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Effect of Dapagliflozin on Heart Failure and Mortality in Type 2 Diabetes Mellitus

2019· article· en· W2921866736 on OpenAlexaff
Eri Kato, Michael G. Silverman, Ofri Mosenzon, Thomas A. Zelniker, Avivit Cahn, Remo H.M. Furtado, Julia Kuder, Sabina A. Murphy, Deepak L. Bhatt, Lawrence A. Leiter, Darren K. McGuire, John Wilding, Marc P. Bonaca, Christian T. Ruff, Akshay S. Desai, Shinya Goto, Peter A. Johansson, Ingrid Gause‐Nilsson, Per Johanson, Anna Maria Langkilde, Itamar Raz, Marc S. Sabatine, Stephen D. Wiviott

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsDapagliflozinMedicineInternal medicineHeart failureEjection fractionTIMIHazard ratioCardiologyMyocardial infarctionDiabetes mellitusType 2 diabetesPopulationThrombolysisEndocrinologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: In DECLARE-TIMI 58 (Dapagliflozin Effect on Cardiovascular Events-Thrombolysis in Myocardial Infarction 58), the sodium-glucose cotransporter 2 inhibitor dapagliflozin reduced the composite end point of cardiovascular death/hospitalization for heart failure (HHF) in a broad population of patients with type 2 diabetes mellitus. However, the impact of baseline left ventricular ejection fraction (EF) on the clinical benefit of sodium-glucose cotransporter 2 inhibition is unknown. METHODS: In the DECLARE-TIMI 58 trial, baseline heart failure (HF) status was collected from all patients, and EF was collected when available. HF with reduced EF (HFrEF) was defined as EF <45%. Outcomes of interest were the composite of cardiovascular death/HHF, its components, and all-cause mortality. RESULTS: Of 17 160 patients, 671 (3.9%) had HFrEF, 1316 (7.7%) had HF without known reduced EF, and 15 173 (88.4%) had no history of HF at baseline. Dapagliflozin reduced cardiovascular death/HHF more in patients with HFrEF (hazard ratio [HR], 0.62 [95% CI, 0.45-0.86]) than in those without HFrEF (HR, 0.88 [95% CI, 0.76-1.02]; P for interaction=0.046), in whom the treatment effect of dapagliflozin was similar in those with HF without known reduced EF (HR, 0.88 [95% CI, 0.66-1.17]) and those without HF (HR, 0.88 [95% CI, 0.74-1.03]). Whereas dapagliflozin reduced HHF both in those with (HR, 0.64 [95% CI, 0.43-0.95]) and in those without HFrEF (HR, 0.76 [95% CI, 0.62-0.92]), it reduced cardiovascular death only in patients with HFrEF (HR, 0.55 [95% CI, 0.34-0.90]) but not in those without HFrEF (HR, 1.08 [95% CI, 0.89-1.31]; P for interaction=0.012). Likewise, dapagliflozin reduced all-cause mortality in patients with HFrEF (HR, 0.59 [95% CI, 0.40-0.88;) but not in those without HFrEF (HR, 0.97 [95% CI, 0.86-1.10]; P for interaction=0.016). CONCLUSIONS: In the first sodium-glucose cotransporter 2 inhibitor cardiovascular outcome trial to evaluate patients with type 2 diabetes mellitus stratified by EF, we found that dapagliflozin reduced HHF in patients with and without HFrEF and reduced cardiovascular death and all-cause mortality in patients with HFrEF. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01730534.

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 score0.009

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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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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Citations563
Published2019
Admission routes1
Has abstractyes

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