The specificity of course of acute period of craniocerebral injury and organization of medical care support are the factors determining outcomes for this category of patients. The purpose of the study is to investigate changes in predictors of course of acute period course of craniocerebral injury under implementation of stream model of medical care organization. The sampling included 150 patients with moderate and severe craniocerebral injury based on data obtained in 2013 and 2019, respectively. The clinical characteristics of patients (gender, age, level of consciousness, alcoholic intoxication, type of injury) and the characteristics of organization of medical care (mode of admission, qualification of hospital physician, time prior to surgery intervention) were evaluated. The selection of predictors significant for prognosis of outcomes of acute period of craniocerebral injury was implemented on the basis of logit-regression analysis and artificial neural network technology. The sampling of patients was divided into groups on the basis of outcomes of acute period of craniocerebral injury. The groups with relatively favorable and unfavorable course of acute period of craniocerebral injury were identified. It is demonstrated that prior to implementation of stream model of medical care provision, the most significant factors determining outcomes of the acute period of craniocerebral injury were characteristics of organization of medical care of these patients. After implementation of stream model the leading predictors became clinical characteristics of patients.
Keywords: acute period; artificial neural networks; craniocerebral injury; logit-regression analysis; outcome; predictors.