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Record W4409054418 · doi:10.1016/j.xjon.2025.03.018

Safety and efficacy of empagliflozin in heart failure among patients with a history of valvular heart disease: Insights from EMPEROR-Pooled

2025· article· en· W4409054418 on OpenAlexaff
Nitish K. Dhingra, Ekene Nwajei, Raj Kumar Verma, Egon Pfarr, Tomasz Gąsior, Subodh Verma

Bibliographic record

VenueJTCVS Open · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsSt. Michael's Hospital
FundersBoehringer IngelheimEli Lilly and Company
KeywordsEmpagliflozinEmperorvalvular heart diseaseHeart failureMedicineInternal medicineDiseaseCardiologyHistoryAncient historyEndocrinology

Abstract

fetched live from OpenAlex

Background: Valvular heart disease (VHD)-associated heart failure (HF) remains an important and growing cause of morbidity and mortality. There are no contemporary data on the efficacy and safety of SGLT2 inhibitors in patients with a history of VHD. Methods: The EMPEROR-Pooled trial analyzed 9718 patients with HF who were enrolled in the randomized trials of empagliflozin versus placebo in HF with reduced left ventricular ejection fraction (HfrEF; EMPEROR-Reduced) and HF with preserved left ventricular ejection fraction (HFpEF; EMPEROR-Preserved). These trials evaluated a primary outcome of time to first HF hospitalization or cardiovascular death. Here we analyze outcomes of the EMPEROR-Pooled patients according to the presence and etiology of VHD history. Results: > .05). Conclusions: We present the first large analysis of SGLT2i (empagliflozin) use in HF patients by history of VHD. Although VHD history was associated with worse outcomes in HF patients, empagliflozin demonstrated consistent safety, efficacy, and patient-reported outcomes across all categories of VHD history.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.230
Teacher spread0.224 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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