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Record W1988047978 · doi:10.1136/ip.2010.029215.550

Emergency Department presentations for injuries related to cribs

2010· article· en· W1988047978 on OpenAlexaffabout
Steven McFaull, S. Rachel Skinner, M. Herbert

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsMedicinePoison controlInjury preventionOccupational safety and healthInjury surveillanceMedical emergencySuicide preventionEmergency medicineEmergency departmentHuman factors and ergonomicsPediatrics

Abstract

fetched live from OpenAlex

Introduction Safe design and use of cribs is fundamental to infant safety. Because international coding (ICD) does not specify crib-related injuries, few surveillance systems provide data to study these injuries. Methods The Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) collects information on injuries treated in the emergency departments of 11 paediatric and 3 general hospitals. Its database was used to study crib-related injuries to children under 5 years of age, 1990–2007. Results 3201 cases were identified. The proportion of crib cases among all CHIRPP injuries remained relatively constant over time. The median age was 16 months (IQR, 1023 months). The male to female ratio was 1.2:1. Falls out of cribs accounted for 75% of injuries followed by body part entrapment (7.2%), accessing hazardous objects (2.3%) and crib malfunction (<1%). Head/face/neck injuries occurred in 56% of cases and among these half were closed head injuries. A novel scale was developed to classify the severity of these injuries; the majority (82.5%) were minor, 5.2% moderate and 1.4% serious/fatal. In this study 4.5% of infants were admitted to hospital and there was one death (suffocation related to bedding materials). Discussion Although Canada introduced product standards for cribs before 1990 (updates pending), crib-related injuries continue to occur. Injuries could be reduced through review/enforcement of standards, and, vigilance by parents regarding: correct installation and maintenance of approved cribs, minimising bedding and removing extra objects, removing hazards around the crib, and, discontinuing use when a child can climb out.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.025
GPT teacher head0.403
Teacher spread0.377 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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