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Dapagliflozin and Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus and Previous Myocardial Infarction

2019· article· en· W2919368874 on OpenAlexaff
Remo H.M. Furtado, Marc P. Bonaca, Itamar Raz, Thomas A. Zelniker, Ofri Mosenzon, Avivit Cahn, Julia Kuder, Sabina A. Murphy, Deepak L. Bhatt, Lawrence A. Leiter, Darren K. McGuire, John Wilding, Christian T. Ruff, José Carlos Nicolau, Ingrid Gause‐Nilsson, Martin Fredriksson, Anna Maria Langkilde, Marc S. Sabatine, Stephen D. Wiviott

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsSt. Michael's Hospital
FundersDeutsche ForschungsgemeinschaftFundação LemannFoundation for Cardiovascular ResearchHarvard University
KeywordsMedicineDapagliflozinMyocardial infarctionInternal medicineCardiologyDiabetes mellitusType 2 Diabetes MellitusType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Sodium glucose transporter-2 inhibitors reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus and a history of atherosclerotic cardiovascular disease. Because of their baseline risk, patients with previous myocardial infarction (MI) may derive even greater benefit from sodium glucose transporter-2 inhibitor therapy. METHODS: DECLARE-TIMI 58 (Dapagliflozin Effect on Cardiovascular Events-Thrombolysis in Myocardial Infarction 58) randomized 17 160 patients with type 2 diabetes mellitus and either established atherosclerotic cardiovascular disease (n=6974) or multiple risk factors (n=10 186) to dapagliflozin versus placebo. The 2 primary end points were composite of MACE (cardiovascular death, MI, or ischemic stroke) and the composite of cardiovascular death or hospitalization for heart failure. Those with previous MI (n=3584) made up a prespecified subgroup of interest. RESULTS: In patients with previous MI (n=3584), dapagliflozin reduced the relative risk of MACE by 16% and the absolute risk by 2.6% (15.2% versus 17.8%; hazard ratio [HR], 0.84; 95% CI, 0.72-0.99; P=0.039), whereas there was no effect in patients without previous MI (7.1% versus 7.1%; HR, 1.00; 95% CI, 0.88-1.13; P=0.97; P for interaction for relative difference=0.11; P for interaction for absolute risk difference=0.048), including in patients with established atherosclerotic cardiovascular disease but no history of MI (12.6% versus 12.8%; HR, 0.98; 95% CI, 0.81-1.19). There seemed to be a greater benefit for MACE within 2 years after the last acute event ( P for interaction trend=0.007). The relative risk reductions in cardiovascular death/hospitalization for heart failure were more similar, but the absolute risk reductions tended to be greater: 1.9% (8.6% versus 10.5%; HR, 0.81; 95% CI, 0.65-1.00; P=0.046) and 0.6% (3.9% versus 4.5%; HR, 0.85; 95% CI, 0.72-1.00; P=0.055) in patients with and without previous MI, respectively ( P interaction for relative difference=0.69; P interaction for absolute risk difference=0.010). CONCLUSIONS: Patients with type 2 diabetes mellitus and previous MI are at high risk of MACE and cardiovascular death/hospitalization for heart failure. Dapagliflozin appears to robustly reduce the risk of both composite outcomes in these patients. Future studies should aim to confirm the large clinical benefits with sodium glucose transporter-2 inhibitors we observed in patients with previous MI. 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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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 designNon-randomized 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

Citations330
Published2019
Admission routes1
Has abstractyes

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