Inhaled beta-2 agonist salbutamol and acute lung injury: an association with improvement in acute lung injury
Bibliographic record
Abstract
INTRODUCTION: Beta2 agonists have several properties that could be beneficial in acute lung injury (ALI). We therefore chose to study the effect of inhaled beta2 agonist use (salbutamol) on duration and severity of ALI. METHODS: We undertook a retrospective chart review of 86 consecutive mechanically ventilated patients with ALI, who had varying exposure to inhaled salbutamol. The cohort was divided into two groups according to the average daily dose of inhaled salbutamol they received ('high dose' > or = 2.2 mg/day and 'low dose' < 2.2 mg/day). Severity of ALI and non-pulmonary organ dysfunction was compared between the groups by calculating the days alive and free of ALI and other organ dysfunctions. RESULTS: The high dose and low dose groups received a mean of 3.72 mg and 0.64 mg salbutamol per day, respectively. The high dose salbutamol group had significantly more days alive and free of ALI than the low dose group (12.2 +/- 4.4 days versus 7.6 +/- 1.9 days, p = 0.02). There were no associations between dose of beta agonist and non-pulmonary organ dysfunctions. High dose salbutamol (p = 0.04), APACHE II score (p = 0.02), and cause of ALI (p = 0.02) were independent variables associated with number of days alive and free of ALI in a multivariate linear regression model. CONCLUSION: Our retrospective study suggests that salbutamol, an inhaled beta2 agonist, is associated with a shorter duration and lower severity of ALI. A dose greater than 2.2 mg/day of inhaled salbutamol could be a minimal effective dose to evaluate in a randomized controlled trial.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".