End-tidal capnometry during emergency department procedural sedation and analgesia: a randomized, controlled study
Bibliographic record
Abstract
BACKGROUND: This prospective, randomized trial was undertaken to evaluate the utility of adding end-tidal capnometry (ETC) to pulse oximetry (PO) in patients undergoing procedural sedation and analgesia (PSA) in the emergency department (ED). METHODS: The patients were randomized to monitoring with or without ETC in addition to the current standard of care. Primary endpoints included respiratory adverse events, with secondary endpoints of level of sedation, hypotension, other PSA-related adverse events and patient satisfaction. RESULTS: Of 986 patients, 501 were randomized to usual care and 485 to additional ETC monitoring. In this series, 48% of the patients were female, with a mean age of 46 years. Orthopedic manipulations (71%), cardioversion (12%) and abscess incision and drainage (12%) were the most common procedures, and propofol and fentanyl were the sedative/analgesic combination used for most patients. There was no difference in patients experiencing de-saturation (SaO2<90%) between the two groups; however, patients in the ETC group were more likely to require airway repositioning (12.9% vs. 9.3%, P=0.003). Hypotension (SBP<100 mmHg or <85 mmHg if baseline <100 mmHg) was observed in 16 (3.3%) patients in the ETC group and 7 (1.4%) in the control group (P=0.048). CONCLUSIONS: The addition of ETC does not appear to change any clinically significant outcomes. We found an increased incidence of the use of airway repositioning maneuvers and hypotension in cases where ETC was used. We do not believe that ETC should be recommended as a standard of care for the monitoring of patients undergoing PSA.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".