Impact of Reverse Triggering Dyssynchrony during Lung-Protective Ventilation on Diaphragm Function: An Experimental Model
Bibliographic record
Abstract
Abstract Rationale Reverse triggering dyssynchrony (RT) is a patient–ventilator interaction where a respiratory muscle contraction is triggered by a passive mechanical insufflation. Its impact on diaphragm structure and function is unknown. Objectives To establish an animal model of RT with lung injury receiving lung-protective ventilation and to assess its impact on the structure and function of the diaphragm. Methods Lung injury was induced by surfactant depletion and high-stress ventilation in 32 ventilated pigs. Animals were allocated to receive passive mechanical ventilation (Vt: 10 ml/kg; respiratory rate [RR]: 30–35 breaths/min; n = 8) or a more lung-protective strategy (Vt: 6–8 ml/kg; n = 24) with adjustments in RR to facilitate the occurrence of RT for 3 hours. Diaphragm function (transdiaphragmatic pressure [Pdi] during phrenic nerve stimulation [force/frequency curve]) and structure (biopsies) were assessed. The impact of RT on diaphragm function was analyzed according to the breathing effort assessed by the pressure–time product. Measurements and Main Results Compared with passive ventilation, the protective ventilation group with RT received significantly lower Vt (7 vs. 10 ml/kg) and higher RR (45 vs. 31 breaths/min). An entrainment pattern of 1:1 was the most frequently occurring in 83% of the animals. Breathing effort induced by RT was highly variable across animals. RT with the lowest tercile of breathing effort was associated with 23% higher twitch Pdi compared with passive ventilation, whereas RT with high breathing effort was associated with a 10% lower twitch Pdi and a higher proportion of abnormal muscle fibers. Conclusions In a reproducible animal model of RT with variable levels of breathing effort and entrainment patterns, RT with high effort is associated with impaired diaphragm function, whereas RT with low effort is associated with preserved diaphragm force.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".