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Published on: June 30, 2023
Risk classification for long-term mortality among patients with acute heart failure: China PEACE 4YMortality
Wei Wang1,2, Lihua Zhang1, Guangda He1
1National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Insights
A new risk prediction model was developed to identify patients hospitalized with acute heart failure (AHF) at high risk of long-term mortality. This tool aids in stratifying risk for improved patient outcomes in China.
Area of Science:
- Cardiology
- Public Health
- Medical Informatics
Background:
- Limited tools exist for predicting long-term mortality in Chinese patients hospitalized with acute heart failure (AHF).
- Accurate risk stratification is crucial for managing AHF patients post-discharge.
Purpose of the Study:
- To develop and validate a predictive model for 4-year mortality risk in patients discharged alive after AHF hospitalization.
- To establish a practical risk score for clinical use.
Main Methods:
- Utilized data from the China Patient-Centred Evaluative Assessment of Cardiac Events Prospective Heart Failure Study.
- Employed a multivariate Cox proportional hazard model for prediction model development and internal validation.
- Selected 13 predictors including clinical data and biomarkers.
Main Results:
- The study included 4875 AHF patients; 42.38% died within 4 years.
- The developed model demonstrated good predictive performance (C-index 0.726 in development, 0.727 in validation).
- A point-based risk score stratified patients into low, intermediate, and high-risk groups.
Conclusions:
- A validated risk prediction model using accessible predictors for 4-year mortality in AHF patients was successfully developed.
- The model is beneficial for individual risk stratification and improving patient outcomes.
- This tool supports clinical decision-making for AHF survivors.
Aims:
There 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.
Methods:
We 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.
Results:
The 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.
Conclusions:
By 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.
