Adverse cardiovascular events during treatment with glyburide (glibenclamide) or gliclazide in a high‐risk population
Bibliographic record
Abstract
AIMS: Sulphonylureas promote insulin release by inhibiting pancreatic potassium channels. Older sulphonylureas such as glyburide (glibenclamide), but not newer ones such as gliclazide, antagonize similar channels in myocardium, interfering with the protective effects of ischaemic preconditioning. Whether this imparts a higher risk of adverse cardiac events is unknown. METHODS: We conducted a population-based cohort study of patients aged 66 years and older who were hospitalized for acute myocardial infarction or who underwent percutaneous coronary intervention between 1 April 2007 and 31 March 2010 while receiving either glyburide or gliclazide. We used a high-dimensional propensity score matching process to ensure similarity of glyburide- and gliclazide-treated patients. The primary outcome was a composite of death or hospitalization for myocardial infarction or heart failure. RESULTS: During the 2-year study period, we matched 1690 patients treated with glyburide to 984 patients treated with gliclazide at the time of hospitalization for acute myocardial infarction or percutaneous coronary intervention. We found no difference in the risk of the composite outcome among patients receiving glyburide (adjusted hazard ratio 1.01; 95% CI 0.86-1.18). We found similar results in secondary analyses of each outcome individually, and in two supplementary analyses (haemorrhage and pneumonia) in which we anticipated no difference between the two patient groups. CONCLUSIONS: Among older patients hospitalized for acute myocardial infarction or percutaneous coronary intervention, treatment with glyburide is not associated with an increased risk of future adverse cardiovascular events relative to gliclazide, suggesting that the effect of glyburide on ischaemic preconditioning is of little clinical relevance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".