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Record W2113837763 · doi:10.1136/ip.2010.029215.239

Prevention of severe injuries in preschool children: what are the priorities?

2010· article· en· W2113837763 on OpenAlexaboutno aff
Chantal Cyr

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsInjury preventionMedicinePoison controlOccupational safety and healthGlasgow Coma ScaleStairsSuicide preventionRetrospective cohort studyInjury Severity ScoreEmergency medicineHuman factors and ergonomicsPediatric traumaPediatricsMedical emergencyPhysical therapySurgery

Abstract

fetched live from OpenAlex

Injury is the leading cause of death in childhood. Most of these injuries are preventable events. With limited resources, strategies for prevention should target severe injuries and be based on developmental stage. The aim of this study was to characterise mechanisms of severe injuries in children aged 1 to 4 years old. Methods Retrospective review of trauma registry of two paediatric trauma centres in Quebec between January 1999 and April 2006. The Injury Prevention Priority Score (IPPS) and Injury Severity Score (ISS) assigned a priority rank to mechanisms of severe injuries based on frequency and on severity. Results A total of 640 children 1 to 4 years old with severe injury were identified. Glasgow coma score (GCS) was 7 or less in 33 patients (5%) and mean length of stay was 6.4 days. There were 15 deaths (2.3%). IPPS identified respectively Fall from height, Motor vehicle injuries, Child abuses, Pedestrians struck by motor vehicle and Cycle injuries as the most important mechanisms. The majority of falls occurred at home, mostly in stairs. Less than 30% of victims of motor vehicle accident were adequately restrained. There were 11 all-terrain vehicle-related injuries as a driver or a passenger even in children less than 4 years of age. Conclusion This study highlights mechanisms that can be targeted by community prevention programs to fight injuries with the highest mortality and morbidity in 1 to 4 years old children.

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)0.002
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 score0.132
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.318
Teacher spread0.305 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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