Variations in knowledge, awareness and treatment of hypertension and stroke risk by country income level
Bibliographic record
Abstract
OBJECTIVE: Hypertension is the most important modifiable risk factor for stroke globally. We hypothesised that country-income level variations in knowledge, detection and treatment of hypertension may contribute to variations in the association of blood pressure with stroke. METHODS: We undertook a standardised case-control study in 32 countries (INTERSTROKE). Cases were patients with acute first stroke (n=13 462) who were matched by age, sex and site to controls (n=13 483). We evaluated the associations of knowledge, awareness and treatment of hypertension with risk of stroke and its subtypes and whether this varied by gross national income (GNI) of country. We estimated OR and population attributable risk (PAR) associated with treated and untreated hypertension. RESULTS: Hypertension was associated with a graded increase in OR by reducing GNI, ranging from OR 1.92 (99% CI 1.48 to 2.49) to OR 3.27 (2.72 to 3.93) for highest to lowest country-level GNI (p-heterogeneity<0.0001). Untreated hypertension was associated with a higher OR for stroke (OR 5.25; 4.53 to 6.10) than treated hypertension (OR 2.60; 2.32 to 2.91) and younger age of first stroke (61.4 vs 65.4 years; p<0.01). Untreated hypertension was associated with a greater risk of intracerebral haemorrhage (OR 6.95; 5.61 to 8.60) than ischaemic stroke (OR 4.76; 3.99 to 5.68). The PAR associated with untreated hypertension was higher in lower-income regions, PAR 36.3%, 26.3%, 19.8% to 10.4% by increasing GNI of countries. Lifetime non-measurement of blood pressure was associated with stroke (OR 1.80; 1.32 to 2.46). CONCLUSIONS: Deficits in knowledge, detection and treatment of hypertension contribute to higher risk of stroke, younger age of onset and larger proportion of intracerebral haemorrhage in lower-income countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".