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Record W4390816339 · doi:10.4081/cardio.2023.2

SGLT2 inhibitors and risk reduction for mortality in high-risk patients: a meta-analysis of randomized controlled trials

2023· article· en· W4390816339 on OpenAlexaff
Tariq Jamal Siddiqi, Javed Butler, Andrew J.S. Coats, Subodh Verma, Tim Friede, Gerasimos Filippatos, Stefan D. Anker

Bibliographic record

VenueGlobal Cardiology · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsEmpagliflozinDapagliflozinMedicineHazard ratioInternal medicinePlaceboRandomized controlled trialRelative riskMeta-analysisDiabetes mellitusConfidence intervalType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.036
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.050
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.045
GPT teacher head0.331
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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