ROUTINE INFLAMMATORY AND METABOLIC BIOMARKERS. Can They Predict a Positive Head CT in Paediatric Minor Traumatic Brain Injury?

Epidemiology and Clinical Context Traumatic brain injury (TBI) is a significant global health concern, with an estimated paediatric global annual incidence of 226.4 cases per 100,000 children (1). The vast majority of these cases are categorized as non-severe, as up to 95% of head injuries in children are classified as minor or mild (mTBI) (1,2). Nevertheless, approximately one-third of paediatric patients experience persistent symptoms lasting beyond one month (3).

The current diagnostic gold standard remains non-contrast head Computed Tomography (CT). However, CT utilization carries significant associated risks, including exposure to ionizing radiation, high institutional costs, and the frequent necessity for procedural sedation (4). To mitigate these risks, clinical decision rules such as PECARN, CATCH, and CHALICE were developed to identify children at high risk for intracranial lesions. Despite these tools, most CT scans are still performed in cases of mTBI where the diagnostic yield is remarkably low (5).

As such, additional aiding tools have been investigated for refining the clinical decision rules regarding the paediatric mTBI patients in need of a CT scan.

Brain-Specific Biomarkers (GFAP, UCH-L1, S100B) In 2018, the US FDA authorized the first biomarkers (GFAP and UCH-L1) for predicting the necessity of CT scans in patients with minor TBI, supported by the ALERT-TBI trial (6). These markers serve as critical tools for both diagnosis and prognosis in neurotrauma (7).

GFAP (Glial Fibrillary Acidic Protein) is an astroglial protein that can predict positive CT findings in children with a sensitivity of 94% and a specificity of 47% (8). Its high sensitivity makes it an ideal "rule-out" marker.