脑小血管病患者认知障碍影响因素分析及列线图模型的构建与验证

doi:10.3969/j.issn.1673-5765.2024.10.005

摘要/Abstract

摘要： 目的分析影响脑小血管病患者发生认知障碍的因素。
方法回顾性选取（系统抽样）沧州市中心医院2020年1月—2022年5月收治的脑小血管病患者作为建模组，根据是否发生认知障碍分为无认知障碍组和认知障碍组。多因素logistic回归模型分析脑小血管病患者发生认知障碍的因素，于R3.6.3中构建预测脑小血管病认知障碍的列线图模型。另以建模组∶验证组=7∶3的方案收集2022年5月—2023年5月收治的脑小血管病患者为验证组，对构建的模型进行外部验证；绘制ROC曲线评价列线图模型在脑小血管病认知障碍风险评估中的区分度。
结果本研究共纳入247例患者，建模组173例，验证组74例；建模组中61例（35.26%）存在认知障碍，验证组中24例（32.43%）存在认知障碍。多因素分析显示，CRP水平较高（OR 1.527，95%CI 1.271～1.834，P＜0.001）、高血压（OR 2.106，95%CI 1.044～4.248，P=0.037）、颈动脉粥样硬化（OR 3.917，95%CI 1.416～10.833，P=0.009）、高同型半胱氨酸血症（OR 3.220，95%CI 1.261～8.226，P=0.015）、脑白质损伤病变程度（OR 2.862，95%CI 1.496～5.475，P=0.001）是脑小血管病患者发生认知障碍的危险因素。ROC的AUC为0.834（95%CI 0.791～0.902，P＜0.001），提示列线图预测模型的区分度较好；校准曲线斜率≈1（χ²=4.388、P=0.820），提示列线图模型拟合效度较好。外部验证结果显示，ROC的AUC为0.845（95%CI 0.802～0.911，P＜0.001），校准曲线斜率接近1，拟合效度较好（χ²=6.042，P=0.302）。
结论 CRP、高血压、颈动脉粥样硬化、高同型半胱氨酸血症、脑白质损伤病变程度均可能导致脑小血管病患者发生认知障碍，基于以上指标构建的预测脑小血管病患者认知障碍发生风险的列线图模型具有较好的区分度和一致性。

文章导读： 本研究基于CRP水平、高血压、颈动脉粥样硬化、高同型半胱氨酸血症和脑白质损伤病变程度构建的预测脑小血管病患者认知障碍发生的列线图模型具有较高的区分度，可作为临床制定个体化预测的有效工具，为制定个体化防治措施提供指导。

关键词: 脑小血管病; 认知障碍; 影响因素; 列线图模型

Abstract: Objective To analyze the factors influencing cognitive impairment in patients with cerebral small vessel disease.
Methods Patients with cerebral small vessel disease admitted to Cangzhou Central Hospital from January 2020 to May 2022 were retrospectively selected (systematic sampling) as the modeling group, and divided into the non-cognitive impairment group and the cognitive impairment group according to the occurrence of cognitive impairment. Multivariate logistic regression model was used to analyze the influencing factors of cognitive impairment in patients with cerebral small vessel disease. A nomogram model was constructed in R3.6.3 to predict cognitive impairment in cerebral small vessel disease. In addition, patients with cerebral small vessel disease admitted from May 2022 to May 2023 were collected as the validation group. The radio of the modeling group to the validation group is 7∶3. This validation group was used for external validation of the constructed model. The ROC curve was developed to evaluate the discrimination of the nomogram model in assessing cognitive impairment in cerebral small vessel disease.
Results A total of 247 patients were included in this study, including 173 in the modeling group and 74 in the validation group. In the modeling group, 61 cases (35.26%) had cognitive impairment, while in the validation group, 24 cases (32.43%) had cognitive impairment. Multivariate analysis showed that high levels of CRP (OR 1.527, 95%CI 1.271-1.834, P＜0.001), hypertension (OR 2.106, 95%CI 1.044-4.248, P=0.037), carotid atherosclerosis (OR 3.917, 95%CI 1.416-10.833, P=0.009), hyperhomocysteinemia (OR 3.220, 95%CI 1.261-8.226, P=0.015), and the degree of white matter lesion (OR 2.862, 95%CI 1.496-5.475, P=0.001) were the risk factors for cognitive impairment in patients with cerebral small vessel disease. The AUC of ROC was 0.834 (95%CI 0.791-0.902, P<0.001), indicating that the discrimination of the nomogram model was good. The calibration curve slope was approximately 1 (χ²=4.388, P=0.820), indicating that the fitting degree of the nomogram model was good. External validation results showed that the AUC of ROC was 0.845 (95%CI 0.802-0.911, P<0.001), the slope of calibration curve was close to 1, and the fitting degree was good (χ²=6.042, P=0.302).
Conclusions CRP, hypertension, carotid atherosclerosis, hyperhomocysteinemia, and the degree of white matter lesion may all lead to cognitive impairment in patients with cerebral small vessel disease. The nomogram model constructed with these indicators to predict the risk of cognitive impairment in patients with cerebral small vessel disease has good discrimination and consistency.

Key words: Cerebral small vessel disease; Cognitive impairment; Influencing factor; Nomogram model

中图分类号:

代杰, 张素响, 赵沙沙, 张晓凤. 脑小血管病患者认知障碍影响因素分析及列线图模型的构建与验证[J]. 中国卒中杂志, 2024, 19(10): 1136-1142.

DAI Jie, ZHANG Suxiang, ZHAO Shasha, ZHANG Xiaofeng. Analysis of Influencing Factors of Cognitive Impairment in Patients with Cerebral Small Vessel Disease and Construction and Validation of a Nomogram Model[J]. Chinese Journal of Stroke, 2024, 19(10): 1136-1142.

参考文献

[1] VAN VELUW S J，ARFANAKIS K，SCHNEIDER J A. Neuropathology of vascular brain health：insights from ex vivo magnetic resonance imaging-histopathology studies in cerebral small vessel disease[J]. Stroke，2022，53（2）：404-415.
[2] ZHANG C T，CHENG H L，CHEN K L，et al. Progress on prevention and treatment of cerebral small vascular disease using integrative medicine[J]. Chin J Integr Med，2023，29（2）：186-191.
[3] 马春丽，王以宁，张本卓. 脑小血管病的临床队列研究及其相关因素分析[J]. 中国现代医生，2021，59（9）：60-63.
MM C L，WANG Y Y，ZHANG B Z. Clinical cohort research of cerebral small vessel disease and analysis on its related factors[J]. China Modern Doctor，2021，59（9）：60-63.
[4] GEORGAKIS M K，FANG R，DÜRING M，et al. Cerebral small vessel disease burden and cognitive and functional outcomes after stroke：a multicenter prospective cohort study[J]. Alzheimers Dement，2023，19（4）：1152-1163.
[5] ELYAS S，ADINGUPU D，AIZAWA K，et al. Cerebral small vessel disease，systemic vascular characteristics and potential therapeutic targets[J]. Aging（Albany NY），2021，13（18）：22030-22039.
[6] ZANON ZOTIN M C，SVEIKATA L，VISWANATHAN A，et al. Cerebral small vessel disease and vascular cognitive impairment：from diagnosis to management[J]. Curr Opin Neurol，2021，34（2）：246-257.
[7] 中华医学会神经病学分会，中华医学会神经病学分会脑血管病学组. 中国脑小血管病诊治共识[J]. 中华神经科杂志，2015，48（10）：838-844.
Chinese Society of Neurology，Chinese Stroke Society. Consensus on diagnosis and treatment of small cerebral vascular diseases in China[J]. Chinese Journal of Neurology，2015，48（10）：838-844.
[8] 中华医学会老年医学分会老年神经病学组，脑小血管病认知功能障碍诊疗指南中国撰写专家组. 脑小血管病相关认知功能障碍中国诊疗指南（2019）[J]. 中华老年医学杂志，2019，38（4）：345-354.
Chinese Medical Association Geriatric Medicine Branch Geriatric Neurology Group，Writing Group of Clinical Practice Guideline for Cognitive Impairment of Cerebral Small Vessel Disease. Clinical practice guideline for cognitive impairment of cerebral small vessel disease of China（2019）[J]. Chinese Journal of Geriatrics，2019，38（4）：345-354.
[9] PINTO T C C，MACHADO L，BULGACOV T M，et al. Is the montreal cognitive assessment（MoCA）screening superior to the mini-mental state examination（MMSE）in the detection of mild cognitive impairment（MCI）and Alzheimer’s disease（AD）in the elderly[J]. Int Psychogeriatr，2019，31（4）：491-504.
[10] PASI M，SUGITA L，XIONG L，et al. Association of cerebral small vessel disease and cognitive decline after intracerebral hemorrhage[J/OL]. Neurology，2021，96（2）：e182-e192[2023-11-01]. https://doi.org/10.1212/WNL.0000000000011050.
[11] 王俊荣. 脑小血管病患者认知与情感障碍的相关性及影响因素分析[D]. 济南：山东大学，2020.
WANG J R. Analysis of the correlation between cognition and affective disorders in patients with cerebral small vessel disease and the influencing factors[D]. Jinan：Shandong University，2020.
[12] NANNONI S，OHLMEIER L，BROWN R B，et al. Cognitive impact of cerebral microbleeds in patients with symptomatic small vessel disease[J]. Int J Stroke，2022，17（4）：415-424.
[13] 吴睿，甄娜，王欣丽，等. 老年脑小血管病患者认知障碍发生率及影响因素分析[J]. 中国神经免疫学和神经病学杂志，2022，29（2）：89-92，97.
WU R，ZHEN N，WANG X L，et al. Analysis of incidence and influencing factors of cognitive impairment in elderly patients with cerebral small vessel disease[J]. Chinese J Neuroimmunol ＆ Neurol，2022，29（2）：89-92，97.
[14] 修丽娜. 脑小血管病认知功能障碍的临床预测模型建立及风险评估[D]. 大连：大连医科大学，2022.
XIU L N. Establishment of clinical predictive model and risk assessment of cognitive impairment in small cerebral vascular disease[D]. Dalian：Dalian Medical University，2022.
[15] MYSERLIS E P，ANDERSON C D，GEORGAKIS M K. Genetically proxied CRP（C-reactive protein）levels and lobar intracerebral hemorrhage risk
[J/OL]. Stroke，2023，54（4）：e130-e132[2023-11-01]. https://doi.org/10.1161/STROKEAHA.122.041889.
[16] LOW A，MAK E，ROWE J B，et al. Inflammation and cerebral small vessel disease：a systematic review[J/OL]. Ageing Res Rev，2019，53：100916[2023-11-01]. https://doi.org/10.1016/j.
arr.2019.100916.
[17] WEBB A J S，WERRING D J. New insights into cerebrovascular pathophysiology and hypertension[J]. Stroke，2022，53（4）：1054-1064.
[18] MILLS K T，STEFANESCU A，HE J. The global epidemiology of hypertension[J]. Nat Rev Nephrol，2020，16（4）：223-237.
[19] TABARES-GUEVARA J H，VILLA-PULGARIN J A，HERNANDEZ J C. Atherosclerosis：immunopathogenesis and strategies for immunotherapy[J]. Immunotherapy，2021，13（14）：1231-1244.
[20] CLARK L R，KOSCIK R L，ALLISON S L，et al. Hypertension and obesity moderate the relationship between β-amyloid and cognitive decline in midlife[J]. Alzheimers Dement，2019，15（3）：418-428.
[21] GUÉANT J L，GUÉANT-RODRIGUEZ R M，OUSSALAH A，et al. Hyperhomocysteinemia in cardiovascular diseases：revisiting observational studies and clinical trials[J]. Thromb Haemost，2023，123（3）：270-282.
[22] 曹倩，苏牟潇，魏继鸿，等. 基于随机森林算法的脑小血管病伴轻度认知障碍的诊断模型研究[J]. 精神医学杂志，2022，35（4）：365-369.
CAO Q，SU M X，WEI J H，et al. A study on diagnostic model of cerebral small vessel disease with mild cognitive impairment based on random forest algorithm[J]. Journal of Psychiatry，2022，35（4）：365-369.