World Stroke Organization: Global Stroke Fact Sheet 2025
Bibliographic record
Abstract
BACKGROUND: Among non-communicable disorders (NCDs), stroke remains the second leading cause of death and the third leading cause of death and disability combined (as expressed by disability-adjusted life-years lost-DALYs) in the world. AIMS: The study was aimed to estimate global, regional and nationa burden of stroke and its risk factors from 1990 to 2021. METHODS: Finding presented in this paper were derived mainly from the Global Burden of Disease 2021 Study on stroke burden published in The Lancet Neurology 2024:23:973-1003. RESULTS: The estimated global cost of stroke is over US$890 billion (0.66% of the global GDP). From 1990 to 2021, the burden (in terms of the absolute number of cases) increased substantially (70.0% increase in incident strokes, 44.0% deaths from stroke, 86.0% prevalent strokes, and 32% DALYs), with the bulk of the global stroke burden (87.0% of deaths and 89.0% of DALYs) residing in lower-income and lower-middle-income countries (LMICs). Stroke attributable to metabolic risks constituted 69.0% of all strokes, environmental risks constituted 37.0%, and behavioral risks constituted 35.0%. CONCLUSION: This World Stroke Organization (WSO) Global Stroke Fact Sheet 2025 provides the most updated information that can be used to inform communication with all internal and external stakeholders; all statistics have been reviewed and approved for use by the WSO Executive Committee and leaders from the Global Burden of Disease research group.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.029 |
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".