Cardiovascular, kidney and safety outcomes with canagliflozin in older adults: A combined analysis from the <scp>CANVAS</scp> Program and <scp>CREDENCE</scp> trial
Bibliographic record
Abstract
AIM: SGLT2 inhibitors may be underused in older adults with type 2 diabetes due to concerns about safety and tolerability. This pooled analysis of the CANVAS Program and CREDENCE trial examined the efficacy and safety of canagliflozin according to age. METHODS: Pooled individual participant data from the CANVAS Program (n = 10 142) and CREDENCE trial (n = 4401) were analysed by baseline age (<65 years, 65 to <75 years, and ≥75 years). A range of adjudicated clinical outcomes were assessed, including major adverse cardiovascular events and CKD progression, as well as safety outcomes. Cox proportional hazards models and Fine and Gray competing risk analysis were used. RESULTS: Among the 14 543 participants, 7927 (54.5%) were <65 years, 5281 (36.3%) were 65 to <75 years and 1335 (9.2%) were ≥75 years. Older participants had higher rates of atherosclerotic cardiovascular disease and heart failure, longer diabetes duration and lower mean eGFR. Reductions in cardiovascular and kidney outcomes with canagliflozin were consistent across age categories (all p trend >0.10), although there was some evidence that effects on cardiovascular death and all-cause death were attenuated with older age (p trend = 0.02 and 0.03, respectively). Although the incidence of adverse events increased with age, effects of canagliflozin on safety outcomes including acute kidney injury, volume depletion, urinary tract infections and hypoglycaemia, were not modified by age (all p trend >0.10). CONCLUSIONS: In patients with varying degrees of kidney function, canagliflozin reduced cardiovascular and kidney outcomes, regardless of age, with no additional safety concerns identified in older patients.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".