Rationale and Design of INTERSTROKE: A Global Case-Control Study of Risk Factors for Stroke
Bibliographic record
Abstract
UNLABELLED: Stroke is a major global health problem. It is the third leading cause of death and the leading cause of adult disability. INTERHEART, a global case-control study of acute myocardial infarction in 52 countries (29,972 participants), identified nine modifiable risk factors that accounted for >90% of population-attributable risk. However, traditional risk factors (e.g. hypertension, cholesterol) appear to exert contrasting risks for stroke compared with coronary heart disease, and the etiology of stroke is far more heterogeneous. In addition, our knowledge of risk factors for stroke in low-income countries is inadequate, where a very large burden of stroke occurs. Accordingly, a similar epidemiological study is required for stroke, to inform effective population-based strategies to reduce the risk of stroke. METHODS: INTERSTROKE is an international, multicenter case-control study. Cases are patients with a first stroke within 72 h of hospital presentation in whom CT or MRI is performed. Proxy respondents are used for cases unable to communicate. Etiological and topographical stroke subtype is documented for all cases. Controls are hospital- and community-based, matched for gender, ethnicity and age (+/-5 years). A questionnaire (cases and controls) is used to acquire information on known and proposed risk factors for stroke. Cardiovascular (e.g. blood pressure) and anthropometric (e.g. waist-to-hip ratio) measurements are obtained at the time of interview. Nonfasting blood samples and random urine samples are obtained from cases and controls. Study Significance: An effective global strategy to reduce the risk of stroke mandates systematic measurement of the contribution of the major vascular risk factors within defined ethnic groups and geographical locations.
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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 | 0.061 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".