Successful Implementation of a Neonatal Pain and Sedation Protocol at 2 NICUs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the implementation of a neonatal pain and sedation protocol at 2 ICUs. METHODS: The intervention started with the evaluation of local practice, problems, and staff satisfaction. We then developed and implemented the Vienna Protocol for Neonatal Pain and Sedation. The protocol included well-defined strategies for both nonpharmacologic and pharmacologic interventions based on regular assessment of a translated version of the Neonatal Pain Agitation and Sedation Scale and titration of analgesic and sedative therapy according to aim scores. Health care staff was trained in the assessment by using a video-based tutorial and bedside teaching. In addition, we performed reevaluation, retraining, and random quality checks. Frequency and quality of assessments, pharmacologic therapy, duration of mechanical ventilation, and outcome were compared between baseline (12 months before implementation) and 12 months after implementation. RESULTS: Cumulative median (interquartile range) opiate dose (baseline dose of 1.4 [0.5-5.9] mg/kg versus intervention group dose of 2.7 [0.4-57] mg/kg morphine equivalents; P = .002), pharmacologic interventions per episode of continuous sedation/analgesia (4 [2-10] vs 6 [2-13]; P = .005), and overall staff satisfaction (physicians: 31% vs 89%; P < .001; nurses: 17% vs 55%; P < .001) increased after implementation. Time on mechanical ventilation, length of stay at the ICU, and adverse outcomes were similar before and after implementation. CONCLUSIONS: Implementation of a neonatal pain and sedation protocol at 2 ICUs resulted in an increase in opiate prescription, pharmacologic interventions, and staff satisfaction without affecting time on mechanical ventilation, length of intensive care stay, and adverse outcomes.
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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 | 0.038 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".