MétaCan
Menu
Back to cohort
Record W3003318480 · doi:10.1111/apa.15196

Epidemiology of severe paediatric trauma following winter sport accidents

2020· article· en· W3003318480 on OpenAlexaff
Emilien Maisonneuve, Nadia Roumeliotis, Amélie Basso, Damien Venchiarutti, Cécile Vallot, C. Ricard, Pierre Bouzat, Guillaume Mortamet

Bibliographic record

VenueActa Paediatrica · 2020
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineEpidemiologyPoison controlInjury preventionOccupational safety and healthInjury Severity ScoreIntensive care unitRetrospective cohort studyEmergency medicinePhysical therapyPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

AIM: This study describes the epidemiology of severe injuries related to winter sports (skiing, snowboarding and sledding) in children and assesses potential preventive actions. METHODS: A single-centre retrospective study performed at Pediatric or Adult Intensive Care Unit in the French Alps. All patients less than 15 years old, admitted to the Intensive Care Unit following a skiing, snowboarding or sledding accident from 2011 to 2018, were included. RESULTS: We included 186 patients (mean age 10.6 years and 68% were male); of which 136 (73%), 21 (11%) and 29 (16%) had skiing, snowboarding and sledding accidents, respectively. The average ISS (injury severity score) was 16. The major lesions were head (n = 94 patients, 51%) and intra-abdominal (n = 56 patients, 30%) injuries. Compared to skiing/snowboarding, sledding accidents affected younger children (7 vs 11 years, P < .001); most of whom did not wear a helmet (89% vs 8%, P < .001). Severity scores were statistically different amongst winter sports (ISS = 16 (IQR 9-24) for skiing, 9 (IQR 4-16) for snowboarding and 16 (IQR 13-20) for sledding accident, P = .02). CONCLUSION: Winter sports can cause severe trauma in children. Sledding accidents affect younger children that may benefit from wearing protective equipment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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.

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".

Quick stats

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueActa PaediatricaSame topicWinter Sports Injuries and PerformanceFrench-language works237,207