Asthma and COPD Overlap Syndrome (ACOS): A Systematic Review and Meta Analysis
Bibliographic record
Abstract
BACKGROUND: The combination of asthma and chronic obstructive pulmonary disease (COPD), or ACOS is a recently defined syndrome. The epidemiology of the condition is poorly described and previous research has suggested ACOS is associated with worse outcomes than either condition alone. We therefore decided to complete a systematic review of the published literature. METHODS: This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta- Analyses guidelines. A structured search was performed in the PubMed, Embase, and Medline databases up to Feb 2015 to identify studies reporting incidence, prevalence, health care utilization, morbidity, or mortality in COPD and asthma. RESULTS: A total of 19 studies were included in the present study. The pooled prevalence of overlap among COPD was 27% (95% CI: 0.16-0.38, p<0.0001) and 28% (95% CI: 0.09-0.47, p = 0.0032) in the population and hospital-based studies, respectively. We found no significant difference between ACOS and COPD in terms of gender, smoking status, lung function and 6mWD. However, in comparison to subject with only COPD, ACOS subjects were significantly younger, had higher BMI, healthcare utilization, and lower HRQoL. CONCLUSION: ACOS is a common condition that exists in a substantial proportion of subjects with COPD. ACOS represents a distinct clinical phenotype with more frequent exacerbations, hospitalization, worse health-related quality of life, and higher healthcare costs than either disease alone. There is a critical need to better define the management and treatment of this syndrome.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| 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) | 0.004 | 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".