Saxagliptin and Cardiovascular Outcomes in Patients With Type 2 Diabetes and Moderate or Severe Renal Impairment: Observations From the SAVOR-TIMI 53 Trial
Bibliographic record
Abstract
OBJECTIVE: The glycemic management of patients with type 2 diabetes mellitus (T2DM) and renal impairment is challenging, with few treatment options. We investigated the effect of saxagliptin in the Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus (SAVOR)-Thrombolysis in Myocardial Infarction (TIMI) 53 trial according to baseline renal function. RESEARCH DESIGN AND METHODS: Patients with T2DM at risk for cardiovascular events were stratified as having normal or mildly impaired renal function (estimated glomerular filtration rate [eGFR] >50 mL/min/1.73 m(2); n = 13,916), moderate renal impairment (eGFR 30-50 mL/min/1.73 m(2); n = 2,240), or severe renal impairment (eGFR <30 mL/min/1.73 m(2); n = 336) and randomized to receive saxagliptin or placebo. The primary end point was cardiovascular death, myocardial infarction, or ischemic stroke. RESULTS: After a median duration of 2 years, saxagliptin neither increased nor decreased the risk of the primary and secondary composite end points compared with placebo, irrespective of renal function (all P for interactions ≥ 0.19). Overall, the risk of hospitalization for heart failure among the three eGFR groups of patients was 2.2% (referent), 7.4% (adjusted hazard ratio [HR] 2.38 [95% CI 1.95-2.91], P < 0.001), and 13.0% (adjusted HR 4.59 [95% CI 3.28-6.28], P < 0.001), respectively. The relative risk of hospitalization for heart failure with saxagliptin was similar (P for interaction = 0.43) in patients with eGFR >50 mL/min/1.73 m(2) (HR 1.23 [95% CI 0.99-1.55]), eGFR 30-50 mL/min/1.73 m(2) (HR 1.46 [95% CI 1.07-2.00]), and in patients with eGFR <30 (HR 0.94 [95% CI 0.52-1.71]). Patients with renal impairment achieved reductions in microalbuminuria with saxagliptin (P = 0.041) that were similar to those of the overall trial population. CONCLUSIONS: Saxagliptin did not affect the risk of ischemic cardiovascular events, increased the risk of heart failure hospitalization, and reduced progressive albuminuria, irrespective of baseline renal function.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".