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Empagliflozin and Clinical Outcomes in Patients With Type 2 Diabetes Mellitus, Established Cardiovascular Disease, and Chronic Kidney Disease

2017· article· en· W2756191633 on OpenAlexaff
Christoph Wanner, John M. Lachin, Silvio E. Inzucchi, David Fitchett, Michaela Mattheus, Jyothis T. George, Hans J. Woerle, Uli C. Broedl, Maximilian von Eynatten, Bernard Zinman

Bibliographic record

VenueCirculation · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteSt. Michael's Hospital
Fundersnot available
KeywordsMedicineEmpagliflozinDiseaseDiabetes mellitusKidney diseaseType 2 Diabetes MellitusType 2 diabetesInternal medicineIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: Empagliflozin, a sodium-glucose cotransporter 2 inhibitor, reduced cardiovascular morbidity and mortality in patients with type 2 diabetes mellitus and established cardiovascular disease in the EMPA-REG OUTCOME trial (Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients). Urinary glucose excretion with empagliflozin decreases with declining renal function, resulting in less potency for glucose lowering in patients with kidney disease. We investigated the effects of empagliflozin on clinical outcomes in patients with type 2 diabetes mellitus, established cardiovascular disease, and chronic kidney disease. Methods: Patients with type 2 diabetes mellitus, established cardiovascular disease, and estimated glomerular filtration rate (eGFR) ≥30 mL·min −1 ·1.73 m −2 at screening were randomized to receive empagliflozin 10 mg, empagliflozin 25 mg, or placebo once daily in addition to standard of care. We analyzed cardiovascular death, hospitalization for heart failure, all-cause hospitalization, and all-cause mortality in patients with prevalent kidney disease (defined as eGFR <60 mL·min −1 ·1.73 m −2 and/or urine albumin-creatinine ratio >300 mg/g) at baseline. Additional analyses were performed in subgroups by baseline eGFR (<45, 45–<60, 60–<90, ≥90 mL·min −1 ·1.73 m −2 ) and baseline urine albumin-creatinine ratio (>300, 30–≤300, <30 mg/g). Results: Of 7020 patients treated, 2250 patients had prevalent kidney disease at baseline, of whom 67% had a diagnosis of type 2 diabetes mellitus for >10 years, 58% were receiving insulin, and 84% were taking angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. In patients with prevalent kidney disease at baseline, empagliflozin reduced the risk of cardiovascular death by 29% compared with placebo (hazard ratio [HR], 0.71; 95% confidence interval [CI], 0.52–0.98), the risk of all-cause mortality by 24% (HR, 0.76; 95% CI, 0.59–0.99), the risk of hospitalization for heart failure by 39% (HR, 0.61; 95% CI, 0.42–0.87), and the risk of all-cause hospitalization by 19% (HR, 0.81; 95% CI, 0.72–0.92). Effects of empagliflozin on these outcomes were consistent across categories of eGFR and urine albumin-creatinine ratio at baseline and across the 2 doses studied. The adverse event profile of empagliflozin in patients with eGFR <60 mL·min −1 ·1.73 m −2 was consistent with the overall trial population. Conclusions: Empagliflozin improved clinical outcomes and reduced mortality in vulnerable patients with type 2 diabetes mellitus, established cardiovascular disease, and chronic kidney disease. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01131676.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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 designNon-randomized trial
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".

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Citations471
Published2017
Admission routes1
Has abstractyes

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