Prognostication of the acute ischemic stroke based on EEG with the use of binary logistic regression method
This research was aimed to develop rules for prognostication of the acute hemispheric ischemic stroke, based on the EEG data, received during the first days of the disease. The article summarizes EEG results of 84 patients with primary hemispheric ischemic stroke. The decision rules are elicited through the use of binary logistic regression method, ROC-curve and the cross validation method. As a result there was worked out a decision rule for the 30th -day outcome prognosis based on the NIH scale (sensitivity 81.3%, specificity 88.9%) and a decision rule for the 30th -day functional recovery (Barthel Index) (sensitivity 88.9%, specificity 88.9%). Based on these rules the program calculator was developed for use in the clinical practice.