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Record W4293354571 · doi:10.1016/j.jacc.2022.07.021

Dapagliflozin in Patients Recently Hospitalized With Heart Failure and Mildly Reduced or Preserved Ejection Fraction

2022· article· en· W4293354571 on OpenAlexaff
Jonathan W. Cunningham, Muthiah Vaduganathan, Brian Claggett, Ian J. Kulac, Akshay S. Desai, Pardeep S. Jhund, Rudolf A. de Boer, David L. DeMets, Adrian F. Hernandez, Silvio E. Inzucchi, Mikhail Kosiborod, Carolyn S.P. Lam, Felipe A. Martínez, Sanjiv J. Shah, Martina M. McGrath, Eileen O’Meara, Ulrica Wilderäng, Daniel Lindholm, Magnus Petersson, Anna Maria Langkilde, John J.V. McMurray, Scott D. Solomon

Bibliographic record

VenueJournal of the American College of Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsDapagliflozinMedicineEjection fractionHeart failureInternal medicinePlaceboCardiologyAdverse effectRandomized controlled trialDiabetes mellitusType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Patients recently hospitalized for heart failure (HF) are at high risk for rehospitalization and death. The purpose of this study was to investigate clinical outcomes and response to dapagliflozin in patients with HF with mildly reduced or preserved left ventricular ejection fraction (LVEF) who were enrolled during or following hospitalization. The DELIVER (Dapagliflozin Evaluation to Improve the LIVES of Patients With PReserved Ejection Fraction Heart Failure) trial randomized patients with HF and LVEF >40% to dapagliflozin or placebo. DELIVER permitted randomization during or shortly after hospitalization for HF in clinically stable patients off intravenous HF therapies. This prespecified analysis investigated whether recent HF hospitalization modified risk of clinical events or response to dapagliflozin. The primary outcome was worsening HF event or cardiovascular death. Of 6,263 patients in DELIVER, 654 (10.4%) were randomized during HF hospitalization or within 30 days of discharge. Recent HF hospitalization was associated with greater risk of the primary outcome after multivariable adjustment (HR: 1.88; 95% CI: 1.60-2.21; P < 0.001). Dapagliflozin reduced the primary outcome by 22% in recently hospitalized patients (HR: 0.78; 95% CI: 0.60-1.03) and 18% in patients without recent hospitalization (HR: 0.82; 95% CI: 0.72-0.94; Pinteraction = 0.71). Rates of adverse events, including volume depletion, diabetic ketoacidosis, or renal events, were similar with dapagliflozin and placebo in recently hospitalized patients. Dapagliflozin safely reduced risk of worsening HF or cardiovascular death similarly in patients with and without history of recent HF hospitalization. Starting dapagliflozin during or shortly after HF hospitalization in patients with mildly reduced or preserved LVEF appears safe and effective. (Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved Ejection Fraction Heart Failure [DELIVER]; NCT03619213)

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)0.001
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: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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 designRandomized 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".

Quick stats

Citations91
Published2022
Admission routes1
Has abstractyes

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