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Record W2980801638 · doi:10.1177/0009922819879457

Concussion Management for Children Has Changed: New Pediatric Protocols Using the Latest Evidence

2019· article· en· W2980801638 on OpenAlexaff
Carol DeMatteo, Sarah Randall, Katie Falla, Chia-Yu Lin, Lucy Giglia, Michael F. Mazurek, Eric Koelink

Bibliographic record

VenueClinical Pediatrics · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcMaster University Medical CentreMcMaster Children's HospitalMcMaster University
Fundersnot available
KeywordsMedicineConcussionProtocol (science)CohortInjury preventionPhysical therapyPoison controlMedical emergencyAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Return to activity (RTA) and return to school (RTS) are important issues in pediatric concussion management. This study aims to update CanChild's 2015 RTA and RTS protocols, on the basis of empirical data and feedback collected from our recently completed prospective cohort study, focusing on concussed children and their caregivers; systematic review of evidence published since 2015; and consultation with concussion management experts. The new protocols highlight differences from the earlier versions, mainly, (1) symptom strata to allow quicker progression for those who recover most quickly; (2) a shortened rest period (24-48 hours) accompanied by symptom-guided activity; (3) the recommendation that children progress through the stages before they are symptom free, if symptoms have decreased and do not worsen with activity; (4) specific activity suggestions at each stage of the RTA protocol; (5) recommendations for the amount of time to spend per stage; and (6) integration of RTS and RTA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.129
metaresearch head score (Gemma)0.256
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.129
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1290.256
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0060.005
Science and technology studies0.0010.002
Scholarly communication0.0060.007
Open science0.0040.006
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.430
GPT teacher head0.507
Teacher spread0.078 · 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 designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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