Elastance May Determine the Neuromuscular Blockade Effect on Mortality in Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
Abstract Rationale Patients with acute respiratory distress syndrome (ARDS) have a reduction in functional lung volume that results in increased respiratory system elastance (Ers); however, the extent of this increase varies by patient. Patients with high Ers are at risk of excess lung-distending pressures and may derive greater clinical benefit from neuromuscular blockade (NMB). Objectives We sought to evaluate whether the effect of early NMB administration on mortality varies according to baseline physiological and biological biomarkers of lung injury, including Ers. Methods We conducted a secondary analysis of the Reevaluation of Systemic Early Neuromuscular Blockade, or ROSE, trial. Bayesian logistic regression modeling was used to estimate the posterior probability of NMB effect moderation by baseline Ers, ventilatory ratio, and select ARDS plasma biomarkers on 90-day mortality. Measurements and Main Results The probability of mortality benefit with NMB increased substantially with higher baseline Ers (posterior probability of interaction, 92%; interaction odds ratio = 0.76; 90% credible interval = 0.59–0.99). In patients with an Ers ⩾2 cm H2O/(ml/kg), the posterior probability of benefit was 96% (median absolute risk reduction, 9%; 90% credible interval = 0.5–17.9). The effect of NMB did not vary meaningfully according to ventilatory ratio (posterior probability of interaction, 62%) or baseline plasma levels of receptor for advanced glycation end-products, tumor necrosis factor receptor-1, IL-6, or IL-8 (posterior probabilities of interaction: 12%, 18%, 44%, and 22% respectively). Conclusions These findings suggest that the mortality benefit of NMB varies with baseline Ers. High Ers may represent a physiological phenotype of acute respiratory distress syndrome. Future prospective testing to confirm benefit in this potentially treatment-responsive group is needed.
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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 | 0.026 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".