Clinical Effectiveness of a Blood-Based Biomarker in Patients with Mild Traumatic Brain Injury

Abstract Mild traumatic brain injury (mTBI) is among the most prevalent neurological conditions worldwide. Its diagnosis predominantly depends on computed tomography (CT) imaging, despite the majority of scans yielding negative results, leading to unnecessary resource utilization and avoidable radiation exposure. This study aims to investigate the potential of glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) as serum biomarkers for ruling out clinically significant intracranial injuries. This prospective cohort study enrolled adult patients (aged >18 years) presenting to the emergency department with nonpenetrating mTBI between October 2023 and October 2024. All participants underwent brain CT imaging and venous blood sampling for quantification of GFAP and UCH-L1. Diagnostic performance metrics, including sensitivity, specificity, positive predictive value, and negative predictive value, were calculated to assess biomarker accuracy in detecting intracranial abnormalities. A total of 123 patients were enrolled, with a mean age of 70 years. The predominant mechanism of injury was a ground-level fall. The combined use of GFAP and UCH-L1 demonstrated excellent sensitivity (100%; 95% CI: 89.1–100%) and negative predictive value (100%; 95% CI: 76.8–100%) for detecting intracranial injury. However, specificity was low (15.4%; 95% CI: 8.7–24.5%), indicating limited ability to rule in pathology based on biomarker elevation alone. This study demonstrates the high sensitivity and negative predictive value of GFAP and UCH-L1 as a combined biomarker test for evaluating moderate- and high-risk mTBI. Patients with a negative biomarker result may safely forgo head CT, thereby reducing unnecessary radiation exposure and avoiding unwarranted CT utilization. Nevertheless, practical challenges remain before routine clinical adoption is feasible. Future cost analyses will be essential to determine the economic viability of these biomarkers, particularly in resource-limited settings.