![]() ![]() ![]() A total of 8893 patients (median: age 81, Q1–Q3: 71–87 years old) were included, in whom 9% had 30 day mortality and 17% had 90 day mortality. Comparisons were made with decision tree and multivariable logistic regression. Variables were ranked in the order of importance with a total score of 100 and used to build the frailty models. Gradient boosting, which is a supervised sequential ensemble learning algorithm with weak prediction submodels (typically decision trees), was applied to predict mortality. ![]() Age, sex, variables in the modified frailty index, Deyo's Charlson co‐morbidity index (≥2), neutrophil‐to‐lymphocyte ratio (NLR), and prognostic nutritional index at baseline were analysed. This was a retrospective observational study that included patients admitted to nine public hospitals for heart failure from Hong Kong between 20. ![]()
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