Cardiovascular outcomes and mortality after initiation of canagliflozin: Analyses from the EASEL Study
Bibliographic record
Abstract
Abstract Introduction In the EASEL study of patients with type 2 diabetes and high cardiovascular risk, initiation of sodium glucose co‐transporter 2 inhibitors (SGLT2i) was associated with lower risk of cardiovascular events and mortality and higher risk of below‐knee lower extremity (BKLE) amputation versus non‐SGLT2i therapies. This analysis further examined risk of cardiovascular events, cardiovascular and noncardiovascular death and BKLE amputation with the SGLT2i canagliflozin versus non‐SGLT2i. Methods New user cohorts were constructed from Department of Defense Military Health System patients initiating canagliflozin or non‐SGLT2i (4/1/2013‐12/31/2016). Propensity score matching (1:1) controlled for imbalances in baseline covariates. Incidence rates, hazard ratios and 95% confidence intervals for time to first composite outcome of all‐cause mortality (ACM) and hospitalization for heart failure (HHF), composite major adverse cardiovascular events (MACE) and individual components were evaluated using conditional Cox models. The National Death Index was used to differentiate cardiovascular from noncardiovascular death. The exploratory safety end‐point was BKLE amputation. Results After propensity matching, 15 394 patients with well‐balanced baseline covariates were followed for a median of 2.03 years (intent‐to‐treat). Canagliflozin showed significant benefit for ACM and HHF (P < .0001), MACE (P = .0001), cardiovascular death (P < .0001) and noncardiovascular death (P = .0018). No significant difference in risk of BKLE amputation was observed (P = .20), though few events were observed. Results were generally consistent in on‐treatment analyses. Conclusions In this high cardiovascular risk cohort studied in routine clinical practice, canagliflozin was associated with lower risk of cardiovascular events, cardiovascular death and all‐cause mortality with no significant increase in BKLE amputation risk versus non‐SGLT2i.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".