Influence Factors and Predictive Models for the Outcome of Patients with Ischemic Stroke after Intravenous Thrombolysis: A Multicenter Retrospective Cohort Study

Abstract

Objective. Intravenous thrombolysis (IVT) is currently the main effective treatment for patients with ischemic stroke. This study aimed to analyze the factors affecting the early neurological recovery and prognosis of thrombolytic therapy after surgery and to construct predictive models. Materials and Methods. A total of 849 patients with ischemic stroke who received IVT treatment at six centers from June 2017 to March 2021 were included. Patients were divided into the training cohort and the validation cohort. Based on the independent factors that influence the early recovery of neurological function and the prognosis, the respective predictive nomograms were established. The predictive accuracy and discrimination ability of the nomograms were evaluated by ROC and calibration curve, while the decision curve and clinical impact curve were adopted to evaluate the clinical applicability of the nomograms. Results. The nomogram constructed based on the factors affecting the prognosis in 3 months had ideal accuracy as the AUC (95% CI) was 0.901 (0.874~0.927) in the training cohort and 0.877 (0.826~0.929) in the validation cohort. The accuracy of the nomogram is required to be improved, since the AUC (95% CI) of the training cohort and the validation cohort was 0.641 (0.597~0.685) and 0.627 (0.559~0.696), respectively. Conclusions. Based on this ideal and practical prediction model, we can early identify and actively intervene in patients with ischemic stroke after IVT to improve their prognosis. Nevertheless, the accuracy of predicting nomograms for the recovery of early neurological function after IVT still needs improvement.