Monitoring and Controlling Respiratory Effort in Acute Hypoxemic Respiratory Failure
Bibliographic record
Abstract
Ventilation and sedation are used to manage acute hypoxemic respiratory failure (AHRF), but their individual and interactive effects on respiratory effort (|∆Pes|) and lung-distending pressure (∆PL,dyn) are unknown. This is a secondary analysis of a trial of a lung- and diaphragm-protection strategy in patients with AHRF, where ventilator settings and sedation were systematically manipulated to optimize |∆Pes| and ∆PL,dyn. The study showed that propofol attenuates |∆Pes| and ∆PL,dyn. Sedation with fentanyl was associated with lower respiratory drive, but not with lower respiratory effort. Increasing inspiratory pressure also attenuated |∆Pes|, but not ∆PL,dyn. The effect of inspiratory pressure varied according to the propofol dose: increasing inspiratory pressure resulted in higher ∆PL,dyn in patients receiving higher propofol dose. Patients on VV-ECMO had lower |∆Pes| and required lower propofol dose to control respiratory effort. This study highlights the complex interactions between interventions to modulate respiratory effort and provides insights on optimal management strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".