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Record W4308062270 · doi:10.1001/jamacardio.2022.4210

Dapagliflozin and Kidney Outcomes in Patients With Heart Failure With Mildly Reduced or Preserved Ejection Fraction

2022· article· en· W4308062270 on OpenAlexaff
Finnian R. Mc Causland, Brian Claggett, Muthiah Vaduganathan, Akshay S. Desai, Pardeep S. Jhund, Rudolf A. de Boer, Kieran F. Docherty, James C. Fang, Adrian F. Hernandez, Silvio E. Inzucchi, Mikhail Kosiborod, Carolyn S.P. Lam, Felipe A. Martínez, José Francisco Kerr Saraiva, Martina M. McGrath, Sanjiv J. Shah, Subodh Verma, Anna Maria Langkilde, Magnus Petersson, John J.V. McMurray, Scott D. Solomon

Bibliographic record

VenueJAMA Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineEjection fractionHeart failureDapagliflozinRenal functionKidney diseaseInternal medicineCardiologyHeart failure with preserved ejection fractionPlaceboKidneyUrologyEndocrinologyDiabetes mellitusPathologyType 2 diabetes

Abstract

fetched live from OpenAlex

Importance: Sodium-glucose cotransporter 2 inhibitors are known to reduce heart failure events and slow progression of kidney disease among patients with heart failure and a reduced ejection fraction. Objective: To determine the effect of dapagliflozin on cardiovascular and kidney outcomes and the influence of baseline kidney disease among patients with heart failure and a mildly reduced or preserved ejection fraction enrolled in the Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure (DELIVER) trial. Design, Setting, and Participants: This was a prespecified analysis conducted from July 1 to September 18, 2022 of the DELIVER randomized clinical trial. This was an international, multicenter trial including patients with ejection fraction greater than 40% and estimated glomerular filtration rate (eGFR) of 25 mL/min/1.73 m2 or higher. Interventions: Dapagliflozin, 10 mg, per day or placebo. Main Outcomes and Measures: Outcomes assessed were whether baseline kidney function modified the treatment effect on the primary outcome (cardiovascular death or worsening heart failure). Also examined was the treatment effect on the prespecified outcomes of eGFR slope and a post hoc composite kidney outcome (first ≥50% decline in eGFR from baseline; first eGFR <15 mL/min/1.73 m2; end-stage kidney disease; death from kidney causes). Results: A total of 6262 patients (mean [SD] age, 72 [10] years; 3516 male [56%]) had mean (SD) eGFR measurements available: 61 (19) mL/min/1.73 m2; 3070 patients (49%) had an eGFR less than 60 mL/min/1.73 m2. The effect of dapagliflozin on the primary outcome was not influenced by baseline eGFR category (eGFR ≥60 mL/min/1.73 m2: hazard ratio [HR], 0.84; 95% CI, 0.70-1.00; eGFR 45-<60 mL/min/1.73 m2: HR, 0.68; 95% CI, 0.54-0.87; eGFR <45 mL/min/1.73 m2: HR, 0.93; 95% CI, 0.76-1.14; P for interaction = .16). Over a median (IQR) follow-up of 2.3 (1.7-2.8) years, the overall incidence rate of the kidney composite outcome was low (1.1 events per 100 patient-years) and was not affected by treatment with dapagliflozin (HR, 1.08; 95% CI, 0.79-1.49). However, dapagliflozin attenuated the decline in eGFR from baseline (difference, 0.5; 95% CI, 0.1-0.9 mL/min/1.73 m2 per year; P = .01) and from month 1 to 36 (difference, 1.4; 95% CI, 1.0-1.8) mL/min/1.73 m2 per year; P < .001). Conclusions and Relevance: Results of this prespecified analysis showed that baseline kidney function did not modify the benefit of dapagliflozin in patients with heart failure and a mildly reduced or preserved ejection fraction. Dapagliflozin did not significantly reduce the frequency of the kidney composite outcome, although the overall event rate was low. However, dapagliflozin slowed the rate of decline in eGFR compared with placebo. Trial Registration: ClinicalTrials.gov Identifier: 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)0.002
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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".

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Citations122
Published2022
Admission routes1
Has abstractyes

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