SGLT2 inhibitors and risk reduction for mortality in high-risk patients: a meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Background: The aim of this paper is to assess the impact of sodium-glucose cotransporters-2 (SGLT2) inhibitors on all-cause and cardiovascular (CV) death in high-risk patients and compare the efficacy of empagliflozin and dapagliflozin. Methods: PubMed was queried from inception to the last week of September 2023 for randomized controlled trials that compared SGLT2 inhibitors’ empagliflozin or dapagliflozin with placebo and included patients with heart failure (HF), type 2 diabetes mellitus (T2DM), or chronic kidney disease (CKD). The outcome of interest was CV death or all-cause death. Hazard ratios (HR) with 95% confidence intervals (CI) were pooled using a random effect model, and forest plots were created to analyze the results visually. A chi-square test was performed to assess subgroup differences between empagliflozin and dapagliflozin. Results: Eight trials (N=55,818) were included in our analysis, namely EMPA-REG, EMPEROR-Reduced, EMPEROR-Preserved, EMPA-KIDNEY, DECLARE-TIMI, DAPA-HF, DELIVER and DAPA-CKD. Pooled analysis demonstrated that compared to placebo, SGLT2 inhibition reduced the risk of CV death (SGLT2i arm = 1405 events, 29,089 total patients; placebo arm = 1515 events, 26,729 total patients; HR: 0.85; 95%CI: 0.79-0.93, p<0.001) and all-cause death (SGLT2i arm = 2,491 events, 29,062 total patients; placebo arm= 2,625 events, 26,729 total patients; HR: 0.86; 95% CI 0.79-0.95, p=0.002) in high-risk patients identified as having either T2DM, HF, or CKD. No differences were observed in the effect of empagliflozin and dapagliflozin on CV death (HRempagliflozin: 0.81; 95% CI 0.68-0.97, HRdapagliflozin: 0.88; 0.82-0.95, p=0.39) and all-cause death (HRempagliflozin: 0.86; 95% CI 0.73-1.02, HRdapagliflozin: 0.87; 0.78-0.97, p=0.94). Conclusions: SGLT2 inhibitors reduce the risk of all-cause and CV death in high-risk patients. Notably, there were no discernible differences in the benefits of empagliflozin and dapagliflozin on these outcomes.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.050 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".