Cardiovascular disease mortality in the Americas: current trends and disparities
Bibliographic record
Abstract
OBJECTIVE: To describe the current situation and trends in mortality due to cardiovascular disease (CVD) in the Americas and explore their association with economic indicators. DESIGN AND SETTING: This time series study analysed mortality data from 21 countries in the region of the Americas from 2000 to the latest available year. MAIN OUTCOMES MEASURES: Age-adjusted death rates, annual variation in death rates. Regression analysis was used to estimate the annual variation and the association between age-adjusted rates and country income. RESULTS: Currently, CVD comprised 33.7% of all deaths in the Americas. Rates were higher in Guyana (292/100 000), Trinidad and Tobago (289/100 000) and Venezuela (246/100 000), and lower in Canada (108/100 000), Puerto Rico (121/100 000) and Chile (125/100 000). Male rates were higher than female rates in all countries. The trend analysis showed that CVD death rates in the Americas declined -19% overall (-20% among women and -18% among men). Most countries had a significant annual decline, except Guatemala, Guyana, Suriname, Paraguay and Panama. The largest annual declines were observed in Canada (-4.8%), the USA (-3.9%) and Puerto Rico (-3.6%). Minor declines were in Mexico (-0.8%) and Cuba (-1.1%). Compared with high-income countries the difference between the median of death rates in lower middle-income countries was 56.7% higher and between upper middle-income countries was 20.6% higher. CONCLUSIONS: CVD death rates have been decreasing in most countries in the Americas. Considerable disparities still remain in the current rates and trends.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".