Abstract MP52: International Variations in Age-Standardized Stroke-Related Mortality in Men and Women
Bibliographic record
Abstract
Background: Stroke is one of the leading causes of mortality worldwide. We aimed to evaluate the international variations in stroke-related mortality in men and women. Methods: We completed a systematic review of all population-based cohort studies published during the decade 2010-2020. We retained only studies which reported age-adjusted and sex-specific stroke-related all-cause mortality (per 100 000 population). We computed the median sex-specific stroke-related mortality for each of the following group of countries: developed countries (as defined by the International Monetary Fund) with predominantly white population (Canada, United States of America, Western Europe, Australia, New Zealand), Eastern Europe, Latin America, Asia and Africa. We compared stroke-related mortality between women and men and between regions. Results: Of the 210 articles screened, there were seven studies which reported population-based age-standardized and sex-specific stroke-related mortality in 57 countries. We presented the most recent age-adjusted and sex-specific stroke-related mortality medians (and 25 th and 75 th percentiles) in Figure 1. Globally, we observed a significantly lower stroke-related mortality rate in women compared to men (23.6 and 30.8, respectively) (p-value = 0.007). Age-adjusted stroke-related mortality was the highest for both sexes in Eastern Europe, followed by the African rates. Age-adjusted stroke-related mortality was the lowest for both men and women (p<0.0001) in developed countries with predominantly white population compared to the other regions. Conclusions: There were marked international variations in the age-adjusted stroke-related mortality for both men and women. The high stroke-related mortality in Eastern Europe and Africa should motivate further improvement in stroke care in these regions. Finally, future research is needed to understand and decrease the sex-related difference in stroke-related mortality.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".