ABSTRACT Aim As the aging population grows, it is crucial to evaluate the quality of surgical care considering geriatric‐specific factors and outcomes. The aim of this study was to develop and validate prediction models for mortality and morbidity in patients aged 65 and older by using a large‐scale, nationwide, real‐world dataset to enable robust and generalizable modeling and to evaluate the contribution of geriatric‐specific risk factors to the model. Methods Data from the National Clinical Database in 2021, incorporating 22 geriatric‐specific variables, was used to develop prediction models for 30‐day mortality and major complications using 70% of the dataset (development cohort), with validation on the remaining 30% (validation cohort). Results A total of 64 868 cases from gastroenterological surgeries were analyzed. In this geriatric cohort, the 30‐day mortality rate was 1.8%, and the major complication rate was 11.3%. The prediction models demonstrated strong discrimination and calibration (HL = 0.198 and c‐statistics = 0.84 for mortality, HL = 0.0003 and c‐statistics = 0.68 for morbidity). The mortality prediction model identified three significant geriatric‐specific factors as independent predictors: surrogate consent (odds ratio OR 1.91; 95% confidence interval CI 1.55–2.35), depression (OR 1.68; 95% CI 1.02–2.75), and hospitalization from outside the home (OR 1.24; 95% CI 1.01–1.54), along with age (75–79 years vs. 65–69 years, OR 1.62; 95% CI 1.20–2.19). Conclusions Incorporating geriatric‐specific factors along with age identified clinically relevant predictors of mortality and morbidity, reinforcing the importance of geriatric assessment in elderly surgical patients.
Sato et al. (2026) studied this question.