1168 CHARACTERIZATION OF CHRONIC SLEEP-WAKE DISTURBANCES OCCURRING AFTER MODERATE TO SEVERE TRAUMATIC BRAIN INJURY
Bibliographic record
Abstract
Sleep-wake disturbances (SWD) are among the most prevalent and disabling consequences reported after a moderate-to-severe traumatic brain injury (TBI), but remain poorly understood. Our aim was to better characterize post-TBI SWD using a combination of subjective and objective measures. Moreover, we aimed to verify whether specific types of SWD were associated with markers of TBI severity. Thirty-five individuals with moderate to severe TBI (24M/11F; aged: 27.6 ± 9.6 years; Glasgow Coma Scale (GSC) score at hospital admission: 8.6 ± 3.3) were evaluated between 1–3 years post-injury. SWD were assessed using questionnaires (e.g. Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index and Fatigue Severity Scale), as well as with a 7-day sleep diary and simultaneous actigraphy. We also used the Beck Depression Inventory and Beck Anxiety Inventory, as mood fluctuations have been associated with SWD in this population. Scores on questionnaires and actigraphy variables (sleep efficiency, total sleep time and number of naps) were entered into a principal component analysis (PCA) to extract non-correlated SWD and mood components. We performed correlations between each of these components and clinical variables representing TBI severity (e.g., duration of post-traumatic amnesia and GCS score). The rotated PCA produced four non-correlated components, namely 1) Fatigue/Mood fluctuation, 2) Daytime sleepiness, 3) Increased sleep duration and 4) Sleep efficiency, which explained 75% of the variance on questionnaires and actigraphic measures. The component “Fatigue/Mood fluctuation” was positively correlated with more prolonged post-traumatic amnesia (r=0.44 p<0.01). However, the other three components were not associated with markers of TBI severity. Our results suggest that SWD after moderate-to-severe TBI are highly heterogeneous, but they can be conceptualized into two wakefulness and two sleep non-correlated components. Interestingly, daytime disturbances were not associated with sleep disturbances, which suggest that the injured brain deregulates wakefulness mechanisms independently of sleep.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".