Clinical review: Ventilator-induced diaphragmatic dysfunction - human studies confirm animal model findings!
Bibliographic record
Abstract
Diaphragmatic function is a major determinant of the ability to successfully wean patients from mechanical ventilation. However, the use of controlled mechanical ventilation in animal models results in a major reduction of diaphragmatic force-generating capacity together with structural injury and atrophy of diaphragm muscle fibers, a condition termed ventilator-induced diaphragmatic dysfunction (VIDD). Increased oxidative stress and exaggerated proteolysis in the diaphragm have been linked to the development of VIDD in animal models, but much less is known about the extent to which these phenomena occur in humans undergoing mechanical ventilation in the ICU. In the present review, we first briefly summarize the large body of evidence demonstrating the existence of VIDD in animal models, and outline the major cellular mechanisms that have been implicated in this process. We then relate these findings to very recently published data in critically ill patients, which have thus far been found to exhibit a remarkable degree of similarity with the animal model data. Hence, the human studies to date have indicated that mechanical ventilation is associated with increased oxidative stress, atrophy, and injury of diaphragmatic muscle fibers along with a rapid loss of diaphragmatic force production. These changes are, to a large extent, directly proportional to the duration of mechanical ventilation. In the context of these human data, we also review the methods that can be used in the clinical setting to diagnose and/or monitor the development of VIDD in critically ill patients. Finally, we discuss the potential for using different mechanical ventilation strategies and pharmacological approaches to prevent and/or to treat VIDD and suggest promising avenues for future research in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".