Fatigue Following Traumatic Brain Injury in Children and Adolescents: A Longitudinal Follow-Up 6 to 12 Months After Injury
Bibliographic record
Abstract
BACKGROUND: Longitudinal fatigue data in children suffering from traumatic brain injury (TBI) are lacking. OBJECTIVES: To examine the effects of time postinjury (6-12 months) and injury severity on fatigue after childhood TBI. Secondarily, we compared fatigue 12 months postinjury against published control data. SETTING: Three tertiary children's hospitals across Australia (n = 1) and Canada (n = 2). PARTICIPANTS: Parents (n = 109) of children (mean [M] = 9.9 years at injury; range, 1.0-16.9 years) admitted to one of 3 participating hospitals with mild (n = 69) or moderate/severe (n = 37) TBI. DESIGN: Longitudinal prospective study. MEASURES: Primary: Pediatric Quality of Life Multidimensional Fatigue Scale (total, general, sleep/rest, and cognitive), rated by parents 6 and 12 months postinjury. Secondary: Pediatric Injury Functional Outcome Scale (fatigue and sleep items, rated on recruitment and 6 and 12 months postinjury). Demographic and children data were collected at recruitment. RESULTS: Mixed-models analysis demonstrated nonsignificant effects of time (6 vs 12 months postinjury) on multidimensional fatigue scores. Cognitive fatigue worsened over time. Moderate/severe TBI was associated with worse fatigue 12 months postinjury (general, P = .03; cognitive, P = .02). Across all severities, fatigue 12 months postinjury was significantly worse compared with control data (total fatigue, P < .001; all domains, all Ps < .025). CONCLUSION: Fatigue remains significant at 12 months since injury, particularly for those with moderate/severe TBI.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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".