In predicting outcomes in patients with acute brain injury, current practice focuses special attention on neuron-specific proteins that reliably reflect the severity of the lesion. Further studies of molecular markers and their specificity and sensitivity could contribute to broadening the understanding of pathophysiological, diagnostic, and prognostic methods, which is vital to reducing the mortality and disability associated with these critical conditions. The purpose of this study was to assess the biomarkers of brain lesions and their correlative relations with the integral Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS) in predicting severity and treatment outcomes in patients with acute neuropathologies. Ninety patients were examined, including those with traumatic brain lesions (16.6%, n = 15), hemorrhagic stroke (52.2%, n = 47), and ischemic stroke (31.1%, n = 28). Patients were classified into two groups according to the outcome of the disease: those who survived (group I, 57.8%, n = 52) and those who died (group II, 42.2%, n = 38). In comparison with the survivors, the group of patients who died demonstrated an initial increase in neuron-specific enolase (NSE) by 1.23 and S100 by 6.45 times, and in dynamics by 1.5 and 7.4 times. A significant correlation with NIHSS and GCS was determined for NSE (r = 0.1149; P = 0.3073 and r = -0.0758; P = 0.5011) and for S100 (r = 0.3243; P = 0.0031 and r = -0.2661; P = 0.0163). The receiver operating characteristic (ROC) curves were 0.828 for S100 and 0.712 for NSE. The degree of sensitivity and specificity of the markers was studied. Increased levels of S100 and NSE correlated with NIHSS and GCS, with sensitivity of 80.77 and 63.46% and specificity of 42.11 and 73.68%, respectively, and were predictive of adverse disease outcome. The survival analysis showed that early detection of these biomarkers enables the timely prognostication of the progression of secondary brain injury and aids in implementing treatment.
Keywords: Acute neuropathologies; Integral scales; Neuromarkers; Prognosis; Sensitivity; Specificity; Survival.