Application of the atherosclerosis risk in communities heart failure risk prediction model in predicting the incidence of heart failure in a Chinese community population
Application of the atherosclerosis risk in communities heart failure risk prediction model in predicting the incidence of heart failure in a Chinese community population
Objective:To externally validate the predictive accuracy of the heart failure(HF)risk model(ARIC)in the Chinese community population for incident HF.Methods:A total of 2 509 participants aged 55-84 free of baseline HF were included from the Chinese multi-provincial cohort study(CMCS)-Beijing project in this analysis.We extracted the coefficient of each predictor in ARIC equations to calculate the 9-year risk of incident HF.The discrimination of the model was evaluated using the C-statistic,and the calibration of the model was assessed using the Hosmer-Lemeshow x2 test and decile plots.Results:During the 9-year follow-up period,a total of 174 heart failure events occurred.In the CMCS-Beijing population,the discrimination of the ARIC model was excellent,with 0.809(95％ CI:0.723-0.895)for males and 0.730(95％CI:0.620-0.840)for females;however,the HF risk prediction model was not well calibrated,where the ARIC model overestimated the HF incident risk in both males and females compared with actual observed proportions.Conclusions:The heart failure risk prediction model(ARIC)could predict 9-year incident HF risk in the Chinese population with good performance,especially for males,though overestimation of the incident HF risk,which provides a basic fundament for the management and utility of established heart failure risk assessment tools in China.
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