A Study of the Physiologic Responses to a Lung Recruitment Maneuver in Acute Lung Injury and Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
OBJECTIVE: To determine the magnitude, duration, and consistency of the effects of lung recruitment maneuvers (RMs) on oxygenation, lung mechanics, and comfort in patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). METHODS: We conducted a prospective physiologic study at 3 tertiary-care hospitals. We enrolled 28 consecutive eligible patients with ARDS or ALI and a ratio of P(aO(2)) to fraction of inspired oxygen (P(aO(2))/F(IO(2))) or= 0.50. We performed RMs twice daily for 3 days. The first RM was at 35 cm H(2)O for 20 s. If initial response was equivocal, the clinician immediately administered another RM at a higher pressure (40 cm H(2)O, then 45 cm H(2)O) or for longer period (30 s, then 40 s), in a randomized order. Each patient had up to 6 sets of up to 3 RMs. RESULTS: Twenty-seven patients met the criteria for ARDS at baseline; 1 had ALI. There was no net effect on oxygenation or pulmonary mechanics following the first or subsequent RMs. The largest rise in P(aO(2)) was from 61 mm Hg to 71 mm Hg, and the largest decrease was 6 mm Hg following the first RM. Augmenting the inflation pressure or duration had no significant effect. These findings precluded analyses about predictors of response or consistency of response. Over the entire study of 122 RMs, 5 patients developed ventilator asynchrony, 3 appeared uncomfortable, 2 experienced transient hypotension, and 4 developed barotrauma that required intervention. CONCLUSIONS: These results do not support the addition of scheduled RMs to usual treatment for ALI or ARDS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".