Effect of high‐flow nasal oxygen on hypoxaemia during procedural sedation: a systematic review and meta‐analysis
Bibliographic record
Abstract
Summary We conducted a systematic review to evaluate the effect of high‐flow nasal oxygen and conventional oxygen therapy during procedural sedation amongst adults and children. We searched MEDLINE, EMBASE and CINAHL for randomised controlled trials that reported the effects of high‐flow nasal oxygen during procedural sedation. The primary outcome measure was hypoxaemia and the secondary outcomes were minimum oxygen saturation; hypercarbia; requirement for airway manoeuvres; and procedure interruptions. The quality of evidence was assessed using the revised Cochrane risk‐of bias tool and grading of recommendations, assessment, development and evaluation (GRADE). Nineteen randomised controlled trials (4121 patients) including three in children were included. Administration of high‐flow nasal oxygen reduced hypoxaemia, risk ratio (95%CI) 0.37 (0.24–0.56), p < 0.001; minor airway manoeuvre requirements, risk ratio (95%CI) 0.26 (0.11–0.59), p < 0.001; procedural interruptions, risk ratio (95%CI) 0.17 (0.05–0.53), p = 0.002; and increased minimum oxygen saturation, mean difference (95%CI) 4.1 (2.70–5.50), p < 0.001; as compared with the control group. High‐flow nasal oxygen had no impact on hypercarbia, risk ratio (95%CI) 1.24 (0.97–1.58), p = 0.09, I 2 = 0%. High‐flow nasal oxygen reduced the incidence of hypoxaemia regardless of the procedure involved, degree of fractional inspired oxygen, risk‐profile of patients and mode of propofol administration. The evidence was ascertained as moderate for all outcomes except for procedure interruptions. In summary, high‐flow nasal oxygen compared with conventional oxygenation techniques reduced the risk of hypoxaemia, increased minimum oxygen saturation and reduced the requirement for airway manoeuvres. High‐flow nasal oxygen should be considered in patients at risk of hypoxaemia during procedural sedation.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.024 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".