Highlighting the differences in post-traumatic symptoms between patients with complicated and uncomplicated mild traumatic brain injury and injured controls
Bibliographic record
Abstract
OBJECTIVE: The goal of the current study is to explore the difference in acute post-concussive symptoms (PCS), headaches, sleep and mood complaints between groups of patients with complicated and uncomplicated mild traumatic brain injuries (mTBIs) and a comparable group of injured controls. Interactions among the following four factors were studied: presence of (1) PCS; (2) headaches; (3) sleep disorders; and (4) psychological status. METHODS: A total of 198 patients, followed at the outpatient mTBI clinic of the MUHC-MGH, completed questionnaires and a brief neurological assessment two weeks post-trauma. RESULTS: Whether they had a TBI or not, all patients presented PCS, headaches, sleep and mood complaints. No significant differences between groups in terms of reported symptoms were found. Variables such as depression and anxiety symptoms, as well as sleep difficulties and headaches were found to correlate with PCS. The high rate of PCS in trauma patients was observed independently of traumatic brain injury status. This study has also shown that patients with complicated mTBI were more likely to have vestibular impairment after their injury. CONCLUSION: The vestibular function should be assessed systematically after a complicated mTBI. Furthermore, the mTBI diagnosis should be based on operational criteria, and not on reported symptoms.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".