Justification of Indication for Cranial CT Imaging After Mild Traumatic Brain Injury According to the Current National Guidelines

The primary aim was to evaluate the compliance of cranial CT indication with the national guideline-based decision rules in patients after mTBI. The secondary aim was to determine the incidence of CT pathologies among justified and unjustified CT scans and to investigate the diagnostic value of these decision rules. This is a retrospective, single-center study on 1837 patients (mean age = 70.7 years) referred to a clinic of oral and maxillofacial surgery following mTBI over a five-year period. The current national clinical decision rules and recommendations for mTBI were retrospectively applied to calculate the incidence of unjustified CT imaging. The intracranial pathologies among the justified and unjustified CT scans were presented using descriptive statistical analysis. The performance of the decision rules was ascertained by calculating the sensitivity, specificity, and predictive values. A total of 123 intracerebral lesions were radiologically detected in 102 (5.5%) of the study patients. Most (62.1%) of the CT scans strictly complied with the guideline recommendations, and 37.8% were not justified and likely avoidable. A significantly higher incidence of intracranial pathology was observed in patients with justified CT scans compared with patients with unjustified CT scans (7.9% vs. 2.5%, < 0.0001). Patients with loss of consciousness, amnesia, seizures, cephalgia, somnolence, dizziness, nausea, and clinical signs of cranial fractures presented pathologic CT findings more frequently ( < 0.05). The decision rules identified CT pathologies with 92.28% sensitivity and 39.08% specificity. To conclude, compliance with the national decision rules for mTBI was low, and more than a third of the CT scans performed were identified as "likely avoidable". A higher incidence of pathologic CT findings was detected in patients with justified cranial CT imaging. The investigated decision rules showed a high sensitivity but low specificity for predicting CT pathologies.