ArticleJournal of the American College of Cardiology2019
10-Year Risk Equations for Incident Heart Failure in the General Population.
Article in Journal of the American College of Cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
123 citing papers in PubMed, 4 syntheses or guidelines pooled it, 187 citations in OpenAlex.
- Pooled it
- Artificial intelligence in electrocardiogram-based prediction of heart failure: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2025Pooled it
- Age dependent associations of risk factors with heart failure: pooled population based cohort study.BMJ (Clinical research ed.) · 2021Pooled it
- Sex-Specific Associations of Cardiovascular Risk Factors and Biomarkers With Incident Heart Failure.Journal of the American College of Cardiology · 2020Pooled it
- Using PREVENT Equations to Compare Intensive vs Standard Systolic Blood Pressure Control for Primary Prevention in SPRINT.Journal of the American College of Cardiology · 2025Trial
- Development of a heart failure with preserved ejection fraction risk prediction score in primary care settings with a high HIV prevalence.Open heart · 2026Observational
- Body mass index, waist-to-height ratio, and the risks of early-onset heart failure in adults age under 45.American journal of preventive cardiology · 2026Article
- Prediction of incident heart failure in men and women with a history of myocardial infarction.ESC heart failure · 2026Article
- Modeling day-long ECG signals to predict heart failure risk with explainable AI.NPJ digital medicine · 2026Article
- Systematic examination of the PREVENT equations for cardiovascular disease risk.American journal of preventive cardiology · 2026Article
- AI-CVD-HF: A heart failure risk prediction model based on coronary artery calcium scans compared with PREVENT-HF.American journal of preventive cardiology · 2026Article
- Development and Validation of a Machine Learning Model for Incident Heart Failure Prediction in Chronic Kidney Disease: A Multicenter Cohort Study.Journal of the American Heart Association · 2026Article
- Artificial Intelligence-Driven Electrocardiogram Screening for Asymptomatic Left Ventricular Systolic Dysfunction in the General Population.JACC. Advances · 2026Article
- Artificial Intelligence-Enabled ECG Analysis to Predict Incident Heart Failure.Circulation. Heart failure · 2026Article
- The Prevention of Heart Failure Risk Assessment and Early Intervention along the Cardiovascular Continuum.Current heart failure reports · 2026Review
- Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification.Current heart failure reports · 2026Review
- Biomarkers for Screening and Diagnosis of Heart Failure in Cardiovascular-Kidney-Metabolic Syndrome: A Narrative Review.International journal of molecular sciences · 2026Review
- Validation and longitudinal trajectory analysis of an AI-based ECG model for aortic stenosis: from community screening to pre-TAVR risk stratification.European heart journal. Digital health · 2026Article
- Prediction models for incident stroke in the community: a systematic review and meta-analysis of predictive performance.European heart journal. Digital health · 2026Article
- Integrating ketone bodies in multi-marker risk prediction of incident heart failure in the multi-ethnic study of atherosclerosis.European journal of preventive cardiology · 2026Article
63 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundPrimary prevention strategies to mitigate the burden of heart failure (HF) are urgently needed. However, no validated risk prediction tools are currently in use.
objectivesThis study sought to derive 10-year risk equations of developing incident HF.
methodsRace- 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.
resultsIn 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.
conclusionsThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.