Cardiovascular Complications and Mortality After Diabetes Diagnosis for South Asian and Chinese Patients
Bibliographic record
Abstract
OBJECTIVE: Many non-European ethnic groups have an increased risk for diabetes; however, the published literature demonstrates considerable uncertainty about the rates of diabetes complications among minority populations. The objective of this study was to determine the risks of cardiovascular complications and of mortality after diabetes diagnosis for South Asian and Chinese patients, compared with European patients. RESEARCH DESIGN AND METHODS: A population-based cohort study identified all 491,243 adults with newly diagnosed diabetes in Ontario, Canada, between April 2002 and March 2009. Subjects were followed until March 2011 for the first occurrence of any cardiovascular complication of diabetes (coronary artery disease, stroke, or lower-extremity amputation) and for all-cause mortality. Median follow-up was 4.7 years. RESULTS: The crude incidence of cardiovascular complications after diabetes diagnosis was 17.9 per 1,000 patient-years among European patients, 12.0 among South Asian patients, and 7.7 among Chinese patients. After adjusting for baseline characteristics, the cause-specific hazard ratios (HRs) for cardiovascular complications relative to European patients were 0.95 (95% CI 0.90-1.00; P = 0.056) and 0.50 (0.46-0.53; P < 0.001) for South Asian and Chinese patients, respectively. Mortality was lower for both minority groups (adjusted HR for South Asian patients 0.56 [95% CI 0.52-0.60]; P < 0.001; for Chinese patients 0.58 [0.55-0.62]; P < 0.001). CONCLUSIONS: Chinese patients were at substantially lower risk than European patients for cardiovascular complications after diabetes diagnosis, whereas South Asian patients were at comparable risk. Mortality after diabetes diagnosis was markedly lower for both minority populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".