Nomogram prediction model for the risk of intracranial hemorrhagic transformation after intravenous thrombolysis in patients with acute ischemic stroke

BackgroundHemorrhagic transformation (HT) after intravenous thrombolysis (IVT) might worsen the clinical outcomes, and a reliable predictive system is needed to identify the risk of hemorrhagic transformation after IVT.MethodsRetrospective collection of patients with acute cerebral infarction treated with intravenous thrombolysis in our hospital from 2018 to 2022. 197 patients were included in the research study. Multivariate logistic regression analysis was used to screen the factors in the predictive nomogram. The performance of nomogram was assessed on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots and decision curve analysis (DCA).ResultsA total of 197 patients were recruited, of whom 24 (12.1%) developed HT. In multivariate logistic regression model National Institute of Health Stroke Scale (NIHSS) (OR, 1.362; 95% CI, 1.161–1.652; p = 0.001), N-terminal pro-brain natriuretic peptide (NT-pro BNP) (OR, 1.012; 95% CI, 1.004–1.020; p = 0.003), neutrophil to lymphocyte ratio (NLR) (OR, 3.430; 95% CI, 2.082–6.262; p