Trends in COPD mortality and hospitalizations in countries and regions of Asia‐Pacific
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: The growing burden of COPD in the Asia-Pacific region supports the need for more intensive research and analysis of the epidemiology of COPD to raise awareness of the disease and its causes, to ensure the development of effective national health policies and to facilitate equitable deployment of finite health-care resources in the prevention and management of COPD. This study estimated and compared COPD mortality and hospital morbidity rates and trends in these rates over time across countries and regions of Asia-Pacific. METHODS: Data consistent with standard definitions of COPD (ICD-9/ICD-10) for the period 1991-2004 were obtained from national health statistics agencies. For countries/regions with complete national mortality and hospitalization data (Australia, Pacific Canada (British Columbia, Hong Kong, South Korea and Taiwan), annual age-standardized mortality and hospitalization rates were calculated for men and women aged >or= 40 years. Negative binomial regression modelling was used to estimate rate ratios for country/region, gender and age differences and general trends over time. RESULTS: Mortality rates per 10,000 population ranged 6.4-9.2 in men, 2.1-3.5 in women and 3.7-5.3 overall in 2003. Corresponding ranges for morbidity were 32.6-334.7, 21.2-129 and 28.1-207.3 per 10 000. Trend analysis of data since 1997 produced annual percentage changes in mortality versus hospitalization of -4.4% versus -0.7% in Australia, -3.6% versus 7.5% in Pacific Canada (British Columbia), -7.15% versus -5.6% in Hong Kong and -2.9% versus -4.2% in Taiwan. CONCLUSIONS: In Asia-Pacific, overall mortality and morbidity rates are high and trends in mortality and morbidity vary between countries/regions. Differences in rates and trends for men and women most likely reflect the different trends in historical and prevalent smoking profiles for COPD in the different countries and regions.
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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 | 0.002 |
| 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 | 0.000 |
| 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".