Logistic Regression Analysis on Self-Identification Screening System of Vascular Cognitive Impairment

NAN Yinan; HUA Qian; JIN Xianglan; BAI Wen; DAI Zhong; ZHAO Jianjun; CAO Xiaolan; ZHANG Yulian; CHEN Zhiqiang; ZHANG Yunling

doi:10.13288/j.11-2166/r.2014.12.008

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Logistic Regression Analysis on Self-Identification Screening System of Vascular Cognitive Impairment

更新时间：2021-11-17

- Logistic Regression Analysis on Self-Identification Screening System of Vascular Cognitive Impairment
- Journal of Traditional Chinese Medicine Vol. 55, Issue 12, Pages: 1018-1021(2014)
- 作者机构：
  
  1. 北京中医药大学基础医学院
  2. 北京中医药大学东方医院
  3. 北京大学人民院
  4. 北京大学人民医院
  5. 长春中医药大学第一附属医院
  6. 山东中医药大学附属医院
  7. 天津中医药大学第二附属医院
  8. 河北省中医院
- 作者简介：
- 基金信息：
- DOI：10.13288/j.11-2166/r.2014.12.008
  CLC： R749.1
- Published：2014
- 稿件说明：
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[1]南一楠,华茜,金香兰,白文,戴中,赵建军,曹晓兰,张玉莲,陈志强,张允岭.血管源性认知障碍自我辨识筛查系统的Logistic回归分析[J].中医杂志,2014,55(12):1018-1021.

NAN Yinan, HUA Qian, JIN Xianglan, et al. Logistic Regression Analysis on Self-Identification Screening System of Vascular Cognitive Impairment[J]. Journal of Traditional Chinese Medicine2014, 55(12): 1018-1021.
[1]南一楠,华茜,金香兰,白文,戴中,赵建军,曹晓兰,张玉莲,陈志强,张允岭.血管源性认知障碍自我辨识筛查系统的Logistic回归分析[J].中医杂志,2014,55(12):1018-1021. DOI： 10.13288/j.11-2166/r.2014.12.008.

NAN Yinan, HUA Qian, JIN Xianglan, et al. Logistic Regression Analysis on Self-Identification Screening System of Vascular Cognitive Impairment[J]. Journal of Traditional Chinese Medicine2014, 55(12): 1018-1021. DOI： 10.13288/j.11-2166/r.2014.12.008.

摘要

目的通过血管源性认知障碍自我辨识筛查量表建立筛查数学模型

初步筛查出轻度血管源性认知障碍患者。方法收集年龄≥50岁、存在血管源性危险因素的人群共计610例

通过简易智能精神状态检查量表（MMSE）及蒙特利尔认知评估量表（MoCA）分为认知正常组和认知障碍组。调查病例的一般资料、自我辨识筛查量表资料以及MMSE、MoCA量表资料

并对其进行Logistic回归分析。结果年龄、学历、高血压病、脑血管病对认知功能影响较大。通过Logistic回归分析得到的函数总体预测结果的一致率达到66.3%

灵敏度（Sen）为79.8%

特异度（Spe）为44.3%。结论本研究建立的数学模型适用于在具有血管源性危险因素的人群中进行轻度认知障碍患者的筛查。

Abstract

Objective A mathematical model was built according to vascular cognitive impairment self-identification scale（ VCI-SIS） to preliminary screen VCI patients. Methods Totally 610 persons aged older than or equal to 50 years with vascular risk factors were collected and divided into the normal cognition group

mild VCI group and mild vascular dementia group by Mini-Mental State Examination（ MMSE） and Montreal Cognitive Assessment（ MoCA）. The general information and data of VCI-SIS

MMSE and MoCA was investigated and analyzed with Logistic regression analysis. Results Age

education

hypertension and cerebrovascular disease had a greater impact on cognitive function. The consistent percentage

sensitivity（ Sen） and specificity（ Spe） of overall predicted results of functions obtained by Logistic regression analysis was 79. 8%

44. 3% and 66. 3% respectively. Conclusion The mathematical model built in this research is applicable to screen mild cognitive impairment patients in vascular risk populations.

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