Dataset Information

10-Year Risk Equations for Incident Heart Failure in the General Population.

ABSTRACT: BACKGROUND:Primary prevention strategies to mitigate the burden of heart failure (HF) are urgently needed. However, no validated risk prediction tools are currently in use. OBJECTIVES:This study sought to derive 10-year risk equations of developing incident HF. METHODS:Race- and sex-specific 10-year risk equations for HF were derived and validated from individual-level data from 7 community-based cohorts with at least 12 years of follow-up. Participants who were recruited between 1985 and 2000, between 30 to 79 years, and were free of cardiovascular disease at baseline were included to create a pooled cohort (PC) and were randomly split for derivation and internal validation. Model performance was also assessed in 2 additional cohorts. RESULTS:In the derivation sample of the PC (n = 11,771), 58% were women, 22% were black with a mean age of 52 ± 12 years, and HF occurred in 1,339 participants. Predictors of HF included in the race-sex-specific models were age, blood pressure (treated or untreated), fasting glucose (treated or untreated), body mass index, cholesterol, smoking status, and QRS duration. The PC equations to Prevent HF model had good discrimination and strong calibration in internal and external validation cohorts. A web-based tool was developed to facilitate clinical application of this tool. CONCLUSIONS:The authors present a contemporary analysis from 33,010 men and women demonstrating the utility of the sex- and race-specific 10-year PC equations to Prevent HF risk score, which integrates clinical parameters readily available in primary care settings. This tool can be useful in risk-based decision making to determine who may merit intensive screening and/or targeted prevention strategies.

SUBMITTER: Khan SS

PROVIDER: S-EPMC6527121 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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10-Year Risk Equations for Incident Heart Failure in the General Population.

Khan Sadiya S SS Ning Hongyan H Shah Sanjiv J SJ Yancy Clyde W CW Carnethon Mercedes M Berry Jarett D JD Mentz Robert J RJ O'Brien Emily E Correa Adolfo A Suthahar Navin N de Boer Rudolf A RA Wilkins John T JT Lloyd-Jones Donald M DM

Journal of the American College of Cardiology 20190501 19

<h4>Background</h4>Primary prevention strategies to mitigate the burden of heart failure (HF) are urgently needed. However, no validated risk prediction tools are currently in use.<h4>Objectives</h4>This study sought to derive 10-year risk equations of developing incident HF.<h4>Methods</h4>Race- and sex-specific 10-year risk equations for HF were derived and validated from individual-level data from 7 community-based cohorts with at least 12 years of follow-up. Participants who were recruited b ...[more]

PMID: 31097157

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Project description:ImportanceThe Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) estimate the 10-year risk for symptomatic heart failure (HF) from routine clinical data. The PCP-HF score should detect asymptomatic individuals with cardiac maladaptation preceding HF symptoms for it to be a useful HF prediction tool in primary prevention.ObjectiveTo assess the concordance between PCP-HF risk scoring and the presence of subclinical cardiac maladaptation in the community.Design, setting, and participantsThis cross-sectional analysis included participants enrolled in the Flemish Study on Environment, Genes and Health Outcomes who underwent a clinical examination including echocardiography between May 2005 and January 2015. Participants younger than 30 years, older than 79 years, had prevalent cardiovascular disease, and/or had suboptimal echocardiographic imaging quality were excluded. Analysis began February 2020 and ended April 2020.ExposuresTen-year HF risk as calculated from routine clinical data using the PCP-HF. Based on tertile limits, participants were categorized as having low (≤0.4%), intermediate (0.4%-2.4%), and high (≥2.4%) 10-year HF risk score.Main outcomes and measuresEchocardiographic profiles of subclinical heart remodeling and dysfunction.ResultsA total of 1020 individuals were analyzed (mean [SD] age, 52.8 [11.4] years; 541 female [53.0%]). The prevalence of left ventricular (LV) remodeling and dysfunction was significantly higher from low to intermediate and high 10-year HF risk score. A doubling in 10-year HF risk score was associated with higher odds for LV concentric remodeling (odds ratio [OR], 1.48; 95% CI, 1.36-1.61; P < .001), LV hypertrophy (OR, 1.66; 95% CI, 1.51-1.83; P < .001), abnormal LV longitudinal strain (OR, 1.12; 95% CI, 1.05-1.19; P < .001), and LV diastolic dysfunction (OR, 2.28; 95% CI, 1.94-2.69; P < .001). Moreover, the PCP-HF score detected echocardiographic abnormalities with an accuracy of 74% (LV concentric remodeling), 78% (LV hypertrophy), 59% (abnormal LV longitudinal strain), and 87% (LV diastolic dysfunction). The likelihood of LV concentric remodeling, hypertrophy, and diastolic dysfunction were 3.1, 3.8, and 9.4 times higher in participants with high 10-year HF risk score than the average population risk, respectively (P < .001). Of all PCP-HF score components, age, body mass index, and systolic blood pressure were key correlates of echocardiographic abnormalities in multivariable-adjusted analysis.Conclusions and relevancePCP-HF risk scoring adequately detected individuals with subclinical heart maladaptation that precedes HF symptoms by years. Thus, it may be a valuable HF prediction tool in primary prevention.

Project description:AimsWe aimed to investigate whether metabolomic profiling of blood can lead to novel insights into heart failure pathogenesis or improved risk prediction.Methods and resultsMass spectrometry-based metabolomic profiling was performed in plasma or serum samples from three community-based cohorts without heart failure at baseline (total n = 3924; 341 incident heart failure events; median follow-up ranging from 4.6 to 13.9 years). Cox proportional hazard models were applied to assess the association of each of the 206 identified metabolites with incident heart failure in the discovery cohorts Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) (n = 920) and Uppsala Longitudinal Study of Adult Men (ULSAM) (n = 1121). Replication was undertaken in the independent cohort TwinGene (n = 1797). We also assessed whether metabolites could improve the prediction of heart failure beyond established risk factors (age, sex, body mass index, low-density and high-density lipoprotein cholesterol, triglycerides, lipid medication, diabetes, systolic and diastolic blood pressure, blood pressure medication, glomerular filtration rate, smoking status, and myocardial infarction prior to or during follow-up). Higher circulating urobilin and lower sphingomyelin (30:1) were associated with incident heart failure in age-adjusted and sex-adjusted models in the discovery and replication sample. The hazard ratio for urobilin in the replication cohort was estimated to 1.29 per standard deviation unit, 95% confidence interval (CI 1.03-1.63), and for sphingomyelin (30:1) to 0.72 (95% CI 0.58-0.89). Results remained similar after further adjustment for established heart failure risk factors in meta-analyses of all three cohorts. Urobilin concentrations were inversely associated with left ventricular ejection fraction at baseline in the PIVUS cohort (β = -0.70, 95% CI -1.03 to -0.38). No major improvement in risk prediction was observed when adding the top 2 metabolites (C-index 0.787, 95% CI 0.752-0.823) or nine Lasso-selected metabolites (0.790, 95% CI 0.754-0.826) to a modified Atherosclerosis Risk in Communities heart failure risk score model (0.780, 95% CI 0.745-0.816).ConclusionsOur metabolomic profiling of three community-based cohorts study identified associations of circulating levels of the haem breakdown product urobilin, and sphingomyelin (30:1), a cell membrane component involved in signal transduction and apoptosis, with incident heart failure.

Dataset Information

10-Year Risk Equations for Incident Heart Failure in the General Population.

Publications

10-Year Risk Equations for Incident Heart Failure in the General Population.

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