Impact of Canagliflozin on Kidney and Cardiovascular Outcomes by Type 2 Diabetes Duration: A Pooled Analysis of the CANVAS Program and CREDENCE Trials
Bibliographic record
Abstract
OBJECTIVE: The study was undertaken because it was unknown whether the duration of type 2 diabetes modifies the effects of sodium-glucose cotransporter 2 inhibitor canagliflozin on cardiovascular (CV) and kidney outcomes. RESEARCH DESIGN AND METHODS: This post hoc analysis of the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program (N = 10,142) and Evaluation of the Effects of Canagliflozin on Renal and Cardiovascular Outcomes in Participants With Diabetic Nephropathy (CREDENCE) trial (N = 4,401) evaluated hazard ratios and 95% CIs using Cox proportional hazards for the effects of canagliflozin on CV and kidney outcomes, including progression and regression of albuminuria over 5-year intervals of disease duration. RESULTS: Canagliflozin had ranges of benefit across intervals of diabetes duration, with no heterogeneity for major adverse CV events, CV death or heart failure hospitalization, and kidney failure requiring therapy or doubling serum creatinine. Furthermore, canagliflozin reduced albuminuria progression and increased albuminuria regression with no interaction across all diabetes duration subgroups. CONCLUSIONS: Our findings suggest that earlier treatment with canagliflozin confers consistent cardiorenal benefits to individuals with type 2 diabetes.
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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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.019 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".