The Impact of Glucagon-Like Peptide-1 Receptor Agonist on the Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus: A Meta-Analysis and Systematic Review
Bibliographic record
Abstract
Background: Since 2005, the cardioprotective effects of glucagon-like peptide 1 receptor agonists (GLP-1 RAs) have garnered attention. The cardioprotective effect could be an added benefit to the use of GLP-1 RA. This systematic review and meta-analysis aimed at summarizing observational studies that recruited type 2 diabetes individuals with fewer cardiovascular (CV) events before enrolling in the research. Methods: Systematically, the databases were searched for observational studies reporting compound CV events and deaths in type 2 diabetics without having the risk of cardiovascular diseases (CVDs) compared to other glucose-lowering agents. A meta-analysis was carried out using random effects model to estimate the overall hazard ratio (HR) with a 95% confidence interval (CI). Five studies were found eligible for the systematic review including a total of 64,452 patients receiving either liraglutide (three studies) or exenatide (two studies). Results: The pooled HR for major adverse cardiac event (MACE) and extended MACE was 0.72 (95% CI: 0.65 - 0.93, I 2 = 68%) and 0.93 (95% CI: 0.89 - 0.98, I 2 = 29%), respectively. The pooled HR for hospitalization due to heart failure (HHF) and occurrence of HF was 0.84 (95% CI: 0.77 - 0.91, I 2 = 79%) and 0.83 (95% CI: 0.75 - 0.94, I 2 = 95%), respectively. For stroke, GLP-1 RA was associated with a significant risk reduction of 0.86 (95% CI: 0.75 - 0.98, I 2 = 81%). There was no significant myocardial infarction (MI) risk reduction with GLP-1 RA. As for all-cause mortality, the pooled HR for the occurrence of all-cause mortality was 0.82 (95% CI: 0.76 - 0.88, I 2 = 0%). The pooled HR for the occurrence of CV death was 0.75 (95% CI: 0.65 - 0.85, I 2 = 38%). GLP-1 RA therapy was associated with a significantly low risk of MACE, extended MACE, all-cause mortality, and CV mortality. Except for MACE, the heterogenicity among the studies was low. Conclusion: We conclude that GLP-1 RA is associated with a low risk of CV events composites and mortality. The findings support the cardioprotective effect of GLP-1 RA. Cardiol Res. 2023;14(4):250-260 doi: https://doi.org/10.14740/cr1523
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".