Abstract 4147578: Temporal Trends in Stroke-related Mortality in Canada Over the Past 30 Years
Bibliographic record
Abstract
Introduction: Stroke is among the leading global health burdens worldwide due to the resultant morbidity and mortality. Accordingly, thorough evaluation of the temporal trends in stroke-related mortality in Canada is mandatory to effectively tackle the associated global and socioeconomic burden. Research Question: Are there temporal trends in stroke-related mortality in Canada during the last 3 decades? Aim: To evaluate the temporal trends in stroke-related mortality in Canada over the past 3 decades. Methods: Mortality trends of stroke in Canada have been evaluated by initially retrieving data from Global Burden of Diseases 2019 database. JoinPoint Analysis software was utilized to calculate the Annual Percentage Change (APC) and the Average Annual Percentage Change (AAPC). Results: There was a total of 1,269,854 stroke-related death reported during the period of 1990-2019. There is an overall decline in stroke-related death, with females displaying a higher decline in mortality from 1990 to 2019 with AAPC of -1.00 (95%CI: - 1.04 to -0.96; p<0.001) than males (AAPC -0.68 95%CI: -0.73 to -0.62; p<0.001). Additionally. There is a declining mortality among all age groups, most significantly in the group of 50-74 years of age (AAPC -1.23, 95%CI: -1.31 to -1.15; p<0.001) followed by the 75 years and older age group (AAPC -1.20, 95%CI: -1.27 to -1.12; p<0.001), while the group of the 15-49 year old had the smallest decrease in mortality (AAPC - 0.97, 95%CI: -1.16 to -0.72; p<0.001). Conclusion: A noticeable decline in the stroke-related mortality across both genders and all age groups in Canada has been demonstrated across the past 30 years. Comparison of these trends with other international and global trends is warranted to identify the factors associated with this decline.
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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 | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".