Potential for Lung Recruitment Estimated by the Recruitment-to-Inflation Ratio in Acute Respiratory Distress Syndrome. A Clinical Trial
Bibliographic record
Abstract
Abstract Rationale Response to positive end-expiratory pressure (PEEP) in acute respiratory distress syndrome depends on recruitability. We propose a bedside approach to estimate recruitability accounting for the presence of complete airway closure. Objectives To validate a single-breath method for measuring recruited volume and test whether it differentiates patients with different responses to PEEP. Methods Patients with acute respiratory distress syndrome were ventilated at 15 and 5 cm H2O of PEEP. Multiple pressure–volume curves were compared with a single-breath technique. Abruptly releasing PEEP (from 15 to 5 cm H2O) increases expired volume: the difference between this volume and the volume predicted by compliance at low PEEP (or above airway opening pressure) estimated the recruited volume by PEEP. This recruited volume divided by the effective pressure change gave the compliance of the recruited lung; the ratio of this compliance to the compliance at low PEEP gave the recruitment-to-inflation ratio. Response to PEEP was compared between high and low recruiters based on this ratio. Measurements and Main Results Forty-five patients were enrolled. Four patients had airway closure higher than high PEEP, and thus recruitment could not be assessed. In others, recruited volume measured by the experimental and the reference methods were strongly correlated (R2 = 0.798; P < 0.0001) with small bias (−21 ml). The recruitment-to-inflation ratio (median, 0.5; range, 0–2.0) correlated with both oxygenation at low PEEP and the oxygenation response; at PEEP 15, high recruiters had better oxygenation (P = 0.004), whereas low recruiters experienced lower systolic arterial pressure (P = 0.008). Conclusions A single-breath method quantifies recruited volume. The recruitment-to-inflation ratio might help to characterize lung recruitability at the bedside. Clinical trial registered with www.clinicaltrials.gov (NCT02457741).
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".