Cardiovascular safety of evogliptin dual and triple therapy in patients with type 2 diabetes: a nationwide cohort study
Bibliographic record
Abstract
OBJECTIVE: To investigate the risk of cardiovascular events associated with commonly used dual and triple therapies of evogliptin, a recently introduced dipeptidyl peptidase-4 inhibitor (DPP4i), for managing type 2 diabetes in routine clinical practice. DESIGN: A retrospective cohort study. SETTING: Korean Health Insurance Review and Assessment database. PARTICIPANTS: Patients who initiated metformin-based dual therapy and metformin+sulfonylurea-based triple therapy in South Korea from 2014 to 2018. INTERVENTIONS: Initiation of combination therapy with evogliptin. PRIMARY AND SECONDARY OUTCOME MEASURES: Hazards of cardiovascular events, a composite endpoint of myocardial infarction, heart failure and cerebrovascular events, and its individual components. Cox proportional hazards model with propensity score-based inverse probability of treatment weighting were used to estimate HRs and 95% CIs. RESULTS: From the dual and triple therapy cohorts, 5830 metformin+evogliptin users and 2198 metformin+sulfonylurea+evogliptin users were identified, respectively. Metformin+evogliptin users, as compared with metformin+non-DPP4i, had a 29% reduced risk of cardiovascular events (HR 0.71, 95% CI 0.62 to 0.82); HRs for individual outcomes were cerebrovascular events (0.71, 95% CI 0.53 to 0.95), heart failure (0.70, 95% CI 0.59 to 0.82), myocardial infarction (0.89, 95% CI 0.60 to 1.31). Metformin+sulfonylurea+evogliptin users, compared with metformin+sulfonylurea+non-DPP4i, had a 24% reduced risk of cardiovascular events (0.76, 95% CI 0.59 to 0.97); HRs for individual outcomes were myocardial infarction (0.57, 95% CI 0.27 to 1.19), heart failure (0.74, 95% CI 0.55 to 1.01), cerebrovascular events (0.96, 95% CI 0.61 to 1.51). CONCLUSIONS: These findings suggest that dual or triple therapies of evogliptin for the management of type 2 diabetes in routine clinical practice present no cardiovascular harms, but could alternatively offer cardiovascular benefits in this patient population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".