Bench-to-bedside review: high-frequency oscillatory ventilation in adults with acute respiratory distress syndrome.
Bibliographic record
Abstract
Mechanical ventilation is the cornerstone of therapy for patients with acute respiratory distress syndrome (ARDS). Paradoxically, mechanical ventilation can exacerbate lung damage--a phenomenon known as ventilator-induced lung injury. While new ventilation strategies have reduced the mortality rate in patients with ARDS, this mortality rate still remains high. High-frequency oscillatory ventilation (HFOV) is an unconventional form of ventilation that may improve oxygenation in patients with ARDS, while limiting further lung injury associated with high ventilatory pressures and volumes delivered during conventional ventilation. HFOV has been used for almost two decades in the neonatal population, but there is more limited experience with HFOV in the adult population. In adults, the majority of the published literature is in the form of small observational studies in which HFOV was used as 'rescue' therapy for patients with very severe ARDS who were failing conventional ventilation. Two prospective randomized controlled trials, however, while showing no mortality benefit, have suggested that HFOV, compared with conventional ventilation, is a safe and effective ventilation strategy for adults with ARDS. Several studies suggest that HFOV may improve outcomes if used early in the course of ARDS, or if used in certain populations. This review will summarize the evidence supporting the use of HFOV in adults with ARDS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".