High-flow nasal Oxygen with or without alternating helmet Non-invasive ventilation for Oxygenation sUpport in acute Respiratory failure (HONOUR): a protocol for a pilot randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Acute hypoxaemic respiratory failure is a common reason for intensive care unit (ICU) admission. Non-invasive respiratory support strategies such as high-flow nasal oxygen (HFNO) and helmet non-invasive ventilation may reduce the need for invasive mechanical ventilation and death. The High-flow nasal Oxygen with or without alternating helmet Non-invasive ventilation for Oxygenation sUpport in acute Respiratory failure pilot trial is designed to compare helmet non-invasive ventilation combined with HFNO vs HFNO alone in patients with acute hypoxaemic respiratory failure and to determine the feasibility of a larger randomised controlled trial. METHODS AND ANALYSIS: This is a pragmatic, open-label, multicentre randomised controlled pilot trial enrolling 200 critically ill adults with acute hypoxaemic respiratory failure across 12 Canadian ICUs. Participants are randomised 1 to 1 to receive either helmet non-invasive ventilation plus HFNO or HFNO alone for at least 48 hours. The primary aim is to assess feasibility metrics including recruitment rate, protocol adherence and fidelity to pre-specified intubation criteria. Secondary outcomes include rates of intubation, all-cause mortality, ventilator-free days, ICU length of stay and quality of life at 6 months. Primary and secondary outcomes will be analysed using Bayesian methods. ETHICS AND DISSEMINATION: Ethics approval has been obtained at all participating centres. Findings will inform the feasibility and design of a future full-scale trial and be disseminated through peer review publications and conference presentations. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT05078034.
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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 | 0.074 | 0.065 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.082 | 0.017 |
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".