1173 FATIGUE AND SLEEP SLOW OSCILLATIONS ARE ASSOCIATED WITH WHITE MATTER INTEGRITY FOLLOWING MODERATE TO SEVERE TRAUMATIC BRAIN INJURY
Bibliographic record
Abstract
Chronic sleep-wake disturbances are among the most invalidating and frequently reported symptoms following a traumatic brain injury (TBI), but their pathophysiological mechanisms are still poorly understood. We aimed to explore potential mechanisms by which anatomical damage due to TBI, more specifically white matter damage, can cause the reported symptoms. Twenty-three subjects (17M/6F; age: 31 ± 11 years) were tested 23 ± 9 months following a moderate to severe TBI (Glasgow Coma Scale Score at hospital admission: 8.1 ± 2.9); twenty-seven age- and sex-matched healthy controls were also tested. Magnetic resonance imaging (3T) including a diffusion weighted sequence, 1-night polysomnography, and sleep questionnaires (Pittsburgh Sleep Quality Index, Fatigue Severity Scale and Epworth Sleepiness Scale) were used. Voxelwise t-tests and correlations were carried out with FSL, using tract-based spatial statistics and the Randomise tool. Extensive white matter damage (i.e. increased diffusivity and reduced anisotropy) was observed for most cerebral tracks in TBI subjects compared to controls. TBI subjects also had lower slow wave frequency (F=6.9; p=0.01), longer negative and positive phase durations (F=4.0–8.0; p=0.05-0.007), and reduced slope (F=4.8; p=0.03). In TBI participants, lower white matter integrity was associated with higher slow wave amplitude (r=0.46–0.79; p<0.05), longer positive and negative phase durations (r=0.69, p<0.05; r=0.55–0.67, p<0.05, respectively), as well as with higher subjective fatigue (r=0.06–0.08; p<0.05). These results suggest that TBI subjects with greater damage in white matter track integrity report more fatigue symptoms and have larger and elongated sleep slow waves. These slow waves may represent a mechanism that compensates for a possible higher mental effort exerted to accomplish tasks during the day. Our results bring new elements to explain the pathophysiology of post-TBI fatigue and sleep disturbances. Canadian Institutes of Health Research (CIHR), Fonds de Recherche Santé-Québec (FRSQ)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".