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7. Major lipids, apolipoproteins, and risk of vascular disease

Author

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.

Subjects
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.

Published
2016
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10. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis

Author

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.

Subjects
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.

Published
2010
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11. Emerging Risk Factors Collaboration. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

hompson S, Kaptoge S, White I, Wood A, Thompson SG, White IR, Wood AM, Perry PL, Danesh J, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Willeit J, Kiechl S, Santer P, Mayr A, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Tracy RP, Tybjærg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, 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, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Lappas G, 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 JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin 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, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Umans J, Onat A, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot M, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marín Ibañez A, Feskens EJ, Kromhout D, Di Angelantonio E, Erqou S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Thompson A, Walker M, Watson S, Wensley F, Perry P, Danesh J., PANICO, SALVATORE, Hompson, S, Kaptoge, S, White, I, Wood, A, Thompson, Sg, White, Ir, Wood, Am, Perry, Pl, Danesh, J, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Tracy, Rp, Tybjærg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, 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, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Lappas, G, 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, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, 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, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Umans, J, Onat, A, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, M, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marín Ibañez, A, Feskens, Ej, Kromhout, D, Di Angelantonio, E, Erqou, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, Walker, M, Watson, S, Wensley, F, Perry, P, and Danesh, J.

Published
2010

12. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

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.

Subjects
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.

Published
2009
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13. 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

Author

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.

Subjects
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.

Published
2007
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17. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

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.

Published
2010

18. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

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.

Published
2009

27. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Author

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

Subjects
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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29. Variations in antihypertensive medication treatment and blood pressure control among Veterans with HIV and existing hypertension.

Author

Kim CW, Haji M, Lopes VV, Halladay C, Sullivan JL, Ross D, Slazinski K, Taveira TH, Menon A, Gaitanis M, Longenecker CT, Bloomfield GS, Rudolph JL, Wu WC, and Erqou S

Subjects
Humans, Male, Female, Middle Aged, United States epidemiology, Blood Pressure drug effects, Aged, United States Department of Veterans Affairs statistics & numerical data, Retrospective Studies, Antihypertensive Agents therapeutic use, Hypertension drug therapy, Hypertension epidemiology, HIV Infections drug therapy, HIV Infections complications, HIV Infections epidemiology, Veterans statistics & numerical data
Abstract

Background: Hypertension is a leading risk factor for cardiovascular disease among patients living with HIV (PLWH). Understanding the predictors and patterns of antihypertensive medication prescription and blood pressure (BP) control among PLWH with hypertension (HTN) is important to improve the primary prevention efforts for this high-risk population. We sought to assess important patient-level correlates (eg, race) and inter-facility variations in antihypertension medication prescriptions and BP control among Veterans living with HIV (VLWH) and HTN., Methods: We studied VLWH with a diagnosis of HTN who received care in the Veterans Health Administration (VHA) from January 2018 to December 2019. We evaluated HTN treatment and blood pressure control across demographic variables, including race, and by medical comorbidities. Data were also compared among VHA facilities. Predictors of HTN treatment and control were assessed in 2-level hierarchical multivariate logistic regression models to estimate odds ratios (ORs). The VHA facility random-effects parameters from the hierarchical models were used to calculate the median odds ratios to characterize the variation across the different VHA facilities., Results: A total of 17,468 VLWH with HTN (mean age 61 years, 97% male, 54% Black, 40% White) who received care within the VHA facilities in 2018-2019 were included. 73% were prescribed antihypertension medications with higher prescription rates among Black vs White patients (75% vs 71%) and higher prescription rates among patients with a history of cardiovascular disease, diabetes, and kidney disease (>80%), and those receiving antiretroviral therapy and with controlled HIV viral load (∼75%). Only 27% of VLWH with HTN had optimal BP control of systolic BP <130 mmHg and diastolic BP <80 mmHg, with a lower rate of control among Black vs White patients (24% v. 31%). In multivariate regression, Black patients had a higher likelihood of HTN medication prescription (OR 1.32, 95% CI: 1.22-1.42) but were less likely to have optimal BP control (OR 0.82; 0.76-0.88). Important positive correlates of antihypertensive prescription and optimal BP control included: number of outpatient visits in prior year, and histories of diabetes, coronary artery disease, and heart failure. There was about 10% variability in both antihypertensive prescription and BP control patterns between VHA facilities for patients with similar characteristics. There was increased inter-facility variation in antihypertensive prescription among those with a history of heart failure and those not receiving antiretroviral therapy., Conclusion: In a retrospective analysis of large VHA data, we found that VLWH with HTN have suboptimal antihypertensive medication prescription and BP control. Black VLWH had higher HTN medication prescription rates but lower optimal BP control., Competing Interests: Conflict of interest None reported., (Published by Elsevier Inc.)

Published
2024
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30. Clinical Outcomes After Acute Coronary Syndromes or Revascularization Among People Living With HIV: A Systematic Review and Meta-Analysis.

Author

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

Subjects
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.

Published
2024
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32. Risk of death and readmission among individuals with heart failure and HIV: A systematic review and meta-analysis.

Author

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

Subjects
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.)

Published
2024
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33. Proprotein convertase subtilisn/kexin type 9 inhibitors and small interfering RNA therapy for cardiovascular risk reduction: A systematic review and meta-analysis.

Author

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

Subjects
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
Abstract

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.)

Published
2023
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34. Acute Antipsychotic Use and Presence of Dysphagia Among Older Veterans with Heart Failure.

Author

Robison RD, Singh M, Jiang L, Riester M, Duprey M, McGeary JE, Goyal P, Wu WC, Erqou S, Zullo A, Rudolph JL, and Rogus-Pulia N

Subjects
Humans, Female, Aged, United States, Aged, 80 and over, Retrospective Studies, Medicare, Hospitalization, Antipsychotic Agents adverse effects, Deglutition Disorders, Veterans, Heart Failure complications, Heart Failure drug therapy, Dementia complications, Dementia drug therapy, Dementia chemically induced
Abstract

Objective: Examine whether new antipsychotic (AP) exposure is associated with dysphagia in hospitalized patients with heart failure (HF)., Design: Retrospective cohort., Settings and Participants: AP-naïve Veterans hospitalized with HF and subsequently discharged to a skilled nursing facility (SNF) between October 1, 2010, and November 30, 2019., Methods: We linked Veterans Health Administration (VHA) electronic medical records with Centers for Medicare & Medicaid (CMS) Minimum Data Set (MDS) version 3.0 assessments and CMS claims. The exposure variable was administration of ≥1 dose of a typical or atypical AP during hospitalization. Our main outcome measure was dysphagia presence defined by (1) inpatient dysphagia diagnosis codes and (2) the SNF admission MDS 3.0 swallowing-related items to examine post-acute care dysphagia status. Inverse probability of treatment weighting was used for risk adjustment., Results: The analytic cohort consisted of 29,591 Veterans (mean age 78.5 ± 10.0 years; female 2.9%; n = 865). Acute APs were administered to 9.9% (n = 2941). Those receiving APs had differences in prior dementia [37.1%, n = 1091, vs 22.3%, n = 5942; standardized mean difference (SMD) = 0.33] and hospital delirium diagnoses (7.7%, n = 227 vs 2.8%, n = 754; SMD = 0.22). Acute AP exposure was associated with nearly double the risk for hospital dysphagia diagnosis codes [adjusted (adj.) relative risk (RR) 1.9, 95% CI 1.8, 2.1]. At the SNF admission MDS assessment, acute AP administration during hospitalization was associated with an increased dysphagia risk (adj. RR 1.2, 95% CI 1.0, 1.5) both in the oral (adj. RR 1.7, 95% CI 1.2, 2.0) and pharyngeal phases (adj. RR 1.3, 95% CI 1.0, 1.7)., Conclusions and Implications: In this retrospective study, AP medication exposure was associated with increased dysphagia coding and MDS assessment. Considering other adverse effects, acute AP should be cautiously administered during hospitalization, particularly in those with dementia. Swallowing function is critical to hydration, nutrition, and medical management of HF; therefore, when acute APs are initiated, a swallow evaluation should be considered., (Published by Elsevier Inc.)

Published
2023
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35. Type 1 diabetes and risk of heart failure: A systematic review and meta-analysis.

Author

Haji M, Erqou S, Fonarow GC, and Echouffo-Tcheugui JB

Subjects
Male, Humans, Female, Diabetes Mellitus, Type 1 complications, Diabetes Mellitus, Type 1 epidemiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Heart Failure epidemiology, Heart Failure etiology
Abstract

Aim: Robust data on type 1 diabetes (T1DM) and the risk of heart failure (HF) is scarce., Methods: We searched PubMed and EMBASE for relevant studies, abstracted data on HF incidence rate and adjusted relative risk (aRR) for T1DM, type 2 diabetes (T2DM) and controls, and pooled incidence rates and aRRs for HF across studies., Results: Four studies including 61,885 T1DM patients, 4,599,213 non-diabetic controls, and 248,021 T2DM patients (three studies) were included. The pooled average proportions of men were 56%, 54%, and 55%, for T1DM, T2DM, and controls, respectively. The corresponding pooled average participants' ages were 40, 65 and 57 years, respectively. Over a 1 to 12 years follow-up, 1378, 3993, 18,945 HF events occurred among individuals with T1DM, T2DM, and controls, yielding pooled HF incidence rates of 5.8 (95%CI: 4.1-7.6), 10.0 (95% CI: 6.1-13.9), 2.3 (95% CI: 1.5-3.2) per 1000 person-years, respectively. Compared to controls, T1DM patients had a 3-fold higher HF risk (aRR 3.4, 95% CI 2.71-4.26). The RR of HF was ∼ 5-fold higher in women (aRR: 4.9, 95% CI: 4.1-5.9) vs. 3-fold higher in men (aRR: 3.0, 95% CI: 2.2-4.0)., Conclusions: Individuals with T1DM had a substantially higher risk of HF compared to those without diabetes., Competing Interests: Declaration of Competing Interest Dr Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer,Cytokinetics, Eli Lilly, Janssen, Medtronic, Merck, Novartis, and Pfizer. All the other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Published
2023
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37. Performance of Cardiovascular Risk Prediction Models Among People Living With HIV: A Systematic Review and Meta-analysis.

Author

Soares C, Kwok M, Boucher KA, Haji M, Echouffo-Tcheugui JB, Longenecker CT, Bloomfield GS, Ross D, Jutkowtiz E, Sullivan JL, Rudolph JL, Wu WC, and Erqou S

Subjects
Adult, United States, Humans, Male, Risk Factors, Heart Disease Risk Factors, Risk Assessment, Cardiovascular Diseases epidemiology, Cardiovascular Diseases diagnosis, HIV Infections complications, HIV Infections drug therapy, HIV Infections epidemiology
Abstract

Importance: Extant data on the performance of cardiovascular disease (CVD) risk score models in people living with HIV have not been synthesized., Objective: To synthesize available data on the performance of the various CVD risk scores in people living with HIV., Data Sources: PubMed and Embase were searched from inception through January 31, 2021., Study Selection: Selected studies (1) were chosen based on cohort design, (2) included adults with a diagnosis of HIV, (3) assessed CVD outcomes, and (4) had available data on a minimum of 1 CVD risk score., Data Extraction and Synthesis: Relevant data related to study characteristics, CVD outcome, and risk prediction models were extracted in duplicate. Measures of calibration and discrimination are presented in tables and qualitatively summarized. Additionally, where possible, estimates of discrimination and calibration measures were combined and stratified by type of risk model., Main Outcomes and Measures: Measures of calibration and discrimination., Results: Nine unique observational studies involving 75 304 people (weighted average age, 42 years; 59 490 male individuals [79%]) living with HIV were included. In the studies reporting these data, 86% were receiving antiretroviral therapy and had a weighted average CD4+ count of 449 cells/μL. Included in the study were current smokers (50%), patients with diabetes (5%), and patients with hypertension (25%). Ten risk prediction scores (6 in the general population and 4 in the HIV-specific population) were analyzed. Most risk scores had a moderate performance in discrimination (C statistic: 0.7-0.8), without a significant difference in performance between the risk scores of the general and HIV-specific populations. One of the HIV-specific risk models (Data Collection on Adverse Effects of Anti-HIV Drugs Cohort 2016) and 2 of the general population risk models (Framingham Risk Score [FRS] and Pooled Cohort Equation [PCE] 10 year) had the highest performance in discrimination. In general, models tended to underpredict CVD risk, except for FRS and PCE 10-year scores, which were better calibrated. There was substantial heterogeneity across the studies, with only a few studies contributing data for each risk score., Conclusions and Relevance: Results of this systematic review and meta-analysis suggest that general population and HIV-specific CVD risk models had comparable, moderate discrimination ability in people living with HIV, with a general tendency to underpredict risk. These results reinforce the current recommendations provided by the American College of Cardiology/American Heart Association guidelines to consider HIV as a risk-enhancing factor when estimating CVD risk.

Published
2023
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38. Incidence of New Dementia Diagnosis in Veterans Admitted to Nursing Homes After Heart Failure Hospitalization.

Author

Bayer TA, Jiang L, Erqou S, Kunicki ZJ, Singh M, Duprey M, Bozzay M, McGeary JE, Zullo AR, Wu WC, Gravenstein S, and Rudolph JL

Subjects
Humans, United States epidemiology, Retrospective Studies, Incidence, Hospitalization, Nursing Homes, Veterans, Alzheimer Disease diagnosis, Heart Failure diagnosis, Heart Failure epidemiology
Abstract

Background: Hospitalization with heart failure (HF) may signal an increased risk of Alzheimer's disease and related dementias (ADRD). Nursing homes routinely assess cognition but the association of these results with new ADRD diagnosis in a population at high risk of ADRD is not known., Objective: To determine the association between nursing home cognitive assessment results and new diagnosis of dementia after heart failure hospitalization., Methods: This retrospective cohort study included Veterans hospitalized for HF and discharged to nursing homes, from 2010 to 2015, without a prior diagnosis of ADRD. We determined mild, moderate, or severe cognitive impairment using multiple items of the nursing home admission assessment. We used Cox regression to determine the association of cognitive impairment with new ADRD diagnosis during 365 days of follow-up., Results: The cohort included 7,472 residents, new diagnosis of ADRD occurred in 4,182 (56%). The adjusted hazard ratio of ADRD diagnosis was 4.5 (95% CI 4.2, 4.8) for the mild impairment group, 5.4 (95% CI 4.8, 5.9) for moderate impairment, and 4.0 (95% CI 3.2, 5.0) for severe impairment compared to the cognitively intact group., Conclusion: New ADRD diagnoses occurred in more than half of Veterans with HF admitted to nursing homes for post-acute care.

Published
2023
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39. Comparing Lookback Periods to Ascertain Alzheimer's Disease and Related Dementias.

Author

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

Subjects
Humans, Prevalence, Alzheimer Disease diagnosis, Alzheimer Disease epidemiology
Abstract

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.

Published
2023
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40. Particulate matter 2.5, metropolitan status, and heart failure outcomes in US counties: A nationwide ecologic analysis.

Author

Chen EW, Ahmad K, Erqou S, and Wu WC

Subjects
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
Abstract

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.)

Published
2022
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41. Utilization of Palliative Care in Veterans Admitted With Heart Failure Experiencing Homelessness.

Author

Gula AL, Ramos J, Simpson JM, Jiang L, Martin E, Wice M, Erqou S, Wu WC, and Rudolph JL

Subjects
Hospitalization, Humans, Palliative Care, Retrospective Studies, United States epidemiology, United States Department of Veterans Affairs, Heart Failure epidemiology, Heart Failure therapy, Ill-Housed Persons, Veterans
Abstract

Context: Patients experiencing housing insecurity have numerous barriers affecting their utilization of medical care., Objectives: Determine if housing insecurity is associated with palliative care (PC) encounters and hospice services in patients with heart failure who receive care in United States Veterans Affairs (VA) medical centers., Methods: This retrospective study included inpatients in VA hospitals with a primary diagnosis of congestive heart failure from 2010 to 2020. Housing stability was collected from coding and separated into three cohorts: at risk for homelessness, experiencing homelessness, and stably housed. The primary outcome was a PC encounter during admission and the stably housed cohort was used as the analytic reference. Inverse-probability-weighting (IPTW) was calculated to adjust the likelihood of receiving PC during the index admission., Results: Seventy thousand eight hundred fourty nine veterans were identified. Veterans were identified as at risk for homelessness (n=4039, 5.7%), experiencing homelessness (n=1967, 2.8%) and stably housed (n=64,843, 91.5%). PC was delivered to veterans at risk for homelessness (n=484, 12.0%), veterans experiencing homelessness, (n=161, 8.2%) and patients with stable housing (n=6249, 9.6%). Relative to the stably housed and adjusted for IPTW, those at risk for homelessness received PC services similarly (adjusted OR=1.06, 95% CI 0.94,1.19) and those experiencing homelessness were at lower odds of receiving PC services (adjusted OR=0.62, 95% CI 0.52,0.75)., Conclusion: Housing stability may be a factor in Veterans receiving PC during hospitalization for heart failure. While the logistical challenges of delivering PC and hospice to people experiencing homelessness are daunting, advocating for these services shows commitment to reducing suffering in life-limiting Illness., (Published by Elsevier Inc.)

Published
2022
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42. New Antipsychotic Prescribing Continued into Skilled Nursing Facilities Following a Heart Failure Hospitalization: a Retrospective Cohort Study.

Author

Riester MR, Goyal P, Jiang L, Erqou S, Rudolph JL, McGeary JE, Rogus-Pulia NM, Madrigal C, Quach L, Wu WC, and Zullo AR

Subjects
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
Abstract

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.)

Published
2022
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43. Two decade trends in cardiovascular disease outcomes and cardiovascular risk factors among US veterans living with HIV.

Author

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

Abstract

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.)

Published
2022
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44. Long-term Cardiovascular Manifestations and Complications of COVID-19: Spectrum and Approach to Diagnosis and Management.

Author

Khetpal V, Berkowitz J, Vijayakumar S, Choudhary G, Mukand JA, Rudolph JL, Wu WC, and Erqou S

Subjects
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
Abstract

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.

Published
2022

45. Associations between cumulative social risk, psychosocial risk, and ideal cardiovascular health: Insights from the HeartSCORE study.

Author

Berkowitz J, Khetpal V, Echouffo-Tcheugui JB, Bambs CE, Aiyer A, Kip KE, Reis SE, and Erqou S

Abstract

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.)

Published
2022
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46. Racial Differences in Burdensome Transitions in Heart Failure Patients with Palliative Care: A Propensity-Matched Analysis.

Author

Zametkin E, Williams E, Feingold-Link M, Jiang L, Martin E, Erqou S, Gravenstein S, Wice M, Wu WC, and Rudolph JL

Subjects
Humans, Race Factors, Retrospective Studies, United States, United States Department of Veterans Affairs, Heart Failure therapy, Palliative Care
Abstract

Background: Examining racial disparities in the treatment of heart failure (HF) patients and the effects of palliative care (PC) consultation is important to developing culturally competent clinical behaviors. Objective: To compare burdensome transitions for Black and White Veterans hospitalized with HF after PC consultation. Participants: This retrospective study evaluated Veterans admitted for HF to Veterans Administration hospitals who received PC consultation from October 2010 through August 2017. Methods: We propensity-matched Black to White Veterans using demographic, comorbidity, clinical, hospital, and survival time data. Results: Propensity matching of our cohort ( n  = 5638) yielded 796 Black and White Veterans (total n  = 1592) who were well-matched on observed variables (standard mean difference <0.15 for all variables). Matched Black Veterans had more burdensome transitions than White Veterans ( n  = 218, 27.4% vs. n  = 174, 21.9%; p  = 0.011) over the six-month follow-up period. Conclusions: This propensity-matched cohort found racial differences in burdensome transitions among admitted HF patients after PC consultation.

Published
2022
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47. Variation in statin prescription among veterans with HIV and known atherosclerotic cardiovascular disease.

Author

Erqou S, Papaila A, Halladay C, Ge A, Liu MA, Jiang L, Lally M, Menon A, Shah NR, Miech E, Virani SS, Zullo AR, Shireman TI, Longenecker CT, Ross D, Sullivan JL, Wu WC, and Rudolph JL

Subjects
Aged, Female, Humans, Male, Middle Aged, Prescriptions, Atherosclerosis complications, Atherosclerosis drug therapy, Atherosclerosis epidemiology, Cardiovascular Diseases drug therapy, Cardiovascular Diseases epidemiology, Cardiovascular Diseases prevention & control, HIV Infections complications, HIV Infections drug therapy, HIV Infections epidemiology, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Peripheral Arterial Disease drug therapy, Veterans
Abstract

Background: People with HIV have increased atherosclerotic cardiovascular disease (ASCVD) risk, worse outcomes following incident ASCVD, and experience gaps in cardiovascular care, highlighting the need to improve delivery of preventive therapies in this population., Objective: Assess patient-level correlates and inter-facility variations in statin prescription among Veterans with HIV and known ASCVD., Methods: We studied Veterans with HIV and existing ASCVD, ie, coronary artery disease (CAD), ischemic cerebrovascular disease (ICVD), and peripheral arterial disease (PAD), who received care across 130 VA medical centers for the years 2018-2019. We assessed correlates of statin prescription using two-level hierarchical multivariable logistic regression. Median odds ratios (MORs) were used to quantify inter-facility variation in statin prescription., Results: Nine thousand six hundred eight Veterans with HIV and known ASCVD (mean age 64.3 ± 8.9 years, 97% male, 48% Black) were included. Only 68% of the participants were prescribed any-statin. Substantially higher statin prescription was observed for those with diabetes (adjusted odds ratio [OR] = 2.3, 95% confidence interval [CI], 2.0-2.6), history of coronary revascularization (OR = 4.0, CI, 3.2-5.0), and receiving antiretroviral therapy (OR = 3.0, CI, 2.7-3.4). Blacks (OR = 0.7, CI, 0.6-0.9), those with non-coronary ASCVD, ie, ICVD and/or PAD only, (OR 0.53, 95% CI: 0.48-0.57), and those with history of illicit substance use (OR=0.7, CI, 0.6-0.9) were less likely to be prescribed statins. There was significant variation in statin prescription across VA facilities (10th, 90th centile: 55%, 78%), with an estimated 20% higher likelihood of difference in statin prescription practice for two clinically similar individuals treated at two comparable facilities (adjusted MOR = 1.21, CI, 1.18-1.24), and a greater variation observed for Blacks or those with non-coronary ASCVD or history of illicit drug use., Conclusion: In an analysis of large-scale VA data, we found suboptimal statin prescription and significant interfacility variation in statin prescription among Veterans with HIV and known ASCVD, particularly among Blacks and those with a history of non-coronary ASCVD., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Published
2022
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48. Severe Hypoglycemia and Incidence of QT Interval Prolongation Among Adults With Type 2 Diabetes.

Author

Kaze AD, Yuyun MF, Erqou S, Fonarow GC, and Echouffo-Tcheugui JB

Subjects
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.)

Published
2022
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49. Outcomes in heart failure patients discharged to skilled nursing facilities with delirium.

Author

Lafo J, Singh M, Jiang L, Correia S, Madrigal C, Clements R, Wu WC, Erqou S, and Rudolph JL

Subjects
Female, Humans, Male, Medicare, Patient Discharge, Retrospective Studies, Skilled Nursing Facilities, United States epidemiology, Delirium epidemiology, Dementia epidemiology, Heart Failure epidemiology, Heart Failure therapy
Abstract

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.)

Published
2022
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