Reverse Triggering during Controlled Ventilation: From Physiology to Clinical Management
Bibliographic record
Abstract
Reverse triggering dyssynchrony is a frequent phenomenon recently recognized in sedated critically ill patients under controlled ventilation. It occurs in at least 30-55% of these patients and often occurs in the transition from fully passive to assisted mechanical ventilation. During reverse triggering, patient inspiratory efforts start after the passive insufflation by mechanical breaths. The most often referred mechanism is the entrainment of the patient's intrinsic respiratory rhythm from the brainstem respiratory centers to periodic mechanical insufflations from the ventilator. However, reverse triggering might also occur because of local reflexes without involving the respiratory rhythm generator in the brainstem. Reverse triggering is observed during the acute phase of the disease, when patients may be susceptible to potential deleterious consequences of injurious or asynchronous efforts. Diagnosing reverse triggering might be challenging and can easily be missed. Inspection of ventilator waveforms or more sophisticated methods, such as the electrical activity of the diaphragm or esophageal pressure, can be used for diagnosis. The occurrence of reverse triggering might have clinical consequences. On the basis of physiological data, reverse triggering might be beneficial or injurious for the diaphragm and the lung, depending on the magnitude of the inspiratory effort. Reverse triggering can cause breath-stacking and loss of protective lung ventilation when triggering a second cycle. Little is known about how to manage patients with reverse triggering; however, available evidence can guide management on the basis of physiological principles.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".