Sleep-Wake Disturbances and Fatigue after Pediatric Traumatic Brain Injury: A Systematic Review of the Literature
Bibliographic record
Abstract
Sleep-wake disturbances (SWD) after traumatic brain injury (TBI) are frequently reported and can persist several years post-injury. The adult literature covering this topic is exhaustive; numerous robust studies using objective measures of sleep and advanced methodologies support the presence of SWD post-TBI. Despite being the leading cause of morbidity in children and adolescents, however, relatively few studies exist investigating SWD and symptoms of fatigue after pediatric TBI. We undertook a systematic search of the literature in PsycINFO, MEDLINE, CINAHL, and Web of Science databases with the aim of documenting persistent fatigue and SWD after pediatric TBI. Terms and keywords pertaining to TBI, children/adolescents, and sleep/fatigue were used, and of the 461 articles initially identified, 24 studies met our inclusion criteria. According to the results of the literature search, SWD and fatigue are common after pediatric TBI. The methodologies used in the studies reported varied widely, however, and were mainly subjective (e.g., questionnaires and interviews with caregivers). Moreover, no study targeted preschool children despite the fact that there is evidence regarding the critical importance of sleep for appropriate cognitive development, especially in high-order cognitive functioning. In sum, the results of the studies analyzed were consistent with the presence of SWD and fatigue after pediatric TBI, but there is a lack of information concerning this relationship in younger children. The use of more objective measures, such as actigraphy, could bring better insight to the impact of TBI on the quality of children's sleep.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".