Risk of acute coronary events associated with glyburide compared with gliclazide use in patients with type 2 diabetes: a nested case–control study
Bibliographic record
Abstract
AIM: Sulfonylureas might increase the risk of adverse cardiovascular events; however, emerging evidence suggests there may be important differences amongst these drugs. Some, like glyburide, inhibit KATP channels in the heart and pancreas, while others, like gliclazide, are more likely to selectively inhibit KATP channels in the pancreas. We hypothesized that the risk of acute coronary syndrome (ACS) events would be higher in patients using glyburide compared with gliclazide. METHODS: This nested case-control study used administrative health data from Alberta, Canada. New users of glyburide or gliclazide aged ≥66 years between 1998 and 2010 were included. Cases were individuals with an ACS-related hospitalization or death. Up to four controls were matched based on birth year, sex, cohort-entry year and follow-up time. Multivariable conditional logistic regression was used to estimate adjusted odds ratios (OR), controlling for baseline drug use and co-morbidities. RESULTS: Our cohort included 7441 gliclazide and 13 884 glyburide users; 51.4% men, mean (s.d.) age 75.5 (6.6) years and mean (s.d.) duration of follow-up 5.5 (4.0) years. A total of 4239 patients had an ACS-related hospitalization or death and were matched to 16 723 controls. Compared with gliclazide use, glyburide use was associated with a higher risk (adjusted OR 1.14; 95% CI 1.06-1.23) of ACS-related hospitalization or death over 5.5 years (number needed to harm: 50). CONCLUSION: In this observational study, glyburide use was associated with a 14% higher risk of ACS events compared with gliclazide use. Although the difference is small and probably to have implications at the population level rather than the individual patient or clinician, any causal inferences regarding sulfonylurea use and adverse cardiovascular risk should be tested in a large-scale randomized controlled trial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".