Researchers developed an interpretable gradient-boosting and random-forest ensemble to predict 180-day all-cause mortality among older adults newly admitted to long-term care facilities in Taiwan, using only assessment data available at intake. In 23,901 residents admitted 2020-2023, 22.1% died within six months; in the 2024 temporal validation cohort of 6,216, 28.7% died and the model reached an AUROC of 0.90 (95% CI 0.89-0.91) with calibration weakening at the highest predicted risks. Frequent hospitalisation in the prior six months, impairment in activities of daily living and weight loss were the most influential predictors.
Why it is interesting: A prognostic model that needs no hospital record linkage, validated on a later cohort, with a background mortality rate after care-home entry that is itself notable.