Bibliographic record
Abstract
BACKGROUND: Evidence suggests that minor paediatric fractures can be followed by primary care paediatricians (PCPs). OBJECTIVES: To determine PCP opinions, knowledge and perceived barriers to managing minor paediatric fractures in the office. METHODS: An online survey was sent between June and September 2013 to all paediatricians who subscribed to the American Academy of Pediatrics PROS-Net Listerv and to those who were registered with the Scott's Canadian Medical Directory as paediatricians who treated children in a primary care capacity. The primary outcome was the proportion of PCPs who agreed with PCP follow-up of minor paediatric fractures. Secondary outcomes included PCP's perceived barriers to office follow-up. RESULTS: A total of 1752 surveys were sent; 1235 were eligible and 459 (37.2%) responded to the survey. Overall, 296 (69.5% [95% CI 65.2% to 74.0%]) PCPs agreed that minor paediatric fractures could be followed in a PCP office. The most frequently reported barriers were lack of materials to replace immobilization (58.1%), PCP knowledge deficits (44.8%) and a perceived parental preference for an orthopedic surgeon (38.6%). Finally, 58.8% of respondents believed that further education was necessary if PCPs assumed responsibility for follow-up of midshaft clavicle fractures, while 66.5% and 77.1% (P<0.0001) believed this was necessary for distal radius buckle and fibular fractures, respectively. CONCLUSIONS: More than two-thirds of responding PCPs in Canada and the United States agreed that minor common paediatric fractures can be followed-up by paediatricians. However, PCPs reported some barriers to this management strategy, including a desire for more education on this topic.
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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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".