Management of neonatal jaundice varies by practitioner type.
Bibliographic record
Abstract
OBJECTIVE: To survey current practices among different types of medical practitioners in Ontario to assess if national guidelines for screening and management of neonatal hyperbilirubinemia were being followed. DESIGN: An anonymized, cross-sectional survey distributed by mail and e-mail. SETTING: Ontario. PARTICIPANTS: From each group (general practitioners, family medicine practitioners, and pediatricians), 500 participants were randomly selected, and all 390 registered midwives were selected. MAIN OUTCOME MEASURES: Compliance with national guidelines for screening, postdischarge follow-up, and management of newborns with hyperbilirubinemia. RESULTS: Of the 1890 potential respondents, 321 (17%) completed the survey. Only 41% of family physicians reported using national guidelines, compared with 75% and 69% of pediatricians and midwives, respectively (P < .001). Bilirubin was routinely measured for all newborns before discharge by 42% of family physicians, 63% of pediatricians, and 22% of midwives (P < .001). Newborn follow-up was completed within 72 hours after discharge by 60% of family physicians, 89% of pediatricians, and 100% of midwives. Management of neonatal hyperbilirubinemia differed significantly (P < .001), with 91% of family physicians, 99% of pediatricians, and 79% of midwives correctly managing a case scenario according to the guidelines. CONCLUSION: The management of jaundice varied considerably among the different practitioner types, with pediatricians both most aware of the guidelines and most likely to follow them. Increased knowledge translation efforts are required to promote adherence to the jaundice management guidelines across all practitioner types, but particularly among family physicians.
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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 | 0.000 | 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) | 0.002 | 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".