Drugs for anesthesia and analgesia in the preterm infant
Bibliographic record
Abstract
INTRODUCTION: There is largely an absence of validated evidence-based therapies in term- and preterm newborn infants, due to a lack of pharmacological clinical trials. As a consequence, the drugs and doses used in clinical practice are extrapolated from dose-ranging trials performed in older patients. Drugs administered to the preterm infant are invariably off-label. The aim of this current review is to identify commonly used anesthetic and analgesic agents in this patient population, assess the existing evidence base, in terms of safety, efficacy, pharmacokinetics and pharmacodynamics, current indications and doses. EVIDENCE ACQUISITION: We searched the PubMed, Google Scholar, Web of Science, U.S. Food and Drug Administration and World Health Organization databases and analyzed any studies for general anesthesia; analgo-sedation; regional anesthesia; pharmacokinetics, pharmacodynamics and pharmacogenomics in this patient population. EVIDENCE SYNTHESIS: A total of 412 studies (meta-analysis, systematic reviews, randomized controlled trial (RCT), and observational) were identified and analyzed. CONCLUSIONS: Preterm infants are characterized by remarkable metabolic and developmental differences when compared with adults. It is not possible to derive guidelines or clinical recommendations based on the existing evidence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".