In this study, we identified several significant predictors of brain CT scan abnormalities in patients with mild traumatic brain injury (mTBI). The analysis revealed that loss of consciousness (LOC), alteration of consciousness (AOC), post-traumatic amnesia (PTA), associated vomiting, and associated seizures were all significantly associated with abnormal CT findings. These results highlight the importance of these clinical factors in the initial assessment and decision-making process for mTBI patients.

These findings are supported by previous studies, which emphasized the significance of neuroimaging in all TBI patients, including those with a GCS of 15. A study of over 2000 patients found that even the mildest cases of TBI could present with significant CT abnormalities, with variables such as LOC, AOC, and PTA being significantly associated with adverse outcomes, including ICU admission and mortality [3]. Similarly, a 2017 study that included 453 patients with GCS 15 found that presence of vomiting or any symptom combination including LOC, bleeding, seizure or vomiting was significantly associated with having an abnormal brain CT (P < 0.0001) [8].

Further, these findings highlight the challenges in developing standardized assessment protocols for mTBI in emergency settings, particularly given the heterogeneity of mTBI presentations and the lack of consensus on management guidelines, especially in mild cases [9, 10]. This underscores the need for integrating identified clinical predictors into decision-making processes, which can help standardize and improve the assessment, leading to better patient outcomes.

The most common clinical decision tool used to determine whether a head CT should be done after a mTBI is the Canadian head CT rule [11]. This rule states that if all criteria are negative, then the sensitivity of the rule for any intracranial traumatic finding is 83–100%. The included high-risk criteria are age > 65, suspected skull fracture, signs of basilar skull fracture, or 2 or more episodes of vomiting. Medium risk criteria include 30 or more minutes of amnesia to the event (PTA), and a dangerous mechanism for the TBI, defined as pedestrian struck by motor vehicle, occupant ejected from motor vehicle, or fall from > 3 feet or > 5 stairs. In our cohort, after removing every patient who had even 1 of these criteria, there were still 1309 patients left, or 47%. All of these would be deemed to not need a head CT because traumatic findings would not be expected. Indeed, a quarter of these patients actually did have intracranial hemorrhage, and 7% had a fracture.

One of the key strengths of this study is the large sample size, which provides robust evidence for the identified predictors. The multivariate logistic regression model used in this analysis demonstrated a strong predictive capability, with an R² of 14.2%, indicating a substantial proportion of the variance in CT abnormalities can be explained by the included predictors. The inclusion of a wide range of clinical variables enhances the comprehensiveness of our analysis, ensuring that the identified predictors are not confounded by other factors.

Despite these strengths, it is crucial to acknowledge the limitations of this study. CT scans primarily offer structural information and may not detect functional abnormalities, which are often critical in the assessment of mTBI. Functional changes in brain activity, which can significantly impact cognitive function, are not directly observable on CT scans. Additionally, the timing of CT scans may affect the detection of abnormalities. Early CT scans might miss evolving injuries that become apparent only later, emphasizing the potential need for follow-up imaging and more frequent monitoring of mTBI patients.

The identification of intracranial hemorrhage on CT in mTBI is important, even if neurosurgical intervention is not performed. A 2021 study in JAMA Neurology [12] reports that patients who sustained a subarachnoid hemorrhage, epidural hematoma or subdural hematoma were significantly more likely to have incomplete recovery from their TBI, even at 1 year. This information is important to frame prognosis and make rehabilitation plans for the patient.

The findings from this study have significant implications for clinical practice. Incorporating the identified predictors into clinical decision rules could improve the accuracy of triaging mTBI patients, ensuring that those at higher risk receive timely and appropriate imaging and care. This targeted approach can optimize resource allocation in emergency departments, reducing unnecessary CT scans for low-risk patients while prioritizing high-risk cases. Future research should focus on developing and validating clinical decision rules that integrate these predictors, potentially incorporating advanced imaging techniques and functional assessments to enhance the diagnostic process for mTBI.

Overall, this study underscores the critical role of specific clinical predictors in identifying brain CT abnormalities in mTBI patients. These findings contribute to the growing body of evidence that informs clinical guidelines and decision-making protocols, ultimately aiming to improve patient outcomes and healthcare efficiency. By integrating clinical predictors with neuroimaging and understanding the broader context of TBI management, clinicians can adopt a more comprehensive approach to diagnosis and treatment, hopefully leading to better outcomes for mTBI patients.