Cardiovascular events and all‐cause mortality associated with sulphonylureas compared with other antihyperglycaemic drugs: <scp>A B</scp> ayesian meta‐analysis of survival data
Bibliographic record
Abstract
AIM: To conduct a systematic review and meta-analysis to determine the risk of cardiovascular events and all-cause mortality associated with sulphonylureas (SUs) vs other glucose lowering drugs in patients with T2DM (T2DM). MATERIALS AND METHODS: A systematic review of Medline, Embase, Cochrane and clinicaltrials.gov was conducted for studies comparing SUs with placebo or other antihyperglycaemic drugs in patients with T2DM. A cloglog model was used in the Bayesian framework to obtain comparative hazard ratios (HRs) for the different interventions. For the analysis of observational data, conventional fixed-effect pairwise meta-analyses were used. RESULTS: The systematic review identified 82 randomized controlled trials (RCTs) and 26 observational studies. Meta-analyses of RCT data showed an increased risk of all-cause mortality and cardiovascular-related mortality for SUs compared with all other treatments combined (HR 1.26, 95% confidence interval [CI] 1.10-1.44 and HR 1.46, 95% CI 1.21-1.77, respectively). The risk of myocardial infarction was significantly higher for SUs compared with dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium-glucose co-transporter-2 inhibitors (HR 2.54, 95% CI 1.14-6.57 and HR 41.80, 95% CI 1.64-360.4, respectively). The risk of stroke was significantly higher for SUs than for DPP-4 inhibitors, glucagon-like peptide-1 agonists, thiazolidinediones and insulin. CONCLUSIONS: The present meta-analysis showed an association between SU therapy and a higher risk of major cardiovascular disease-related events compared with other glucose lowering drugs. Results of ongoing RCTs, which should be available in 2018, will provide definitive results on the risk of cardiovascular events and all-cause mortality associated with SUs vs other antihyperglycaemic drugs.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.049 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".