Study on risk assessment model of post-stroke dementia based on serum biomarkers

LI Xiao-xing; JIAO Bing; FANG Hua; LI Kun-bin; YAO Xian-li; WU Zhi-yuan; SUN Ping-ge; WANG Liu-xiang

doi:10.13820/j.cnki.gdyx.20232234

Abstract：Objective To develop a risk assessment model for post-stroke dementia(PSD)based on serum bio-markers.Methods This was a longitudinal predictive model development study conducted in the Neurorehabilitation De-partment from October 2020 to October 2022.Laboratory test results were obtained from peripheral venous blood samples collected within one day of patient admission.Post-stroke cognitive impairment(PSCI)was defined as a Montreal Cogni-tive Assessment(MoCA)score of＜22 at 6 months after stroke onset.A logistic model was generated using multivariate logistic regression.Results Among the 114 individuals who completed follow-up,61 subjects(53.5％)were identi-fied as having PSCI.The PSCI(MoCA＜22)group and the non-PSCI(MoCA ≥22)group showed significant differ-ences in age,gender,education level,hypertension,NIHSS score,Fazekas score,ICAS≥50％,cortical infarction,uric acid,homocysteine(Hcy),matrix metalloproteinase-9(MMP-9),tissue inhibitor of metalloproteinase-1(TIMP-1),neutrophil-to-lymphocyte ratio(NLR),and lymphocyte-to-monocyte ratio(LMR)(P＜0.05),which were included in the initial regression model.In the binary logistic regression model(LR method),seven potential predictor variables were considered for model development:age,Fazekas score,cortical infarction,MMP-9,TIMP-1,NLR,and LMR.The area under the receiver operating characteristic(ROC)curve(AUC)of the developed model was 0.837,with a sensitivity of 71.2％and specificity of 84.5％.The calibration curve of the PSCI prediction probability nomogram for ischemic stroke patients demonstrated good consistency in this cohort.The estimated AUC from 1 000 bootstrap samples was 0.814,indicating that the model had good discrimination ability.Conclusion This study established an easy-to-use nomogram model for predicting cognitive impairment after ischemic stroke.