Neuropsychological assessments in a hyperbaric trial of post-concussive symptoms.
Bibliographic record
Abstract
Results of studies addressing the effect of mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) on symptoms and neuropsychological assessments are mixed regarding cognitive deficits in these populations. Neuropsychological assessments were compared between U.S. military service members with mTBI only (n=36) vs. those with mTBI÷ PTSD (n=35) from a randomized interventional study of mTBI participants with persistent post-concussive symptoms (PCS). The mTBI group endorsed worse symptoms than published norms on PCS, PTSD and pain scales (⟩50% abnormal on Neurobehavioral Symptom Inventory (NSI), PTSD Checklist-Civilian, McGill Pain Questionnaire-Short Form) and some quality of life domains. Worse symptom reporting was found in the mTBI÷ PTSD group compared to mTBI (e.g., mean NSI total score in mTBI 27.5 (SD=12.7), mTBI÷ PTSD 39.9 (SD=13.6), p⟨0.001). The mTBI÷PTSD group performed worse than mTBI on the Weschler Adult Intelligence Scale digit span (mean difference -1.5, 95% CI[-2.9,-0.1], p=0.04) and symbol search (mean difference -1.5, 95% CI[-2.7,-0.2], p=0.03) and Grooved Pegboard (dominant hand mean difference -7.0, 95% CI[-11.5,-2.4], p=0.003; non-dominant mean difference -9.8, 95% CI[-14.9,-4.7], p⟨0.001). Differences were detected in ANAM simple reaction time (p=0.04) and mathematical processing (p=0.03) but not verbal fluency or visuospatial memory assessments. Results indicate increased symptom severity and some cognitive deficits in mTBI÷ PTSD compared to mTBI alone. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01611194; https://clinicaltrials.gov/show/NCT01611194.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".