Integrated Pulmonary Index during nurse‐administered procedural sedation: Study protocol for a cluster‐randomized trial
Bibliographic record
Abstract
AIM: To determine if smart alarm-guided treatment of respiratory depression using the Integrated Pulmonary Index is an effective way to implement capnography during nurse-administered sedation. DESIGN: Parallel cluster-randomized trial. METHODS: Nurses will be randomized to use capnography with or without the Integrated Pulmonary Index enabled. Capnography alarm performance will be compared between nurses using capnography alone or with the Integrated Pulmonary Index enabled. The target sample size is 400 adult patients scheduled for elective procedures with nurse-administered sedation. The primary outcome is the number of seconds in an alert condition state without an intervention being applied. Secondary outcomes are alarm burden, number of appropriate alarms, number of inappropriate alarms, total duration of alert conditions, choice of alarm settings and adverse sedation events. This study has been funded since April 2021. DISCUSSION: Implementing capnography into practice for respiratory monitoring during nurse-administered sedation is considered a high priority. The Integrated Pulmonary Index shows promise as a strategy to optimize the implementation of capnography for respiratory monitoring during nurse-administered sedation. If it is found in this study that using the Integrated Pulmonary Index improves the nursing management of physiologically abnormal states during nurse-administered sedation, it would provide the high-level evidence needed to support broader use of this 'smart alarm' strategy for respiratory monitoring in practice. IMPACT: With advances in medical technology continuing to expand the indications for minimally invasive surgical techniques, the use of nurse-administered sedation during medical procedures is likely to expand in the future. The findings may be applied to other populations receiving nurse-administered sedation during medical procedures. Results from this study will help translate the usage of smart alarm-guided treatment of respiratory depression during procedural sedation. TRIAL REGISTRATION: NCT05068700.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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 teacher head, 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".