Burden of asthma and COPD overlap (ACO) in Taiwan: a nationwide population-based study
Bibliographic record
Abstract
BACKGROUND: Patients with symptoms of both asthma and chronic obstructive pulmonary disease (COPD) may be classified with the term asthma-COPD overlap (ACO). ACO is of considerable interest as it is currently poorly characterised and has been associated with worse health outcomes and higher healthcare costs compared with COPD or asthma alone. Patients with ACO in Asia remain poorly described, and there is limited information regarding their resource utilisation compared with patients with asthma or COPD only. This study investigated the characteristics, disease burden and medical resource utilisation of patients with ACO in Taiwan. METHODS: This was a retrospective cohort study of patients identified from National Health Insurance (NHI) claims data in Taiwan in 2009-2011. Patients were classified into incident ACO, COPD or asthma cohorts according to International Classification of Disease, ninth revision, clinical modification codes in claims. Eligible patients were ≥40 years of age with 12 months' continuous enrolment in the NHI programme pre- and post-index date (date of the first relevant medical claim). RESULTS: -agonist combination prescriptions ranged from 11.1% (COPD cohort) to 35.0% (ACO cohort) in the 12 months following index. Patients with ACO generally had the highest medication costs of any cohort (long-acting muscarinic antagonist costs ranged from $227/patient [asthma cohort] to $349/patient [ACO cohort]); they also experienced more respiratory-related hospital visits than patients with asthma or COPD (mean outpatient/inpatient visits per patient post-index: 9.1/1.9 [ACO cohort] vs 5.7/1.4 [asthma cohort] and 6.4/1.7 [COPD cohort]). CONCLUSIONS: Patients with ACO in Taiwan experience a greater disease burden with greater healthcare resource utilisation, and higher costs, than patients with asthma or COPD alone.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".