pennells, L, Perry, Pl, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, White, Ir, Wood, Am, and Danesh, J.
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Lung Diseases ,Male ,Databases, Factual ,Plasma-fibrinogen ,Blood Pressure ,Coronary Disease ,030204 cardiovascular system & hematology ,Associations ,Body Mass Index ,Low-density-lipoprotein ,Leukocyte Count ,0302 clinical medicine ,Risk Factors ,Neoplasms ,030212 general & internal medicine ,Stroke ,Framingham Risk Score ,biology ,Smoking ,11 Medical And Health Sciences ,General Medicine ,Articles ,Middle Aged ,3. Good health ,C-Reactive Protein ,Cholesterol ,Regression Analysis ,low-density lipoprotein cardiovascular-disease nonvascular mortality regression dilution plasma-fibrinogen mendelian randomization independent predictor prospective cohorts vascular-disease inflammation ,Female ,Risk assessment ,medicine.medical_specialty ,Alcohol Drinking ,Regression dilution ,Motor Activity ,Risk Assessment ,03 medical and health sciences ,Sex Factors ,Cardiovascular-disease ,General & Internal Medicine ,Internal medicine ,Diabetes Mellitus ,medicine ,Humans ,Women ,Risk factor ,Serum Albumin ,Triglycerides ,Inflammation ,Markers ,Independent predictor ,Interleukin-6 ,business.industry ,Vascular disease ,C-reactive protein ,Fibrinogen ,medicine.disease ,Surgery ,Relative risk ,biology.protein ,Nonvascular mortality ,business ,Biomarkers - Abstract
Udgivelsesdato: 2010-Jan-9 BACKGROUND: Associations of C-reactive protein (CRP) concentration with risk of major diseases can best be assessed by long-term prospective follow-up of large numbers of people. We assessed the associations of CRP concentration with risk of vascular and non-vascular outcomes under different circumstances. METHODS: We meta-analysed individual records of 160 309 people without a history of vascular disease (ie, 1.31 million person-years at risk, 27 769 fatal or non-fatal disease outcomes) from 54 long-term prospective studies. Within-study regression analyses were adjusted for within-person variation in risk factor levels. RESULTS: Log(e) CRP concentration was linearly associated with several conventional risk factors and inflammatory markers, and nearly log-linearly with the risk of ischaemic vascular disease and non-vascular mortality. Risk ratios (RRs) for coronary heart disease per 1-SD higher log(e) CRP concentration (three-fold higher) were 1.63 (95% CI 1.51-1.76) when initially adjusted for age and sex only, and 1.37 (1.27-1.48) when adjusted further for conventional risk factors; 1.44 (1.32-1.57) and 1.27 (1.15-1.40) for ischaemic stroke; 1.71 (1.53-1.91) and 1.55 (1.37-1.76) for vascular mortality; and 1.55 (1.41-1.69) and 1.54 (1.40-1.68) for non-vascular mortality. RRs were largely unchanged after exclusion of smokers or initial follow-up. After further adjustment for fibrinogen, the corresponding RRs were 1.23 (1.07-1.42) for coronary heart disease; 1.32 (1.18-1.49) for ischaemic stroke; 1.34 (1.18-1.52) for vascular mortality; and 1.34 (1.20-1.50) for non-vascular mortality. INTERPRETATION: CRP concentration has continuous associations with the risk of coronary heart disease, ischaemic stroke, vascular mortality, and death from several cancers and lung disease that are each of broadly similar size. The relevance of CRP to such a range of disorders is unclear. Associations with ischaemic vascular disease depend considerably on conventional risk factors and other markers of inflammation. FUNDING: British Heart Foundation, UK Medical Research Council, BUPA Foundation, and GlaxoSmithKline.
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- 2010
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9. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality
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Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry PL, Di Angelantonio E, Thompson A, White IR, Marcovina SM, Collins R, Thompson SG, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Folsom AR, Chambless L, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Frikke Schmidt R, Kamstrup PR, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Cooper JA, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Daniels LB, Laughlin GA, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe G, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Best L, Umans J, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Sundström J, Lind L, Lannfelt L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe S, Robertson M, He Y, Marin Ibanñez A, Feskens E, Kromhout D, Walker M, Watson S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Wensley F, Wood AM, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Emerging Risk Factors, Collaboration, Erqou, S, Kaptoge, S, Perry, Pl, Di Angelantonio, E, Thompson, A, White, Ir, Marcovina, Sm, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Kamstrup, Pr, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Cooper, Ja, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Daniels, Lb, Laughlin, Ga, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, G, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Sundström, J, Lind, L, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, S, Robertson, M, He, Y, Marin Ibanñez, A, Feskens, E, Kromhout, D, Walker, M, Watson, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Wensley, F, Wood, Am, and Danesh, J.
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medicine.medical_specialty ,Context (language use) ,Coronary Disease ,Article ,Risk Factors ,General & Internal Medicine ,Internal medicine ,Cause of Death ,medicine ,Humans ,Myocardial infarction ,Prospective cohort study ,Stroke ,biology ,business.industry ,11 Medical And Health Sciences ,General Medicine ,Lipoprotein(a) ,medicine.disease ,Surgery ,Relative risk ,Nested case-control study ,biology.protein ,business ,Cohort study - Abstract
Udgivelsesdato: 2009-Jul-22 CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION: Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. DATA EXTRACTION: Individual records were provided for each of 126,634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22,076 first-ever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. DATA SYNTHESIS: Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 person-years and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes.
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- 2009
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10. The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases
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Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, Edoardo, Tikhonoff, Valerie, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, Rs, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, Wood, Am, Emerging Risk Factors Collaboration, Interne Geneeskunde, RS: NUTRIM School of Nutrition and Translational Research in Metabolism, RS: CARIM School for Cardiovascular Diseases, Movement Behavior, Executive board Vrije Universiteit, Clinical Child and Family Studies, Sociology and Social Gerontology, Earth and Climate, Environmental Policy Analysis, Developmental Genetics, Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, and Wood, A. M.
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Databases, Factual ,Nutrition and Disease ,Epidemiology ,Inflammatory markers ,middle-aged men ,Disease ,Leukocyte Count ,c-reactive protein ,Risk Factors ,Voeding en Ziekte ,adult-treatment-panel ,Prospective Studies ,Myocardial infarction ,Prospective cohort study ,education.field_of_study ,biology ,plasma-fibrinogen ,Asia, Eastern ,Confounding ,density-lipoprotein cholesterol ,Cardiovascular disease ,Lipids ,myocardial-infarction ,Coronary heart disease ,Cardiovascular Diseases ,Meta-analysis ,Lipoproteins, HDL ,high blood cholesterol ,medicine.medical_specialty ,low-dose aspirin ,Population ,10-year follow-up ,SDG 3 - Good Health and Well-being ,Albumins ,medicine ,Humans ,education ,Triglycerides ,VLAG ,Inflammation ,Estimation ,business.industry ,C-reactive protein ,medicine.disease ,Surgery ,Emergency medicine ,biology.protein ,business ,coronary-heart-disease ,Biomarkers - Abstract
Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age-and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily,with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.
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- 2007
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11. Burden of undiagnosed hypertension in sub-saharan africa : A systematic review and meta-analysis
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Ataklte, F., Erqou, S., Kaptoge, S., Taye, B., Echouffo-Tcheugui, J.B., Kengne, Andre Pascal, Ataklte, F., Erqou, S., Kaptoge, S., Taye, B., Echouffo-Tcheugui, J.B., and Kengne, Andre Pascal
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- 2015
12. Burden of undiagnosed hypertension in sub-saharan africa: A systematic review and meta-analysis
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Julius Centrum, Ataklte, F., Erqou, S., Kaptoge, S., Taye, B., Echouffo-Tcheugui, J.B., Kengne, Andre Pascal, Julius Centrum, Ataklte, F., Erqou, S., Kaptoge, S., Taye, B., Echouffo-Tcheugui, J.B., and Kengne, Andre Pascal
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- 2015
13. Effect of Aspirin on Vascular and Nonvascular Outcomes
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Seshasai, SRK, Wijesuriya, S, Sivakumaran, R, Nethercott, S, Erqou, S, Sattar, N, and Ray, KK
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General & Internal Medicine ,11 Medical And Health Sciences - Published
- 2012
14. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies
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Thompson, S. Kaptoge, S. White, I. Wood, A. Perry, P. Danesh, J. The Emerging Risk Factors Collaboration Thompson, S.G. Kaptoge, S. White, I.R. Wood, A.M. Perry, P.L. Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Chambless, L.E. Panagiotakos, D.B. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Knuiman, M. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P.H. Wannamethee, S.G. Morris, R.W. Willeit, J. Kiechl, S. Santer, P. Mayr, A. Lawlor, D.A. Yarnell, J.W.G. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Keil, J.E. Cushman, M. Tracy, R.P. Tybjærg-Hansen, A. Nordestgaard, B.G. Benn, M. Frikke- Schmidt, R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Gómez de la Cámara, A. Gómez- Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A.J. Taylor, J. Guralnik, J.M. Wallace, R. Guralnik, J. Blazer, D.G. Guralnik, J.M. Guralnik, J.M. Khaw, K.-T. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D'Agostino, R.B. Vasan, R.S. Pencina, M.J. Bladbjerg, E.M. Jørgensen, T. Jespersen, J. Møller, L. Dankner, R. Chetrit, A. Lubin, F. Rosengren, A. Lappas, G. Björkelund, C. Lissner, L. Bengtsson, C. Cremer, P. Nagel, D. Tilvis, R.S. Strandberg, T.E. Kiyohara, Y. Arima, H. Doi, Y. Ninomiya, T. Rodriguez, B. Dekker, J.M. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Kitamura, A. Iso, H. Goldbourt, U. Noda, H. Harald, K. Jousilahti, P. Vartiainen, E. Salonen, J.T. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Meade, T.W. Cooper, J.A. Hedblad, B. Berglund, G. Engstrom, G. Verschuren, W.M.M. Blokstra, A. Cushman, M. Shea, S. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bas Bueno-de-Mesquita, H. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R. Mussolino, M. Rimm, E. Manson, J.E. Pai, J.K. Meade, T.W. Cooper, J.A. Cooper, J.A. Knottenbelt, C. Bauer, K.A. Naito, Y. Holme, I. Hankinson, S. Tverdal, A. Nystad, W. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Wingard, D.L. Bettencourt, R. Gudnason, V. Aspelund, T. Sigurdsson, G. Thorsson, B. Trevisan, M. Witteman, J. Kardys, I. Breteler, M. Hofman, A. Tunstall-Pedoe, H. Tavendale, R. Lowe, G.D.O. Ben-Shlomo, Y. Howard, B.V. Zhang, Y. Umans, J. Onat, A. Davey-Smith, G. Wilsgaard, T. Ingelsson, E. Lind, L. Giedraitis, V. Lannfelt, L. Gaziano, J.M. Ridker, P. Gaziano, J.M. Ridker, P. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Wassertheil-Smoller, S. Manson, J.E. Marmot, M. Clarke, R. Collins, R. Brunner, E. Shipley, M. Ridker, P. Buring, J. Shepherd, J. Cobbe, S.M. Robertson, M. He, Y. Marín Ibañez, A. Feskens, E.J.M. Kromhout, D. Collins, R. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Walker, M. Watson, S. Wensley, F. White, I.R. Wood, A.M.
- Abstract
Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure-risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure-risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure-risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within-and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses. © The Author 2010; all rights reserved.
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- 2010
15. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality
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Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Folsom, A.R. Chambless, L. Panagiotakos, D. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P. Wannamethee, S.G. Morris, R.W. Kiechl, S. Willeit, J. Santer, P. Mayr, A. Wald, N. Ebrahim, S. Lawlor, D. Yarnell, J. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Cushman, M. Psaty, B.M. Tracy, R. Tybjærg-Hansen, A. Nordestgaard, B.G. Frikke-Schmidt, R. Kamstrup, P.R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Pilotto, L. De La Cámara, A.G. Gómez Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A. Smith, F.B. Taylor, J. Guralnik, J.M. Phillips, C.L. Wallace, R.B. Blazer, D.G. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.-H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D’Agostino, R.B. Wolf, P.A. Vasan, R.S. Pencina, M.J. Bladbjerg, E.-M. Jørgensen, T. Møller, L. Jespersen, J. Dankner, R. Chetrit, A. Lubin, F. Rosengren, A. Wilhelmsen, L. Lappas, G. Eriksson, H. Björkelund, C. Lissner, L. Bengtsson, C. Cremer, P. Nagel, D. Tilvis, R.S. Strandberg, T.E. Rodriguez, B. Dekker, J. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Iso, H. Kitamura, A. Noda, H. Salonen, J.T. Nyyssönen, K. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Hedblad, B. Berglund, G. Engström, G. Verschuren, W.M.M. Blokstra, A. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bueno-De-Mesquita, H.B. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R.F. Mussolino, M. Hankinson, S. Manson, J.E. Cooper, J.A. Bauer, K.A. Naito, Y. Holme, I. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Luc, G. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Lamarche, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Daniels, L.B. Laughlin, G.A. Gudnason, V. Aspelund, T. Sigurdsson, G. Thorsson, B. Trevisan, M. Witteman, J. Kardys, I. Breteler, M.M.B. Hofman, A. Tunstall-Pedoe, H. Tavendale, R. Lowe, G. Ben-Shlomo, Y. Davey-Smith, G. Howard, B.V. Zhang, Y. Best, L. Umans, J. Onat, A. Njølstad, I. Mathiesen, E.B. Løchen, M.-L. Wilsgaard, T. Ingelsson, E. Sundström, J. Lind, L. Lannfelt, L. Gaziano, J.M. Stampfer, M. Ridker, P.M. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Marmot, M. Clarke, R. Collins, R. Fletcher, A. Brunner, E. Shipley, M. Buring, J. Cobbe, S. Robertson, M. He, Y. Ibañez, A.M. Feskens, E. Kromhout, D. Walker, M. Watson, S. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Wensley, F. White, I.R. Wood, A.M. Danesh, J.
- Abstract
Context Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein–like particle, may be associated with risk of coronary heart disease (CHD) and stroke. Objective To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. Study Selection Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. Data Extraction Individual records were provided for each of 126 634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22 076 firstever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. Data Synthesis Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 personyears and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. Conclusion Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes. ©2009 American Medical Association. All rights reserved.
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- 2009
16. Racial differences in the burden of coronary artery calcium and carotid intima media thickness between Blacks and Whites
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Erqou, S., primary, Kip, K. E., additional, Mulukutla, S. R., additional, Aiyer, A. N., additional, and Reis, S. E., additional
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- 2014
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17. Apolipoprotein (a) Isoforms and the Risk of Vascular Disease: A Systematic Review of 40 Studies Involving 58,000 Participants
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Erqou, S., primary, Thompson, A., additional, and Angelantonio, D., additional
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- 2011
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18. Association between glycated haemoglobin and the risk of congestive heart failure in diabetes mellitus: systematic review and meta-analysis.
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Erqou S, Lee CT, Suffoletto M, Echouffo-Tcheugui JB, de Boer RA, van Melle JP, and Adler AI
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- 2013
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19. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies
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Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Tipping RW, Ford CE, Pressel SL, Folsom AR, Chambless LE, Wagenknecht LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Oberhollenzer F, Mayr A, Wald N, Ebrahim S, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, de Boer IH, Kizer JR, Mukamal KJ, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Rubio MA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Phillips CL, Wallace R, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Giampaoli S, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Fox CS, Pencina MJ, Bladbjerg E, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Wilhelmsen L, Eriksson H, Svärdsudd K, Welin L, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Strandberg TE, Tilvis RS, Miettinen TA, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Goldbourt U, Nyyssönen K, Tuomainen TP, Salonen JT, Deeg D, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Cushman M, Psaty BM, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Fletcher A, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Bauer KA, Davidson KW, Kirkland S, Shaffer J, Korin MR, Holme I, Ducimetiere P, Jouven X, Bakker SJ, Gansevoort RT, Hillege HL, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrières J, Schulte H, Assmann G, Westendorp RG, Buckley BM, Packard CJ, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Hergenç G, Can G, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Zethelius B, Risérus U, Berne C, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Tinker L, Liu S, Marmot IM, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe SM, Ford I, Robertson M, Ibañez AM, Feskens EJ, Kromhout D, Walker M, Watson S, Alexander M, Erqou S, Haycock P, Perry PL, Thompson SG, Wood AM, Wormser D, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, RS: NUTRIM - R1 - Metabolic Syndrome, RS: CARIM School for Cardiovascular Diseases, Emerging Risk Factors, Collaboration, Sarwar, N, Gao, P, Seshasai, Sr, Gobin, R, Kaptoge, S, Di Angelantonio, E, Ingelsson, E, Lawlor, Da, Selvin, E, Stampfer, M, Stehouwer, Cd, Lewington, S, Pennells, L, Thompson, A, Sattar, N, White, Ir, Ray, Kk, Danesh J., Tipping RW, Ford, Ce, Pressel, Sl, Folsom, Ar, Chambless, Le, Wagenknecht, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Oberhollenzer, F, Mayr, A, Wald, N, Ebrahim, S, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, de Boer, Ih, Kizer, Jr, Mukamal, Kj, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Rubio, Ma, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Giampaoli, S, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Fox, C, Pencina, Mj, Bladbjerg, E, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Wilhelmsen, L, Eriksson, H, Svärdsudd, K, Welin, L, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Strandberg, Te, Tilvis, R, Miettinen, Ta, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Nyyssönen, K, Tuomainen, Tp, Salonen, Jt, Deeg, D, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Cushman, M, Psaty, Bm, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Fletcher, A, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Bauer, Ka, Davidson, Kw, Kirkland, S, Shaffer, J, Korin, Mr, Holme, I, Ducimetiere, P, Jouven, X, Bakker, Sj, Gansevoort, Rt, Hillege, Hl, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Westendorp, Rg, Buckley, Bm, Packard, Cj, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Hergenç, G, Can, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Zethelius, B, Risérus, U, Berne, C, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Tinker, L, Liu, S, Marmot, Im, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Alexander, M, Erqou, S, Haycock, P, Perry, Pl, Thompson, Sg, Wood, Am, Wormser, D, Danesh, J., and University of Groningen
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Adult ,Blood Glucose ,Male ,medicine.medical_specialty ,PATHOPHYSIOLOGY ,030209 endocrinology & metabolism ,Coronary Disease ,Disease ,030204 cardiovascular system & hematology ,THERAPY ,Diabetes Complications ,03 medical and health sciences ,0302 clinical medicine ,Risk Factors ,Diabetes mellitus ,Internal medicine ,General & Internal Medicine ,medicine ,Diabetes Mellitus ,Humans ,CORONARY-HEART-DISEASE ,Prospective cohort study ,Stroke ,Aged ,Glucose Metabolism Disorders ,business.industry ,Vascular disease ,MORTALITY ,Absolute risk reduction ,ASIA-PACIFIC REGION ,WOMEN ,General Medicine ,Fasting ,11 Medical And Health Sciences ,Articles ,Middle Aged ,medicine.disease ,Impaired fasting glucose ,3. Good health ,Endocrinology ,Blood pressure ,ATHEROSCLEROSIS ,Cardiovascular Diseases ,CARDIOVASCULAR-DISEASES ,Female ,coronary-heart-disease asia-pacific region cardiovascular-diseases task-force pathophysiology atherosclerosis mortality therapy women ,business ,TASK-FORCE - Abstract
Summary Background Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. Methods We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. Findings Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8·49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2·00 (95% CI 1·83–2·19) for coronary heart disease; 2·27 (1·95–2·65) for ischaemic stroke; 1·56 (1·19–2·05) for haemorrhagic stroke; 1·84 (1·59–2·13) for unclassified stroke; and 1·73 (1·51–1·98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40–59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10–12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3·90 mmol/L and 5·59 mmol/L. Compared with fasting blood glucose concentrations of 3·90–5·59 mmol/L, HRs for coronary heart disease were: 1·07 (0·97–1·18) for lower than 3·90 mmol/L; 1·11 (1·04–1·18) for 5·60–6·09 mmol/L; and 1·17 (1·08–1·26) for 6·10–6·99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. Interpretation Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease. Funding British Heart Foundation, UK Medical Research Council, and Pfizer.
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20. Clinical Outcomes After Acute Coronary Syndromes or Revascularization Among People Living With HIV: A Systematic Review and Meta-Analysis.
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Haji M, Capilupi M, Kwok M, Ibrahim N, Bloomfield GS, Longenecker CT, Rodriguez-Barradas MC, Ashong CN, Jutkowitz E, Taveira TH, Richard M, Sullivan JL, Rudolph JL, Wu WC, and Erqou S
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- Humans, Male, Middle Aged, Female, Treatment Outcome, Myocardial Revascularization statistics & numerical data, Adult, HIV Infections complications, HIV Infections epidemiology, Acute Coronary Syndrome surgery, Acute Coronary Syndrome epidemiology, Percutaneous Coronary Intervention statistics & numerical data
- Abstract
Importance: Clinical outcomes after acute coronary syndromes (ACS) or percutaneous coronary interventions (PCIs) in people living with HIV have not been characterized in sufficient detail, and extant data have not been synthesized adequately., Objective: To better characterize clinical outcomes and postdischarge treatment of patients living with HIV after ACS or PCIs compared with patients in an HIV-negative control group., Data Sources: Ovid MEDLINE, Embase, and Web of Science were searched for all available longitudinal studies of patients living with HIV after ACS or PCIs from inception until August 2023., Study Selection: Included studies met the following criteria: patients living with HIV and HIV-negative comparator group included, patients presenting with ACS or undergoing PCI included, and longitudinal follow-up data collected after the initial event., Data Extraction and Synthesis: Data extraction was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Clinical outcome data were pooled using a random-effects model meta-analysis., Main Outcome and Measures: The following clinical outcomes were studied: all-cause mortality, major adverse cardiovascular events, cardiovascular death, recurrent ACS, stroke, new heart failure, total lesion revascularization, and total vessel revascularization. The maximally adjusted relative risk (RR) of clinical outcomes on follow-up comparing patients living with HIV with patients in control groups was taken as the main outcome measure., Results: A total of 15 studies including 9499 patients living with HIV (pooled proportion [range], 76.4% [64.3%-100%] male; pooled mean [range] age, 56.2 [47.0-63.0] years) and 1 531 117 patients without HIV in a control group (pooled proportion [range], 61.7% [59.7%-100%] male; pooled mean [range] age, 67.7 [42.0-69.4] years) were included; both populations were predominantly male, but patients living with HIV were younger by approximately 11 years. Patients living with HIV were also significantly more likely to be current smokers (pooled proportion [range], 59.1% [24.0%-75.0%] smokers vs 42.8% [26.0%-64.1%] smokers) and engage in illicit drug use (pooled proportion [range], 31.2% [2.0%-33.7%] drug use vs 6.8% [0%-11.5%] drug use) and had higher triglyceride (pooled mean [range], 233 [167-268] vs 171 [148-220] mg/dL) and lower high-density lipoprotein-cholesterol (pooled mean [range], 40 [26-43] vs 46 [29-46] mg/dL) levels. Populations with and without HIV were followed up for a pooled mean (range) of 16.2 (3.0-60.8) months and 11.9 (3.0-60.8) months, respectively. On postdischarge follow-up, patients living with HIV had lower prevalence of statin (pooled proportion [range], 53.3% [45.8%-96.1%] vs 59.9% [58.4%-99.0%]) and β-blocker (pooled proportion [range], 54.0% [51.3%-90.0%] vs 60.6% [59.6%-93.6%]) prescriptions compared with those in the control group, but these differences were not statistically significant. There was a significantly increased risk among patients living with HIV vs those without HIV for all-cause mortality (RR, 1.64; 95% CI, 1.32-2.04), major adverse cardiovascular events (RR, 1.11; 95% CI, 1.01-1.22), recurrent ACS (RR, 1.83; 95% CI, 1.12-2.97), and admissions for new heart failure (RR, 3.39; 95% CI, 1.73-6.62)., Conclusions and Relevance: These findings suggest the need for attention toward secondary prevention strategies to address poor outcomes of cardiovascular disease among patients living with HIV.
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- 2024
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21. Systematic Review of Advanced Heart Failure Therapy Outcomes in People With Human Immunodeficiency Virus.
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Haji M, Soares C, Agyeman H, Ehsan A, Longenecker CT, Bloomfield GS, Joseph J, Rudolph JL, Wu WC, and Erqou S
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- 2024
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22. Risk of death and readmission among individuals with heart failure and HIV: A systematic review and meta-analysis.
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Zhou Y, Zhang X, Gao Y, Alvi RM, Erqou S, Chen Y, Wang H, Wang W, Li X, Zanni MV, Neilan TG, Vermund SH, Qian HZ, and Qian F
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- Adult, Humans, Patient Readmission, Cohort Studies, HIV Infections complications, HIV Infections epidemiology, Heart Failure epidemiology, Heart Failure complications
- Abstract
The association between human immunodeficiency virus (HIV) status and readmissions and death outcomes in patients with established heart failure (HF) remains unclear. We conducted a systematic search of PubMed, EMBASE, Cochrane Library, and Web of Science up to March 1st, 2023, for cohort studies of adult patients (≥18 years) diagnosed with HF and recorded HIV status at baseline. Our analysis included 7 studies with 10,328 HF patients living with HIV and 48,757 HF patients without HIV. Compared to HF patients without HIV, those with HIV had a higher risk of all-cause deaths (HR: 1.20, 95% CI: 1.15-1.25). HIV infection was also associated with increased risks of HF-associated readmission (HR: 1.34, 95% CI: 1.03-1.75) and all-cause readmission (HR: 1.27, 95% CI: 1.10-1.46). Our study highlights the independent association between HIV and poor HF outcomes, emphasizing the need for improved management in individuals living with HIV., Competing Interests: Declaration of Competing Interest Dr. Neilan has been a consultant to and received fees from Bristol Myers Squibb, Genentech, CRC Oncology, Roche, Sanofi and Parexel Imaging Pharmaceuticals. Dr. Neilan also reports grant funding from Astra Zeneca and Bristol Myers Squibb related to the cardiac effects of immune checkpoint inhibitors, all outside of the current work. Dr. Zanni is Principal Investigator on an investigator-initiated research grant from Gilead to her institution, which is unrelated to this work. Other authors have no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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23. Proprotein convertase subtilisn/kexin type 9 inhibitors and small interfering RNA therapy for cardiovascular risk reduction: A systematic review and meta-analysis.
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Imran TF, Khan AA, Has P, Jacobson A, Bogin S, Khalid M, Khan A, Kim S, Erqou S, Choudhary G, Aspry K, and Wu WC
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- Humans, PCSK9 Inhibitors, Cholesterol, LDL, Proprotein Convertase 9 genetics, Heart Disease Risk Factors, RNA, Small Interfering therapeutic use, Myocardial Infarction drug therapy, Atherosclerosis drug therapy, Anticholesteremic Agents therapeutic use, Cardiovascular Diseases drug therapy, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use
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Background: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of mortality worldwide. Atherosclerosis occurs due to accumulation of low-density lipoprotein cholesterol (LDL-c) in the arterial system. Thus, lipid lowering therapy is essential for both primary and secondary prevention. Proprotein convertase subtilisn/kexin type 9 (PCSK9) inhibitors (Evolocumab, Alirocumab) and small interfering RNA (siRNA) therapy (Inclisiran) have been demonstrated to lower LDL-c and ASCVD events in conjunction with maximally tolerated statin therapy. However, the degree of LDL-c reduction and the impact on reducing major adverse cardiac events, including their impact on mortality, remains unclear., Objective: The purpose of this study is to examine the effects of PCSK9 inhibitors and small interfering RNA (siRNA) therapy on LDL-c reduction and major adverse cardiac events (MACE) and mortality by conducting a meta-analysis of randomized controlled trials., Methods: Using Pubmed, Embase, Cochrane Library and clinicaltrials.gov until April 2023, we extracted randomized controlled trials (RCTs) of PCSK9 inhibitors (Evolocumab, Alirocumab) and siRNA therapy (Inclisiran) for lipid lowering and risk of MACE. Using random-effects models, we pooled the relative risks and 95% CIs and weighted least-squares mean difference in LDL-c levels. We estimated odds ratios with 95% CIs among MACE subtypes and all-cause mortality. Fixed-effect model was used, and heterogeneity was assessed using the I2 statistic., Results: In all, 54 studies with 87,669 participants (142,262 person-years) met criteria for inclusion. LDL-c percent change was reported in 47 studies (n = 62,634) evaluating two PCSK9 inhibitors and siRNA therapy. Of those, 21 studies (n = 41,361) included treatment with Evolocumab (140mg), 22 (n = 11,751) included Alirocumab (75mg), and 4 studies (n = 9,522) included Inclisiran (284mg and 300mg). Compared with placebo, after a median of 24 weeks (IQR 12-52), Evolocumab reduced LDL-c by -61.09% (95% CI: -64.81, -57.38, p<0.01) and Alirocumab reduced LDL-c by -46.35% (95% CI: -51.75, -41.13, p<0.01). Inclisiran 284mg reduced LDL-c by -54.83% (95% CI: -59.04, -50.62, p = 0.05) and Inclisiran 300mg reduced LDL-c by -43.11% (95% CI: -52.42, -33.80, p = 0.01). After a median of 8 months (IQR 6-15), Evolocumab reduced the risk of myocardial infarction (MI), OR 0.72 (95% CI: 0.64, 0.81, p<0.01), coronary revascularization, 0.77 (95% CI: 0.70, 0.84, p<0.01), stroke, 0.79 (95% CI: 0.66, 0.94, p = 0.01) and overall MACE 0.85 (95% CI: 0.80, 0.89, p<0.01). Alirocumab reduced MI, 0.57 (0.38, 0.86, p = 0.01), cardiovascular mortality 0.35 (95% CI: 0.16, 0.77, p = 0.01), all-cause mortality 0.60 (95% CI: 0.43, 0.84, p<0.01), and overall MACE 0.35 (0.16, 0.77, p = 0.01)., Conclusion: PCSK9 inhibitors (Evolocumab, Alirocumab) and siRNA therapy (Inclisiran) significantly reduced LDL-c by >40% in high-risk individuals. Additionally, both Alirocumab and Evolocumab reduced the risk of MACE, and Alirocumab reduced cardiovascular and all-cause mortality., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)
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- 2023
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24. Long-Term Outcomes of Veterans With a Diagnosis of Heart Failure After COVID-19.
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Khetpal V, Berkowitz J, Jiang L, Menon A, Shah N, Heffernan DS, Choudhary G, Rudolph JL, Wu WC, and Erqou S
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- 2023
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25. Comparing Lookback Periods to Ascertain Alzheimer's Disease and Related Dementias.
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Kunicki ZJ, Bayer T, Jiang L, Bozzay ML, Quinn MJ, De Vito AN, Emrani S, Erqou S, McGeary JE, Zullo AR, Duprey MS, Singh M, Primack JM, Kelso CM, Wu WC, and Rudolph JL
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- Humans, Prevalence, Alzheimer Disease diagnosis, Alzheimer Disease epidemiology
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Claims data are a valuable resource for studying Alzheimer's disease and related dementias (ADRD). Alzheimer's disease and related dementias is often identified using a list of claims codes and a fixed lookback period of 3 years of data. However, a 1-year lookback or an approach using all-available lookback data could be beneficial based on different research questions. Thus, the purpose of this study was to compare 1-year and all-available lookback approaches to ascertaining ADRD compared to the standard 3-year approach. Using a cohort of Veterans hospitalized for heart failure (N = 373, 897), our results suggested high agreement (93% or greater) between the lookback periods. The 1-year lookback period had lower sensitivity (60%) and underestimated the prevalence of ADRD. These results suggest that 1-year and all-available lookback periods are viable approaches when using claims data.
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- 2023
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26. Particulate matter 2.5, metropolitan status, and heart failure outcomes in US counties: A nationwide ecologic analysis.
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Chen EW, Ahmad K, Erqou S, and Wu WC
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- Aged, Humans, United States epidemiology, Particulate Matter adverse effects, Particulate Matter analysis, Cross-Sectional Studies, Medicare, Socioeconomic Factors, Environmental Exposure adverse effects, Environmental Exposure analysis, Heart Failure epidemiology, Air Pollutants analysis, Air Pollution adverse effects, Air Pollution analysis
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The relationship between particulate matter with a diameter of 2.5 micrometers or less (PM2.5) and heart failure (HF) hospitalizations and mortality in the US is unclear. Prior studies are limited to studying the effects of daily PM2.5 exposure on HF hospitalizations in specific geographic regions. Because PM2.5 can vary by geography, this study examines the effects of annual ambient PM2.5 exposure on HF hospitalizations and mortality at a county-level across the US. A cross-sectional analysis of county-level ambient PM2.5 concentration, HF hospitalizations, and HF mortality across 3135 US counties nationwide was performed, adjusting for county-level demographics, socioeconomic factors, comorbidities, and healthcare-associated behaviors. There was a moderate correlation between county PM2.5 and HF hospitalization among Medicare beneficiaries (r = 0.41) and a weak correlation between county PM2.5 and HF mortality (r = 0.08) (p-values < 0.01). After adjustment for various county level covariates, every 1 ug/m3 increase in annual PM2.5 concentration was associated with an increase of 0.51 HF Hospitalizations/1,000 Medicare Beneficiaries and 0.74 HF deaths/100,000 residents (p-values < 0.05). In addition, the relationship between PM2.5 and HF hospitalizations was similar when factoring in metropolitan status of the counties. In conclusion, increased ambient PM2.5 concentration level was associated with increased incidence of HF hospitalizations and mortality at the county level across the US. This calls for future studies exploring policies that reduce ambient particulate matter pollution and their downstream effects on potentially improving HF outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)
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- 2022
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27. New Antipsychotic Prescribing Continued into Skilled Nursing Facilities Following a Heart Failure Hospitalization: a Retrospective Cohort Study.
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Riester MR, Goyal P, Jiang L, Erqou S, Rudolph JL, McGeary JE, Rogus-Pulia NM, Madrigal C, Quach L, Wu WC, and Zullo AR
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- Aged, Cohort Studies, Hospitalization, Humans, Medicare, Patient Discharge, Retrospective Studies, Skilled Nursing Facilities, United States epidemiology, Antipsychotic Agents therapeutic use, Heart Failure drug therapy, Heart Failure epidemiology
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Background: Multimorbidity and polypharmacy are common among individuals hospitalized for heart failure (HF). Initiating high-risk medications such as antipsychotics may increase the risk of poor clinical outcomes, especially if these medications are continued unnecessarily into skilled nursing facilities (SNFs) after hospital discharge., Objective: Examine how often older adults hospitalized with HF were initiated on antipsychotics and characteristics associated with antipsychotic continuation into SNFs after hospital discharge., Design: Retrospective cohort., Participants: Veterans without prior outpatient antipsychotic use, who were hospitalized with HF between October 1, 2010, and September 30, 2015, and were subsequently discharged to a SNF., Main Measures: Demographics, clinical conditions, prior healthcare utilization, and antipsychotic use data were ascertained from Veterans Administration records, Minimum Data Set assessments, and Medicare claims. The outcome of interest was continuation of antipsychotics into SNFs after hospital discharge., Key Results: Among 18,008 Veterans, antipsychotics were newly prescribed for 1931 (10.7%) Veterans during the index hospitalization. Among new antipsychotic users, 415 (21.5%) continued antipsychotics in skilled nursing facilities after discharge. Dementia (adjusted OR (aOR) 1.48, 95% CI 1.11-1.98), psychosis (aOR 1.62, 95% CI 1.11-2.38), proportion of inpatient days with antipsychotic use (aOR 1.08, 95% CI 1.07-1.09, per 10% increase), inpatient use of only typical (aOR 0.47, 95% CI 0.30-0.72) or parenteral antipsychotics (aOR 0.39, 95% CI 0.20-0.78), and the day of hospital admission that antipsychotics were started (day 0-4 aOR 0.36, 95% CI 0.23-0.56; day 5-7 aOR 0.54, 95% CI 0.35-0.84 (reference: day > 7 of hospital admission)) were significant predictors of continuing antipsychotics into SNFs after hospital discharge., Conclusions: Antipsychotics are initiated fairly often during HF admissions and are commonly continued into SNFs after discharge. Hospital providers should review antipsychotic indications and doses throughout admission and communicate a clear plan to SNFs if antipsychotics are continued after discharge., (© 2021. Society of General Internal Medicine.)
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- 2022
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28. Two decade trends in cardiovascular disease outcomes and cardiovascular risk factors among US veterans living with HIV.
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Haji M, Lopes VV, Ge A, Halladay C, Soares C, Shah NR, Longenecker CT, Lally M, Bloomfield GS, Shireman TI, Ross D, Sullivan JL, Rudolph JL, Wu WC, and Erqou S
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Coomprhensive data on temporal trends in cardiovascular disease (CVD) risk factors and outcomes in people living with HIV are limited. Using retrospective data on 50,284 US Veterans living with HIV (VLWH) who received care in the VA from 2001 to 2019, we calculated the prevalence and incidence estimates of CVD risk factors and outcomes, as well as the average annual percent changes (AAPC) in the estimates. The mean age of the Veterans increased from 47.8 (9.1) years to 58.0 (12.4) years during the study period. The population remained predominantly (>95%) male and majority Black (∼50%). The prevalence of the CVD outcomes increased progressively over the study period: coronary artery disease (3.9%-18.7%), peripheral artery disease (2.3%, 10.3%), ischemic cerebrovascular disease (1.1%-9.9%), and heart failure (2.4%-10.5%). There was a progressive increase in risk factor burden, except for smoking which declined after 2015. The AAPC in prevalence was statistically significant for the CVD outcomes and risk factors. When adjusted for age, the predicted prevalence of CVD risk factors and outcomes showed comparable (but attenuated) trends. There was generally a comparable (but attenuated) trend in incidence of CVD outcomes, procedures, and risk factors over the study period. The use of statins increased from 10.6% (2001) to 40.8% (2019). Antiretroviral therapy usage increased from 77.7% (2001) to 85.0% (2019). In conclusion, in a retrospective analysis of large-scale VA data we found the burden and incidence of several CVD risk factors and outcomes have increased among VLWH over the past 20 years., Competing Interests: All authors declared none., (© 2022 The Authors.)
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- 2022
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29. Long-term Cardiovascular Manifestations and Complications of COVID-19: Spectrum and Approach to Diagnosis and Management.
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Khetpal V, Berkowitz J, Vijayakumar S, Choudhary G, Mukand JA, Rudolph JL, Wu WC, and Erqou S
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- Arrhythmias, Cardiac diagnosis, Arrhythmias, Cardiac etiology, Arrhythmias, Cardiac therapy, COVID-19 Testing, Chest Pain etiology, Humans, Post-Acute COVID-19 Syndrome, COVID-19 complications, Myocarditis
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Survivors of coronavirus disease 2019 (COVID-19) may experience persistent symptoms, abnormal diagnostic test findings, incident disease in specific organ systems, or progression of existing disease. Post-acute COVID-19 syndrome (PACS) is defined by persistent, recurrent, or new symptoms, findings, or diagnoses beyond four weeks after the initial infection. PACS has been characterized as a multi-organ syndrome, often with cardiopulmonary symptoms that include fatigue, dyspnea, chest pain, and palpitations. Cardiovascular pathologies in PACS include new-onset arrhythmia, myocarditis, unmasked coronary artery disease, and diastolic dysfunction as well as abnormal findings on electrocardiogram, troponin testing, and cardiac magnetic resonance imaging. In this review, we discuss the cardiovascular symptoms, pathophysiology, clinical investigation, and management strategies for cardiopulmonary symptoms of PACS. We offer a treatment algorithm for primary care clinicians encountering patients with cardiopulmonary PACS and discuss ongoing research on this topic.
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- 2022
30. Associations between cumulative social risk, psychosocial risk, and ideal cardiovascular health: Insights from the HeartSCORE study.
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Berkowitz J, Khetpal V, Echouffo-Tcheugui JB, Bambs CE, Aiyer A, Kip KE, Reis SE, and Erqou S
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Background: Limited studies have assessed the effects of psychosocial risk factors on achievement of ideal cardiovascular health (CVH) ., Methods: Using the Heart Strategies Concentrating on Risk Evaluation (HeartSCORE) cohort, we examined the cross-sectional associations of cumulative social risk (CSR) and three psychosocial factors (depression, stress, perceived discrimination) with ideal CVH . CSR was calculated by assigning one point for each of: low family income, low education level, minority race (Black), and single-living status. Ideal CVH was calculated by assigning one point for ideal levels of each factor in American Heart Association's Life's Simple 7. Ideal CVH was dichotomized into fewer versus higher by combining participants achieving <3 versus ≥3 factors. Logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of having fewer ideal CVH factors. Psychosocial factors were assessed as mediators of the association between CSR and ideal CVH ., Results: We included 2000 participants (mean age 59.1 [7.5] years, 34.6% male, 42.7% Black, and 29.1% with low income), among whom 60.6% had <3 ideal CVH factors. The odds of having fewer ideal CVH factors increased significantly with increasing CSR scores from 1 to 2, to ≥3 compared to individuals with CSR score of zero, after adjusting for age and sex (OR [95% CIs]: 1.77 [1.41 - 2.22]; 2.09 [1.62 - 2.69] 2.67 [1.97 - 3.62], respectively). Taking the components of ideal CVH separately, higher CSR was directly associated with odds of being in 'non-ideal' category for six of the seven factors, but was inversely associated with probability of being in 'non-ideal' category for cholesterol. The association was modestly attenuated after adjusting for depression, stress, and perceived discrimination (corresponding OR [95% CI]: 1.69 [1.34 - 2.12], 1.96 [1.51 - 2.55], 2.34 [1.71 - 3.20]). The psychosocial factors appeared to mediate between 10% and 20% of relationship between CSR and ideal CVH ., Conclusions: Increased CSR was associated with lower probability of achieving ideal CVH factors. A modest amount of the effect of CSR on ideal CVH appeared to be mediated by depression, stress and perceived discrimination. Public health strategies aimed at improving ideal cardiovascular health may benefit from including interventions targeting social and psychosocial risk factors., Competing Interests: All authors declared no conflict of interest., (Published by Elsevier B.V.)
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- 2022
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31. Severe Hypoglycemia and Incidence of QT Interval Prolongation Among Adults With Type 2 Diabetes.
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Kaze AD, Yuyun MF, Erqou S, Fonarow GC, and Echouffo-Tcheugui JB
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- Adult, Electrocardiography adverse effects, Female, Humans, Incidence, Male, Middle Aged, Prospective Studies, Risk Factors, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Hypoglycemia complications, Hypoglycemia epidemiology, Long QT Syndrome epidemiology, Long QT Syndrome etiology
- Abstract
Context: There is a paucity of large-scale epidemiological studies on the link between severe hypoglycemia (SH) and corrected QT (QTc) interval prolongation in type 2 diabetes (T2DM)., Objective: To evaluate the association of SH with QTc prolongation in adults with T2DM., Methods: Prospective cohort analysis of participants enrolled in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study without QTc prolongation at baseline. SH was assessed over a 24-month period. Incident QTc prolongation was ascertained using follow-up electrocardiograms. Modified Poisson regression was used to generate the risk ratio (RR) and 95% CI for QTc prolongation., Results: Among 8277 participants (mean age 62.6 years [SD 6.5], 38.7% women, 62.8% White), 324 had ≥1 SH episode (3.9%). Over a median of 5 years, 517 individuals developed QTc prolongation (6.3%). Participants with SH had a 66% higher risk of QTc prolongation (RR 1.66, 95% CI 1.16-2.38). The incidence of QTc prolongation was 10.3% (27/261) and 14.3% (9/63) for participants with 1 and ≥2 SH, respectively. Compared with no SH, RRs for patients with 1 and ≥2 SH episodes were 1.57 (95% CI 1.04-2.39) and 2.01 (95% CI 1.07-3.78), respectively. Age modified the association of SH with QTc prolongation (PInteraction = .008). The association remained significant among younger participants (<61.9 years [median age]: RR 2.63, 95% CI 1.49-4.64), but was nonsignificant among older participants (≥61.9 years: RR 1.37, 95% CI 0.87-2.17)., Conclusion: In a large population with T2DM, SH was associated with an increased risk of QTc prolongation independently of other risk factors such as cardiac autonomic neuropathy. The association was strongest among younger participants., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
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- 2022
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32. Outcomes in heart failure patients discharged to skilled nursing facilities with delirium.
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Lafo J, Singh M, Jiang L, Correia S, Madrigal C, Clements R, Wu WC, Erqou S, and Rudolph JL
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- Female, Humans, Male, Medicare, Patient Discharge, Retrospective Studies, Skilled Nursing Facilities, United States epidemiology, Delirium epidemiology, Dementia epidemiology, Heart Failure epidemiology, Heart Failure therapy
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Aim: Heart failure (HF) outcomes are disproportionately worse in patients discharged to skilled nursing facilities (SNF) as opposed to home. We hypothesized that dementia and delirium were key factors influencing these differences. Our aim was to explore the associations of dementia and delirium with risk of hospital readmission and mortality in HF patients discharged to SNF., Methods and Results: The study population included Veterans hospitalized for a primary diagnosis of HF and discharged to SNFs between 2010 and 2015. Pre-existing dementia was identified based on International Classification of Diseases-9 codes. Delirium was determined using the Minimum Data Set 3.0 Confusion Assessment Method algorithm. Proportional hazard regression analyses were used to model outcomes and were adjusted for covariates of interest. Patients (n = 21 655) were older (77.0 ± 10.5 years) and predominantly male (96.9%). Four groups were created according to presence (+) or absence (-) of dementia and delirium. Relative to the dementia-/delirium- group, the dementia-/delirium+ group was associated with increased 30 day mortality [adjusted hazard ratio (HR) = 2.2, 95% confidence interval (CI) = 1.7, 3.0] and 365 day mortality (adjusted HR = 1.5, 95% CI = 1.3, 1.7). Readmission was highest in the dementia-/delirium+ group after 30 days (HR = 1.2, 95% CI = 1.0, 1.5). In the group with dementia (delirium-/dementia+), 30 day mortality (12.8%; HR = 0.7, 95% CI = 0.7, 0.8) and readmissions (5.3%; HR = 1.0, 95% CI = 0.8, 1.1) were not different relative to the reference group., Conclusions: Delirium, independent of pre-existing dementia, confers increased risk of hospital readmission and mortality in HF patients discharged to SNFs. Managing HF after hospitalization is a complex cognitive task and an increased focus on mental status in the acute care setting prior to discharge is needed to improve HF management and transitional care, mitigate adverse outcomes, and reduce healthcare costs., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)
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- 2022
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33. Insulin resistance and incident heart failure: a meta-analysis.
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Erqou S, Adler AI, Challa AA, Fonarow GC, and Echouffo-Tcheugui JB
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- Humans, Incidence, Insulin, Risk Factors, Heart Failure epidemiology, Insulin Resistance
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- 2022
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34. Cardiac autonomic neuropathy and risk of incident heart failure among adults with type 2 diabetes.
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Kaze AD, Yuyun MF, Erqou S, Fonarow GC, and Echouffo-Tcheugui JB
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- Adult, Autonomic Nervous System, Female, Heart, Heart Rate physiology, Humans, Male, Middle Aged, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Heart Failure
- Abstract
Aims: Community-based data on the association between cardiac autonomic neuropathy (CAN) and incident heart failure (HF) in type 2 diabetes are limited. We evaluated the association of CAN with incident HF in adults with type 2 diabetes., Methods and Results: This analysis included participants from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study without HF at baseline. CAN was assessed by electrocardiogram-based measures of heart rate variability (HRV) and QT interval index (QTI). HRV was measured using standard deviation of all normal-to-normal intervals (SDNN) and root mean square of successive differences between normal-to-normal intervals (rMSSD). CAN was defined using composite measures of the lowest quartile of SDNN and highest quartiles of QTI and heart rate. Multivariable Cox regression models were used to generate adjusted hazard ratios (aHR) for HF in relation to various CAN measures. A total of 7160 participants (mean age 62.3 [standard deviation 6.4] years, 40.8% women, 61.9% white) were included. Over a median follow-up of 4.9 years (interquartile range 4.0-5.7), 222 participants developed incident HF. After multivariable adjustment for relevant confounders, lower HRV as assessed by SDNN was associated with a higher risk of HF (aHR for the lowest vs highest quartile of SDNN: 1.70, 95% confidence interval [CI] 1.14-2.54). Participants with CAN (defined as lowest quartile of SDNN and highest quartiles of QTI and heart rate) had a 2.7-fold greater risk of HF (aHR 2.65, 95% CI 1.57-4.48)., Conclusions: In a large cohort of adults with type 2 diabetes, CAN was independently associated with higher risk of incident HF., (© 2022 European Society of Cardiology.)
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- 2022
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35. Mortality in patients with heart failure and suicidal ideation discharged to skilled nursing facilities.
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Bozzay ML, Jiang L, Zullo AR, Riester MR, Lafo JA, Kunicki ZJ, Rudolph JL, Madrigal C, Clements R, Erqou S, Wu WC, Correia S, and Primack JM
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- 2022
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36. Body Weight Variability and Risk of Cardiovascular Outcomes and Death in the Context of Weight Loss Intervention Among Patients With Type 2 Diabetes.
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Kaze AD, Santhanam P, Erqou S, Ahima RS, Bertoni AG, and Echouffo-Tcheugui JB
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- Adiposity physiology, Aged, Cardiovascular Diseases complications, Cardiovascular Diseases epidemiology, Cardiovascular Diseases mortality, Female, Humans, Life Style, Male, Middle Aged, Prospective Studies, United States, Waist Circumference physiology, Body Weight physiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology
- Abstract
Importance: Body weight fluctuation is associated with greater risks of adverse health outcomes. Whether intensive weight loss interventions affect the association of variability in adiposity measures with adverse health outcomes in individuals with type 2 diabetes has not been studied previously., Objective: To evaluate the associations of long-term variability in adiposity indices with cardiovascular disease (CVD) outcomes and whether these associations are affected by an intensive lifestyle intervention among adults with type 2 diabetes., Design, Setting, and Participants: This prospective cohort study included participants in the Action for Health in Diabetes (Look AHEAD) trial without CVD at baseline (August 2001 to April 2004). The Look AHEAD study included 16 centers in the United States. Data analysis was performed from December 2020 to June 2021., Exposures: Variability of body mass index (BMI) and waist circumference (WC) across 4 annual visits, assessed using the coefficient of variation (CV), variability independent of the mean (VIM), and standard deviation (SD)., Main Outcomes and Measures: Main outcomes were (1) all-cause mortality, (2) cardiovascular deaths (deaths from myocardial infarction [MI] or stroke), and (3) CVD events (MI, stroke, and/or death from cardiovascular causes)., Results: Among 3604 study participants (mean [SD] age, 58.4 [6.6] years; 2240 [62.3%] women; 1364 [37.7%] Black participants; 2404 [66%] White participants), there were 216 CVD events, 33 CVD deaths, and 166 deaths over a median of 6.7 years. In the control group, the hazard ratios (HRs) for the highest quartile (quartile 4) compared with the lowest quartile (quartile 1) of CV of BMI were 4.06 (95% CI, 2.17-7.57), 15.28 (95% CI, 2.89-80.90), and 2.16 (95% CI, 1.21-3.87) for all-cause mortality, CVD mortality, and cardiovascular events, respectively. In the intervention group, the corresponding HRs were 0.99 (95% CI, 0.45-2.16), 1.14 (95% CI, 0.12-10.53), and 0.77 (95% CI, 0.40-1.49) for quartile 4 vs quartile 1. Regarding WC, in the control group, HRs for quartile 4 vs quartile 1 were 1.84 (95% CI, 1.01-3.35), 6.46 (95% CI, 1.16-36.01), and 1.28 (95% CI, 0.72-2.29). In the intervention group, HRs were 1.23 (95% CI, 0.61-2.46), 0.55 (95% CI, 0.15-2.11), and 0.70 (95% CI, 0.39-1.25) for quartile 4 vs quartile 1., Conclusions and Relevance: In this cohort study of individuals with type 2 diabetes, higher variability of adiposity indices was associated with significantly increased risk of CVD outcomes and death in the control group but not in the intensive lifestyle intervention group.
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- 2022
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37. Variability of adiposity indices and incident heart failure among adults with type 2 diabetes.
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Kaze AD, Erqou S, Santhanam P, Bertoni AG, Ahima RS, Fonarow GC, and Echouffo-Tcheugui JB
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- Aged, Body Mass Index, Diabetes Mellitus, Type 2 diagnosis, Female, Heart Disease Risk Factors, Heart Failure diagnosis, Humans, Incidence, Male, Middle Aged, Obesity diagnosis, Obesity physiopathology, Predictive Value of Tests, Prognosis, Prospective Studies, Randomized Controlled Trials as Topic, Risk Assessment, Time Factors, United States epidemiology, Waist Circumference, Adiposity, Diabetes Mellitus, Type 2 epidemiology, Heart Failure epidemiology, Obesity epidemiology
- Abstract
Background: It remains unclear how the variability of adiposity indices relates to incident HF. This study evaluated the associations of the variability in several adiposity indices with incident heart failure (HF) in individuals with type 2 diabetes (T2DM)., Methods: We included 4073 participants from the Look AHEAD (Action for Health in Diabetes) study. We assessed variability of body mass index (BMI), waist circumference (WC), and body weight across four annual visits using three variability metrics, the variability independent of the mean (VIM), coefficient of variation (CV), and intraindividual standard deviation (SD). Multivariable Cox regression models were used to generate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for incident HF., Results: Over a median of 6.7 years, 120 participants developed incident HF. After adjusting for relevant confounders including baseline adiposity levels, the aHR for the highest (Q4) versus lowest quartile (Q1) of VIM of BMI was 3.61 (95% CI 1.91-6.80). The corresponding aHRs for CV and SD of BMI were 2.48 (95% CI 1.36-4.53) and 2.88 (1.52-5.46), respectively. Regarding WC variability, the equivalent aHRs were 1.90 (95% CI 1.11-3.26), 1.79 (95% CI 1.07-3.01), and 1.73 (1.01-2.95) for Q4 versus Q1 of VIM, CV and SD of WC, respectively., Conclusions: In a large sample of adults with T2DM, a greater variability of adiposity indices was associated with higher risks of incident HF, independently of traditional risk factors and baseline adiposity levels. Registration-URL: https://clinicaltrials.gov/ct2/show/NCT00000620 ., (© 2022. The Author(s).)
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- 2022
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38. Anticipating and Addressing Challenges During Implementation of Clinical Decision Support Systems.
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Shah NR, Khetpal V, and Erqou S
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- Electronic Health Records, Humans, Decision Support Systems, Clinical
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- 2022
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39. Correlates of cardiorespiratory fitness among overweight or obese individuals with type 2 diabetes.
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Kaze AD, Agoons DD, Santhanam P, Erqou S, Ahima RS, and Echouffo-Tcheugui JB
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- Adult, Female, Humans, Longitudinal Studies, Male, Obesity complications, Obesity epidemiology, Overweight complications, Overweight epidemiology, Risk Factors, Cardiorespiratory Fitness physiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 metabolism
- Abstract
Introduction: Mechanistic studies suggest that type 2 diabetes is independently associated with low cardiorespiratory fitness (CRF). Little is known about the CRF profile in type 2 diabetes; we assessed the correlates of low CRF among overweight/obese adults with type 2 diabetes., Research Design and Methods: A total of 4215 participants with type 2 diabetes and without cardiovascular disease underwent maximal exercise testing in the Look AHEAD (Action for Health in Diabetes) study. Low CRF was defined based on the Aerobics Center Longitudinal Study reference standards. Calorie intake and physical activity were assessed using questionnaires. Body fat composition was assessed using dual-energy X-ray absorptiometry., Results: Waist circumference, systolic blood pressure, glycemic measures, whole body fat, caloric intake, and fat-free mass were inversely associated with fitness across sex (all p<0.001). Comparing with moderate or high CRF groups, the low CRF group was associated with higher adjusted odds of obesity (OR 3.19 (95% CI 1.95 to 5.20) in men, 3.86 (95% CI 2.55 to 5.84)) in women), abdominal obesity (OR 3.99 (95% CI 2.00 to 7.96) in men, 2.28 (95% CI 1.08 to 4.79) in women), hypertension (OR 1.74 (95% CI 1.09 to 2.77) in men, 1.44 (95% CI 1.02 to 2.05) in women), metabolic syndrome (OR 5.52 (95% CI 2.51 to 12.14) in men, 2.25 (95% CI 1.35 to 3.76) in women), use of beta-blocker (1.22 (95% CI 0.86 to 1.73) in men, 1.33 (95% CI 1.03 to 1.73) in women), and ACE inhibitor/angiotensin-receptor blocker (1.86 (95% CI 1.39 to 2.50) in men, 1.07 (95% CI 0.86 to 1.32) in women). Women with low CRF had higher odds of current smoking (2.02 (95% CI 1.25 to 3.28))., Conclusions: Low CRF was associated with increased odds of cardiometabolic correlates in a large cohort of adults with type 2 diabetes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2022
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40. Coronary Artery Calcification and Plaque Characteristics in People Living With HIV: A Systematic Review and Meta-Analysis.
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Soares C, Samara A, Yuyun MF, Echouffo-Tcheugui JB, Masri A, Samara A, Morrison AR, Lin N, Wu WC, and Erqou S
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- Calcium, Female, Humans, Male, Middle Aged, Coronary Artery Disease diagnostic imaging, Coronary Artery Disease epidemiology, HIV Infections complications, HIV Infections epidemiology, Plaque, Atherosclerotic epidemiology
- Abstract
Background Studies have reported that people living with HIV have higher burden of subclinical cardiovascular disease, but the data are not adequately synthesized. We performed meta-analyses of studies of coronary artery calcium and coronary plaque in people living with HIV. Methods and Results We performed systematic search in electronic databases, and data were abstracted in standardized forms. Study-specific estimates were pooled using meta-analysis. 43 reports representing 27 unique studies and involving 10 867 participants (6699 HIV positive, 4168 HIV negative, mean age 52 years, 86% men, 32% Black) were included. The HIV-positive participants were younger (mean age 49 versus 57 years) and had lower Framingham Risk Score (mean score 6 versus 18) compared with the HIV-negative participants. The pooled estimate of percentage with coronary artery calcium >0 was 45% (95% CI, 43%-47%) for HIV-positive participants, and 52% (50%-53%) for HIV-negative participants. This difference was no longer significant after adjusting for difference in Framingham Risk Score between the 2 groups. The odds ratio of coronary artery calcium progression for HIV-positive versus -negative participants was 1.64 (95% CI, 0.91-2.37). The pooled estimate for prevalence of noncalcified plaque was 49% (95% CI, 47%-52%) versus 20% (95% CI, 17%-23%) for HIV-positive versus HIV-negative participants, respectively. Odds ratio for noncalcified plaque for HIV-positive versus -negative participants was 1.23 (95% CI, 1.08-1.38). There was significant heterogeneity that was only partially explained by available study-level characteristics. Conclusions People living with HIV have higher prevalence of noncalcified coronary plaques and similar prevalence of coronary artery calcium, compared with HIV-negative individuals. Future studies on coronary artery calcium and plaque progression can further elucidate subclinical atherosclerosis in people living with HIV.
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- 2021
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41. Long-term variability of blood pressure and incidence of heart failure among individuals with Type 2 diabetes.
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Kaze AD, Santhanam P, Erqou S, Bertoni AG, Ahima RS, and Echouffo-Tcheugui JB
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- Adult, Blood Pressure, Female, Humans, Incidence, Middle Aged, Risk Factors, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Heart Failure epidemiology, Heart Failure etiology
- Abstract
Aims: Data on the association of long-term variability of blood pressure (BP) with incident heart failure (HF) in individuals with Type 2 diabetes are scarce. We evaluated this association in a large community-based sample of adults with Type 2 diabetes., Methods and Results: A total of 4200 participants with Type 2 diabetes who had available BP measurements at four visits (baseline and 12, 24, and 36 months) in the Look AHEAD (Action for Health in Diabetes) study were included. Variability of systolic BP (SBP) and diastolic BP (DBP) across the four visits was assessed using four metrics. Participants free of HF during the first 36 months were followed for HF events. Cox regression was used to generate hazard ratios (HRs) and 95% confidence intervals (CIs) for HF. Of the 4200 participants, the average age was 59 years [standard deviation (SD): 6.8]; 58.5% were women. Over a median follow-up of 6.7 years, 129 developed HF events. After adjusting for relevant confounders, the HR of incident HF for the highest vs. lowest quartile of SD of SBP was 1.77 (95% CI 1.01-3.09); the HR for the highest (vs. lowest) quartile of variability independent of the mean of SBP was 1.29 (95% CI 0.78-2.14). The adjusted HR for participants in the highest (compared with the lowest) quartile of SD of DBP was 1.61 (95% CI 1.01-2.59), and the adjusted HR for variability independent of the mean of DBP was 1.65 (95% CI 1.03-2.65)., Conclusions: A greater variability in SBP and DBP is independently associated with greater risk of incident HF in individuals with Type 2 diabetes., (© 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)
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- 2021
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42. Microvascular Disease and Incident Heart Failure Among Individuals With Type 2 Diabetes Mellitus.
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Kaze AD, Santhanam P, Erqou S, Ahima RS, Bertoni A, and Echouffo-Tcheugui JB
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- Aged, Databases, Factual, Diabetes Mellitus, Type 2 diagnosis, Diabetic Angiopathies diagnosis, Diabetic Nephropathies epidemiology, Diabetic Neuropathies epidemiology, Diabetic Retinopathy epidemiology, Female, Heart Failure diagnosis, Humans, Incidence, Male, Middle Aged, Prognosis, Prospective Studies, Randomized Controlled Trials as Topic, Risk Assessment, Risk Factors, Time Factors, United States epidemiology, Diabetes Mellitus, Type 2 epidemiology, Diabetic Angiopathies epidemiology, Heart Failure epidemiology
- Abstract
Background Microvascular disease (MVD) is a potential contributor to the pathogenesis of diabetes mellitus-related cardiac dysfunction. However, there is a paucity of data on the link between MVD and incident heart failure (HF) in type 2 diabetes mellitus. We examined the association of MVD with incident HF in adults with type 2 diabetes mellitus. Methods and Results A total of 4095 participants with type 2 diabetes mellitus and free of HF were assessed for diabetes mellitus-related MVD including nephropathy, retinopathy, or neuropathy at baseline in the Look AHEAD (Action for Health in Diabetes) study. Incident HF events were prospectively assessed and adjudicated using hospital and death records. Cox models were used to generate hazard ratios and 95% CIs for HF. Of 4095 participants, 34.8% (n=1424) had MVD, defined as the presence of ≥1 of nephropathy, retinopathy, or neuropathy at baseline. Over a median of 9.7 years, there were 117 HF events. After adjusting for relevant confounders, participants with MVD had a 2.5-fold higher risk of incident HF than those without MVD (hazard ratio, 2.54; 95% CI, 1.73-3.75). This association remained significant after additional adjustment for interval development of coronary artery disease (hazard ratio, 2.42; 95% CI, 1.64-3.57). The hazard ratios for HF by type of MVD were 2.22 (95% CI, 1.51-3.27), 1.30 (95% CI, 0.72-2.36), and 1.33 (95% CI, 0.86-2.07) for nephropathy, retinopathy, and neuropathy, respectively. CONCLUSIONS MVD is associated with an excess HF risk in individuals with type 2 diabetes mellitus after adjusting for other known risk factors. Our findings underscore the contribution of MVD to the development of diabetes mellitus-related HF. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00017953.
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- 2021
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43. Age at Diagnosis of Heart Failure in United States Veterans With and Without HIV Infection.
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Erqou S, Jiang L, Choudhary G, Lally M, Freiberg M, Lin NH, Shireman TI, Rudolph JL, and Wu WC
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- Age Factors, Aged, Aged, 80 and over, Female, HIV Infections complications, Heart Failure complications, Heart Failure epidemiology, Humans, Incidence, Male, Middle Aged, Retrospective Studies, United States epidemiology, Echocardiography methods, HIV, HIV Infections epidemiology, Heart Failure diagnosis, Veterans
- Abstract
Background Although HIV is associated with increased risk of heart failure (HF), it is not known if people living with HIV develop HF at a younger age compared with individuals without HIV. Crude comparisons of age at diagnosis of HF between individuals with and without HIV does not account for differences in underlying age structures between the populations. Methods and Results We used Veterans Health Administration data to compare the age at HF diagnosis between veterans with and without HIV, with adjustment for difference in population age structure. Statistical weights, calculated for each 1-year strata of veterans with HIV in each calendar year from 2000 to 2018, were applied to the veterans without HIV to standardize the age structure. We identified 5093 veterans with HIV (98% men, 34% White) with first HF episode recorded after HIV diagnosis (median age at incidence of HF, 58 years), and 1 425 987 veterans without HIV (98% men, 78% White) with HF (corresponding age, 72 years), with an absolute difference of 14 years. After accounting for difference in age structure, the adjusted median age at HF diagnosis for veterans without HIV was 63 years, 5 years difference with veterans with HIV ( P <0.001). The age differences were consistent across important subgroups such as preserved versus reduced ejection fraction and inpatient versus outpatient index HF. Conclusions Veterans with HIV are diagnosed with HF at a significantly younger age compared with veterans without HIV. These findings may have implications for HF prevention in individuals with HIV. Future studies are needed to make the findings more generalizable.
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- 2021
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44. Outcomes of coronavirus disease-2019 among veterans with pre-existing diagnosis of heart failure.
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Rumery K, Seo A, Jiang L, Choudhary G, Shah NR, Rudolph JL, Wu WC, and Erqou S
- Subjects
- COVID-19 Testing, Female, Humans, Male, Retrospective Studies, SARS-CoV-2, Stroke Volume, Ventricular Function, Left, COVID-19, Heart Failure diagnosis, Heart Failure epidemiology, Veterans
- Abstract
Aims: Pre-existing cardiovascular disease in general and related risk factors have been associated with poor coronavirus disease-2019 (COVID-19) outcomes. However, data on outcomes of COVID-19 among people with pre-existing diagnosis of heart failure (HF) have not been studied in sufficient detail. We aimed to perform detailed characterization of the association of pre-existing HF with COVID-19 outcomes., Methods and Results: A retrospective cohort study based on Veterans Health Administration (VHA) data comparing 30 day mortality and hospital admission rates after COVID-19 diagnosis among Veterans with and without pre-existing diagnosis of HF. Cox-regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) with adjustment for covariates. Among 31 051 veterans (97% male) with COVID-19, 6148 had pre-existing diagnosis of HF. The mean (SD) age of patients with HF was 70 (13) whereas the mean (SD) age of patients without HF was 57 (17). Within the HF group with available data on left ventricular ejection fraction (EF), 1844 patients (63.4%) had an EF of >45%, and 1063 patients (36.6%) had an EF of ≤45%. Patients in the HF cohort had higher 30 day mortality (5.4% vs. 1.5%) and admission (18.5% vs. 8.4%) rates after diagnosis of COVID-19. After adjustment for age, sex, and race, HRs (95% CIs) for 30 day mortality and for 30 day hospital admissions were 1.87 (1.61-2.17) and 1.79 (1.66-1.93), respectively. After additional adjustment for medical comorbidities, HRs for 30 day mortality and for 30 day hospital admissions were 1.37 (1.15-1.64) and 1.27 (1.16-1.38), respectively. The findings were similar among HF patients with preserved vs. reduced EF, among those taking vs. not taking angiotensin-converting enzyme inhibitors, angiotensin receptor blockers or angiotensin receptor neprilysin inhibitors, and among those taking vs. not taking anticoagulants., Conclusions: Patients with COVID-19 and pre-existing diagnosis of HF had a higher risk of 30 day mortality and hospital admissions compared to those without history of HF. The findings were similar by EF categories and by angiotensin-converting enzyme inhibitors/angiotensin receptor blocker/angiotensin receptor neprilysin inhibitors or anticoagulant use., (© 2021 European Society of Cardiology. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)
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- 2021
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45. The Intersection of Physical and Social Frailty in Older Adults.
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Quach LT, Primack J, Bozzay M, Madrigal C, Erqou S, and Rudolph JL
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- Aged, Frail Elderly, Geriatric Assessment, Humans, Income, Patient Care, Disabled Persons, Frailty
- Abstract
Frailty, a vulnerability to stressors, has been increasingly woven into the clinical understanding of older people who are unable to respond to the impact of diseases, disability, and age-related decline. While the literature has focused on physical frailty, social frailty has been conceptualized within the domains of social needs (social and emotional support, loneliness), resources (income, food, housing, medical care, etc), social fulfillment (engagement in work and activities), and self-management (cognitive function, mental health, advance planning). This review outlines the assessment of the four domains of social frailty within the structure of clinical visits, particularly annual wellness and advance care planning. Increasing connectivity with the community, health system, and government support is the primary recommended intervention. On a policy level, expanding opportunities to connect socially frail people with resources may help mitigate the vulnerability of physical frailty.
- Published
- 2021
46. Delirium and Functional Recovery in Patients Discharged to Skilled Nursing Facilities After Hospitalization for Heart Failure.
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Madrigal C, Kim J, Jiang L, Lafo J, Bozzay M, Primack J, Correia S, Erqou S, Wu WC, and Rudolph JL
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- Aged, Aged, 80 and over, Dementia, Female, Heart Failure psychology, Heart Failure therapy, Humans, Male, Patient Discharge, Patient Readmission, Retrospective Studies, United States, Activities of Daily Living, Delirium, Heart Failure rehabilitation, Hospitalization, Recovery of Function, Skilled Nursing Facilities
- Abstract
Importance: A substantial number of patients discharged to skilled nursing facilities (SNFs) after heart failure (HF) hospitalization experience regression in function or do not improve. Delirium is one of few modifiable risk factors in this patient population. Therefore, understanding the role of delirium in functional recovery may be useful for improving outcomes., Objective: To assess the association of delirium with 30-day functional improvement in patients discharged to SNFs after HF hospitalization., Design, Setting, and Participants: This retrospective cohort study included patients hospitalized for HF in 129 US Department of Veterans Affairs hospitals who were discharged to SNFs from October 1, 2010, to September 30, 2015. Data were analyzed from June 14 to December 18, 2020., Exposures: Delirium, as determined by the Minimum Data Set (MDS) 3.0 Confusion Assessment Method, with dementia as a covariate, determined via International Classification of Diseases, Ninth Revision (ICD-9) coding., Main Outcomes and Measures: The difference between admission and 30-day MDS 3.0 Activities of Daily Living (ADL) scores., Results: A total of 20 495 patients (mean [SD] age, 78 [10.3] years; 78.9% White; and 97% male) were included in the analysis. Of the total sample, 882 patients (4.3%) had delirium on an SNF admission. The mean (SD) baseline ADL score on admission to SNF was significantly worse among patients with delirium than without (18.3 [4.7] vs 16.1 [5.2]; P < .001; d = 0.44.). On the 30-day repeated assessment, mean (SD) function (ADL scores) improved for both patients with delirium (0.6 [2.9]) and without delirium (1.8 [3.6]) (P < .001; d = -0.38). In the multivariate adjusted model, delirium was associated with statistically significant lower ADL improvement (difference in ADL score, -1.07; 95% CI, -1.31 to -0.83; P < .001)., Conclusions and Relevance: In this retrospective cohort study, patients with HF discharged to SNFs with delirium were less likely to show improvement in function compared with patients without delirium. Findings suggest a potential need to reexamine how and when health care professionals assess delirium in HF patients throughout their hospitalization and SNF course. Identifying and treating delirium for HF patients earlier in their care trajectory may play an important role in improving care and long-term functional outcomes in this population. Future research is warranted to further investigate the association between delirium and functional recovery for HF and other patient populations.
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- 2021
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47. Association of poor housing conditions with COVID-19 incidence and mortality across US counties.
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Ahmad K, Erqou S, Shah N, Nazir U, Morrison AR, Choudhary G, and Wu WC
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- Adult, Aged, Betacoronavirus isolation & purification, COVID-19, Coronavirus Infections epidemiology, Coronavirus Infections mortality, Coronavirus Infections virology, Cross-Sectional Studies, Family Characteristics, Female, Housing, Humans, Incidence, Male, Middle Aged, Pandemics, Pneumonia, Viral epidemiology, Pneumonia, Viral mortality, Pneumonia, Viral virology, Risk, SARS-CoV-2, United States epidemiology, Young Adult, Coronavirus Infections pathology, Pneumonia, Viral pathology, Social Class
- Abstract
Objective: Poor housing conditions have been linked with worse health outcomes and infectious disease spread. Since the relationship of poor housing conditions with incidence and mortality of COVID-19 is unknown, we investigated the association between poor housing condition and COVID-19 incidence and mortality in US counties., Methods: We conducted cross-sectional analysis of county-level data from the US Centers for Disease Control, US Census Bureau and John Hopkins Coronavirus Resource Center for 3135 US counties. The exposure of interest was percentage of households with poor housing conditions (one or greater of: overcrowding, high housing cost, incomplete kitchen facilities, or incomplete plumbing facilities). Outcomes were incidence rate ratios (IRR) and mortality rate ratios (MRR) of COVID-19 across US counties through 4/21/2020. Multilevel generalized linear modeling (with total population of each county as a denominator) was utilized to estimate relative risk of incidence and mortality related to poor housing conditions with adjustment for population density and county characteristics including demographics, income, education, prevalence of medical comorbidities, access to healthcare insurance and emergency rooms, and state-level COVID-19 test density. We report incidence rate ratios (IRRs) and mortality ratios (MRRs) for a 5% increase in prevalence in households with poor housing conditions., Results: Across 3135 US counties, the mean percentage of households with poor housing conditions was 14.2% (range 2.7% to 60.2%). On April 21st, the mean (SD) number of cases and deaths of COVID-19 were 255.68 (2877.03) cases and 13.90 (272.22) deaths per county, respectively. In the adjusted models standardized by county population, with each 5% increase in percent households with poor housing conditions, there was a 50% higher risk of COVID-19 incidence (IRR 1.50, 95% CI: 1.38-1.62) and a 42% higher risk of COVID-19 mortality (MRR 1.42, 95% CI: 1.25-1.61). Results remained similar using earlier timepoints (3/31/2020 and 4/10/2020)., Conclusions and Relevance: Counties with a higher percentage of households with poor housing had higher incidence of, and mortality associated with, COVID-19. These findings suggest targeted health policies to support individuals living in poor housing conditions should be considered in further efforts to mitigate adverse outcomes associated with COVID-19., Competing Interests: The authors have declared that no competing interests exist.
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- 2020
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48. Long-term variability of glycemic markers and risk of all-cause mortality in type 2 diabetes: the Look AHEAD study.
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Kaze AD, Santhanam P, Erqou S, Ahima RS, and Echouffo-Tcheugui JB
- Subjects
- Follow-Up Studies, Humans, Prospective Studies, Risk Factors, Blood Glucose, Diabetes Mellitus, Type 2
- Abstract
Introduction: Glycemic variability may predict poor outcomes in type 2 diabetes. We evaluated the associations of long-term variability in glycosylated hemoglobin (HbA
1C ) and fasting plasma glucose (FPG) with cardiovascular disease (CVD) and death among individuals with type 2 diabetes., Research Design and Methods: We conducted a secondary, prospective cohort analysis of the Look AHEAD (Action for Health in Diabetes) data, including 3560 participants who attended four visits (baseline, 12 months, 24 months, and 36 months) at the outset. Variability of HbA1C and FPG was assessed using four indices across measurements from four study visits. Participants without CVD during the first 36 months were followed for incident outcomes including a CVD composite (myocardial infarction, stroke, hospitalization for angina, and CVD-related deaths), heart failure (HF), and deaths., Results: Over a median follow-up of 6.8 years, there were 164 deaths from any cause, 33 CVD-related deaths, 91 HF events, and 340 participants experienced the CVD composite. Adjusted HRs comparing the highest to lowest quartile of SD of HbA1C were 2.10 (95% CI 1.26 to 3.51), 3.43 (95% CI 0.95 to 12.38), 1.01 (95% CI 0.69 to 1.46), and 1.71 (95% CI 0.69 to 4.24) for all-cause mortality, CVD mortality, CVD composite and HF, respectively. The equivalent HRs for highest versus lowest quartile of SD of FPG were 1.66 (95% CI 0.96 to 2.85), 2.20 (95% CI 0.67 to 7.25), 0.94 (95% CI 0.65 to 1.35), and 2.05 (95% CI 0.80 to 5.31), respectively., Conclusions: A greater variability in HbA1C was associated with elevated risk of mortality. Our findings underscore the need to achieve normal and consistent glycemic control to improve clinical outcomes among individuals with type 2 diabetes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)- Published
- 2020
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49. Secondary Prevention of Myocardial Infarction in People Living With HIV Infection.
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Erqou S and Rodriguez-Barradas MC
- Subjects
- Heart Disease Risk Factors, Humans, Risk Factors, Secondary Prevention, Acute Coronary Syndrome, Cardiovascular Diseases, HIV Infections complications, HIV Infections epidemiology, Myocardial Infarction epidemiology, Myocardial Infarction prevention & control
- Published
- 2020
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50. Heart Failure Outcomes and Associated Factors Among Veterans With Human Immunodeficiency Virus Infection.
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Erqou S, Jiang L, Choudhary G, Lally M, Bloomfield GS, Zullo AR, Shireman TI, Freiberg M, Justice AC, Rudolph J, Lin N, and Wu WC
- Subjects
- Aged, Comorbidity, Female, Follow-Up Studies, Humans, Incidence, Male, Middle Aged, Retrospective Studies, Risk Factors, United States epidemiology, HIV, HIV Infections epidemiology, Heart Failure epidemiology, Hospitalization trends, Risk Assessment methods, Veterans statistics & numerical data
- Abstract
Objectives: This study sought to investigate outcomes of heart failure (HF) in veterans living with human immunodeficiency virus (HIV)., Background: Data on outcomes of HF among people living with human immunodeficiency virus (PLHIV) are limited., Methods: We performed a retrospective cohort study of Veterans Health Affairs data to investigate outcomes of HF in PLHIV. We identified 5,747 HIV+ veterans with diagnosis of HF from 2000 to 2018 and 33,497 HIV- frequency-matched controls were included. Clinical outcomes included all-cause mortality, HF hospital admission, and all-cause hospital admission., Results: Compared with HIV- veterans with HF, HIV+ veterans with HF were more likely to be black (56% vs. 14%), be smokers (52% vs. 29%), use alcohol (32% vs. 13%) or drugs (37% vs. 8%), and have a higher comorbidity burden (Elixhauser comorbidity index 5.1 vs. 2.6). The mean ejection fraction (EF) (45 ± 16%) was comparable between HIV+ and HIV- veterans. HIV+ veterans with HF had a higher age-, sex-, and race-adjusted 1-year all-cause mortality (30.7% vs. 20.3%), HF hospital admission (21.2% vs. 18.0%), and all-cause admission (50.2% vs. 38.5%) rates. Among veterans with HIV and HF, those with low CD4 count (<200 cells/ml) and high HIV viral load (>75 copies/μl) had worse outcomes. The associations remained statistically significant after adjusting for extensive list of covariates. The incidence of all-cause mortality and HF admissions was higher among HIV+ veterans with ejection fraction <45% CONCLUSIONS: HIV+ veterans with HF had higher risk of hospitalization and mortality compared with their HIV- counterparts, with worse outcomes reported for individuals with lower CD4 count, higher viral load, and lower ejection fraction., (Published by Elsevier Inc.)
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- 2020
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