Association Between Hemoglobin A1c and Development of Cardiovascular Disease in Canadian Men and Women Without Diabetes at Baseline: A Population‐Based Study of 608 474 Adults
Bibliographic record
Abstract
BACKGROUND: We examined the association between hemoglobin A1c (HbA1c) and the development of cardiovascular disease (CVD) in men and women, without diabetes or CVD at baseline. METHODS AND RESULTS: This retrospective cohort study included adults aged 40 to <80 years in Alberta, Canada. Men and women were divided into categories based on a random HbA1c during a 3-year enrollment period. The primary outcome of CVD hospitalization and secondary outcome of combined CVD hospitalization/mortality were examined during a 5-year follow-up period until March 31, 2021. A total of 608 474 individuals (55.2% women) were included. Compared with HbA1c 5.0% to 5.4%, men with HbA1c of 5.5% to 5.9% had an increased risk of CVD hospitalization (adjusted hazard ratio [aHR], 1.12 [95% CI, 1.07-1.19]) whereas women did not (aHR, 1.01 [95% CI, 0.95-1.08]). Men and women with HbA1c of 6.0% to 6.4% had a 38% and 17% higher risk and men and women with HbA1c ≥6.5% had a 79% and 51% higher risk of CVD hospitalization, respectively. In addition, HbA1c of 6.0% to 6.4% and HbA1c ≥6.5% were associated with a higher risk (14% and 41%, respectively) of CVD hospitalization/death in men, but HbA1c ≥6.5% was associated with a 24% higher risk only among women. CONCLUSIONS: In both men and women, HbA1c ≥6.0% was associated with an increased risk of CVD and mortality outcomes. The association between CVD and HbA1c levels of 5.5% to 5.9%, considered to be in the "normal" range, highlights the importance of optimizing cardiovascular risk profiles at all levels of glycemia, especially in men.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".