PREDICTION OF OUTCOMES AFTER STROKE: A SYSTEMATIC REVIEW

Abstract

In the contemporary world one of the leading causes of death and disability of the population belongs to the stroke. The average frequency of death within the first 30 days after stroke varies from 17 % to 34 %. During the first year about 50 % of patients die. Only 20 % of stroke survivors recover completely, while 80 % of these patients are permanently disabled. Along with the issues of stroke's prevention, treatment and its rehabilitation, it is a relevant aspect to predict the outcome of the patient in the post-stroke condition. It is known that the timely prediction of the cerebral stroke's outcome allows to avoid patient's death and to reduce the neurological deficit in case of correct appointment. Predictive models and scales are the simplest and most accessible instrument for estimating the patient's condition and predicting the outcome after stroke. Despite a considerable quantity of studies in this area the problem of forecasting the stroke's outcome is still relevant. Over the past 10 years the predictive value of some clinical scales has been further investigated, new information about biomarkers has been obtained, whose appearance in the blood correlates with the outcome of stroke, and which could potentially be used in predictive models. The information is not always available for physicians and researchers because of the presence of fragmentation and a language barrier. So the aim of this systematic review was analyzing and combining the available information of the methods predicting the stroke's outcome in the past 10 This review article presents an analysis of methods predicting the outcome in patients after stroke. The study included full-text publications in the English language for the last 10 years, describing the scales or models predicting the post-stroke's outcome in patient. We studied 668 sources in databases MEDLINE, SCOPUS, describing the clinical scales or prediction models that use serum biomarkers as predictors. After screening, 35 articles were selected and included in the analysis.