External validation of the updated Brain Injury Guidelines for complicated mild traumatic brain injuries: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: Approximately 10% of patients with mild traumatic brain injury (mTBI) have intracranial bleeding (complicated mTBI) and 3.5% eventually require neurosurgical intervention, which is mostly available at centers with a higher level of trauma care designation and often requires interhospital transfer. In 2018, the Brain Injury Guidelines (BIG) were updated in the United States to guide emergency department care and patient disposition for complicated mild to moderate TBI. The aim of this study was to validate the sensitivity and specificity of the updated BIG (uBIG) for predicting the need for interhospital transfer in Canadian patients with complicated mTBI. METHODS: This study took place at three level I trauma centers. Consecutive medical records of patients with complicated mTBI (Glasgow Coma Scale score 13-15) who were aged ≥ 16 years and presented between September 2016 and December 2017 were retrospectively reviewed. Patients with a penetrating trauma and those who had a documented cerebral tumor or aneurysm were excluded. The primary outcome was a combination of neurosurgical intervention and/or mTBI-related death. Sensitivity and specificity analyses were performed. RESULTS: A total of 477 patients were included, of whom 8.4% received neurosurgical intervention and 3% died as a result of their mTBI. Forty patients (8%) were classified as uBIG-1, 168 (35%) as uBIG-2, and 269 (56%) as uBIG-3. No patients in uBIG-1 underwent neurosurgical intervention or died as a result of their injury. This translates into a sensitivity for predicting the need for a transfer of 100% (95% CI 93.2%-100%) and a specificity of 9.4% (95% CI 6.8%-12.6%). Using the uBIG could potentially reduce the number of transfers by 6% to 25%. CONCLUSIONS: The patients in uBIG-1 could be safely managed at their initial center without the need for transfer to a center with a higher level of neurotrauma care. Although the uBIG could decrease the number of transfers, further refinement of the criteria could improve its specificity.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".