Risk Stratification Model for 30-Day Heart Failure Readmission in a Multiethnic South East Asian Community

There are limited accurate 30-day heart failure (HF) readmission risk scores using readily available clinical patient information on a well-defined HF cohort. We analyzed 1,475 admissions discharged from our hospital with a primary diagnosis of HF between 2010 and 2012. HF diagnostic criteria included satisfying clinical' Framingham criteria, elevated serum N-terminal pro-natriuretic peptide, and evidence of cardiac dysfunction on trans thoracic echocardiography. The patients were randomly divided into 2 groups; 60% were used as the derivation cohort and 40% as the validation cohort. Bivariate analysis and logistic regression were used to develop the model. Weighted risk scores were derived from the odds ratio of the logistic regression model. Total risk scores were computed by simple summation for each patient. The 7 significant independent predictors of 30-day HF readmission used to derive the risk scoring tool were the number of previous HF-related admission in the preceding 1 year, index admission length of stay, serum creatinine level, electrocardiograph QRS duration, serum N-terminal pro-natriuretic peptide level, number of Medical Social Service needs, and 13 blocker prescription on discharge. The area under the curve was 0.76. Sensitivity and specificity were 78.3% and 60.7%, respectively. The positive predictive value and negative predictive value were 18.9% and 96%, respectively. The actual observed and predicted 30-day heart failure readmission rates matched. In conclusion, we have developed the first 30-day HF readmission risk score, with good discriminatory ability, for an urban multiethnic Asian heart failure cohort with stringent diagnostic criteria. It consists of 7 easily obtained variables. 2017 Elsevier Inc. All rights reserved.