大动脉粥样硬化型脑卒中早期神经功能恶化的预测模型构建OA

Objective:To investigate the risk factors for early neurological deterioration(END)in patients with acute ischemic stroke with TOAST classification of large artery atherosclerosis(LAA),and to establish a nomogram prediction model and evalu-ate it.Methods:Consecutive patients with large-artery atherosclerotic acute ischemic stroke(LAA-AIS)who were hospitalized in our hospital between October 2023 and September 2024 were included.Patients were categorized into END and non-END groups based on an increase of≥2 points in the total NIHSS score or an increase of≥1 point in the score of motor function within 7 d af-ter onset.SPSS27.0 was applied to perform univariate analysis,and binary Logistic regression analysis was used for variables with P<0.05 to screen out the independent risk factors for END in LAA-AIS patients,a nomogram prediction model was constructed.The ROC curve and its area under the curve(AUC)value were used to assess the differentiation of the model,the calibration curve was used to assess the accuracy of the model,and the decision curve analysis(DCA)was used to assess the clinical utility of the model.Results:A total of 249 patients with LAA-AIS were included,including 190(76.3％)males and 59(23.7％)fe-males,aged 63(53,73)years;62(24.9％)in the END group and 187(75.1％)in the non-END group.Univariate analysis found 6 variables to be statistically different(P<0.05),and 4 variables were screened out by including them in binary Logistic re-gression analysis:BMI(OR=1.171,95％CI 1.032 to 1.329,P=0.015),systolic blood pressure at admission(OR=1.015,95％CI 1.001 to 1.030,P=0.030),glycosylated hemoglobin(OR=1.286,95％CI 1.064 to 1.555,P=0.009),and low-density lipoprotein cholesterol(LDL-C)(OR=2.278,95％CI 1.272 to 4.079,P=0.006)were the independent risk factors for the devel-opment of END in LAA-AIS patients.A nomogram prediction model was constructed based on the above 4 factors,and internal validation was performed using the Bootstrap method to draw ROC curves,calibration curves,and DCA curves.The results showed that the AUC of the model was 0.735;the calibration plot predicted values were in good agreement with the actual values,and the DCA curve showed that the prediction model had high clinical utility.Conclusion:Elevated LDL cholesterol,systolic blood pressure on admission,BMI,and glycosylated hemoglobin levels are independent risk factors for the development of END in patients with LAA-AIS,and the column-line graphic prediction model based on them is a reliable and easy-to-use tool for pre-dicting the development of END in patients with LAA-AIS.