The utility of the adjusted-optimize-hf risk model for predicting in-hospital length of stay in the Chinese population

Abstract

Background: Various risk scores exist for predicting in-hospital mortality in patients with heart failure (HF), including the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) risk model. However, the relations between these risk scores and length of in-hospital stay (LOS) in patients with acute decompensated heart failure (ADHF) has not received much attention. We aim to explore the relationship between the adjusted-OPTIMIZE-HF risk model and LOS in the Chinese population. Methods: This was a single-center, retrospective study that enrolled a total of 4,481 patients with ADHF. We investigated the relation between a wide range of patient variables present at hospital admission, including those that comprise the adjusted-OPTIMIZE-HF risk model and LOS (primary outcome). We divided patients into a short LOS (n=2,177, LOS <6 days) and a long LOS (n=2,304, LOS ≥6 days) group. We then explored the relations between the adjusted-OPTIMIZE-HF risk score and LOS using logistic regression, receiver operating characteristic (ROC) curves, and subgroup analyses. Results: A total of 4,481 people [61.6% male, median age 71 years (interquartile range, 16 years)] were included in this study. In univariate regression analyses, numerous variables were significantly different between the long and short LOS groups. Multivariate logistic regression showed that the adjusted-OPTIMIZE-HF risk score had a significant predictive ability for LOS (OR 1.248, 95% CI: 1.094–1.424), P=0.001). The results of the ROC curve analysis [area under the curve (AUC) 0.583, 95% CI: 0.567–0.600] demonstrated the potential value of the risk score for predicting LOS. Finally, subgroup analyses showed that the risk score was not only predictive of LOS in the overall population, but also in subgroups of patients defined by gender, history of smoking, history of drinking, presence of hypertension, and diabetes. Conclusions: The adjusted-OPTIMIZE-HF risk model performed well in predicting LOS greater than 6 days in the Chinese patients with ADHF. Moreover, the model proved to be stable across subgroup analyses.