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Effect of Empagliflozin on Cardiovascular and Renal Outcomes in Patients With Heart Failure by Baseline Diabetes Status

2020· article· en· W3103126890 on OpenAlexaff
Stefan D. Anker, Javed Butler, Gerasimos Filippatos, Muhammad Shahzeb Khan, Nikolaus Marx, Carolyn S.P. Lam, Sven Schnaidt, Anne Pernille Ofstad, Martina Brueckmann, Waheed Jamal, E A Bocchi, Piotr Ponikowski, Sergio V. Perrone, James L. Januzzi, Subodh Verma, Michael Böhm, João Pedro Ferreira, Stuart Pocock, Faı̈ez Zannad, Milton Packer

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsEmpagliflozinMedicineDiabetes mellitusBaseline (sea)Heart failureInternal medicineCardiologyBenzhydryl compoundsType 2 diabetesIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: Sodium-glucose cotransporter 2 inhibitors improve outcomes in patients with heart failure with reduced ejection fraction, but additional information is needed about whether glycemic status influences the magnitude of their benefits on heart failure and renal events. Methods: Patients with Class II–IV heart failure and a left ventricular ejection fraction ≤40% were randomized to receive empagliflozin (10 mg daily) or placebo in addition to recommended therapy. We prespecified a comparison of the effect of empagliflozin in patients with and without diabetes. Results: Of the 3730 patients enrolled, 1856 (50%) had diabetes, 1268 (34%) had prediabetes (hemoglobin A1c [HbA1c] 5.7–6.4%), and 606 (16%) had normoglycemia (HbA1c <5.7%). The risks of the primary outcome (cardiovascular death or hospitalization for heart failure), total hospitalizations for heart failure, and adverse renal outcomes were higher in patients with diabetes, but were similar between patients with prediabetes and normoglycemia. Empagliflozin reduced the risk of the primary outcome in patients with and without diabetes (hazard ratio, 0.72 [95% CI, 0.60–0.87] and 0.78 [95% CI, 0.64–0.97], respectively, P -interaction=0.57). Patients with and without diabetes also did not differ with respect to the effect of empagliflozin on total hospitalizations for heart failure, on the decline in estimated glomerular filtration rate over time, and on the risk of serious adverse renal outcomes. Among these end points, the effects of the drug did not differ in patients with prediabetes or normoglycemia. When analyzed as a continuous variable, baseline HbA1c did not significantly modify the benefits of empagliflozin on the primary outcome ( P -interaction=0.40). Empagliflozin did not lower HbA1c in patients with prediabetes or normoglycemia and was not associated with increased risk of hypoglycemia. Conclusions: In EMPEROR-Reduced (Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Reduced Ejection Fraction), empagliflozin significantly improved cardiovascular and renal outcomes in patients with heart failure and a reduced ejection fraction, independent of baseline diabetes status and across the continuum of HbA1c. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03057977.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.204
Teacher spread0.200 · 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 designObservational
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

Citations351
Published2020
Admission routes1
Has abstractyes

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