High-Flow Nasal Oxygen for Severe Hypoxemia: Oxygenation Response and Outcome in Patients with COVID-19
Bibliographic record
Abstract
Abstract Rationale The “Berlin definition” of acute respiratory distress syndrome (ARDS) does not allow inclusion of patients receiving high-flow nasal oxygen (HFNO). However, several articles have proposed that criteria for defining ARDS should be broadened to allow inclusion of patients receiving HFNO. Objectives To compare the proportion of patients fulfilling ARDS criteria during HFNO and soon after intubation, and 28-day mortality between patients treated exclusively with HFNO and patients transitioned from HFNO to invasive mechanical ventilation (IMV). Methods From previously published studies, we analyzed patients with coronavirus disease (COVID-19) who had PaO2/Fi O2 of ⩽300 while treated with ⩾40 L/min HFNO, or noninvasive ventilation (NIV) with positive end-expiratory pressure of ⩾5 cm H2O (comparator). In patients transitioned from HFNO/NIV to invasive mechanical ventilation (IMV), we compared ARDS severity during HFNO/NIV and soon after IMV. We compared 28-day mortality in patients treated exclusively with HFNO/NIV versus patients transitioned to IMV. Measurements and Main Results We analyzed 184 and 131 patients receiving HFNO or NIV, respectively. A total of 112 HFNO and 69 NIV patients transitioned to IMV. Of those, 104 (92.9%) patients on HFNO and 66 (95.7%) on NIV continued to have PaO2/Fi O2 ⩽300 under IMV. Twenty-eight-day mortality in patients who remained on HFNO was 4.2% (3/72), whereas in patients transitioned from HFNO to IMV, it was 28.6% (32/112) (P < 0.001). Twenty-eight-day mortality in patients who remained on NIV was 1.6% (1/62), whereas in patients who transitioned from NIV to IMV, it was 44.9% (31/69) (P < 0.001). Overall mortality was 19.0% (35/184) and 24.4% (32/131) for HFNO and NIV, respectively (P = 0.2479). Conclusions Broadening the ARDS definition to include patients on HFNO with PaO2/Fi O2 ⩽300 may identify patients at earlier stages of disease but with lower mortality.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".