Cardiovascular events and all‐cause mortality associated with sulphonylureas compared with other antihyperglycaemic drugs: <scp>A B</scp> ayesian meta‐analysis of survival data
Why this work is in the frame
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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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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it