The Burden of Atherosclerotic Cardiovascular Disease in South Asians Residing in Canada: A Reflection From the South Asian Heart Alliance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
South Asians (SAs), originating from the Indian subcontinent (India, Pakistan, Sri Lanka, Bangladesh, Nepal, and Bhutan), represent one quarter of the global population and are the largest visible minority in Canada. SAs experience the highest rates of coronary artery disease in Canada. Although conventional cardiovascular risk factors remain predictive in SA, the excess risk is not fully explained by these risk factors alone. Abdominal obesity, metabolic syndrome, and insulin resistance likely contribute a greater risk in SAs than in other populations. The South Asian Heart Alliance has been recently formed to investigate and recommend the best strategies for the prevention of cardiometabolic disease in SAs in Canada. This topic review represents a comprehensive overview of the magnitude of cardiovascular disease in SAs in Canada, with a review of conventional and novel risk markers in the SA population. Both primary and secondary prevention strategies are suggested and when possible, adapted specifically for the SA population. The need for SAs and their healthcare professionals to be more aware of the problem and potential solutions, along with the need for population-specific research, is highlighted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it