Prediction of Early Outcomes of Hemorrhagic Stroke Therapy in a Logistic Regression Model
Significant role of limited cerebrovascular accidents in the morbidity, mortality and disability patterns in the current setting is shown. Development of reliable predictive models of the therapy outcomes at the early stages of stroke diagnostics and treatment is considered. A method for development of mathematical-statistical model based on logistic regression for prediction of therapy outcomes in patients with hemorrhagic stroke is presented. Problems to be addressed during the model study are as follows: model quality assessment; effects of factors included into the model on the lethal outcome probability; risk assessment.