Cigarette smoking as a risk factor for acute respiratory distress syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Numerous experimental studies have linked cigarette smoking to lung injury. However, it is still debated on whether cigarette smoking is a risk factor for the development of acute lung injury/acute respiratory distress syndrome (ALI/ARDS). The study aimed to solve the controversy by performing systematic review and meta-analysis. Methods: Electronic databases including PubMed, Google scholar, Embase and Scopus were searched from inception to April 2014. Studies investigated the association of cigarette smoking and ALI/ARDS were included. Non-randomized studies were assessment for their methodological quality by using Newcastle-Ottawa scale. Meta-analysis was performed by using random effects model and subgroup analyses were performed to address the clinical heterogeneity. Publication bias was assessed by using Egger’s test. Results: Of the 17 studies included in the analysis, 15 provided data on effect size and were meta-analyzable. Component studies involved heterogeneous populations including major surgery, trauma, septic shock, general population, influenza A infection and transfusion. The combined results showed that cigarette smoking was not a risk factor for the development of ALI/ARDS [odds ratio (OR): 1.00, 95% confidence interval (CI): 0.99–1.01]. In subgroup analysis, the same result was obtained in general population (OR: 2.03, 95% CI: 0.06–4.01), patients with major surgery or trauma (OR: 1.20, 95% CI: 0.48–1.93) and patients with other risks of ALI/ARDS (OR: 1.00, 95% CI: 0.99–1.01). Conclusions: The study demonstrates that cigarette smoking is not associated with increased risk of ALI/ARDS in critically ill patients. However, the relationship in general population is still controversial and requires further confirmation.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".