Risk prediction for 30-day heart failure-specific readmission or death after discharge: Data from the Korean Acute Heart Failure (KorAHF) registry. Issue 2 (February 2019)

• Record Type: Journal Article
• Authors: Lim, Nam-Kyoo; Lee, Sang Eun; Lee, Hae-Young; Cho, Hyun-Jai; Choe, Won-Seok; Kim, Hokon; Choi, Jin Oh; Jeon, Eun-Seok; Kim, Min-Seok; Kim, Jae-Joong; Hwang, Kyung-Kuk; Chae, Shung Chull; Baek, Sang Hong; Kang, Seok-Min; Choi, Dong-Ju; Yoo, Byung-Su; Kim, Kye Hun; Cho, Myeong-Chan; Oh, Byung-Hee; Park, Hyun-Young
• Is Part Of: Journal of cardiology. Volume 73:Issue 2(2019)
• Page Start: 108
• Page End: 113
• Publication Date: 2019-02
• Subjects: Heart failure -- 30-day readmission -- Risk score; Cardiology -- Periodicals; 616.12
• DOI: 10.1016/j.jjcc.2018.07.009
• Languages: English
• ISSNs: 0914-5087

Abstract

Highlights: The risk of 30-day heart failure (HF) readmission or death can be estimated with 12 variables. The risk for short-term HF-specific readmission or death can be calculated easily. The model has the potential to reduce readmission by identifying high-risk patients. The risk model can be utilized to guide suitable interventions or care in patients. Abstract: Background: Identifying patients with acute heart failure (HF) at high risk for readmission or death after hospital discharge will enable the optimization of treatment and management. The objective of this study was to develop a risk score for 30-day HF-specific readmission or death in Korea. Methods: We analyzed the data from the Korean Acute Heart Failure (KorAHF) registry to develop a risk score. The model was derived from a multiple logistic regression analysis using a stepwise variable selection method. We also proposed a point-based risk score to predict the risk of 30-day HF-specific readmission or death by simply summing the scores assigned to each risk variable. Model performance was assessed using an area under the receiver operating characteristic curve (AUC), the Hosmer–Lemeshow goodness-of-fit test, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI) index to evaluate discrimination, calibration, and reclassification, respectively. Results: Data from 4566 patients aged ≥40 years were included in the analysis. Among them, 446 (9.8%) had 30-day HF-specific readmission or death. The final model included 12 independent variables (age, New York Heart Association functional class, clinical history of hypertension, HF admission, chronic obstructive pulmonary disease, etiology of cardiomyopathy, systolic blood pressure, left ventricular ejection fraction, serum sodium, brain natriuretic peptide, N-terminal prohormone of brain natriuretic peptide at discharge, and prescription of β-blockers and angiotensin-converting enzyme inhibitors or angiotensin II receptor antagonists at discharge). The point risk score showed moderate discrimination (AUC of 0.710; 95% confidence interval, 0.685–0.735) and good calibration ( χ 2 = 8.540, p = 0.3826). Conclusions: The risk score for the prediction of the risk of 30-day HF-specific readmission or death after hospital discharge was developed using 12 predictors. It can be utilized to guide appropriate interventions or care strategies for patients with HF.