Sleep-wake disturbances in hospitalized patients with traumatic brain injury: association with brain trauma but not with an abnormal melatonin circadian rhythm
Bibliographic record
Abstract
STUDY OBJECTIVES: To test whether the sleep-wake cycle disruption in patients hospitalized with traumatic brain injury (TBI) (1) is also found in patients with traumatic injuries other than TBI (non-TBI) and (2) is associated with a weaker or abnormal circadian clock signal. METHODS: Forty-two non-mechanically ventilated and non-sedated patients hospitalized for moderate-to-severe TBI were compared to 34 non-TBI patients. They wore wrist actigraphs for 9.4 ± 4.2 days, starting 19.3 ± 12.6 days post-injury. Of these, 17 TBI and 14 non-TBI patients had their urine collected every hour for 25 hours, starting 18.3 ± 12.3 days post-injury. We calculated urinary 6-sulfatoxymelatonin concentration to obtain total 24-hour excretion, excretion onset, offset, duration, amplitude, and acrophase. Using Student's t-tests, we compared groups on actigraphy (daytime activity ratio, nighttime total sleep time, and fragmentation index) and melatonin variables. We investigated associations between melatonin and actigraphy variables using Pearson's correlations. RESULTS: TBI patients had poorer daytime activity ratio (TBI: 77.5 ± 9.4%; non-TBI: 84.6 ± 6.9%), shorter nighttime total sleep time (TBI: 353.5 ± 96.6 min; non-TBI: 421.2 ± 72.2 min), and higher fragmentation index (TBI: 72.2 ± 30.0; non-TBI: 53.5 ± 23.6) (all p-values < 0.01). A melatonin rhythm was present in both groups, and no group differences were found on melatonin variables. No associations were found between melatonin and actigraphy variables in TBI patients. CONCLUSION: Moderate-to-severe TBI patients have more serious sleep-wake disturbances than non-TBI patients hospitalized in the same environment, suggesting that the brain injury itself alters the sleep-wake cycle. Despite their deregulated 24-hour sleep-wake cycle, TBI patients have a normal circadian clock signal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".