Abstract 4140060: Impact of SGLT2 Inhibitors on Mortality Risk in Type 2 Diabetes Mellitus and Coronary Artery Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Type 2 diabetes mellitus (T2DM) is a major risk factor for coronary artery disease (CAD). SGLT2 inhibitors (SGLT2i) are effective in reducing cardiovascular mortality in T2DM patients, but their benefits for those with both CAD and T2DM are uncertain. Objective: The primary outcome was to evaluate the efficacy of SGLT2i compared to other hypoglycemic agents or placebo in reducing the risk of all-cause mortality in patients with T2DM and CAD. Secondary outcomes included cardiovascular death, fatal or non-fatal stroke, and fatal or non-fatal myocardial infarction. We hypothesize that SGLT2i are more effective in mortality risk reduction in patients with T2DM and concomitant CAD. Methods: A systematic review following PRISMA-2020 guidelines was conducted across four databases to evaluate the efficacy of SGLT2i in reducing mortality risk in diabetic patients with CAD. Quantitative analysis using Stata v18 employed a random-effects model (Restricted Maximum Likelihood) with Hazard Ratios (HR) as the measure of association. Results: Out of 853 studies identified, 5 publications were included in the final quantitative analysis, which included 5225 patients. The Newcastle-Ottawa Quality Assessment Form showed all included cohort studies had a low risk of bias. Those patients taking SGLT2i had a significant reduction in 38% the risk of all-cause mortality (HR 0.62 [0.47, 0.80]), this same effect was observed when compared with each subgroup vs. other hypoglycemic agents, HR 0.52 [0.29, 0.93]; vs. placebo, HR 0.64 [0.46, 0.90]. Results show very low heterogeneity. In overall cardiovascular death analysis, a significantly greater reduction was observed with SGLT2i (HR 0.61 [0.46, 0.81]), as well as when compared with placebo (HR 0.64 [0.47, 0.86]). In contrast, when compared with other hypoglycemic agents, there was a reduction, but this was not significant (HR 0.45 [0.19, 1.03]). No statistically significant decrease in the risk of fatal or non-fatal stroke and myocardial infarction was found with SGLT2i. Conclusion: SGLT2i demonstrates a greater significant benefit in reducing all-cause and cardiovascular mortality in patients with T2DM and CAD.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".