Reverse Triggering during Venovenous Extracorporeal Membrane Oxygenation: Magnitude of the Reverse Triggering Effort Mediated by Inspiratory Pressure
Bibliographic record
Abstract
An 18-year-old woman was intubated for severe vaping-associated lung injury resulting in an extreme obstructive pulmonary disease with the shedding of bronchial epithelial tissue. She was on pressurecontrolled ventilation (4 mL/kg IBW, respiratory rate 10/min) and veno-venous extracorporeal membrane oxygenation (VV-ECMO; settings: blood flow 3.7 L/min, sweep gas flow (SGF) 4.5 L/min, FiO2 100%) because of severe hypercapnia and barotrauma pneumomediastinum) to provide lung rest for the epithelial tissue to regenerate. On day 5 of VV-ECMO and with high-dose sedation with propofol, midazolam, sufentanyl and ketamine (Richmond Agitation and Sedation Scale score -5) and low-dose neuromuscular blockade, she demonstrated reverse triggering (RT)[1,2](Fig.1). Esophageal pressure (Pes) monitoring was used aiming to achieve lung- and diaphragm-protective targets[3] for effort and transpulmonary driving pressures (PL) by modifying ventilator pressure (Ppeak), SGF or set respiratory rate. With sedation and other settings kept constant, increasing Ppeak reduced the magnitude of RT efforts; however, the resultant dynamic PL increased (Fig.1). Adjusting SGF (4.5–6 –8 L/min) did not alter the magnitude or rate of RT efforts (∆Pes remained constant at 13.7±1.0 cmH2O for all conditions). Changing the set rate (applied range 6–18/min) changed the RT pattern in a nonpredictable manner. Phase-locking was constant across RT breaths during all conditions. Increasing PEEP as potential modifiable factor of effort[4] was not studied to limit the risks of hyperinflation in this patient. RT is complex and a multitude of factors can mediate respiratory entrainment[1]. Our unique observation during VV-ECMO suggests that the magnitude of RT efforts was mediated by lung/chest wall receptors upon passive insufflation (Hering-Breuer reflex), and not by CO2 (no influence of different SGFs). It also highlights the importance of quantifying effort during RT. Because of the high lung stress during RT, rocuronium was increased to resume fully-controlled ventilation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".