Construction And Validation Of Nomogram Model For Predicting The Risk Of Ischemic Stroke In Patients With Carotid Artery Stenosis

Objective: To construct a line graph model for predicting the risk of ischaemic stroke in patients with internal carotid artery stenosis and to validate its predictive power internally.Methods: 407 patients with internal carotid artery stenosis admitted to the Neurosurgery Centre of the First Affiliated Hospital of Xinjiang Medical University from January 2020 to January 2023 were collected,and clinical data including haematological indicators and imaging findings were collected from patients after admission,followed by single-factor and multi-factor logistic regression analysis to explore the influencing factors of ischaemic stroke in patients with carotid artery stenosis,and the R 3.5.3 software and the rms package were used to construct the column line graph model.A calibration curve and ROC curve were used to assess the predictive power of the columnar graph model.Results: A total of 407 patients were included and divided into a stroke group(n=200)and a non-stroke group(n=207)according to the occurrence of ischaemic stroke.200 patients had an ischaemic stroke,with an incidence of 49.1%.Univariate logistic regression analysis showed that age,ipsilateral reduced cerebral perfusion,high carotid plaque grade,total cholesterol,HDL,and homocysteinemia were independent risk factors for ischaemic stroke in patients with internal carotid artery stenosis(p<0.1).In contrast,multifactorial logistic regression analysis showed that age,ipsilateral presence of reduced cerebral perfusion,high carotid plaque classification,total cholesterol,and hyperhomocysteinemia were independent risk factors for ischaemic stroke in patients with internal carotid artery stenosis(P < 0.05).Internal validation of this line plot model by repeated sampling of the original data 1000 times showed that the calibration curve converged to the ideal curve.Based on ROC curve analysis,the area under the curve(AUC)for the model to predict ischaemic stroke in patients with internal carotid artery stenosis was 0.846 [95% CI(0.810,0.882)].Conclusion: Clinical work should pay attention to patients with ipsilateral reduced cerebral perfusion,high carotid plaque grading,total cholesterol,and hyperhomocysteinemia with advanced internal carotid artery stenosis,who have a higher probability of ischaemic stroke.The above results show that the columnar line graph model constructed by this study is a good predictor of the risk of ischaemic stroke in patients with internal carotid artery stenosis.