Effect of Canagliflozin on Total Cardiovascular Burden in Patients With Diabetes and Chronic Kidney Disease: A Post Hoc Analysis From the CREDENCE Trial
Bibliographic record
Abstract
Background The sodium‐glucose cotransporter 2 inhibitor canagliflozin reduced the risk of first cardiovascular composite events in the CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) trial. In this post hoc analysis, we evaluated the effect of canagliflozin on total (first and recurrent) cardiovascular events. Methods and Results The CREDENCE trial compared canagliflozin or matching placebo in 4401 patients with type 2 diabetes, albuminuria, and estimated glomerular filtration rate of 30 to <90 mL/min per 1.73 m 2 , over a median of 2.6 years. The primary outcome was analyzed as a composite of any cardiovascular event including myocardial infarction, stroke, hospitalization for heart failure, hospitalization for unstable angina, and cardiovascular death. Negative binomial regression models were used to assess the effect of canagliflozin on the net burden of cardiovascular events. During the trial, 634 patients had 883 cardiovascular events, of whom 472 (74%) had just 1 cardiovascular event and 162 (26%) had multiple cardiovascular events. Canagliflozin reduced first cardiovascular events by 26% (hazard ratio, 0.74 [95% CI, 0.63–0.86]; P <0.001) and total cardiovascular events by 29% (incidence rate ratio, 0.71 [95% CI, 0.59–0.86]; P <0.001). The absolute risk difference per 1000 patients treated over 2.5 years was −44 (95% CI, −67 to −21) first cardiovascular events and −73 (95% CI, −114 to −33) total events. Conclusions Canagliflozin reduced cardiovascular events, with a larger absolute benefit for total cardiovascular than first cardiovascular events. These findings provide further support for the benefit of continuing canagliflozin therapy after an initial event to prevent recurrent cardiovascular events. Registration Information URL: https://www.clinicaltrials.gov ; Unique Identifier: NCT02065791.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.000 | 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".