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Record W2169705716 · doi:10.1136/emj.19.4.311

Whiplash associated disorder in children attending the emergency department

2002· article· en· W2169705716 on OpenAlexaboutno aff
Rhonda C. Boyd

Bibliographic record

VenueEmergency Medicine Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency departmentIncidence (geometry)Injury preventionPoison controlOccupational safety and healthWhiplashPediatricsCrashProspective cohort studySuicide preventionEmergency medicinePhysical therapyPsychiatrySurgery

Abstract

fetched live from OpenAlex

AIMS: To determine the incidence, severity, and clinical course of whiplash associated disorder (WAD) in children aged 4-16 years involved as passengers in car crashes. METHODS: Prospective surveillance of all paediatric attendances to three English urban emergency departments after car crashes over an eight month period. An initial structured telephone interview at day 2 after the car crash was performed. This was followed by clinical review of symptomatic patients on day 5 after the crash using the Quebec Task Force criteria for outcome assessment, with subsequent clinical review at 14, 28, and 56 days or until earlier symptom resolution. RESULTS: 105 children were identified as having been involved in car crashes as passengers. Forty nine children (47%) experienced symptoms of a WAD. Twenty nine children developed symptoms within 24 hours with the remainder developing symptoms by 48 hours. Forty children experienced a WAD grade 1 and nine children suffered a WAD grade 2 injury. The mean duration of symptoms was 8.8 days (range 3-70, SD 10.7). WAD grade 2 symptoms lasted significantly longer than WAD grade 1 symptoms. CONCLUSIONS: The incidence of WAD in children in this series was higher than in other studies. The clinical course was more favourable than that reported for adults.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1750.000

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 head0.033
GPT teacher head0.306
Teacher spread0.273 · 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 teacher head, not a consensus.

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".

Quick stats

Citations23
Published2002
Admission routes1
Has abstractyes

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