Comparative safety and effectiveness of inhaled bronchodilators and corticosteroids for treating asthma–COPD overlap: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective To determine the safety and effectiveness of current pharmacotherapies consisting of long-acting beta2-agonist (LABA) and/or inhaled corticosteroids (ICS) in patients with asthma–COPD overlap.Data sources A systematic search was conducted using the PubMed, EMBASE, and Web of Science databases up to June 2018.Study selections Only studies comparing the safety and effectiveness of LABA and/or ICS in patients with asthma–COPD overlap were included. A meta-analysis was performed to calculate risk ratio (RR) and 95% confidence interval (CI) using Inverse Variance Random-effects model.Results From a total of 3382 articles retrieved, three randomized controlled trials (RCTs), six cohort studies (CS), one nested case control study fulfilled the inclusion criteria for three independent meta-analyses representing 181,603 participants. Three CS results show LABA was associated with decreased risk of myocardial infarction (combined RR: 0.80, 95% CI 0.74–0.87) versus non-LABA use; ICS/LABA was associated with a lower risk of death or hospitalization (combined RR: 0.82, 95% CI 0.75–0.90) compared to no use. Results from RCTs, no clear difference in lung function decline in FEV1 was found (combined mean difference: 0.08, 95% CI 0.15–0.32) in patients receiving ICS and/or LABA compared to placebo. However, due to lack of data, exacerbations, fractures and nontuberculous mycobacterial pulmonary disease outcomes were not meta-analyzed.Conclusions Among patients with asthma–COPD overlap, LABA is associated with decreased risk of myocardial infarction; and the combination therapy of ICS/LABA appears to reduce the risk of death or hospitalization. More studies of quality data and larger number of patients are needed.REGISTRATION PROSPERO (CRD42018090863).
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.044 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".