A Prospective Study of the Influence of Acute Alcohol Intoxication Versus Chronic Alcohol Consumption on Outcome Following Traumatic Brain Injury
Bibliographic record
Abstract
The purpose of the study was to disentangle the relative contributions of day-of-injury alcohol intoxication and pre-injury alcohol misuse on outcome from TBI. Participants were 142 patients enrolled from a Level 1 Trauma Center (in Vancouver, Canada) following a traumatic brain injury (TBI; 43 uncomplicated mild TBI and 63 complicated mild-severe TBI) or orthopedic injury [36 trauma controls (TC)]. At 6-8 weeks post-injury, diffusion tensor imaging (DTI) of the whole brain was undertaken using a Phillips 3T scanner. Participants also completed neuropsychological testing, an evaluation of lifetime alcohol consumption (LAC), and had blood alcohol levels (BALs) taken at the time of injury. Participants in the uncomplicated mild TBI and complicated mild-severe TBI groups had higher scores on measures of depression and postconcussion symptoms (d = 0.45-0.83), but not anxiety, compared with the TC group. The complicated mild-severe TBI group had more areas of abnormal white matter on DTI measures (all p < .05; d = 0.54-0.61) than the TC group. There were no difference between groups on all neurocognitive measures. Using hierarchical regression analyses and generalized linear modeling, LAC and BAL did provide a unique contribution toward the prediction of attention and executive functioning abilities; however, the variance accounted for was small. LAC and BAL did not provide a unique and meaningful contribution toward the prediction of self-reported symptoms, DTI measures, or the majority of neurocognitive measures. In this study, BAL and LAC were not predictive of mental health symptoms, postconcussion symptoms, cognition, or white-matter changes at 6-8 weeks following TBI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".