Construction and analysis of predictive model of symptomatic intracerebral hemorrhage in patients with acute stroke after mechanical thrombectomy

ObjectiveTo construct a predictive model of symptomatic intracerebral hemorrhage after mechanical thrombectomy in acute stroke, and explore the predictive value of this predictive model in predicting the occurrence of symptomatic intracerebral hemorrhage after mechanical thrombectomy in acute stroke.

MethodsA total of 203 stroke patients from January 2017 to December 2020 were included as the study subjects.All subjects received acute stroke mechanical thrombectomy and were followed up for 36 h.According to the occurrence of symptomatic intracerebral hemorrhage after the operation, the patients were divided into hemorrhage group and non-hemorrhage group.Clinical data were collected such as gender, age and disease history of all patients.Multivariate logistics regression analysis was used to analyze the risk factors of symptomatic intracerebral hemorrhage after mechanical thrombus removal after stroke, and a predictive model was constructed.Then the ROC curve was drawn using MedCalc to test the efficacy of the model.

ResultsA total of 47 cases were lost after the last follow-up, and 156 patients were finally included.A total of 17cases of symptomatic intracerebral hemorrhage occurred after mechanical thrombectomy in acute stroke, with an incidence rate of 10.9%.Then they were divided into hemorrhage group (17 cases) and non-hemorrhage group (139 cases).Comparing the clinical data of the two groups of patients showed that the differences between the groups were statistically significant in terms of patient age, fasting blood glucose, HbA1c, atrial fibrillation, preoperative NIHSS score, and the number of thrombectomy times (P < 0.05 to P < 0.01). Multivariate logistic regression analysis showed that fasting blood glucose, HbA1c, atrial fibrillation, NIHSS score and the number of thrombectomy were independent risk factors for symptomatic intracerebral hemorrhage after mechanical thrombectomy in acute stroke (P < 0.01). ROC curve analysis showed that the area under the curve of the prediction model was 0.920 (95%CI: 0.915-0.925), the cutoff value was 0.40, the sensitivity was 87.90%, and the specificity was 86.10%.

ConclusionsFasting blood glucose, HbA1c, atrial fibrillation, NIHSS score and the number of thrombectomy are all factors that influnce the occurrence of symptomatic intracerebral hemorrhage after mechanical thrombectomy for acute stroke.The establishment of predictive model can achieve the early warning and guide the clinical intervention measures.