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Natural Progression of Symptom Change and Recovery From Concussion in a Pediatric Population

2018· article· en· W2900109014 on OpenAlexafffundabout
Andrée‐Anne Ledoux, Ken Tang, Keith Owen Yeates, Martin Pusic, Kathy Boutis, William Craig, Jocelyn Gravel, Stephen B. Freedman, Isabelle Gagnon, Gérard A. Gioia, Martin H. Osmond, Roger Zemek

Bibliographic record

VenueJAMA Pediatrics · 2018
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of OttawaMontreal Children's HospitalUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineStollery Children's HospitalHospital for Sick ChildrenAlberta Children's HospitalMcGill UniversityChildren's Hospital of Eastern OntarioUniversity of CalgaryHotchkiss Brain Institute
FundersCanadian Institutes of Health Research
KeywordsConcussionMedicinePopulationPediatricsProspective cohort studyCohortCohort studyPhysical therapyInjury preventionPoison controlEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

Importance: The natural progression of symptom change and recovery remains poorly defined in children after concussion. Objectives: To describe the natural progression of symptom change by age group (5-7, 8-12, and 13-18 years) and sex, as well as to develop centile curves to inform families about children after injury recovery. Design, Setting, and Participants: Planned secondary analysis of a prospective multicenter cohort study (Predicting Persistent Postconcussive Problems in Pediatrics). The setting was 9 pediatric emergency departments within the Pediatric Emergency Research Canada (PERC) network. Participants were aged 5 to 18 years with acute concussion, enrolled from August 1, 2013, to May 31, 2015, and data analyses were performed between January 2018 and March 2018. Exposures: Participants had a concussion consistent with the Zurich Consensus Statement on Concussion in Sport diagnostic criteria and 85% completeness of the Postconcussion Symptom Inventory (PCSI) at each time point. Main Outcomes and Measures: The primary outcome was symptom change, defined as current rating minus preinjury rating (delta score), at presentation and 1, 2, 4, 8, and 12 weeks after injury, measured using the PCSI. Symptoms were self-rated for ages 8 to 18 years and rated by the child and parent for ages 5 to 7 years. The secondary outcome was recovery, defined as no change in symptoms relative to current preinjury PCSI ratings (delta score = 0). Mixed-effects models incorporated the total score, adjusting for random effects (site and participant variability), fixed-effects indicators (age, sex, time, age by time interaction, and sex by time interaction), and variables associated with recovery. Recovery centile curves by age and sex were computed. Results: A total of 3063 children (median age, 12.0 years [interquartile range, 9.2-14.6 years]; 60.7% male) completed the primary outcome; 2716 were included in the primary outcome analysis. For the group aged 5 to 7 years, symptom change primarily occurred the first week after injury; by 2 weeks, 75.6% of symptoms had improved (PCSI change between 0 and 2 weeks, -5.3; 95% CI, -5.5 to -5.0). For the groups aged 8 to 12 years and 13 to 18 years, symptom change was prominent the first 2 weeks but flattened between 2 and 4 weeks. By 4 weeks, 83.6% and 86.2% of symptoms, respectively, had improved for the groups aged 8 to 12 years (PCSI change between 0 and 4 weeks, -9.0; 95% CI, -9.6 to -8.4) and 13 to 18 years (PCSI change between 0 and 4 weeks, -28.6; 95% CI, -30.8 to -26.3). Sex by time interaction was significant only for the adolescent group (β = 0.32; 95% CI, 0.21-0.43; P < .001). Most adolescent girls had not recovered by week 12. Conclusions and Relevance: Symptom improvement primarily occurs in the first 2 weeks after concussion in children and in the first 4 weeks after concussion in preadolescents and male adolescents. Female adolescents appear to have protracted recovery. The derived recovery curves may be useful for evidence-based anticipatory guidance.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.053
GPT teacher head0.345
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations196
Published2018
Admission routes3
Has abstractyes

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