37 Pharmacokinetics of intravenous fentanyl in neonates, a systematic review
Bibliographic record
Abstract
Introduction Fentanyl is a frequently used analgesic in the neonatal intensive care unit (NICU). Its minimal effect on hemodynamic stability, and its apparent exemption from the effects of hepatic and renal illness make it an ideal candidate for use in critically ill neonates. Despite its common use, prescribing fentanyl remains off-label for the neonatal population. Our aim was to review the available pharmacokinetic data of fentanyl in neonates. Methodology In this systematic review we searched Ovid MEDLINE, the Cochrane Central Register of Controlled Trials and PubMed from inception to February 2023 for studies that included pharmacokinetic data on the use of intravenous (IV) fentanyl in neonates. We did not apply language or study design limitations. Animal studies and duplicate records were excluded. Two reviewers screened and extracted data. The ROBINS-I was used to assess the risk of bias of individual studies.Results Seven prospective observational studies containing pharmacokinetic data regarding the use of IV fentanyl in 208 neonates up to and including a postconceptional age of 44 weeks were included. Studies included 30 (15%) term and 173 (85%) preterm with GA (min, max) of 23–42.3 weeks and postnatal age (min, max) of 1–71 days. Postnatal age and gestational age were identified as covariates of importance contributing to the interindividual pharmacokinetic variability of IV fentanyl. One study applied a population pharmacokinetic model to recommend gestational age and postnatal age-based dosing. Conclusions Pharmacokinetic data of IV fentanyl in neonates, although limited, is available and can be applied to the use of this drug in neonatal patients. This data needs to be presented in the prescription labelling for enhanced knowledge translation and to achieve optimal safety-efficacy balance in use of this drug. Future research on pharmacokinetics-pharmacodynamic relationship of IV fentanyl in the neonatal population will pave the way toward an individualized approach to therapeutic dosing among these vulnerable neonates.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".