Risk factors and a model for prognosis prediction after intravenous thrombolysis with alteplase in acute ischemic stroke based on propensity score matching.

Abstract

Background: Alteplase intravenous thrombolysis is effective for treating acute ischemic stroke (AIS) within 4.5 h. Nevertheless, the prognosis remains poor for some patients.Objective: To investigate the risk factors for poor prognosis in patients undergoing intravenous thrombolysis with alteplase following AIS based on propensity score matching and to develop a predictive model.Result: Multivariate logistic regression analysis showed that baseline blood glucose (OR = 1.20, 95%CI, 1.03-1.39), baseline NIH Stroke Scale score (OR = 1.23, 95%CI, 1.12-1.35), and hyperlipidemia (OR = 6.60, 95%CI 1.74-25.00) were risk factors for poor prognosis in patients with AIS undergoing alteplase intravenous thrombolysis. Using these factors, a nomogram model was constructed for predicting patient prognosis at 3 months. The areas under the receiver operating characteristic curve (AUCs) of the training and validation groups were 0.792 (95CI% 0.715-0.870) and 0.885 (95CI% 0.798-0.972), respectively, showing good differentiation. The Hosmer Lemeshow goodness-of-fit test showed that the model had good fit. The calibration curve fitted well with the ideal curve, and the decision curve analysis curve showed that the model had good clinical applicability when the threshold probability was between 10%-80%.Conclusion: The established nomogram could successfully predict the 3-month prognosis of patients with AIS after undergoing alteplase intravenous thrombolysis. The model thus has clinical application value.