Nomogram to Predict Symptomatic Intracranial Hemorrhage after Intravenous Thrombolysis in Acute Ischemic Stroke in Asian Population

Abstract

Background: Symptomatic intracranial hemorrhage (sICH) is a serious hemorrhagic complication after intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) patients. Most existing predictive scoring systems were derived from Western countries Objective: To develop a nomogram to predict the possibility of sICH after IVT in an Asian population. Methods: This retrospective cohort study included AIS patients treated with recombinant tissue plasminogen activator (rt-PA) in a tertiary hospital in Shenzhen, China, from January 2014 to December 2020. The end point was sICH within 36 hours of IVT treatment. Multivariable logistic regression was used to identify risk factors of sICH, and a predictive nomogram was developed. Area under the curve of receiver operating characteristic curves (AUC), calibration curve, and decision curve analyses were performed. The nomogram was validated by bootstrap resampling Results: Data on a total of 462 patients were collected, of whom 20 patients (4.3%) developed sICH. In the multivariate logistic regression model, the National Institute of Health stroke scale scores (NIHSS) (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.06–1.23, P < 0.001), onset to treatment time (OTT) (OR, 1.02; 95% CI, 1.01–1.03, P < 0.001), neutrophil to lymphocyte ratio (NLR) (OR, 1.22; 95% CI, 1.09–1.35, P < 0.001), and cardioembolism (OR, 3.74; 95% CI, 1.23–11.39, P = 0.020) were independent predictors for sICH and were used to construct a nomogram. Our nomogram exhibited favorable discrimination ability [AUC, 0.878; specificity, 87.35%; and sensitivity, 73.81%]. Bootstrapping for 500 repetitions was performed to further validate the nomogram. The AUC of the bootstrap model was 0.877 (95% CI: 0.823–0.922). The calibration curve exhibited good fit and calibration. The decision curve revealed good positive net benefits and clinical effects Conclusion: The nomogram consisted of the predictors NIHSS, OTT, NLR, and cardioembolism could be used as an auxiliary tool to predict the individual risk of sICH in Chinese AIS patients after IVT. Further external verification among more diverse patient populations is needed to demonstrate the accuracy of the model’s predictions.