Alogliptin after acute coronary syndrome in patients with type 2 diabetes: a renal function stratified analysis of the EXAMINE trial
Bibliographic record
Abstract
Abstract Background The EXAMINE trial tested the efficacy and safety of alogliptin, an inhibitor of dipeptidyl peptidase 4, compared with placebo in 5380 patients with type 2 diabetes and a recent acute coronary syndrome. Because alogliptin is cleared by the kidney, patients were stratified according to screening renal function within two independently randomized strata: (1) estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73m2 and (2) eGFR < 60 ml/min/1.73m2. We aim to assess the efficacy and safety of alogliptin vs. placebo according to the renal function strata. Methods Cox-proportional hazard models with an interaction term by renal function strata were used. The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction (MI), or nonfatal stroke. Results Patient characteristics were balanced within each renal function strata. In total, 3946 patients were randomized within the eGFR ≥ 60 stratum, and 1434 patients within the eGFR < 60 stratum. The effect of alogliptin was modified by the renal function strata. Primary outcome: eGFR ≥ 60 HR = 0.81, 95%CI, 0.65–0.99, and eGFR < 60 HR = 1.20, 95%CI, 0.95–1.53; interactionp = 0.014. Cardiovascular death: eGFR ≥ 60 HR = 0.61, 95%CI, 0.42–0.88, and eGFR < 60 HR = 1.16, 95%CI, 0.82–1.65; interactionp = 0.013. Non-fatal MI: eGFR ≥ 60 HR = 0.86, 95%CI, 0.66–1.13, and eGFR < 60 HR = 1.48, 95%CI, 1.07–2.06; interactionp = 0.013. Conclusions Alogliptin may benefit patients with eGFR ≥ 60, but may be detrimental to patients with eGFR < 60 ml/min/1.73m2. These hypothesis-generating findings require further validation to assess the potential benefit and risk of alogliptin across the renal function spectrum among patients with type 2 diabetes and a recent acute coronary syndrome. Trial registration ClinicalTrials.gov, NCT00968708
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".