ArticleESC heart failure2025
Risk classification for long-term mortality among patients with acute heart failure: China PEACE 4YMortality.
Article in ESC heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Neutrophil-Percentage-to-Albumin Ratio Outperforms High-Sensitivity C-Reactive Protein in Predicting Mortality in Acute Heart Failure: Evidence from a Nationwide Prospective Cohort.Journal of inflammation research · 2026Article
- Risk classification for long-term mortality among patients with acute heart failure: China PEACE 4YMortality.ESC heart failure · 2025Article
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9 authors.
Funding
Abstract
aimsThere are limited tools to predict long-term mortality among patients hospitalized with acute heart failure (AHF) in China. This study aimed to develop and validate a model to predict long-term mortality risk among patients who were hospitalized with AHF and discharged alive.
methodsWe used data from China Patient-Centred Evaluative Assessment of Cardiac Events Prospective Heart Failure Study. Multivariate Cox proportional hazard model was used to develop and internal validate a model to predict 4 year mortality risk.
resultsThe study included 4875 patients hospitalized for AHF, of whom 2066 (42.38%) died within 4 years following admission, with a median survival time of 3.91 (interquartile range: 1.67, 4.00) years. We selected 13 predictors to establish the model, including age, medical history of hypertension, chronic obstructive pulmonary disease and HF, systolic blood pressure, blood urea nitrogen, albumin, high-sensitivity troponin T, N-terminal pro-brain natriuretic peptide, serum creatine, Kansas City Cardiomyopathy Questionnaire-12 score and left ventricular ejection fraction. The model showed a reasonable performance with the discrimination [C-index was 0.726 (95% confidence interval, CI: 0.714, 0.739) in the development cohort and 0.727 (95% CI: 0.708, 0.747) in the validation cohort]. We then built a point-based risk score algorithm and the patients were stratified to low-risk (0-14), intermediate-risk (15-19) and high-risk (≥20) groups.
conclusionsBy using readily accessible predictors, we developed and validated a risk prediction model to predict 4 year mortality risk among patients who were hospitalized with AHF and discharged alive. This model proved beneficial for individual risk stratification and facilitating ongoing enhancements in patient outcomes.
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