Complications From Recruitment Maneuvers in Patients With Acute Lung Injury: Secondary Analysis From the Lung Open Ventilation Study
Bibliographic record
Abstract
BACKGROUND: There are limited data on the safety and efficacy of recruitment maneuvers (RMs) in acute lung injury (ALI) patients. OBJECTIVE: To evaluate the frequency, timing, and risk factors for complications from RMs in adult ALI patients. METHODS: Secondary analysis of data from a randomized controlled trial of a lung open ventilation strategy that included sustained inflation RMs. RESULTS: Respiratory (eg, desaturation) and cardiovascular (eg, hypotension) complications from recruitment maneuvers were common (22% of all patients receiving RMs), and the majority occurred within 7 days of enrollment. New air leak through an existing chest tube was uncommon (< 5%). As compared to patients receiving 1 or fewer RMs, the number of RMs received was associated with increased risk in both younger (age ≤ 56 y) and older patients (age > 56 y): 2 RMs odds ratio [OR] 6.92 (95% CI 1.70-28.2), ≥ 3 RMs OR 15.4 (95% CI 4.77-49.6), and 2 RMs OR 5.43 (95% CI 1.76-16.8), ≥ 3 RMs OR 4.93 (95% CI 1.78-13.7), respectively. Patients with extrapulmonary ALI had decreased odds of developing complications (OR 0.42, 95% CI 0.22-0.80). CONCLUSIONS: Complications in adult ALI patients receiving RMs were common, but serious complications (eg, new air leak through an existing chest tube) were infrequent. There is a significant association between the number of RMs received and complications, even after controlling for illness severity and duration. Given their uncertain benefit in ALI patients, and the potential for complications with repeated application, the routine use of sustained inflation RMs is not justified.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".