Establishment of the prediction models of malignant brain edema after vascular recanalization in anterior circulation acute large vascular occlusion stroke / 国际外科学杂志

ABSTRACT

Objective:Based on Logistic regression and XGBoost algorithm, the prediction model of malignant brain edema (MBE) after vascular recanalization of anterior circulation acute great vessel occlusive stroke (ALVOS) was constructed, and the prediction performance was compared.Methods:A retrospective selection of 382 patients with anterior circulation ALVOS who underwent early endovascular treatment (EVT) in our hospital from March 2014 to June 2020 and successfully recanalized the occluded blood vessel was selected. The patients were divided into the training group ( n=267) and the test group ( n=115) according to the ratio of 7∶3 by the random number table method. According to whether the patients had MBE after successful recanalization of the occluded blood vessels, the training group was divided into the MBE group ( n=41) and non-MBE group ( n=226). The baseline data, treatment and brain computed tomography perfusion(CTP) results of MBE group and non-MBE group in training group and test group were compared respectively, including age, admission score of National Institutes of Health Stroke Scale (NIHSS), grade of cerebral collateral circulation, cerebral blood volume, and so on. Logistic regression model and XGBoost algorithm model were used to screen the predictors of MBE in ALVOS patients with occluded vessels successfully recanalized, and the discrimination and calibration of the two models were compared. The measurement data conforming to the normal distribution were expressed as mean ± standard deviation ( ± s), and the independent sample t test was used for comparison between the two groups. Non-normally distributed measurement data were represented by M ( Q1, Q3), using independent sample Mann-Whitney U test. The chi-square test was used to compare the count data between groups. Results:There was no significant difference in baseline data, treatment status, and cranial computed tomography perfusion (CTP) imaging results of the training group and the test group ( P>0.05). The age, admission systolic blood pressure, admission NIHSS score, proportion of hypertension, proportion of cerebral collateral circulation 0-2, proportion of thrombus removal times> 3 times, time from onset to recanalization, and cerebral blood volume (CBV) of MBE group were (68.95±8.04) years old, (146.71±22.73) mmHg, 17(13, 21) min, 87.80%, 82.93%, 68.29%, (365.64±87.83) min, (32.56±5.73) mL/100 g, obvious higher than the non-MBE group [(60.27±7.13) years old, (137.92±19.58) mmHg, 14(10, 18) points, 73.01%, 60.62%, 2.65%, (307.59±74.05) min, (27.49±5.46) mL/100 g] ( P<0.05). The results of Logistic regression model showed that age, NIHSS on admission, grade of cerebral collateral circulation, times of thrombectomy and time from onset to recanalization were the predictors of MBE after successful recanalization of occluded vessels after EVT in patients with anterior circulation ALVOS ( P<0.05). The top five important feature scores of XGBoost algorithm model were cerebral collateral circulation classification 34, embolectomy times 27, onset to vascular recanalization time 25, admission NIHSS score 22, age 16.In the training set, the area under the curve of the Logistic regression model was 0.816(95% CI 0.749-0.883), and the Hosmer-Lemeshow test showed that χ2=1.547, P=0.438. The area under the curve of the XGBoost algorithm model was 0.856(95% CI 0.799-0.913), and the Hosmer-Lemeshow test showed that χ2=1.021, P=0.998. Conclusion:Logistic regression model and XGBoost algorithm model had similar prediction performance for MBE after successful recanalization of occluded vessels after EVT in patients with anterior circulation ALVOS, and collateral circulation classification, number of thrombolysis, time from onset to recanalization, NIHSS score on admission, and age could be used as predictors.