Abstract:Objective: To construct and validate the individualized nomogram model for predicting the risk of cardiorenal syndrome in patients with heart failure, by analyzing the independent risk factors of heart failure patients complicated with cardiorenal syndrome. Methods: A total of 621 patients diagnosed with acute heart failure in our hospital from January 2010 to December 2019 were included in the study, and they were randomized into modeling group (70%) and validation group (30%). Univariate and multivariate logistic regression were used to analyze the independent risk factors of cardiorenal syndrome in patients with heart failure. R software was used to construct a nomogram model of the risk of cardiorenal syndrome in patients with heart failure. Results: Multivariate logistic regression analysis showed that age, diabetes mellitus, NYHA grade and estimated glomerular filtration rate (eGFR) were independent risk factors of heart failure complicated with cardiorenal syndrome. Through the internal and external validation, the AUC value was 0.807 (95%CI=0.771-0.843) in the modeling group and 0.798 (95%CI=0.757-0.839) in the validation group. The calibration curves of both the modeling group and the validation group have indicated that the prediction model has good stability. Conclusion: This nomogram can accurately predict the individualized risk of cardiorenal syndrome in patients with heart failure, and has high potential clinical application value.
