Development of Hospital-Based Guidelines for Skeletal Survey in Young Children With Bruises
Bibliographic record
Abstract
OBJECTIVE: To develop guidelines for performing an initial skeletal survey (SS) for children <24 months of age presenting with bruising in the hospital setting, combining available evidence with expert opinion. METHODS: Applying the Rand/UCLA Appropriateness Method, a multispecialty panel of 10 experts relied on evidence from the literature and their own clinical expertise in rating the appropriateness of performing SS for 198 clinical scenarios characterizing children <24 months old with bruising. After a moderated discussion of initial ratings, the scenarios were revised. Panelists re-rated SS appropriateness for 219 revised scenarios. For the 136 clinical scenarios in which SS was deemed appropriate, the panel finally assessed the necessity of SS. RESULTS: Panelists agreed that SS is "appropriate" for 62% (136/219) of scenarios, and "inappropriate" for children ≥ 12 months old with nonpatterned bruising on bony prominences. Panelists agreed that SS is "necessary" for 95% (129/136) of the appropriate scenarios. SS was deemed necessary for infants <6 months old regardless of bruise location, with rare exceptions, but the necessity of SS in older children depends on bruise location. According to the panelists, bruising on the cheek, eye area, ear, neck, upper arm, upper leg, hand, foot, torso, buttock, or genital area necessitates SS in children <12 months. CONCLUSIONS: The appropriateness and necessity of SS in children presenting for care to the hospital setting with bruising, as determined by a diverse panel of experts, depends on age of the child and location of bruising.
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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 | 0.055 | 0.169 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".