Effect of high-flow nasal cannula oxygen therapy in adults with acute hypoxemic respiratory failure: a meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Conflicting recommendations exist on whether high-flow nasal cannula (HFNC) oxygen therapy should be administered to adult patients in critical care with acute hypoxemic respiratory failure. We performed a meta-analysis of randomized controlled trials (RCTs) to evaluate its effect on intubation rates. METHODS: We searched electronic databases from inception to April 2016. We included RCTs that compared HFNC oxygen therapy with usual care (conventional oxygen therapy or noninvasive ventilation) in adults with acute hypoxemic respiratory failure. Because of the different methodologies and variation in clinical outcomes, we conducted 2 subgroup analyses according to oxygen therapy used and disease severity. We pooled data using random-effects models. The primary outcome was the proportion of patients who required endotracheal intubation. RESULTS: We included 6 RCTs (n = 1892). Compared with conventional oxygen therapy, HFNC oxygen therapy was associated with a lower intubation rate (risk ratio [RR] 0.60, 95% confidence interval [CI] 0.38 to 0.94; I2 = 49%). We found no significant difference in the rate between HFNC oxygen therapy and noninvasive ventilation (RR 0.86, 95% CI 0.68 to 1.09; I2 = 2%). In the subgroup analysis by disease severity, no significant differences were found in the intubation rate between HFNC oxygen therapy and either conventional oxygen therapy or noninvasive ventilation (interaction p = 0.3 and 0.4, respectively). INTERPRETATION: The intubation rate with HFNC oxygen therapy was lower than the rate with conventional oxygen therapy and similar to the rate with noninvasive ventilation among patients with acute hypoxemic respiratory failure. Larger, high-quality RCTs are needed to confirm these findings.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.048 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".