Book Review: Insomnia following Traumatic Brain Injury: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sleep disturbances after a traumatic brain injury (TBI) have received very little scientific attention despite the fact that several studies indicate that they may occur in 30% to 70% of patients. For individuals with TBI, problems falling asleep or maintaining sleep can exacerbate other symptoms such as pain, cognitive deficits, fatigue, or irritability. Sleep disturbances can thus compromise the rehabilitation process and the ability to return to work. This article reviews the evidence on the epidemiology, etiology, and treatment of insomnia in the context of TBI and proposes areas for future research. Prevalence estimates of insomnia complaints in TBI patients are summarized. Potential etiological factors (i.e., lesions to the nervous system, anxiety) and possible consequences of insomnia (i.e., fatigue, cognitive problems) in the context of TBI are discussed. Finally, pharmacological and psychological treatments previously shown effective to treat insomnia in healthy individuals are discussed as valuable treatment options for TBI patients. Increased knowledge about the high prevalence, diagnosis, and potential etiological factors of insomnia following TBI may promote a better identification, evaluation, and treatment of sleeping difficulties in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it