Delayed Identification of Pediatric Abuse-Related Fractures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Because physicians may have difficulty distinguishing accidental fractures from those that are caused by abuse, abusive fractures may be at risk for delayed recognition; therefore, the primary objective of this study was to determine how frequently abusive fractures were missed by physicians during previous examinations. A secondary objective was to determine clinical predictors that are associated with unrecognized abuse. METHODS: Children who were younger than 3 years and presented to a large academic children's hospital from January 1993 to December 2007 and received a diagnosis of abusive fractures by a multidisciplinary child protective team were included in this retrospective review. The main outcome measures included the proportion of children who had abusive fractures and had at least 1 previous physician visit with diagnosis of abuse not identified and predictors that were independently associated with missed abuse. RESULTS: Of 258 patients with abusive fractures, 54 (20.9%) had at least 1 previous physician visit at which abuse was missed. The median time to correct diagnosis from the first visit was 8 days (minimum: 1; maximum: 160). Independent predictors of missed abuse were male gender, extremity versus axially located fracture, and presentation to a primary care setting versus pediatric emergency department or to a general versus pediatric emergency department. CONCLUSIONS: One fifth of children with abuse-related fractures are missed during the initial medical visit. In particular, boys who present to a primary care or a general emergency department setting with an extremity fracture are at a particularly high risk for delayed diagnosis.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it