The Beta Agonist Lung Injury Trial Prevention. A Randomized Controlled Trial
Bibliographic record
Abstract
RATIONALE: Experimental studies suggest that pretreatment with β-agonists might prevent acute lung injury (ALI). OBJECTIVES: To determine if in adult patients undergoing elective esophagectomy, perioperative treatment with inhaled β-agonists effects the development of early ALI. METHODS: We conducted a randomized placebo-controlled trial in 12 UK centers (2008-2011). Adult patients undergoing elective esophagectomy were allocated to prerandomized, sequentially numbered treatment packs containing inhaled salmeterol (100 μg twice daily) or a matching placebo. Patients, clinicians, and researchers were masked to treatment allocation. The primary outcome was development of ALI within 72 hours of surgery. Secondary outcomes were ALI within 28 days, organ failure, adverse events, survival, and health-related quality of life. An exploratory substudy measured biomarkers of alveolar-capillary inflammation and injury. MEASUREMENTS AND MAIN RESULTS: A total of 179 patients were randomized to salmeterol and 183 to placebo. Baseline characteristics were similar. Treatment with salmeterol did not prevent early lung injury (32 [19.2%] of 168 vs. 27 [16.0%] of 170; odds ratio [OR], 1.25; 95% confidence interval [CI], 0.71-2.22). There was no difference in organ failure, survival, or health-related quality of life. Adverse events were less frequent in the salmeterol group (55 vs. 70; OR, 0.63; 95% CI, 0.39-0.99), predominantly because of a lower number of pneumonia (7 vs. 17; OR, 0.39; 95% CI, 0.16-0.96). Salmeterol reduced some biomarkers of alveolar inflammation and epithelial injury. CONCLUSION: Perioperative treatment with inhaled salmeterol was well tolerated but did not prevent ALI. Clinical trial registered with International Standard Randomized Controlled Trial Register (ISRCTN47481946) and European Union database of randomized Controlled Trials (EudraCT 2007-004096-19).
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".