Response to Ventilator Adjustments for Predicting Acute Respiratory Distress Syndrome Mortality. Driving Pressure versus Oxygenation
Bibliographic record
Abstract
Abstract Rationale Clinicians commonly use short-term physiologic markers to assess the benefit of ventilator adjustments. Improved arterial oxygen tension/pressure (PaO2)/fraction of inspired oxygen (Fi O2) after ventilator adjustment in acute respiratory distress syndrome is associated with lower mortality. However, as driving pressure (ΔP) reflects lung stress and strain, changes in ΔP may more accurately reflect benefits or harms of ventilator adjustments compared with changes in oxygenation. Objectives We aimed to compare the association between mortality and the changes in PaO2/Fi O2 and ΔP following protocolized ventilator changes. Methods We assessed associations between mortality and changes in PaO2/Fi O2 (ΔPaO2/Fi O2) and ΔP (ΔΔP) after postrandomization positive end-expiratory pressure (PEEP) and tidal volume adjustment in reanalyses of the ALVEOLI (Assessment of Low Tidal Volume and Elevated End-Expiratory Volume to Obviate Lung Injury) and ExPress (Expiratory Pressure) trials. We included subjects with available pre- and postintervention PaO2/Fi O2 and ΔP (372 in ALVEOLI and 596 in ExPress). In each separate trial cohort, we performed multivariable Cox regression testing the association between ΔPaO2/Fi O2 and ΔΔP with mortality. Results In ALVEOLI, when analyzed as separate variables, ΔPaO2/Fi O2 was associated with mortality only in subjects in whom PEEP increased, whereas ΔΔP was associated with mortality irrespective of direction of PEEP change. When modeled together, improved ΔPaO2/Fi O2 was not associated with mortality, whereas ΔΔP remained associated with mortality (adjusted hazard ratio [aHR], 1.50 per 5 cm H2O increase; 95% confidence interval [95% CI], 1.21–1.85). When modeled together in ExPress, ΔΔP (aHR, 1.42; 95% CI, 1.14–1.78) was more strongly associated with mortality than ΔPaO2/Fi O2 (aHR, 0.95 per 25 mm Hg increase; 95% CI, 0.90–1.00). Conclusions Reduced ΔP following protocolized ventilator changes was more strongly and consistently associated with lower mortality than was increased PaO2/Fi O2, making ΔΔP more informative about benefit from ventilator adjustments. Our results reinforce the primacy of ΔP, rather than oxygenation, as the key variable associated with outcome.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".