Response to Recruitment Maneuver Influences Net Alveolar Fluid Clearance in Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
BACKGROUND: Alveolar fluid clearance is impaired in the majority of patients with acute respiratory distress syndrome (ARDS). Experimental studies have shown that a reduction of tidal volume increases alveolar fluid clearance. This study was aimed at assessing the impact of the response to a recruitment maneuver (RM) on net alveolar fluid clearance. METHODS: In 15 patients with ARDS, pulmonary edema fluid and plasma protein concentrations were measured before and after an RM, consisting of a positive end-expiratory pressure maintained 10 cm H2O above the lower inflection point of the pressure-volume curve during 15 min. Cardiorespiratory parameters were measured at baseline (before RM) and 1 and 4 h later. RM-induced lung recruitment was measured using the pressure-volume curve method. Net alveolar fluid clearance was measured by measuring changes in bronchoalveolar protein concentrations before and after RM. RESULTS: In responders, defined as patients showing an RM-induced increase in arterial oxygen tension of 20% of baseline value or greater, net alveolar fluid clearance (19 +/- 13%/h) and significant alveolar recruitment (113 +/- 101 ml) were observed. In nonresponders, neither net alveolar fluid clearance (-24 +/- 11%/h) nor alveolar recruitment was measured. Responders and nonresponders differed only in terms of lung morphology: Responders had a diffuse loss of aeration, whereas nonresponders had a focal loss of aeration, predominating in the lower lobes. CONCLUSION: In the absence of alveolar recruitment and improvement in arterial oxygenation, RM decreases the rate of alveolar fluid clearance, suggesting that lung overinflation may be associated with epithelial dysfunction.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| 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".