Influencing factors of memory impairment in elderly stroke patients and construction of prediction model
10.3760/cma.j.issn.0254-9026.2024.09.011
- VernacularTitle:脑卒中老年患者记忆障碍的影响因素及其预测模型构建
- Author:
Xiao FEI
1
;
Xiaoxia GAO
;
Jianan ZHANG
;
Xiaoping YUN
;
Zejia HE
;
Yu ZHANG
;
Jing GUO
;
Fan XIE
;
Yi ZHANG
Author Information
1. 常州市第一人民医院康复医学科，常州 213003
- Keywords:
Stroke;
Memory disorders;
Mini-mental state examination
- From:
Chinese Journal of Geriatrics
2024;43(9):1149-1154
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To examine the factors that contribute to memory impairment in elderly stroke patients and develop a predictive model.Methods:One hundred stroke patients from the First People's Hospital of Changzhou were selected to assess the incidence of memory impairment using the Montreal cognitive assessment memory index score(MoCA-MIS).Univariate analysis and multivariate Logistic regression were performed to determine the factors influencing memory impairment in these patients.Additionally, the correlation among relevant scale scores was examined, and a prediction model was developed.Results:In the study, 49 patients(49.0%)did not exhibit memory impairment.Patients with memory impairment were found to have higher proportions of individuals over 75 years old, elevated levels of triglyceride(TG), total cholesterol(TC), low-density lipoproteins cholesterol(LDL-C), and National Institute of Health Stroke Scale(NIHSS)scores compared to those without memory impairment.Conversely, patients without memory impairment had higher proportions of individuals with more than 9 years of education, higher levels of high-density lipoprotein cholesterol(HDL-C), mini-mental state examination(MMSE)scores, Rivermead behavioural memory test-Ⅱ(RBMT-Ⅱ)scores, and picture-based memory impairment screen(PMIS)scores(all P<0.05).Furthermore, Montreal cognitive assessment-memory index(MoCA-MIS)scores in stroke patients with memory impairment showed negative correlations with NIHSS scores, TG, and LDL-C, while showing positive correlations with HDL-C, MMSE scores, RBMT-Ⅱ scores, and PMIS scores(all P<0.05).Multifactorial Logistic regression analysis indicated that years of education, TG, HDL-C, NIHSS score, MMSE score, RBMT-Ⅱ score, PMIS score, and the location of the lesion in the cortex or temporal lobe were significant factors influencing memory impairment in stroke patients(all P<0.05).The receiver operating characteristic curve(ROC)analysis revealed an area under curve(AUC)of 0.955(95% CI: 0.921-0.977)for the prediction model of memory impairment in stroke patients, with a Yoden index of 0.841. Conclusions:The risk of memory impairment in stroke patients is associated with education years and blood lipid levels.Factors such as high education level, active cognitive function, and memory training serve as protective factors against memory impairment.The prediction model developed using these influencing factors demonstrates high predictive accuracy for post-stroke memory impairment.
