Mechanical ventilation in acute respiratory distress syndrome at ATS 2016: the search for a patient-specific strategy
Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) was first defined by Ashbaugh et al . in 1967 (1). They described 12 patients who developed the acute onset of hypoxemic respiratory failure, diffuse bilateral alveolar infiltrates, and low respiratory system compliance brought on by a variety of different insults. Decades of dedicated research have followed this initial description, yet ARDS remains a common critical illness with an exceptionally high mortality rate of 35–46% (2). At the 2016 American Thoracic Society (ATS) International Meeting, Dr. Brian Kavanagh, a Professor of Anesthesia from the University of Toronto, delivered a highly popular keynote speech addressing the role professional societies play in promoting universal management guidelines. He made several important points about the challenges and possible downsides to this strategy. This article reviews the potential for a more patient-specific approach to ARDS care based on presentations at the ATS meeting and the recent literature.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".