Six-month recovery from mild to moderate Traumatic Brain Injury: the role of APOE- 4 allele
Bibliographic record
Abstract
The possession of at least one APOE-epsilon4 allele may be linked to poor outcome in patients with predominantly severe traumatic brain injury (TBI). In mild TBI, which accounts for approximately 85% of all cases, the role of the APOE-epsilon4 allele is less clear. Studies completed to date have relied on brief cognitive assessments or coarse measures of global functioning, thereby limiting their conclusions. Our study investigated the influence of the APOE-epsilon4 allele in a prospective sample of 90 adults with mild to moderate TBI in whom neuropsychiatric outcome 6 months after injury was assessed as follows: (i) a detailed neuropsychological battery; (ii) an index of emotional distress (General Health Questionnaire); (iii) a diagnosis of major depression (Structured Clinical Interview for DSM-IV); (iv) a measure of global functioning (Glasgow Outcome Scale); (v) an index of psychosocial outcome (Rivermead Head Injury Follow-up Questionnaire); and (vi) symptoms of persistent post-concussion disorder (Rivermead Post-Concussion Symptoms Questionnaire). No association was found between the presence of the APOE-epsilon4 allele and poor outcome across all measures. Given the homogeneous nature of our sample (mild to moderate injury severity), the uniform follow-up period (6 months) and the comprehensive markers of recovery used, our data suggest that the APOE-epsilon4 allele does not adversely impact outcome in this group of TBI patients.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".