Association Between Glycated Haemoglobin Levels and Cardiovascular Outcomes in Patients with Type 2 Diabetes and Cardiovascular Disease: A Secondary Analysis of the TECOS Randomized Clinical Trial
Bibliographic record
Abstract
Abstract Aims Whether glycaemic control is associated with cardiovascular outcomes in patients with type 2 diabetes (T2D) is unclear. Consequently, we assessed the relationship between glycated haemoglobin (HbA1c) and cardiovascular outcomes in a placebo-controlled randomized trial which demonstrated no cardiovascular effect of sitagliptin in patients with T2D and atherosclerotic vascular disease. Methods and results Secondary analysis of 14 656 TECOS participants with time to event analyses using multivariable Cox proportional hazard models. During a median 3.0 (interquartile range 2.3–3.8) year follow-up, 456 (3.1% of 14 656) patients had first hospitalization for heart failure (HF), 1084 (11.5%) died, 1406 (9.6%) died or were hospitalized for HF, and 1689 (11.5%) had a non-HF cardiovascular event (cardiovascular death, non-fatal stroke, non-fatal myocardial infarction, or hospitalization for unstable angina). Associations between baseline or time-varying HbA1c and cardiovascular outcomes were U-shaped, with the lowest risk when HbA1c was around 7%. Each one-unit increase in the time-varying HbA1c above 7% was associated with an adjusted hazard ratio (HR) of 1.21 [95% confidence interval (CI) 1.11–1.33] for first HF hospitalization, 1.11 (1.03–1.21) for all-cause death, 1.18 (1.09–1.26) for death or HF hospitalization, and 1.10 (1.02–1.17) for non-HF cardiovascular events. Each one-unit decrease in the time-varying HbA1c below 7% was associated with an adjusted HR of 1.35 (95% CI 1.12–1.64) for first HF hospitalization, 1.37 (1.16–1.61) for death, 1.42 (1.23–1.64) for death or HF hospitalization, and 1.22 (1.06–1.41) for non-HF cardiovascular events. Conclusion Glycated haemogobin exhibits a U-shaped association with cardiovascular outcomes in patients with T2D and atherosclerotic vascular disease, with nadir around 7%. Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT00790205.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".