Stroke and dementia, leading causes of neurological disability and death, potential for prevention
Bibliographic record
Abstract
INTRODUCTION: Stroke and dementia share a number of modifiable risk factors and are the leading cause of neurological disability and death worldwide. METHODS: We report the 2019 estimations for global disability-adjusted life years (DALYs) and death numbers and rates related to stroke and dementia, as well as their risk attributed DALYs and deaths and their changes between 2010 and 2019. RESULTS: Stroke accounted for 69.8%, dementia for 17.3%, and combined contributed to 87.2% (8.2 million) of neurological deaths and 61.7% (168.5 million) of neurological DALYs in 2019. For stroke, 86.4% of DALYs and for dementias 32.8% of DALYs are attributable to risk factors. Globally, hypertension (54.8%) and unhealthy diet (30.0%) pose the greatest risk for stroke DALYs, and smoking (15.1%) and obesity (12.5%) for dementia DALYs. DISCUSSION: Worldwide, stroke and dementia cases are increasing in number, but their age-standardized rates are falling. Finding out why offers the possibility of their joint delay, mitigation, or prevention.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".