Abstract
Background: The models for predicting cardiovascular events, including medication data such as dosage and the number of medications, have not been well studied. This study aimed to develop a model, including medication data, for predicting cardiovascular events within one year after discharge in acute decompensated heart failure (ADHF) patients with decreased renal function. Methods This study included 443 first-time admitted ADHF patients with decreased renal function in the Showa University Fujigaoka Hospital between January 2015 and December 2019. Decreased renal function was defined as an eGFR < 60 mL/min/1.73 m 2 at discharge. The primary outcome was cardiovascular events (cardiovascular death and first heart failure rehospitalization) within one year after discharge. The model for predicting events was developed using predictive factors extracted by multivariate analysis. The cardiovascular events curves were visualized using the Kaplan-Meier method and estimated using a log-rank test. Results The incidence of cardiovascular events was 20.1%. By multivariate analysis, atrial fibrillation (AF), weight loss < 5% during admission, brain natriuretic peptide (BNP) ≥ 200 pg/mL at discharge, polypharmacy (≥ 10 drugs), and beta-blockers use below the maintenance dosage were significantly associated with an increased risk of cardiovascular events. The hazard ratios of the five factors for the cardiovascular events were scored (AF, weight loss, polypharmacy, and beta-blockers dosage = 1 point; BNP = 2 points) and patients divided into three groups. The cardiovascular events rate in the high-risk (≥ 4 points) group was four times as high as the rate in the low-risk (≤ 2 point) group (one-year events rate: 41.0% vs 9.2%, p < 0.001, Figure). Conclusions The developed model for cardiovascular events, including polypharmacy and beta-blockers dosage, will be useful for planning more aggressive and earlier management in ADHF patients with decreased renal function.
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