Helmet noninvasive ventilation compared to facemask noninvasive ventilation and high-flow nasal cannula in acute respiratory failure: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although small randomised controlled trials (RCTs) and observational studies have examined helmet noninvasive ventilation (NIV), uncertainty remains regarding its role. We conducted a systematic review and meta-analysis to examine the effect of helmet NIV compared to facemask NIV or high-flow nasal cannula (HFNC) in acute respiratory failure. METHODS: We searched multiple databases to identify RCTs and observational studies reporting on at least one of mortality, intubation, intensive care unit (ICU) length of stay, NIV duration, complications or comfort with NIV therapy. We assessed study risk of bias using the Cochrane Risk of Bias 2 tool for RCTs and the Ottawa-Newcastle Scale for observational studies, and rated certainty of pooled evidence using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) framework. RESULTS: We separately pooled data from 16 RCTs (n=949) and eight observational studies (n=396). Compared to facemask NIV, based on low certainty of evidence, helmet NIV may reduce mortality (relative risk 0.56, 95% CI 0.33-0.95) and intubation (relative risk 0.35, 95% CI 0.22-0.56) in both hypoxic and hypercapnic respiratory failure, but may have no effect on duration of NIV. There was an uncertain effect of helmet NIV on ICU length of stay and development of pressure sores. Data from observational studies were consistent with the foregoing findings but of lower certainty. Based on low and very low certainty data, helmet NIV may reduce intubation compared to HFNC, but its effect on mortality is uncertain. CONCLUSIONS: Compared to facemask NIV, helmet NIV may reduce mortality and intubation; however, the effect of helmet NIV compared to HFNC remains uncertain.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".