Construction of column line graph prediction model for risk of cognitive dysfunction after intervention in patients with ischemic cerebrovascular disease
Objective To analyze the risk factors for the occurrence of cognitive dysfunction in patients with ischemic ce-rebrovascular disease after intervention and construct a columnar graph prediction model to provide reference for early clinical prediction and management.Methods One hundred and twenty-five patients with ischemic cerebrovascular disease who received interventional treatment in our hospital from March 2020 to May 2022 were selected for the study,and were divided into 70 cases in the occurrence group and 55 cases in the non-occurrence group based on whether cognitive dysfunction occurred 6 months after the procedure.Logistic regression model was used to analyze the factors in-fluencing the occurrence of cognitive dysfunction after the intervention,and a prediction model was drawn with a line graph.The discrimination,calibration,and Hosmer-Lemeshow goodness-of-fit tests were used to validate the pre-diction model.Results The incidence of cognitive dysfunction after intervention in 125 patients with ischemic cerebro-vascular disease was 56.00％;The presence of hypertension,diabetes mellitus,coronary artery disease,hyperlipi-demia,carotid stenosis,no physical activity,amyloid β-42(Aβ42)≤16.46 pg/mL,carotid intima-media thick-ness(CIMT)＞1.11 mm,and Tau protein＞18.12 pg/mL were risk factors for the development of cognitive dysfunc-tion after intervention(P＜0.05);The consistency index(C-index),Discrimination,and Calibration of the columnar graph prediction model to predict the development of cognitive dysfunction were 0.934,0.718,and 0.822,respective-ly;the Hosmer-Lemeshow goodness-of-fit test=0.635,P=0.422.Conclusion Hypertension,diabetes,physical exercise,coronary artery disease,hyperlipidemia,carotid stenosis,CIMT,Aβ42,and Tau protein are the influencing factors of cognitive dysfunction after intervention in patients with ischemic cerebrovascular disease.Based on the above influencing factors,a column line graph prediction model was constructed,which has certain predictive value and can be used as an auxiliary tool for clinicians to predict the occurrence of cognitive dysfunction after intervention and guide early clinical intervention.
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