High flow nasal oxygen during procedural sedation for cardiac implantable electronic device procedures
Bibliographic record
Abstract
BACKGROUND: High flow nasal oxygen may better support the vulnerable respiratory state of patients during procedural sedation. OBJECTIVE: The objective of this study was to investigate the effects of high flow nasal oxygen in comparison to facemask oxygen on ventilation during cardiac implantable electronic device procedures performed with procedural sedation. DESIGN: A randomised controlled trial. SETTING: The study was conducted at one academic hospital in Canada. PARTICIPANTS: Adults undergoing elective cardiac implantable electronic device procedures with sedation administered by an anaesthesia assistant, supervised by an anaesthesiologist from August 2019 to March 2020. INTERVENTIONS: Participants were randomised 1 : 1 to facemask (≥ 8 l · min-1) or high flow nasal oxygen (50 l · min-1 and a 50 : 50 oxygen to air ratio). MAIN OUTCOME MEASURES: The primary outcome was peak transcutaneous carbon dioxide. Outcomes were analysed using Bayesian statistics. RESULTS: The 129 participants who were randomised and received sedation were included. The difference in peak transcutaneous carbon dioxide was 0.0 kPa (95% CI -0.17 to 0.18). Minor adverse sedation events were 6.4 times more likely to occur in the high flow nasal oxygen group. This estimate is imprecise (95% CI 1.34 to 42.99). The odds ratio for oxygen desaturation for the high flow nasal oxygen group compared with the facemask group was 1.2 (95% CI 0.37 to 3.75). The difference in satisfaction with sedation scores between groups was 0.0 (95% CI -0.33 to 0.23). CONCLUSIONS: Ventilation, as measured by TcCO2, is highly unlikely to differ by a clinically important amount between high flow nasal oxygen at 50 l min-1 or facemask oxygen at 8 l min-1. Further research with a larger sample size would be required to determine the optimal oxygen:air ratio when using high flow nasal oxygen during cardiac implantable electronic device procedures performed with sedation. TRIAL REGISTRATION NUMBER: NCT03858257.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".