Su Chien-Chou, Yu Yung-Chen, Yang Deng-Chi
Clinical Innovation and Research Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Department of Nursing, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
BMC Geriatr. 2025 Apr 26;25(1):283. doi: 10.1186/s12877-025-05931-8.
Quality of life (QOL) has been reported to be associated with sociodemographic characteristics and geriatric syndromes in older adults, but the impact of interactions among multiple geriatric syndromes on QOL remains unexplored. We aimed to apply a machine learning method to evaluate the effects of interactions among multiple geriatric syndromes on QOL in older adults.
We recruited adults aged ≥ 65 years admitted to a tertiary medical center from June 2018 to September 2018. The main outcome was the three-level five-dimensional Euro-Quality of Life tool (EQ-5D-3 L) utility value. The random forest algorithm was used to identify and rank the strongest predictors of geriatric syndromes. The relation between predictors and outcomes was visualized with accumulated local effects plots and interaction effects. Model performance was evaluated by 5-fold cross-validation with metrics of R-square, the mean square error of estimation and the mean absolute error of estimation.
The study included 160 older adults with a mean age of 79 years. The top ten features that significantly influenced the utility prediction were activities of daily living (ADL), frailty, pain, the number of medications used, age, depression, the Charlson Comorbidity Index (CCI), body mass index (BMI), peptic ulcer, and emotional loneliness. The two-way interactions between ADL, frailty, and pain significantly interacted with other predictors.
ADL, frailty, and pain are important factors to be considered when assessing QOL in older adults. It is important for clinicians to consider them together in clinical decision-making.
据报道，生活质量（QOL）与老年人的社会人口学特征和老年综合征有关，但多种老年综合征之间的相互作用对生活质量的影响仍未得到探索。我们旨在应用机器学习方法评估多种老年综合征之间的相互作用对老年人生活质量的影响。
我们招募了2018年6月至2018年9月入住三级医疗中心的65岁及以上成年人。主要结局是三级五维欧洲生活质量工具（EQ-5D-3L）效用值。随机森林算法用于识别和排名老年综合征的最强预测因素。预测因素与结局之间的关系通过累积局部效应图和交互效应进行可视化。通过5折交叉验证，以R平方、估计均方误差和估计平均绝对误差指标评估模型性能。
该研究纳入了160名老年人，平均年龄为79岁。对效用预测有显著影响的前十大特征是日常生活活动（ADL）、衰弱、疼痛、用药数量、年龄、抑郁、Charlson合并症指数（CCI）、体重指数（BMI）、消化性溃疡和情感孤独感。ADL、衰弱和疼痛之间的双向相互作用与其他预测因素有显著交互作用。
ADL、衰弱和疼痛是评估老年人生活质量时需要考虑的重要因素。临床医生在临床决策中综合考虑这些因素很重要。
