Mechanical Ventilation Management during Extracorporeal Membrane Oxygenation for Acute Respiratory Distress Syndrome. An International Multicenter Prospective Cohort
Bibliographic record
Abstract
Abstract Rationale Current practices regarding mechanical ventilation in patients treated with extracorporeal membrane oxygenation (ECMO) for acute respiratory distress syndrome are unknown. Objectives To report current practices regarding mechanical ventilation in patients treated with ECMO for severe acute respiratory distress syndrome (ARDS) and their association with 6-month outcomes. Methods This was an international, multicenter, prospective cohort study of patients undergoing ECMO for ARDS during a 1-year period in 23 international ICUs. Measurements and Main Results We collected demographics, daily pre- and per-ECMO mechanical ventilation settings and use of adjunctive therapies, ICU, and 6-month outcome data for 350 patients (mean ± SD pre-ECMO PaO2/FiO2 71 ± 34 mm Hg). Pre-ECMO use of prone positioning and neuromuscular blockers were 26% and 62%, respectively. Vt (6.4 ± 2.0 vs. 3.7 ± 2.0 ml/kg), plateau pressure (32 ± 7 vs. 24 ± 7 cm H2O), driving pressure (20 ± 7 vs. 14 ± 4 cm H2O), respiratory rate (26 ± 8 vs. 14 ± 6 breaths/min), and mechanical power (26.1 ± 12.7 vs. 6.6 ± 4.8 J/min) were markedly reduced after ECMO initiation. Six-month survival was 61%. No association was found between ventilator settings during the first 2 days of ECMO and survival in multivariable analysis. A time-varying Cox model retained older age, higher fluid balance, higher lactate, and more need for renal-replacement therapy along the ECMO course as being independently associated with 6-month mortality. A higher Vt and lower driving pressure (likely markers of static compliance improvement) across the ECMO course were also associated with better outcomes. Conclusions Ultraprotective lung ventilation on ECMO was largely adopted across medium– to high–case volume ECMO centers. In contrast with previous observations, mechanical ventilation settings during ECMO did not impact patients’ prognosis in this context.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".