Biofluid Biomarkers in Traumatic Brain Injury: A Systematic Scoping Review.

Emerging evidence suggests that biofluid-based biomarkers have diagnostic and prognostic potential in traumatic brain injuries (TBI). However, owing to the lack of a conceptual framework or comprehensive review, it is difficult to visualize the breadth of materials that might be available. We conducted a systematic scoping review to map and categorize the evidence regarding biofluid-based biochemical markers of TBI. A comprehensive search was undertaken in January 2019. Of 25,354 records identified through the literature search, 1036 original human studies were included. Five hundred forty biofluid biomarkers were extracted from included studies and classified into 19 distinct categories. Three categories of biomarkers including cytokines, coagulation tests, and nerve tissue proteins were investigated more than others and assessed in almost half of the studies (560, 515, and 502 from 1036 studies, respectively). S100 beta as the most common biomarker for TBI was tested in 21.2% of studies (220 articles). Cortisol was the only biomarker measured in blood, cerebrospinal fluid, urine, and saliva. The most common sampling time was at admission and within 24 h of injury. The included studies focused mainly on biomarkers from blood and central nervous system sources, the adult population, and severe and blunt injuries. The most common outcome measures used in studies were changes in biomarker concentration level, Glasgow coma scale, Glasgow outcome scale, brain computed tomography scan, and mortality rate. Biofluid biomarkers could be clinically helpful in the diagnosis and prognosis of TBI. However, there was no single definitive biomarker with accurate characteristics. The present categorization would be a road map to investigate the biomarkers of the brain injury cascade separately and detect the most representative biomarker of each category. Also, this comprehensive categorization could provide a guiding framework to design combined panels of multiple biomarkers.