Prevalence and Risk Factors of ACO (Asthma-COPD Overlap) in Aboriginal People
Bibliographic record
Abstract
Background and Objective. Aboriginal peoples are at a higher risk of many chronic respiratory diseases compared to the general Canadian population. Patients with asthma-COPD overlap (ACO), a disease newly described in 2015, are associated with frequent exacerbations, rapid decline in lung function, poor quality of life, high mortality, and disproportionate utilization of health-care resources than patients with asthma and COPD alone. The objective was to investigate the prevalence and risk factors of ACO in Aboriginal peoples.Methods. Data from the 2012 Aboriginal Peoples Survey (APS) were used for this study. The ACO definition was based on the respondent giving positive responses to both of the following questions“Do you/Does (name) have Asthma diagnosed by a health professional?”and“Do you/Does (name) have chronic bronchitis, emphysema or chronic pulmonary obstructive disease or COPD diagnosed by a health professional?” Results. Aboriginal peoples older than 45 years, women, widowed, separated, or divorced, having a total personal income below $20,000 were associated with a significant risk of ACO. Residing in Ontario, being a daily smoker, living in a rented dwelling, dwelling in need of major repairs, having diabetes, and working more than 40 hrs a week were also significantly associated with increased risk of ACO.Conclusion. The results from this study will provide information to aid the development of prevention and intervention strategies for Aboriginal communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".