Effect of a nursing-implemented sedation protocol on weaning outcome*
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of the implementation of a nursing-driven protocol of sedation on duration of intubation. DESIGN: Before-and-after prospective study. SETTING: 18-bed medical-surgical intensive care unit. PATIENTS: Patients receiving mechanical ventilation longer than 48 hrs who were ready to wean. INTERVENTIONS: During the observational period, sedatives and analgesics were adjusted according to physicians' orders. During the intervention period, sedatives and analgesics were adjusted by nurses according to an algorithm-based sedation guideline, including a sedation scale. MEASUREMENTS AND MAIN RESULTS: A total of 356 patients were included in the study (176 patients in the observational period and 189 patients in the intervention period). There were no significant differences in the duration of intubation between the two periods (median, 7 [interquartile range, 5-13] days vs. 7 [interquartile range, 5-9] days). In a Kaplan-Meier analysis, the probability of successful extubation was higher during the intervention period than during the observational period (log-rank = 0.02). During the intervention period, patients were more awake without a significant increment in the nurse workload; however, there was no significant decrease in the total doses of sedatives and analgesics administered. CONCLUSIONS: The implementation of a nursing-driven protocol of sedation may improve the probability of successful extubation in a heterogeneous population of mechanically ventilated patients.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".