Emergency Department presentations for injuries related to cribs
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".