Posttraumatic headache and clinical recovery after pediatric concussion
Bibliographic record
Abstract
Abstract Objective: To examine the association of posttraumatic headache (PTH) type with postconcussive symptoms (PCS), pain intensity, and fluid cognitive function across recovery after pediatric concussion. Methods: This prospective, longitudinal study recruited children (aged 8–16.99 years) within 24 hours of sustaining a concussion or mild orthopedic injury (OI) from two pediatric hospital emergency departments. Based on parent-proxy ratings of pre- and postinjury headache, children were classified as concussion with no PTH ( n = 18), new PTH ( n = 43), worse PTH ( n = 58), or non-worsening chronic PTH ( n = 19), and children with OI with no PTH ( n = 58). Children and parents rated PCS and children rated pain intensity weekly up to 6 months. Children completed computerized testing of fluid cognition 10 days, 3 months, and 6- months postinjury. Mixed effects models compared groups across time on PCS, pain intensity, and cognition, controlling for preinjury scores and covariates. Results: Group differences in PCS decreased over time. Cognitive and somatic PCS were higher in new, chronic, and worse PTH relative to no PTH (up to 8 weeks postinjury; d = 0.34 to 0.87 when significant) and OI (up to 5 weeks postinjury; d = 0.30 to 1.28 when significant). Pain intensity did not differ by group but declined with time postinjury. Fluid cognition was lower across time in chronic PTH versus no PTH ( d = −0.76) and OI ( d = −0.61) and in new PTH versus no PTH ( d = −0.51). Conclusions: Onset of PTH was associated with worse PCS up to 8 weeks after pediatric concussion. Chronic PTH and new PTH were associated with moderately poorer fluid cognitive functioning up to 6 months postinjury. Pain declined over time regardless of PTH type.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".