Abstract: Objective To explore the risk factors of bleeding in patients with acute ischemic stroke after receiving intravenous thrombolysis, and construct a predictive model. Methods Totally 462 patients with acute ischemic stroke who underwent intravenous thrombolysis in a tertiary grade-A hospital in Shenzhen from January 2014 to December 2020 were divided into bleeding group (n=264) and non-bleeding group (n=198). The binary logistic regression model was used to analyze the risk factors, and the predictive model was constructed and verified. Results Age, the score of National Institutes of Health Stroke Scale (NIHSS) before thrombolysis, time from onset to thrombolysis, history of hypertension, and leukoaraiosis were independent risk factors for hemorrhage after intravenous thrombolysis in patients with acute ischemic stroke. AUC of the predictive model was 0.786 and the specificity and sensitivity were 81.82% and 62.36% respectively. Decision curve analysis showed that implementing decision interventions in the bleeding risk range of 0.306 to 0.990 had net clinical benefit. And after verification, it had been shown that the model had good discrimination (AUC=0.743,95%CI:0.699~0.788) and Calibration degree (Hosmer-Lemeshow test:χ²=11.559,P=0.172). Conclusion The nomogram model constructed in this study has better predictive performance, clinical application value, and high repeatability.

Key words: acute ischemic stroke, intravenous thrombolysis, hemorrhage, risk factor, prediction model, nomogram