Development of a model predicting cardiac events in heart failure patients with decreased renal function: a retrospective study

Background Inappropriate and multiple medications affect the prognosis of patients with acute decompensated heart failure (ADHF). However, in ADHF patients with decreased renal function, there have been no reports on prognostic factors, including medication data, or models for predicting cardiac events. Aim To develop a model including medication data to predict cardiac events in ADHF patients with decreased renal function. Method This retrospective cohort study included 443 first-time admitted ADHF patients with decreased renal function (estimated glomerular filtration rate < 60 mL/min/1.73 m 2 at discharge) in the Showa University Fujigaoka Hospital. The primary outcome was cardiac events within one year after discharge, defined as the composite of HF readmission, HF mortality, and cardiovascular mortality. The model for predicting cardiac events was developed using predictive factors extracted by multivariable analysis. The cardiac events curves were visualized using the Kaplan–Meier method and estimated using a log-rank test. Results The incidence of cardiac events within one year after discharge was 20.1%. By multivariable analysis, we observed that atrial fibrillation, weight loss < 5%, brain natriuretic peptide ≥ 200 pg/mL, polypharmacy, and beta-blockers use below target dosage were significantly associated with an increased risk of cardiac events. The developed model, the cardiac events rate in the high-risk group was significantly higher than in the low-risk group (41.0 vs. 9.2%, p < 0.001). Conclusion The developed model for predicting cardiac events will be useful in decision-making to support appropriate early management of ADHF patients with decreased renal function.