老年住院患者抑郁症状风险筛查模型的开发和验证：一项横断面研究
Development and Validation of a Risk Screening Model for Depressive Symptoms in Older Inpatients: A Cross-Sectional Study.
摘要(中文译文)
抑郁在老年人中常见，并与较高的发病率、死亡率和医疗费用相关。住院老年患者尤其易感。本研究旨在开发一种新颖、便捷且经过验证的工具，用于老年住院患者抑郁症状的初步筛查。本研究利用2023年1月至2024年12月收集的11,269例年龄≥60岁的住院老年患者的临床数据。数据来源包括病历系统、健康信息管理系统和住院心理评估量表信息系统。采用多因素logistic回归分析确定预测因素，并进一步基于这些预测因素构建列线图。使用5000次重抽样的Bootstrap法对列线图进行内部验证。采用受试者工作特征曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）评估模型性能。老年住院患者抑郁症状的患病率为28.64%。共识别出八个独立影响因素：性别、年龄、婚姻状况、收入来源、睡眠障碍、慢性疾病、疼痛和自我评价健康状况。开发集AUC为0.930，内部验证后的校正AUC为0.832。Hosmer-Lemeshow检验（P = 0.126）和校准曲线表明校准良好。DCA证实了在一系列阈值概率范围内具有临床净获益。基于简单且易于获取的临床特征，开发了一种易于使用的列线图，用于识别老年住院患者的抑郁症状，具有良好的筛查能力。该列线图可识别抑郁症状高风险的老年住院患者，可能是一种有用的临床初步筛查工具。
Abstract
Depression is common among the elderly and linked to higher morbidity, mortality, and healthcare costs. Hospitalized elderly patients are especially vulnerable. This study aimed to develop a novel, convenient, and validated tool for preliminary screening of depression symptoms in older inpatients. This study utilized clinical data from 11,269 hospitalized geriatric patients aged ≥60 years, collected from January 2023 to December 2024. Data sources included medical record systems,health information management system and inpatient psychological assessment scale information system. Multivariate logistic regression analysis was performed to determine the predictors and further construct a nomogram based on the predictors. Bootstrap with 5000 resamples was used for internal validation of nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). The prevalence of depressive symptoms in older inpatients was 28.64%. Eight independent influencing factors were identified: gender, age, marital status, income source, sleep disturbance, chronic diseases, pain, and self-rated health. The development set AUC was 0.930, and the corrected AUC after internal validation was 0.832. The Hosmer-Lemeshow test (P = 0.126) and calibration curves indicated favorable calibration. DCA confirmed clinical net benefit across a range of threshold probabilities. An easy-to-use nomogram was developed for identifying depressive symptoms in older inpatients with satisfactory screening ability based on simple and easily accessible clinical features. The nomogram can identify older inpatients at high risk for depressive symptoms and may be a useful preliminary screening tool in clinical.
如何引用
AMA
Lu Wang, Xin Zhang, Shaoping Cheng, Kaiqin Deng. Development and Validation of a Risk Screening Model for Depressive Symptoms in Older Inpatients: A Cross-Sectional Study.. Clinical interventions in aging. 2026; doi:10.2147/CIA.S599044.
APA
Lu Wang, Xin Zhang, Shaoping Cheng, Kaiqin Deng (2026). Development and Validation of a Risk Screening Model for Depressive Symptoms in Older Inpatients: A Cross-Sectional Study.. Clinical interventions in aging. https://doi.org/10.2147/CIA.S599044
GB/T 7714
Lu Wang, Xin Zhang, Shaoping Cheng, Kaiqin Deng. Development and Validation of a Risk Screening Model for Depressive Symptoms in Older Inpatients: A Cross-Sectional Study.[J]. Clinical interventions in aging, 2026 doi:10.2147/CIA.S599044.
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