Objective To investigate the independent risk factors of ischemic early neurological deterioration (END) after intravenous alteplase thrombolysis in patients with acute ischemic stroke (AIS), and construct a clinical prediction model for END risk based on these factors.

Methods A retrospective cohort study was conducted. A total of 210 AIS patients who were admitted to the Advanced Stroke Center and received standard-dose rt-PAIVT treatment from June 2023 to April 2025 were selected. The patients were divided into the END group and non-END group based on whether END occurred within 24 hours after thrombolysis. The baseline data of patients, clinical severity and laboratory test results were collected. The logistic regression analysis was used to determine the independent risk factors, and based on this, a nomogram prediction model and a simple additive multi-factor prediction model were constructed. The model efficacy was evaluated through the receiver operating characteristic (ROC) curve.

Results The proportions of patients with longer onset-thrombolysis time, high NIHSS score at admission, high systolic blood pressure (SBP) before thrombolysis, high random blood glucose level before thrombolysis, proportion of large artery atherosclerosis in TOAST classification, diabetes and high fasting blood glucose in the END group were all higher than those in non-END group, and the differences were statistically significant (P ＜ 0.01). The results of logistic regression analysis showed that the independent risk factors of ischemic END in AIS patients after rt-PAIVT (P ＜ 0.05) included the OR(95%CI) of random blood glucose at admission for 2.046 (1.402–2.987), OR(95%CI) of NIHSS score at admission for 1.825 (1.311–2.543) and OR(95%CI) of systolic blood pressure (SBP) for 1.452 (1.089–1.937). The odds ratio (OR) (95%CI) of onset to thrombolysis time was 1.294 (1.023–1.638). Based on the above independent risk factors, a Nomogram model for END risk prediction and simple additive prediction model were successfully constructed.

Conclusions Long onset-thrombolysis time, high SBP before thrombolysis, high NIHSS score at admission and high random blood glucose level before thrombolysis, etc., are the independent risk factors of ischemic END after rt-PAIVT in AIS patients. The Nomogram model for risk prediction constructed based on the above risk factors has good predictive ability and clinical practicability, which is helpful for the early identification of high-risk END patients after rt-PA thrombolysis, and provides a basis for individualized monitoring and intervention in clinical practice.