Serum bilirubin and chronic obstructive pulmonary disease (COPD): a systematic review
Bibliographic record
Abstract
Abstract Background Bilirubin is a potent antioxidant and higher serum bilirubin levels have been associated with improved COPD outcomes. We performed a systematic review to evaluate the association between serum bilirubin levels and lung function (FEV1), prevalence/incidence of COPD, acute exacerbations of COPD, respiratory health status, and mortality. Methods MEDLINE® and Embase were searched using Ovid® (search updated October 1st, 2019). We included studies that measured serum bilirubin levels and outcomes of interest in adults with or without underlying lung disease. We excluded studies of those with liver disease or drug-induced elevations in bilirubin. We used the Newcastle–Ottawa scale to assess individual study risk of bias (ROB) and the US Agency for Healthcare Research and Quality—Evidence Based Practice tool to assess overall strength of evidence (SOE). Two authors independently determined eligibility, performed data abstraction, assessed ROB, and determined SOE. Results Thirteen studies (5 low risk of bias, 3 moderate and 5 high risk) were included. We found low strength of evidence for the association between higher bilirubin levels and lower risk of acute exacerbations of COPD (2 studies), mortality (3 studies), COPD diagnosis (4 studies), and lung function (FEV1) (8 studies). We found insufficient evidence on the relationship between serum bilirubin and respiratory health status/exercise capacity (1 study) and airflow obstruction (FEV1/FVC ratio) (4 studies). Conclusion Higher bilirubin levels may be associated with lower mortality and improved COPD outcomes. Randomized trials are needed to evaluate the effect of medications that raise serum bilirubin on COPD outcomes. PROSPERO registration: CRD42019145747.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".