Canadian Neonatologist Practices Regarding Opioid Use in Ventilated and Spontaneously Breathing Infants Undergoing Medical Procedures
Bibliographic record
Abstract
OBJECTIVES: Opioids are indicated for the management of procedural pain in neonates. There are limited data describing factors influencing patterns of use. PATIENTS AND METHODS: We conducted an online English survey of Canadian neonatologists using Survey Monkey, whereby they answered questions about the frequency and pattern of use of opioids, and specifically, of morphine and fentanyl, for ventilated and spontaneously breathing infants undergoing selected painful medical procedures. RESULTS: Hundred and twenty nine of 225 (57%) eligible neonatologists participated. They reported that opioids were part of their practice for managing procedural pain in 100% of ventilated infants and 93% of spontaneously breathing infants. Frequency of opioid use was associated with infant ventilation status: spontaneously breathing infants were 28% less likely to receive them (P=0.013). For morphine, the most commonly used dose was 100 microg/kg in ventilated infants and 50 microg/kg in spontaneously breathing infants. For fentanyl, 1 microg/kg was the most frequently used dose in both infant populations. Use of morphine and fentanyl were significantly associated with 2-way interactions (P<0.0001) between infant ventilation status, gestational age, and opioid dose. Eighty-two percent of respondents cited respiratory depression as a concern for spontaneously breathing infants compared with 31% for ventilated infants (P<0.0001). CONCLUSIONS: Neonatologists frequently report using opioids to manage procedural pain, however, spontaneously breathing infants are less likely to receive them, and their use varies according to infant and procedure characteristics. These data point to the need to further investigate, in a more controlled design, the pharmacologic effects of opioids in this population to better guide clinicians about their optimal use.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".