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中华脑科疾病与康复杂志(电子版) ›› 2023, Vol. 13 ›› Issue (03) : 156 -161. doi: 10.3877/cma.j.issn.2095-123X.2023.03.005

临床研究

基于影响因素的老年阿尔茨海默病认知功能障碍预测模型构建及电子化认知康复训练的应用价值
郭翃江, 符雪彩, 朱妍妍, 严之红, 王丽娜, 纪红()   
  1. 100040 北京,航天中心医院老年医学二科
  • 收稿日期:2022-06-08 出版日期:2023-06-15
  • 通信作者: 纪红

Construction of predictive model for cognitive impairment in elderly patients with Alzheimer's disease based on influencing factors and application value of electronic cognitive rehabilitation training

Hongjiang Guo, Xuecai Fu, Yanyan Zhu, Zhihong Yan, Lina Wang, Hong Ji()   

  1. Second Department of Geriatrics, Aerospace Center Hospital, Beijing 100040, China
  • Received:2022-06-08 Published:2023-06-15
  • Corresponding author: Hong Ji
  • Supported by:
    Medical and Health Research Project of China Aerospace Science and Industry Corporation Limited(2019-LCYL-012)
引用本文:

郭翃江, 符雪彩, 朱妍妍, 严之红, 王丽娜, 纪红. 基于影响因素的老年阿尔茨海默病认知功能障碍预测模型构建及电子化认知康复训练的应用价值[J]. 中华脑科疾病与康复杂志(电子版), 2023, 13(03): 156-161.

Hongjiang Guo, Xuecai Fu, Yanyan Zhu, Zhihong Yan, Lina Wang, Hong Ji. Construction of predictive model for cognitive impairment in elderly patients with Alzheimer's disease based on influencing factors and application value of electronic cognitive rehabilitation training[J]. Chinese Journal of Brain Diseases and Rehabilitation(Electronic Edition), 2023, 13(03): 156-161.

目的

探讨基于影响因素的老年阿尔茨海默病(AD)认知功能障碍预测模型的构建及电子化认知康复训练的应用价值。

方法

选择航天中心医院老年医学二科自2019年1月至2020年1月收治的102例老年AD认知功能障碍患者作为观察组,根据治疗方式的不同分为2个亚组,常规认知干预组(51例)和电子化认知康复训练组(51例)。选择同期50例诊断正常的老年人作为对照组。采用单因素和Logistic回归分析构建基于影响因素的老年AD认知功能障碍的预测模型。采用蒙特利尔认知评估量表(MoCA)、日常生活活动能力量表(ADL)评估所有患者的认知功能和日常生活能力。

结果

观察组和对照组在年龄、职业状况、高脂血症占比、服用阿司匹林占比方面比较,差异具有统计学意义(P<0.05);Logistic回归分析结果显示,脑力劳动是老年AD认知功能障碍的危险因素(OR=0.348,P<0.05);采用ROC曲线评价老年AD认知功能障碍预测模型,灵敏度为95.06%,特异度为92.01%,曲线下面积为0.908(95%CI:0.879~1.000)。2组患者干预后MoCA评分均高于干预前,且电子化认知康复训练组高于常规认知干预组,差异具有统计学意义(P<0.05)。2组患者干预后ADL评分均低于干预前,且电子化认知康复训练组低于常规认知干预组,差异具有统计学意义(P<0.05)。

结论

预测模型显示,职业状况是老年AD认知功能障碍的影响因素,其中脑力劳动是老年AD认知功能障碍的一个危险因素,电子化认知康复训练可改善老年AD认知功能障碍患者的认知功能及提高其日常活动能力。

Objective

To explore the construction of a predictive model for cognitive impairment in elderly patients with Alzheimer's disease (AD) based on influencing factors and the application value of electronic cognitive rehabilitation training.

Methods

A total of 102 elderly patients with AD cognitive dysfunction admitted to the Second Department of Geriatrics of Aerospace Center Hospital from January 2019 to January 2020 were selected as the observation group, which were divided into two subgroups according to different treatment methods, including conventional cognitive intervention group (51 cases) and electronic cognitive rehabilitation training group (51 cases). The 50 elderly patients with normal diagnosis in the same period were selected as the control group. Univariate Logistic regression analysis was used to construct a predictive model of cognitive dysfunction in aged AD based on protective factors. Cognitive function and daily living performance were assessed using the Montreal cognitive assessment scale (MoCA) and the activities of daily living (ADL) scale.

Results

The differences between observation and control groups were statistically significant in age, occupational status, proportion of hyperlipidemia and proportion of aspirin (P<0.05); Logistic regression analysis showed that mental work was a risk factor for cognitive dysfunction in aged AD (OR=0.348, P<0.05); The ROC curve was used to evaluate the predictive model of cognitive dysfunction in elderly AD, with a sensitivity of 95.06%, a specificity of 92.01%, and a area under the curve of 0.908 (95%CI: 0.879-1.000). The MoCA scores of both groups of patients after intervention were higher than before intervention, and that of the electronic cognitive rehabilitation training group was higher than that of the conventional cognitive intervention group, with a statistically significant difference (P<0.05). The ADL scores of the patients in the 2 groups were lower than those before the intervention, and the electronic cognitive rehabilitation training group was lower than the conventional cognitive intervention group, and the differences were statistically significant (P<0.05).

Conclusion

The prediction model shows that occupational status is the influencing factor of cognitive dysfunction in elderly AD, and mental work is a risk factor of AD in the elderly. Electronic cognitive rehabilitation training can improve the cognitive function and daily activity ability of elderly patients with cognitive dysfunction.

表1 老年阿尔茨海默病患者认知功能障碍的单因素分析[例(%)]
Tab.1 Univariate analysis of cognitive dysfunction in elderly Alzheimer's disease [n(%)]
表2 老年阿尔茨海默病认知功能障碍影响因素的Logistic回归分析
Tab.2 Logistic regression analysis of risk factors for cognitive dysfunction in elderly Alzheimer's disease
图1 老年阿尔茨海默病认知功能障碍预测模型的ROC曲线
Fig.1 ROC curves of the prediction model of cognitive dysfunction in elderly Alzheimer's disease
表3 常规认知干预组和电子化认知康复训练组干预前后MoCA评分比较(分,Mean±SD)
Tab.3 Comparison of MoCA scores before and after intervention between conventional cognitive intervention group and lectronic cognitive rehabilitation training group (score, Mean±SD)
表4 常规认知干预组和电子化认知康复训练组干预前后ADL评分比较(分,Mean±SD)
Tab.4 Comparison of ADL scores before and after intervention between conventional cognitive intervention group and lectronic cognitive rehabilitation training group (score, Mean±SD)
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