Evaluating the impact of treatment for sleep/wake disorders on recovery of cognition and communication in adults with chronic TBI
Bibliographic record
Abstract
OBJECTIVE: To longitudinally examine objective and self-reported outcomes for recovery of cognition, communication, mood and participation in adults with traumatic brain injury (TBI) and co-morbid post-traumatic sleep/wake disorders. DESIGN: Prospective, longitudinal, single blind outcome study. SETTING: Community-based. PARTICIPANTS: Ten adults with moderate-severe TBI and two adults with mild TBI and persistent symptoms aged 18-58 years. Six males and six females, who were 1-22 years post-injury and presented with self-reported sleep/wake disturbances with onset post-injury. INTERVENTIONS: Individualized treatments for sleep/wake disorders that included sleep hygiene recommendations, pharmacological interventions and/or treatments for sleep apnea with follow-up. MAIN OUTCOME MEASURES: Insomnia Severity Index, Beck Depression and Anxiety Inventories, Latrobe Communication Questionnaire, Speed and Capacity of Language Processing, Test of Everyday Attention, Repeatable Battery for the Assessment of Neuropsychological Status, Daily Cognitive-Communication and Sleep Profile. RESULTS: Group analysis revealed positive trends in change for each measure and across sub-tests of all measures. Statistically significant changes were noted in insomnia severity, p = 0.0003; depression severity, p = 0.03; language, p = 0.01; speed of language processing, p = 0.007. CONCLUSIONS: These results add to a small but growing body of evidence that sleep/wake disorders associated with TBI exacerbate trauma-related cognitive, communication and mood impairments. Treatment for sleep/wake disorders may optimize recovery and outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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 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".