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预防医学  2023, Vol. 35 Issue (12): 1037-1042    DOI: 10.19485/j.cnki.issn2096-5087.2023.12.006
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老年2型糖尿病患者认知衰弱风险预测研究
王晓薇, 许艳岚
复旦大学附属中山医院青浦分院老年科,上海 201700
Prediction of cognitive decline among elderly patients with type 2 diabetes mellitus
WANG Xiaowei, XU Yanlan
Department of Geriatric Medicine, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai 201700, China
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摘要 目的 预测老年2型糖尿病(T2DM)患者认知衰弱的发生风险, 为老年T2DM患者认知衰弱的早期发现提供依据。方法 以复旦大学附属中山医院青浦分院住院治疗的 ≥ 60岁T2DM患者为研究对象, 通过问卷调查收集人口学信息和营养状况等资料; 采用衰弱表型量表、蒙特利尔认知评估量表和临床痴呆评估量表评估认知衰弱情况; 采用多因素logistic回归模型分析认知衰弱的影响因素; 建立列线图, 并采用Bootstrap自抽样法和受试者操作特征曲线评价预测效果。结果 发放问卷270份, 回收有效问卷262份, 问卷有效率为97.04%。调查男性137例, 占52.29%; 60~ < 70岁为主, 146例占55.73%; 已婚179例, 占68.32%; 检出认知衰弱85例, 占32.44%。多因素logistic回归分析结果显示, 性别(女, OR=3.118)、年龄(70~ < 80岁, OR=3.218; ≥ 80岁, OR=3.058)、文化程度(高中或中专, OR=0.335; 大专, OR=0.130; 本科及以上, OR=0.300)、规律运动(OR=0.083)、记忆力(降低, OR=29.723)、营养状况(存在营养不良风险, OR=16.307; 营养不良, OR=39.469)、日常生活活动能力(降低, OR=6.804)和抑郁症状(OR=8.609)是老年T2DM患者认知衰弱的影响因素(均P < 0.05)。构建的列线图模型拟合度、预测能力较好。结论 通过性别、年龄、文化程度、规律运动、记忆力、营养状况、日常生活活动能力和抑郁症状8个因素构建的列线图可用于预测老年T2DM患者认知衰弱风险。
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关键词 老年人2型糖尿病认知衰弱影响因素列线图    
AbstractObjective To predict the risk of cognitive decline among elderly patients with type 2 diabetes mellitus (T2DM), so as to provide insights into the early identification of cognitive decline in elderly patients with T2DM. Methods The elderly patients with T2DM hospitalized in the Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University were selected as subjects. General information was collected by a questionnaire survey, including demographics and nutritional status, and cognitive decline was assessed using the frailty Phenotype Scale, the Montreal Cognitive Assessment and the Clinical Dementia Rating. Multivariable logistic regression model was used to analyze the influencing factors of cognitive decline among elderly patients with T2DM. A nomogram was established, and was verified with Bootstrap resampling method and receiver operation characteristic curve. Results A total of 270 questionnaires were sent out and 262 valid questionnaires were collected, with an effective rate of 97.04%. There were 137 males (52.29%), 146 patients at ages of 60 to 69 years (55.73%), 179 married patients (68.32%), and 85 patients with cognitive decline (32.44%). Multivariable logistic regression analysis identified gender (female, OR=3.118), age (70 to 79 years, OR=3.218; 80 years and older, OR=3.058), educational level (high school or technical secondary school, OR=0.335; junior college, OR=0.130; college and above, OR=0.300), regular exercise (OR=0.083), memory (decreased, OR=29.723), nutritional status (risk of malnutrition, OR=16.307; malnutrition, OR=39.469), activity of daily living (decreased, OR=6.804) and depressive symptoms (OR=8.609) as factors affecting cognitive decline among elderly patients with T2DM (all P<0.05). The nomogram based on the above factors fit well and indicated strong predictive ability. Conclusion Gender, age, educational level, regular exercise, memory, nutritional status, activity of daily living and depressive symptoms can effectively predict the risk of cognitive decline among elderly patients with T2DM.
Key wordselderly    type 2 diabetes mellitus    cognitive decline    influencing factor    nomogram
收稿日期: 2023-07-24      修回日期: 2023-10-19     
中图分类号:  R587.1  
基金资助:上海市卫生健康委员会科研辅助项目(201840069)
作者简介: 王晓薇,本科,主任医师,主要从事老年糖尿病肾病治疗工作
引用本文:   
王晓薇, 许艳岚. 老年2型糖尿病患者认知衰弱风险预测研究[J]. 预防医学, 2023, 35(12): 1037-1042.
WANG Xiaowei, XU Yanlan. Prediction of cognitive decline among elderly patients with type 2 diabetes mellitus. Preventive Medicine, 2023, 35(12): 1037-1042.
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http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2023.12.006      或      http://www.zjyfyxzz.com/CN/Y2023/V35/I12/1037
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