Expiratory muscle dysfunction in critically ill patients: towards improved understanding
Bibliographic record
Abstract
INTRODUCTION: This narrative review summarizes current knowledge on the physiology and pathophysiology of expiratory muscle function in ICU patients, as shared by academic professionals from multidisciplinary, multinational backgrounds, who include clinicians, clinical physiologists and basic physiologists. RESULTS: The expiratory muscles, which include the abdominal wall muscles and some of the rib cage muscles, are an important component of the respiratory muscle pump and are recruited in the presence of high respiratory load or low inspiratory muscle capacity. Recruitment of the expiratory muscles may have beneficial effects, including reduction in end-expiratory lung volume, reduction in transpulmonary pressure and increased inspiratory muscle capacity. However, severe weakness of the expiratory muscles may develop in ICU patients and is associated with worse outcomes, including difficult ventilator weaning and impaired airway clearance. Several techniques are available to assess expiratory muscle function in the critically ill patient, including gastric pressure and ultrasound. CONCLUSION: The expiratory muscles are the "neglected component" of the respiratory muscle pump. Expiratory muscles are frequently recruited in critically ill ventilated patients, but a fundamental understanding of expiratory muscle function is still lacking in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".