Objectives: Patients with anterior circulation large vessel occlusion are at high risk of acute ischemic stroke, which could be disabling or fatal. In this study, we applied machine learning to develop and validate two prediction models for acute ischemic stroke (Model 1) and severity of neurological impairment (Model 2), both caused by anterior circulation large vessel occlusion (AC-LVO), based on medical history and neuroimaging data of patients on admission.Methods: A total of 1,100 patients with AC- LVO from the Second Hospital of Hebei Medical University in North China were enrolled, of which 713 patients presented with acute ischemic stroke (AIS) related to AC- LVO and 387 presented with the non-acute ischemic cerebrovascular event. Among patients with the non-acute ischemic cerebrovascular events, 173 with prior stroke or TIA were excluded. Finally, 927 patients with AC-LVO were entered into the derivation cohort. In the external validation cohort, 150 patients with AC-LVO from the Hebei Province People's Hospital, including 99 patients with AIS related to AC- LVO and 51 asymptomatic AC-LVO patients, were retrospectively reviewed. We developed four machine learning models [logistic regression (LR), regularized LR (RLR), support vector machine (SVM), and random forest (RF)], whose performance was internally validated using 5-fold cross-validation. The performance of each machine learning model for the area under the receiver operating characteristic curve (ROC-AUC) was compared and the variables of each algorithm were ranked.Results: In model 1, among the included patients with AC-LVO, 713 (76.9%) and 99 (66%) suffered an acute ischemic stroke in the derivation and external validation cohorts, respectively. The ROC-AUC of LR, RLR and SVM were significantly higher than that of the RF in the external validation cohorts [0.66 (95% CI 0.57–0.74) for LR, 0.66 (95% CI 0.57–0.74) for RLR, 0.55 (95% CI 0.45–0.64) for RF and 0.67 (95% CI 0.58–0.76) for SVM]. In model 2, 254 (53.9%) and 31 (37.8%) patients suffered disabling ischemic stroke in the derivation and external validation cohorts, respectively. There was no difference in AUC among the four machine learning algorithms in the external validation cohorts.Conclusions: Machine learning methods with multiple clinical variables have the ability to predict acute ischemic stroke and the severity of neurological impairment in patients with AC-LVO.
Background:Acute cerebral artery occlusion is a common disease with high morbidity and mortality. At present, the commonly used mechanical thrombectomy schemes are mechanical thrombectomy and stent thrombectomy. However, the clinical differences between the two methods is not fully understood. The present study aimed to evaluate the clinical effectiveness of Solitaire AB stent thrombectomy for acute cerebral infarction (ACI).Methods:A retrospective study was carried out in 96 ACI patients admitted to our department from January 2017 to January 2020. According to the treatment they received, they were divided into group A (conventional microcatheter mechanical thrombectomy, n = 48) and group B (Solitaire AB stent thrombectomy, n = 48). All patients were followed up for 3 months. Their pre- and post-operative nerve function indices were compared between the 2 groups. The therapeutic effects were evaluated by thrombolysis in cerebral infarction scale system, Glasgow coma scale (GCS), National Institutes of Health Stroke Scale (NIHSS), and modified Rankin scale statistics.Results:Two groups of patients with NIHSS scores postoperative 3 and 30 days decreased significantly compared with preoperation. NIHSS score of group A 3 and 30 days postoperation was significantly higher than group B (P < .05). Two groups of patients with GCS scores postoperative 3 and 30 days increased significantly compared with preoperation. GCS score of group A 3 and 30 days postoperation was significantly lower than group B (P < .05). Group B with vascular recanalization ratio postoperative 30 days was higher than group A, however with no significant differences (P > .05). Moreover, group B with outcomes (modified Rankin scale score ≤2 points) postoperative 3 months was better than group A, however with no significant differences (P > .05).Conclusion:Solitaire AB stent embolectomy shows similar efficacy as mechanical thrombectomy in the treatment of ACI patients.
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