Objectives: This study examined how frailty in traditional risk-adjusted models could improve the predictability of unplanned 30-day readmission and mortality among heart failure patients. Methods: This study was a retrospective analysis of Nationwide Readmissions Database data collected during the years 2010-2018. All patients ≥65 years who had a principal diagnosis of heart failure were included in the analysis. The Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator was used to identify frail patients. Results: There was a total of 819,854 patients admitted for heart failure during the study period. Among them, 63,302 (7.7%) were frail. In the regression analysis, the risk of all-cause 30-day readmission (OR, 1.18; 95% CI, 1.14-1.22) and in-hospital mortality (OR, 1.52; 95% CI, 1.40-1.66) were higher in patients with frailty. Discussion: Inclusion of frailty in comorbidity-based risk-prediction models significantly improved the predictability of unplanned 30-day readmission and in-hospital mortality.
Keywords: frailty; hospitalization cost; in-hospital mortality; length of stay; unplanned readmission.