Rurality, type 2 diabetes and risk of cardiovascular events in Alberta, Canada: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To describe the association between place of residence in Alberta, Canada, and cardiovascular event risk among adults newly treated with metformin for type 2 diabetes. DESIGN: Retrospective cohort study. SETTING: Administrative data from Alberta, Canada between 2008 and 2023. PARTICIPANTS: Adult new metformin users, categorised by residence (rural, urban, metropolitan) from postal codes 1 year before metformin. PRIMARY AND SECONDARY OUTCOME MEASURES: Cause-specific hazard models were constructed for the primary composite outcome (cardiovascular mortality, hospitalisation for an acute coronary syndrome or stroke) and each of the secondary outcomes (components of the primary outcome and all-cause mortality). Models were adjusted for baseline demographics, healthcare utilisation and diabetes complications. RESULTS: A total of 236 005 adult new metformin users were identified and distributed across the rural-urban continuum (66% metropolitan, 10% urban, 24% rural). Mean age was 55 years, 55% were men, and mean follow-up time was 5.7 years. There were 19 059 primary composite outcome events, and rural residents were more likely to experience the outcome, adjusted HR (aHR): 1.09 (95% CI 1.06 to 1.13), compared with metropolitan. A significant interaction between residence and cardiovascular event history was identified. When stratified, risk of the primary outcome among those without cardiovascular history and living in a rural area was aHR: 1.16 (95% CI 1.11 to 1.20). Among rural residents with cardiovascular history, the risk was aHR: 0.84 (95% CI 0.78 to 0.91). CONCLUSIONS: Quantifying the association between residence and risk of cardiovascular events may focus the allocation of healthcare resources. Development of targeted intervention programmes should focus on primary prevention in rural areas and secondary prevention in metropolitan areas.
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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 | 0.003 |
| 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".