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Record W2890444735 · doi:10.17925/ee.2018.14.2.40

Empagliflozin and Cardio-renal Outcomes in Patients with Type 2 Diabetes and Cardiovascular Disease – Implications for Clinical Practice

2018· review· en· W2890444735 on OpenAlexaff
David Fitchett

Bibliographic record

VenuetouchREVIEWS in Endocrinology · 2018
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsEmpagliflozinMedicineCanagliflozinDapagliflozinHazard ratioInternal medicineType 2 diabetesMyocardial infarctionDiabetes mellitusClinical endpointCardiologyHeart failureConfidence intervalRandomized controlled trialEndocrinology

Abstract

fetched live from OpenAlex

In patients with type 2 diabetes (T2D), the excretion of glucose by the kidney with sodium-glucose cotransporter 2 (SGLT2) inhibitors lowers glycosylated haemoglobin (HbA1c) levels, decreases body weight and visceral adiposity, as well as improving cardio-renal haemodynamics. Currently, four SGLT2 inhibitors are approved in the US and Europe to improve glycaemic control – empagliflozin, dapagliflozin, canagliflozin, and ertuglifozin. Recently, the SGLT2 inhibitor empagliflozin was approved by the FDA for the reduction of cardiovascular (CV) death in adults with T2D and CV disease (CVD). This approval was based on the findings of the Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes (EMPA-REG OUTCOME) study, which was the first study to show a significant reduction of a primary CV endpoint with a glucose-lowering agent. In this study, the primary outcome (CV mortality, non-fatal myocardial infarction [MI] and non-fatal stroke) was reduced by empagliflozin (10.5%; 490/4,687) compared with placebo (12.1%; 282/2,333); hazard ratio (HR), 0.86 (95% confidence interval [CI]: 0.74, 0.99). The primary outcome was driven by a large reduction of CV mortality (relative risk reduction [RRR], 38%). Empagliflozin also reduced all-cause mortality (RRR, 32%). Furthermore, empagliflozin reduced the adjudicated outcome of heart failure (HF) hospitalisation by 35% (HR, 0.65; 95% CI: 0.50, 0.85). Other non-adjudicated measures of HF outcomes were similarly reduced including investigator reported HF, the introduction of loop diuretics and death from HF. In the analysis of renal outcomes, incident or worsening nephropathy was reduced for empagliflozin (12.7%) compared with placebo (18.8%); HR, 0.61 (95% CI: 0.53, 0.70). Empagliflozin significantly reduced the risk of progression to macroalbuminuria (38%) and doubling of creatinine (44%), as well as the need of starting renal-replacement therapy (55%). The benefits of empagliflozin for the reduction of CV death, all-cause death and hospitalisation for HF were observed across a range of baseline subgroups such as HbA1c level and renal function (down to estimated glomerular filtration rate [eGFR] 30 ml/min/1.73 m 2 ). The rapid reduction of HF outcomes with empagliflozin is observed across the spectrum of CVD and HF risk and represents a therapeutic advance in the prevention and perhaps also in the treatment of HF, an often poorly recognised complication of T2D. This review discusses the EMPA-REG OUTCOME study and the implications for treating patients with T2D and CVD.

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)0.007
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.403
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2018
Admission routes1
Has abstractyes

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