Predictive model for the risk of hemorrhagic transformation after rt-PA intravenous thrombolysis in patients with acute ischemic stroke: A systematic review and meta-analysis

To systematically review the risk prediction model of Hemorrhages Transformation (HT) after intravenous thrombolysis in patients with Acute Ischemic Stroke (AIS). Web of Science, The Cochrane Library, PubMed, Embase, CINAHL, CNKI, CBM, WanFang, and VIP were searched from inception to February 25, 2023 for literature related to the risk prediction model for HT after thrombolysis in AIS. A total of 17 included studies contained 26 prediction models, and the AUC of all models at the time of modeling ranged from 0.662 to 0.9854, 16 models had AUC>0.8, indicating that the models had good predictive performance. However, most of the included studies were at risk of bias. the results of the Meta-analysis showed that atrial fibrillation (OR=2.72, 95% CI:1.98–3.73), NIHSS score (OR=1.09, 95% CI:1.07–1.11), glucose (OR=1.12, 95% CI:1.06–1.18), moderate to severe leukoaraiosis (OR=3.47, 95% CI:1.61–7.52), hyperdense middle cerebral artery sign (OR=2.35, 95% CI:1.10–4.98), large cerebral infarction (OR=7.57, 95% CI:2.09–27.43), and early signs of infarction (OR=4.80, 95% CI:1.74–13.25) were effective predictors of HT after intravenous thrombolysis in patients with AIS. The performance of the models for HT after thrombolysis in patients with AIS in the Chinese population is good, but there is some risk of bias. Future post-intravenous HT conversion prediction models for AIS patients in the Chinese population should focus on predictors such as atrial fibrillation, NIHSS score, glucose, moderate to severe leukoaraiosis, hyperdense middle cerebral artery sign, massive cerebral infarction, and early signs of infarction.