63 Antibiotic Choices by Pediatric Residents and Recently Graduated Pediatricians in Common Infectious Disease Problems in Children
Bibliographic record
Abstract
Antibiotics are commonly used in pediatrics in both community and hospital settings. To date, no study has examined antibiotic choices in Canada or in the USA by Pediatric Residents (PR) and recently graduated Pediatricians (RGP). To describe the antibiotic choices made by PR and RGP for common infectious disease problems in children. PR who are currently involved in 13 Canadian Pediatric Post-Graduate Programs and RGP practicing in Canada for less than 5 years were mailed a questionnaire describing 10 common pediatric infectious disease clinical scenarios. 251/552 (45.5%) participants completed the survey of which 129/273 were PR (47.3%) and 122/279 (43.7%) were RGP. The following results were found in clinical cases where practice guidelines exist: No statistical differences were seen in levels of training or region for the above scenarios. However, in the use of high dose amoxicillin in Otitis Media, a significant difference was seen by level of training in the PR group (p<.05). Other scenarios yielded more variations in practice. For example, 38 different antibiotic combinations were suggested by PR and RGP in the case of febrile neutropenia. In a clinical presentation of meningitis, 36% of respondents reported using steroids with no significant difference found amongst levels of training or region. In common infectious disease problems in children, where practice guidelines exist, there was a consensus regarding antibiotic choices amongst Pediatric Residents and recently graduated Pediatricians in Canada. Level of training and region of practice do not appear to be significant factors in the choice of therapy for most common scenarios. Conditions with less published evidence or where the evidence is controversial show more variation in practice pattern.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".