Jennifer E Ho1, Danielle Enserro2, Frank P Brouwers2, Jorge R Kizer2, Sanjiv J Shah2, Bruce M Psaty2, Traci M Bartz2, Rajalakshmi Santhanakrishnan2, Douglas S Lee2, Cheeling Chan2, Kiang Liu2, Michael J Blaha2, Hans L Hillege2, Pim van der Harst2, Wiek H van Gilst2, Willem J Kop2, Ron T Gansevoort2, Ramachandran S Vasan2, Julius M Gardin2, Daniel Levy2, John S Gottdiener2, Rudolf A de Boer2, Martin G Larson2. 1. From the Cardiovascular Research Center, Massachusetts General Hospital (J.E.H.); Cardiovascular Medicine Section, Department of Medicine (R.S.) and Section of Preventive Medicine and Epidemiology (R.S.V.), Boston University School of Medicine, MA; National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, MA (J.E.H., R.S.V., D.L., M.G.L.); Department of Mathematics and Statistics, Boston University, MA (D.E., M.G.L.); Department of Cardiology (F.P.B., H.L.H., P.v.d.H., W.H.v.G., R.A.d.B.) and Division of Nephrology, Department of Internal Medicine (R.T.G.), University Medical Center Groningen, The Netherlands; Department of Medicine and Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (J.R.K.); Division of Cardiology (S.J.S.), Department of Medicine (C.C., K.L.), and Department of Preventive Medicine (C.C., K.L.), Northwestern University Feinberg School of Medicine, Chicago, IL; Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, and Department of Health Services (B.M.P.) and Department of Biostatistics (T.M.B.), University of Washington; Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P.); Institute for Clinical Evaluative Sciences, Toronto, Canada (D.S.L.); University Health Network, University of Toronto, Canada (D.S.L.); Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University, Baltimore, MD (M.J.B.); Department of Medicine, Hackensack University Medical Center and Rutgers New Jersey Medical School, Hackensack, NJ (J.M.G.); Center of Research on Psychology in Somatic Diseases, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands (W.J.K.); Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD (D.L.); and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD (J.S.G.). jho 2. From the Cardiovascular Research Center, Massachusetts General Hospital (J.E.H.); Cardiovascular Medicine Section, Department of Medicine (R.S.) and Section of Preventive Medicine and Epidemiology (R.S.V.), Boston University School of Medicine, MA; National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, MA (J.E.H., R.S.V., D.L., M.G.L.); Department of Mathematics and Statistics, Boston University, MA (D.E., M.G.L.); Department of Cardiology (F.P.B., H.L.H., P.v.d.H., W.H.v.G., R.A.d.B.) and Division of Nephrology, Department of Internal Medicine (R.T.G.), University Medical Center Groningen, The Netherlands; Department of Medicine and Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (J.R.K.); Division of Cardiology (S.J.S.), Department of Medicine (C.C., K.L.), and Department of Preventive Medicine (C.C., K.L.), Northwestern University Feinberg School of Medicine, Chicago, IL; Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, and Department of Health Services (B.M.P.) and Department of Biostatistics (T.M.B.), University of Washington; Group Health Research Institute, Group Health Cooperative, Seattle, WA (B.M.P.); Institute for Clinical Evaluative Sciences, Toronto, Canada (D.S.L.); University Health Network, University of Toronto, Canada (D.S.L.); Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University, Baltimore, MD (M.J.B.); Department of Medicine, Hackensack University Medical Center and Rutgers New Jersey Medical School, Hackensack, NJ (J.M.G.); Center of Research on Psychology in Somatic Diseases, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands (W.J.K.); Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD (D.L.); and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD (J.S.G.).
Abstract
BACKGROUND: Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF). METHODS AND RESULTS: Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95% confidence interval [CI], 0.78-0.82) and validation samples (internal: 0.79; 95% CI, 0.77-0.82 and external: 0.76; 95% CI: 0.71-0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95% CI, 0.80-0.84) and validation samples (internal: 0.80; 95% CI, 0.78-0.83 and external: 0.76; 95% CI, 0.71-0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison ≤0.02). CONCLUSIONS: We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes.
BACKGROUND:Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF). METHODS AND RESULTS: Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95% confidence interval [CI], 0.78-0.82) and validation samples (internal: 0.79; 95% CI, 0.77-0.82 and external: 0.76; 95% CI: 0.71-0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95% CI, 0.80-0.84) and validation samples (internal: 0.80; 95% CI, 0.78-0.83 and external: 0.76; 95% CI, 0.71-0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison ≤0.02). CONCLUSIONS: We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes.
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