Impact of dexmedetomidine in conjunction with a weaning protocol on post‐surgical opioid use in a neonatal intensive care unit
Bibliographic record
Abstract
STUDY OBJECTIVE: To describe the impact of protocol-driven dexmedetomidine (and clonidine) use on opioid exposure in post-surgical neonates. DESIGN: Retrospective chart review. SETTING: A Level III, surgical NICU. PATIENTS: Surgical neonates who received clonidine or dexmedetomidine concomitantly with an opioid for sedation and/or analgesia post-operatively. INTERVENTION: Implementation of a standardized sedation/analgesia weaning protocol. MEASUREMENTS AND MAIN RESULTS: There were clinically, although not statistically, significant reductions in opioid wean duration (240 vs. 227 h, p = 0.82), total opioid duration (604 vs. 435 h, p = 0.23), and total opioid exposure (91 vs. 51 mg ME/kg, p = 0.13), and limited impact on NICU outcomes or pain/withdrawal scores with use of the protocol. Increases in use of medications in alignment with the protocol (e.g., scheduled acetaminophen and opioids weaned first) were noted. CONCLUSIONS: We have been unable to demonstrate a reduction in opioid exposure with use of alpha-2 agonists alone; addition of a weaning protocol showed a reduction in opioid duration and exposure (although not statistically significant). At this point, dexmedetomidine and clonidine should not be introduced outside standardized protocols with scheduled acetaminophen post-operatively.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".