多发病老年人轻度认知障碍预测模型的开发和验证
Development and Validation of a Predictive Model for Mild Cognitive Impairment in Older Adults with Multimorbidity.
摘要(中文译文)
探讨多病共存老年人轻度认知障碍（MCI）的相关因素，并构建和验证用于早期筛查的预测模型。本横断面研究连续纳入2022年4月至2025年2月期间在中国温州医科大学附属康宁医院住院的238例多病共存老年患者。采用自行设计的一般资料问卷和蒙特利尔认知评估基础量表（MoCA-B）对参与者进行评估。根据中国专家共识诊断MCI。采用logistic回归分析识别相关因素。基于这些因素构建列线图预测模型。采用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）评价模型性能。使用外部验证队列（n=68）进一步检验模型。MCI患病率为26.81%。危险因素：年龄≥80岁（OR=3.23）、听力障碍（OR=4.04）和情绪障碍（OR=3.25）。保护因素：较高教育程度（OR=0.23）、更频繁的体育锻炼（OR=0.15）和更频繁的社交活动（OR=0.26）（均P<0.05）。AUC为0.862（训练集）和0.832（外部验证）。校准曲线显示良好的一致性，DCA表明在（10-65%）的阈值概率范围内具有净临床获益。年龄、听力障碍、情绪障碍、教育程度、体育锻炼和社交活动与多病共存老年人的MCI显著相关。该列线图具有良好的预测准确性和临床实用性，有助于早期识别和针对性预防。
Abstract
To identify factors associated with mild cognitive impairment (MCI) in older adults with multimorbidity and to develop and validate a predictive model for early screening. This cross-sectional study consecutively enrolled 238 older adult inpatients with multimorbidity at the Affiliated Kangning Hospital of Wenzhou Medical University, China, between April 2022 and February 2025. Participants were assessed using a self-designed general information questionnaire and the Montreal Cognitive Assessment Basic Scale (MoCA-B). MCI was diagnosed according to the Chinese Expert Consensus. Associated factors were identified using logistic regression analysis. A nomogram prediction model was constructed based on these factors. The model's performance was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). An external validation cohort (n=68) was used to further test the model. MCI prevalence was 26.81%. Risk factors: age ≥80 years (OR=3.23), hearing impairment (OR=4.04), and emotional disorders (OR=3.25). Protective factors: higher education (OR=0.23), more frequent physical exercise (OR=0.15), and more frequent social activities (OR=0.26) (all P<0.05). The AUC was 0.862 (training) and 0.832 (external validation). Calibration curves showed good agreement, and DCA indicated net clinical benefit across threshold probabilities of (10-65%). Age, hearing impairment, emotional disorders, education, physical exercise, and social activities are significantly associated with MCI in older adults with multimorbidity. The nomogram demonstrates good predictive accuracy and clinical utility, aiding early identification and targeted prevention.
如何引用
AMA
Lili Shao, Ruyi Zhang, Yinqing Huang, Xiaochun Dai. Development and Validation of a Predictive Model for Mild Cognitive Impairment in Older Adults with Multimorbidity.. Clinical interventions in aging. 2026; doi:10.2147/CIA.S608488.
APA
Lili Shao, Ruyi Zhang, Yinqing Huang, Xiaochun Dai (2026). Development and Validation of a Predictive Model for Mild Cognitive Impairment in Older Adults with Multimorbidity.. Clinical interventions in aging. https://doi.org/10.2147/CIA.S608488
GB/T 7714
Lili Shao, Ruyi Zhang, Yinqing Huang, Xiaochun Dai. Development and Validation of a Predictive Model for Mild Cognitive Impairment in Older Adults with Multimorbidity.[J]. Clinical interventions in aging, 2026 doi:10.2147/CIA.S608488.
在 PubMed增强版 阅读全文
翻译全文 · AI 文献问答 · PDF 原文下载 · 引用导出