Construction of a risk prediction model of mild cognitive impairment in hospitalized patients with hypertension

Objective To explore the risk factors of mild cognitive impairment in hospitalized patients with hypertension, and establish a risk prediction nomogram model. Methods A total of 182 patients with hypertension admitted in our hospital from May to November 2021 were enrolled in this study. They were s...

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Bibliographic Details
Main Authors: WANG Li, ZHOU Lian, YANG Yanni
Format: Article
Language:zho
Published: Editorial Office of Journal of Third Military Medical University 2022-04-01
Series:Di-san junyi daxue xuebao
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Online Access:http://aammt.tmmu.edu.cn/Upload/rhtml/202111189.htm
Description
Summary:Objective To explore the risk factors of mild cognitive impairment in hospitalized patients with hypertension, and establish a risk prediction nomogram model. Methods A total of 182 patients with hypertension admitted in our hospital from May to November 2021 were enrolled in this study. They were surveyed with information questionnaire, Mini-Mental State Examination, Beijing version of Montreal Cognitive Assessment, Coping and Adaptation Processing Scale, Self-Rating Depression Scale and Therapeutic Adherence Scale. Logistic regression stepwise analysis was used to screen the independent risk factors of mild cognitive impairment, and the risk prediction nomogram model was established. Results The prevalence rate of mild cognitive impairment in hospitalized hypertensive patients was 68.1%. Based on the results of logistic regression analysis, 5 risk factors including age (OR=1.053), diabetes (OR=2.359), daily life management (OR=0.926), years of education (OR=0.776), and coping and adaptation (OR=0.947) were finally included to construct a risk prediction model. The calibration curve indicated that the model possessed good accuracy. The area under the curve was 0.844 (95%CI: 0.783~0.893), indicating that the model possessed good discrimination. Conclusion Based on the risk factors of mild cognitive impairment in hospitalized hypertensive patients, our established risk prediction model has good consistency and prediction efficiency.
ISSN:1000-5404