A simple scoring to predict symptomatic intracranial hemorrhage after stroke thrombolysis: the EGAN score

Symptomatic intracranial hemorrhage (sICH) after intravenous thrombolysis represents a critical and fatal complication observed in acute ischemic stroke (AIS) patients. This study aims to establish a simple scoring model to predict sICH. We retrospectively conducted a cohort study of eligible AIS patients treated with rt-PA at a tertiary comprehensive stroke center from January 2018 to December 2022. Backward stepwise multivariable logistic regression provided the final model. The point score was generated from β-coefficients. The area under the curve (AUC) of the receiver operating characteristics (ROC) and the Hosmer–Lemeshow goodness-of-fit test were used to assess the discrimination and calibration of the model. The conditional probabilities were derived based on the Bayes theorem. Of the included patients, sICH occurred in 26 (3.97%) of the 655. The EGAN score consisted of an early infarct sign (10 points), baseline glucose ≥200 mg/dL (11 points), atrial fibrillation (AF) (13 points), and an NIH Stroke Scale (NIHSS) score ≥10 (12 points). With a cut-off point of 13, the EGAN score demonstrated good discrimination (0.7453 [95% CI: 0.649–0.841]), sensitivity (80.77%), and specificity (58.19%), respectively, for identifying sICH. This easy-to-use scoring model, based on predictors quickly obtained in clinical practices, offers a simple approach to screening for post-thrombolysis sICH and can serve as an alternative option in hospitals with limited resources for thrombolysis therapy.