A Scoping Review of Pain in Children after Traumatic Brain Injury: Is There More Than Headache?
Bibliographic record
Abstract
Headache is a common source of pain in children after traumatic brain injury (TBI); however, relatively little is known about nonheadache pain in this pediatric population. The present review seeks to map the extant literature to determine the prevalence, characteristics, and impact of nonheadache pain in children post-TBI of all severities. We found that of 109 studies published on pain in children after a TBI, 95 (87%) were focused exclusively on headache pain and only 14 (13%) reported on nonheadache pain or overall pain, with half (n = 7) in the form of case studies. Overall, the level of evidence was low, with only three level 1 high-quality prospective studies. In one study, over half (57.1%) of adolescents who experienced persistent pain post-TBI reported pain in multiple body sites (e.g., back, lower limb, and neck).1 For each additional noncephalic pain site, the risk for developing chronic migraine is also increased. Nevertheless, pain in body regions other than the head is often not assessed systematically in pediatric TBI research. Findings of the current review suggest that pain assessment in children post-TBI needs improvement, given that pain is linked to worse recovery, poorer quality of life, and can be long-lasting. More rigorous examination of nonheadache pain and its role in impeding recovery in children post-TBI is imperative and has the potential to improve the care and management of children with TBI. We conclude with recommendations for pain assessment, discuss gaps in the literature, and highlight directions for future research.
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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 | 0.007 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".