Background and Purpose-Various risk score models have been developed to predict symptomatic intracerebral hemorrhage (SICH) after intravenous thrombolysis for acute ischemic stroke. In this study, we aimed to determine the prediction performance of these risk scores in a Taiwanese population Methods-Prospectively collected data from 4 hospitals were used to calculate probability of SICH with the scores developed by Cucchiara et al, the Hemorrhage After Thrombolysis (HAT) score, the Safe Implementation of Thrombolysis in Stroke-SICH risk score, the Glucose Race Age Sex Pressure Stroke Severity score, and the Stroke Prognostication using Age and National Institutes of Health Stroke Scale-100 index. We used logistic regression to evaluate the effectiveness of each risk model in predicting SICH and the c statistic to assess performance. Results-A total of 548 patients were included. The rates of SICH were 7.3% by the National Institute of Neurological Diseases and Stroke definition, 5.3% by the European-Australasian Cooperative Acute Stroke Study II definition, and 3.5% by the Safe Implementation of Thrombolysis in Stroke-Monitoring Study definition. The Cucchiara score, the HAT score, and the Safe Implementation of Thrombolysis in Stroke-SICH risk score were significant predictors of SICH for all 3 definitions, whereas the Glucose Race Age Sex Pressure Stroke Severity score and the Stroke Prognostication using Age and National Institutes of Health Stroke Scale-100 index predicted well only for 1 or 2 definitions of SICH. The c statistic was highest for the HAT score (range, 0.69-0.73) across the definitions of SICH. Conclusions-The Cucchiara score, the HAT score, and the Safe Implementation of Thrombolysis in Stroke-SICH risk score predicted SICH reasonably well regardless of which SICH definition was used. However, only the HAT score had an acceptable discriminatory ability.
All Science Journal Classification (ASJC) codes
- Clinical Neurology
- Cardiology and Cardiovascular Medicine
- Advanced and Specialised Nursing