Implementing Protocol-Based Therapy of Continuous Neuromuscular Blockade Provides Cost Minimization
Bibliographic record
Abstract
Objective: To compare empiric and protocol-based therapies of neuromuscular blockade in terms of cost and control of paralysis. Methods: Data were prospectively collected for nine months before and five months after a protocol was implemented in the 24-bed medical/surgical/neurologic intensive care unit as a physician-initiated, doublesided medication order form. Pancuronium was the preferred agent and vecuronium was an alternative for patients with renal dysfunction, hepatic dysfunction, or hemodynamic instability. Results: Twenty-nine empiric-therapy patients and 17 protocol-based therapy patients were comparatively evaluated. Length of stay in the intensive care unit and duration of neuromuscular blockade were similar between groups. Protocol adherence rate was 76.5%. Protocol-based therapy increased the hourly dose of pancuronium (0.29 ± 0.37 mg vs. 0.02 ± 0.10 mg; p < 0.005) and reduced the mean hourly cost of neuromuscular blockade compared with empiric therapy ($5.11 ± 4.76 Canadian [CDN] vs. $9.03 ± 7.03 CDN; p < 0.05). Vecuronium use did not change, but rocuronium and atracurium were not given after protocol implementation. The proportion of recorded train-of-four measurements representing adequate neuromuscular blockade increased (52.3% vs. 32.7%; p < 0.05) with protocol-based therapy. Conclusions: Compliance with a neuromuscular blocking protocol reduces drug costs and improves control of neuromuscular blockade.
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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 | 0.008 | 0.028 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".