Missed diagnosis of traumatic brain injury in patients with traumatic spinal cord injury
Bibliographic record
Abstract
OBJECTIVE: To determine the frequency of missed acute care traumatic brain injury diagnoses in patients with traumatic spinal cord injury, and to examine risk factors for missed traumatic brain injury diagnosis. DESIGN: Prospective magnetic resonance imaging and neuro-psychological assessment plus retrospective medical record review, including computed tomography. SUBJECTS: Ninety-two adults with traumatic spinal cord injury recruited from a large, tertiary spinal cord injury program, initially referred from urban teaching hospitals with neurotrauma facilities. METHODS: Diagnosis of traumatic brain injury made with clinical neurological indices (i.e., Glasgow Coma Scale, post-traumatic amnesia, and loss of consciousness), neuroimaging (computed tomography and structural magnetic resonance imaging), and neuropsychological tests of attention and speed of processing, memory, and executive function; all measures were validated on a case-by-case basis to rule out confounds. Missed traumatic brain injury diagnoses were made via acute care medical record review and were corroborated by patient/family report where possible. RESULTS: The frequency of missed traumatic brain injury diagnoses in our sample was 58.5%. Missed traumatic brain injury diagnoses were more frequent in injuries sustained outside of a motor vehicle collision (MVC), with 75.0% of acute care traumatic brain injury diagnoses missed in non-MVC patients vs. 42.9% missed in MVC patients. Among patients with non-MVC injuries, a comparable percentage of missed traumatic brain injury diagnoses were observed in patients with cervical (79%) and sub-cervical injuries (80%). CONCLUSION: In more than half of the traumatic spinal cord injury patients referred for in-patient rehabilitation, acute care diagnoses of traumatic brain injury were missed. A risk factor for missed diagnosis was an injury caused by a mechanism other than an MVC (e.g., falls, assaults), perhaps due to reduced expectations of traumatic brain injury in non-MVC patients. In our research study, we employed multiple assessments to aid diagnosis, which is particularly important for detecting the milder traumatic brain injuries often associated with spinal cord injury; unfortunately, limited resources may preclude a comprehensive diagnostic approach in clinical settings. Our findings point to the need to examine current acute care diagnostic protocols, and to increase vigilance in patients with traumatic injuries sustained outside of an MVC setting.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".