Association of Baseline HbA1c With Cardiovascular and Renal Outcomes: Analyses From DECLARE-TIMI 58
Bibliographic record
Abstract
OBJECTIVE: Current guidelines recommend prescribing SGLT2 inhibitors to patients with type 2 diabetes and established or at high risk for atherosclerotic cardiovascular disease (ASCVD), irrespective of HbA1c levels. We studied the association of HbA1c with cardiovascular and renal outcomes and whether the benefit of dapagliflozin varies by baseline HbA1c. RESEARCH DESIGN AND METHODS: In the Dapagliflozin Effect on Cardiovascular Events trial (DECLARE-TIMI 58), 17,160 patients with type 2 diabetes were randomly assigned to dapagliflozin or placebo for a median follow-up of 4.2 years. Cardiovascular and renal outcomes by baseline HbA1c in the overall population and with dapagliflozin versus placebo in HbA1c subgroups were studied by Cox regression models. RESULTS: In the overall population, higher baseline HbA1c was associated with a higher risk of cardiovascular death or hospitalization for heart failure (HHF); major adverse cardiovascular events (MACE), including cardiovascular death, myocardial infarction, and ischemic stroke; and cardiorenal outcomes (adjusted hazard ratios 1.12 [95% CI 1.06-1.19], 1.08 [1.04-1.13], and 1.17 [1.11-1.24] per 1% higher level, respectively). Elevated HbA1c was associated with a greater increased risk for MACE and cardiorenal outcomes in patients with multiple risk factors (MRF) than in established ASCVD (P-interaction = 0.0064 and 0.0093, respectively). Compared with placebo, dapagliflozin decreased the risk of cardiovascular death/HHF, HHF, and cardiorenal outcomes, with no heterogeneity by baseline HbA1c (P-interaction > 0.05). CONCLUSIONS: Higher HbA1c levels were associated with greater cardiovascular and renal risk, particularly in the MRF population, yet the benefits of dapagliflozin were observed in all subgroups irrespective of baseline HbA1c, including patients with HbA1c <7%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".