Variation in clinical practice guidelines for use of palivizumab in preventing severe respiratory syncytial viral (RSV) disease in high‐risk infants
Bibliographic record
Abstract
BACKGROUND: Uniformity and compliance with clinical practice guidelines (CPGs) for use of palivizumab in preventing severe respiratory syncytial viral infection in Australian high-risk infants remain unclear. METHODS: An online survey was conducted across the Australian and New Zealand Neonatal Network (ANZNN) to determine clinical practices around palivizumab. A literature search was also performed to identify and compare national and international guidelines. RESULTS: A total of 65 of 422 ANZNN members completed the survey. Respondents included 61 senior medical staff of consultants/staff specialists (78%) and four nursing staff (6%). According to the survey, infants most likely to be recommended palivizumab included preterm infants born <29 weeks gestational age (GA) (30%), children with chronic lung diseases (CLDs) born <32 weeks GA (40%), and with hemodynamically significant heart disease (35%). Many of the respondents (53%) stated that CPGs for palivizumab were developed locally. Literature search identified 20 guidelines (10 international and 10 domestic); 16 (80%) recommended palivizumab use in preterm infants, 16 (80%) recommended use in infants with CLD, 17 (85%) in congenital heart disease and 6 (30%) in bronchopulmonary dysplasia (BPD). Eight (40%) guidelines provided specific recommendations for immunocompromised infants. Canada, Western Australia, and American Academy of Paediatrics provided recommendations for Indigenous children. Frequency and dosage of palivizumab was universal across all CPGs. None of the international guidelines obtained were from low- or middle-income countries. CONCLUSIONS: Standardization of CPGs may improve clinical decision making around use of palivizumab in high-risk infants.
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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 | 0.043 | 0.151 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".