Comparison of years of life lost due to ischemic stroke between two countries with a public health system: 5-year analysis
Bibliographic record
Abstract
Background: Ischemic stroke occurs when there is arterial obstruction, causing paralysis of brain areas, which prevents the passage of oxygen due to the lack of blood circulation. It is one of the main causes of death worldwide, increasing early mortality in several countries with different realities, such as Brazil and Canada. Objective: To compare the rate of years of life lost (YLLs) due to ischemic stroke between two countries with public health systems over five years, identifying differences and trends in early mortality, providing data to guide public health policies and prevention strategies. Methods: This is an observational, descriptive epidemiological study in which data on years of life lost (YLLs) due to stroke from 2017 to 2021 were obtained from the Institute for Health Metrics and Evaluation (IHME) platform, in the Global Burden of Disease (GBD) section. Information on cerebrovascular disease was selected and data on annual ischemic strokes was filtered out. The YLLs were calculated by multiplying the difference between the country‘s life expectancy and the age at death by the number of people who died from the disease in question. In order to make the appropriate correlation with the years of the fourth decade of life and calculate the rate (per 100,000 inhabitants), the age groups of both sexes, 30 to 34 years and 35 to 39 years, classified as age group 1 and age group 2, respectively, were selected. Results: In both countries, age group 2 had the highest rates in all the years analyzed. In the first year, 2017, men in Canada had a rate of 6.86 and women 7.6. In Brazil, in the same year, the male rate was 37.09 and the female rate was 31.34. In 2018, the second year of analysis, the male rate in Canada was 11.23 and the female rate was 8.77. In Brazil, the rate for men was 40.63 and for women 35.69. In 2019 in Canada, the male rate was 12.02 and the female rate was 9.70. In Brazil, the male rate was 40.99, and the female rate was 38.19. In the penultimate year, 2020, in Canada, the male rate was 12.38, and the female rate was 9.56. This year in Brazil, the male rate remained at 40.99, and the female rate increased slightly to 38.42. Last year, for 2021, in Canada, the male rate was 11.96, and the female rate was 9.10. In Brazil, the male rate was 42.98 and the female rate was 40.16. Conclusion: It was concluded that age group 2 had the highest rates in all the years analyzed in both Canada and Brazil. There was a general increase in rates in both countries over the period analyzed, with an increase of 74.3% in Canadian men, 19.7% in Canadian women, 15.8% in Brazilian men and 28.1% in Brazilian women in 2021 compared to 2017, with Brazil showing significantly higher rates than Canada.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".