Cardiovascular disease risk profile and microvascular complications of diabetes: comparison of Indigenous cohorts with diabetes in Australia and Canada
Bibliographic record
Abstract
\n \t\t\tBackgroundIndigenous populations of Australia and Canada experience disproportionately high rates of chronic disease. Our goal was to compare cardiovascular (CVD) risk profile and diabetes complications from three recent comprehensive studies of diabetes complications in different Indigenous populations in Australia and Canada.MethodsWe compared participants from three recent studies: remote Indigenous Australians (2002-2003, n = 37 known diabetes), urban Indigenous Australians (2003-2005, n = 99 known diabetes), and remote Aboriginal Canadians (2001-2002, n = 188 known diabetes).ResultsThe three groups were similar for HbA1c, systolic BP, diabetes duration. Although leaner by body-mass-index criteria, remote Indigenous Australians displayed a more adverse CVD risk profile with respect to: waist-hip-ratio (1.03, 0.99, 0.94, remote Indigenous Australians, urban Indigenous Australians, remote Canadians, p < 0.001); HDL-cholesterol (0.82, 0.96, 1.17 mmol/L, p < 0.001); urine albumin-creatinine-ratio (10.3, 2.4, 4.5 mg/mmol); and C-reactive protein. With respect to diabetes complications, microalbuminuria (50%, 25%, 41%, p = 0.001) was more common among both remote groups than urban Indigenous Australians, but there were no differences for peripheral neuropathy, retinopathy or peripheral vascular disease.ConclusionsAlthough there are many similarities in diabetes phenotype in Indigenous populations, this comparison demonstrates that CVD risk profiles and diabetes complications may differ among groups. Irrespective, management and intervention strategies are required from a young age in Indigenous populations and need to be designed in consultation with communities and tailored to community and individual needs.\n
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".