Classification of Different Degrees of Disability Following Intracerebral Hemorrhage: A Decision Tree Analysis from VISTA-ICH Collaboration

Background and purpose: Prognostication following intracerebral hemorrhage (ICH) has focussed on poor outcome at the expense of lumping together mild and moderate disability. We aimed to develop a novel approach at classifying a range of disability following ICH. Methods: The Virtual International Stroke Trial Archive (VISTA) collaboration database was searched for patients with ICH and known volume of ICH on baseline CT scans. Disability was partitioned into mild (modified Rankin Scale/mRS at 90 days of 0-2), and moderate (mRS=3-4), severe disability (mRS=5-6). We used binary and trichotomy decision tree methodology. The data were randomly divided into training (2/3 of data) and validation (1/3 data) datasets. The area under the receiver operating characteristic curve (AUC) was used to calculate the accuracy of the decision tree model. Results: We identified 957 patients, age 65.9±12.3 years, 63.7% males, ICH volume 22.6±22.1 ml. The binary tree showed that lower ICH volume (27.9 mL), older age (>69.5 years) and low Glasgow Coma Scale (<15) classify severe disability with AUC of 0.80 (95% CI 0.75-0.86). The trichotomy tree showed that ICH volume, age and serum glucose can separate mild, moderate and severe disability groups with AUC 0.79 (95% CI 0.71-0.87). Conclusion: Both the binary and trichotomy methods provide equivalent discrimination of disability outcome after ICH. The trichotomy method can classify 3 categories at once whereas this action was not possible with the binary method. The trichotomy method may be of use to clinicians and trialists for classifying a range of disability in ICH.