Zozulya O. Prognostic criteria of the course and outcomes of the severe craniocerebral injury (clinical and biochemical investigation)

The theses are dedicated to the problems of prediction of the course severity and outcome after severe craniocerebral injury (SCCI) and aimed to the treatment optimization. There were investigated 280 male patients, aged between 20 and 60, with starting consciousness level not more than 8 pts. after Glasgow Coma Scale. About each patient there were gathered data, included 208 clinical and biochemical parameters. The analysis of dynamics of the biochemical parameters using description statistics methods, revealed statistically significant parameters, which were the biochemical predictors of the outcome of SCCI. They are: blood progesterone, serotonin in day urine during the 1st day of SCCI, blood methemoglobin on the 3rd day, blood oxyhemoglobin on the 5th day, BE and lactate in the blood, outflowing of the brain, histamine and serotonin in day urine on the 7th day, blood oxy- and methemoglobin on the 10th, lactate in the blood, outflowing of the brain, DOPA in day urine - on the 14th day. In predictionof the outcome after SCCI there was used mathematical modeling method. The models of the prognosis were made on the 1st, 3rd, 5th, 7th, 10th and 14th day after injury. In the model of prediction of course severity and outcome after SCCI there were included next investigated criteria: age, severity of the structural and functional brain damage and the most significant biochemical markers. The model looked like linear discriminate function (LDF), and it was calculated for each group of patients (survived - LDF1 and died - LDF2). The analysis of the reliability of the received models revealed that when using only biochemical markers of prognosis and their combination with the above-mentioned criteria, it's impossible to get high reliability of prognosis. Only combination of the biochemical markers and such criteria, like the severity of the morphological and functional brain damage, the age of the patient, allow to receive prognostic model with a high (87,5 - 97,6%) resolution capacity through all stages of themonitoring.