Effects of exenatide on coronary stent’s endothelialization in subjects with type 2 diabetes: a randomized controlled trial. The Rebuild study
Bibliographic record
Abstract
BACKGROUND: Subjects with type 2 diabetes (T2D) have a higher risk of in-stent restenosis and stent thrombosis. The activation of the glucagon-like peptide-1 receptor (GLP-1R) has been suggested to induce several effects on the vasculature that may reduce the risk of stent failure following an angioplasty. The aim of this study is to evaluate the effect of the GLP-1R agonist exenatide on endothelialization of a modern drug-eluting stent (DES) in subjects with T2D. METHODS: 38 subjects with T2D who were eligible for revascularization with implantation of DES were randomized to treatment with exenatide (once weekly) plus standard treatment, or to standard treatment alone. After 12 weeks, a new coronary angiography was performed to evaluate the percentage of strut coverage (primary endpoint) and the presence of neo-atherosclerosis by optical coherence tomography. This study was approved by the Stockholm's Ethical Review Board. RESULTS: The two groups were well balanced regarding baseline clinical characteristics. Strut coverage was 95% (88.7-98.5%) in the exenatide group and 91.4% (88.8-98.5%) in the control group (p = 0.692). There were no significant differences between groups neither in the thickness of neo-intima (0.2 mm in both groups, p = 0.471), nor the maximal in-stent obstruction by neo-intima (15.5% in exenatide group vs 14.7% in control group, p = 0.801). No significant differences were detected in the rate of target lesion revascularization between groups (p = 0.224). CONCLUSION: Twelve weeks treatment with exenatide did not lead to a significantly better stent coverage in people with T2D. No significant differences in the occurrence of neo-atherosclerosis were detected between groups. TRIAL REGISTRATION: The study was registered at www. CLINICALTRIALS: gov (Rebuild Study, NCT02621489).
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 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 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".