Effect of blood alcohol level on Glasgow Coma Scale scores following traumatic brain injury
Bibliographic record
Abstract
OBJECTIVE: It is a common clinical perception that alcohol intoxication systematically lowers Glasgow Coma Scale (GCS) scores when evaluating traumatic brain injury (TBI). However, the research findings in this area do not uniformly support this notion. The purpose of this study is to examine the effects of blood alcohol level (BAL) on GCS scores following TBI. METHOD: Participants were 475 patients (64% male) who presented to a Level 1 trauma centre following a TBI. Patients were selected if they were injured in a motor vehicle accident and had an available day-of-injury GCS, BAL and Computed Tomography (CT) brain scan. RESULTS: Overall, acute alcohol intoxication did not significantly affect GCS scores, even in patients with BALs of 200 mg dl(-1) or higher. When controlling for the effects of injury severity, acute alcohol intoxication affected GCS scores only in those patients with BALs greater than 200 mg dl(-1) who also had intracranial abnormalities detected on CT scan. CONCLUSIONS: These findings suggest that GCS scores can be interpreted at face value in the vast majority of patients who are intoxicated. However, GCS scores will likely over-estimate the severity of brain injury in patients with abnormal head CT scans and BALs greater than 200 mg dl(-1).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".