Risk Factors and Nomogram to Predict Intracranial Hemorrhage in Stroke Patients Undergoing Thrombolysis

Introduction: Identification of stroke patients at risk of postthrombolysis intracranial hemorrhage (ICH) in the clinical setting is essential. We aimed to develop and evaluate a nomogram for predicting the probability of intracranial hemorrhage (ICH) in acute ischemic stroke patients undergoing thrombolysis. Methods: A retrospective observational study was conducted with 287 participants from a single center (67.2% males, median age 65 years). The patients were randomly divided into a training set (160) and a validation set (127). Univariate and multivariate logistic regression analyses of clinical variables were performed to screen for significant prognostic factors. Nomograph that included significant prognostic variables was formulated to predict ICH. Areas under curve (AUC) of receiver operating characteristic (ROC) and calibration plots were formulated to evaluate the predictive accuracy of the nomograph. Results: A total of 41(14.3%) ICH events occurred. A nomogram was developed to predict ICH based on three variables in the training set: the presence of atrial fibrillation (OR: 4.01, P =0.009), the National Institutes of Health Stroke Scale (NIHSS) score (OR: 1.16, P =0.001) and glucose (OR: 1.37, P =0.006) on admission. The AUC-ROC for the training set was 0.817 (0.730-0.925), and for the validation set was 0.809 (0.710-0.904). Calibration plots showed good consistency between the two sets. Conclusion: We developed an easy-to-use nomogram model based on 3 independently clinical factors to predict ICH. The nomogram could be useful for individualized prediction of ICH in intravenous thrombolysis-treated stroke patients..