Missed Emergency Department Diagnosis of Mild Traumatic Brain Injury in Patients with Chronic Pain After Motor Vehicle Collision.
Bibliographic record
Abstract
BACKGROUND: Mild traumatic brain injury (mTBI), or concussion, is the most common presentation of TBI in the emergency department (ED), but a diagnosis of mTBI may be missed in patients presenting with other acute injuries after a motor vehicle collision (MVC). OBJECTIVE: To estimate the frequency of missed diagnoses of mTBI in patients seen in the ED after MVC who later developed chronic pain syndromes. STUDY DESIGN: Retrospective cohort study. SETTING: An interventional pain management clinic. METHODS: Data were drawn from information collected during standardized intake assessments completed by 33 patients involved in an MVC referred to a community-based clinic for chronic pain management. The prevalence of missed mTBI and postconcussion syndrome (PCS) were estimated based on the clinical diagnosis, which included reviewing acute care medical records, the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) scores, and patient-reported injury history. RESULTS: There was a high prevalence of presumed mTBI in this sample (69.7%) of patients involved in an MVC, but an acute care diagnosis was made in only 39.1% of cases. Patients diagnosed with mTBI at acute care had significantly lower PCS symptom scores than patients whose diagnosis was missed (P < 0.05). Diagnostic brain imaging (magnetic resonance imaging [MRI] or computed tomography [CT]) was more frequently ordered (P < 0.05) in patients diagnosed with mTBI. Using a modified RPQ developed for use with chronic pain patients, 54.5% of the sample met criteria for PCS. Loss of consciousness, meeting established criteria for mTBI, postinjury headache, and meeting criteria for posttraumatic stress disorder were significantly correlated with the development of PCS. LIMITATIONS: Data may be subject to recall and selection bias. Additional research with a larger study sample is needed to investigate correlations between individual symptoms and the development of PCS following an MVC. CONCLUSION: Patients presenting to the ED following an MVC have a high prevalence of mTBI. Patients whose diagnosis of mTBI is missed end up with significantly more severe postconcussion symptoms. While all patients included in this study were either referred or being treated for chronic pain after an MVC, they all also went on to develop PCS and disability following their accident, suggesting that better screening for mTBI after an MVC might identify those who may require more follow-up or rehabilitation therapy. In particular, those presenting with loss of consciousness, an altered mental state, posttraumatic amnesia, or postinjury headache are at increased risk of PCS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".