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Effects of canagliflozin on cardiovascular and kidney outcomes and mortality in primary and secondary cardiovascular prevention: pooled analysis from the CANVAS program and CREDENCE trial

2022· article· en· W4306319520 on OpenAlexaff
F Ang, W Rapattoni, H S Bajaj, G.B. John Mancini, Paul Poirier, Abhinav Sharma, Norman C. Wong, April Slee, Anna S. Levin, Kenneth W. Mahaffey

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of CalgaryMcGill University Health CentreUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of British Columbia
Fundersnot available
KeywordsCanagliflozinMedicinePlaceboInternal medicineKidney diseaseHazard ratioType 2 diabetesDiabetes mellitusType 2 Diabetes MellitusEmpagliflozinMyocardial infarctionEndocrinologyConfidence intervalPathology

Abstract

fetched live from OpenAlex

Abstract Background/Introduction Individuals with type 2 diabetes mellitus (T2DM) are at a greater risk for experiencing cardiovascular (CV) and kidney events. Canagliflozin is a sodium glucose co-transporter 2 inhibitor that has demonstrated reduction of these events in participants with T2DM with or without a history of CV disease (CVD) in both the CANVAS Program and CREDENCE trial. Purpose To determine the pooled effects of canagliflozin on CV outcomes, kidney outcomes, and all-cause mortality in trial participants with and without a history of CVD (secondary and primary prevention, respectively). Methods This post hoc analysis pooled individual participant data from the CANVAS Program and CREDENCE trial. The effects of canagliflozin versus placebo on time to first event for CV outcomes (major adverse cardiovascular events [MACE], which was defined as CV death, myocardial infarction [MI] or stroke; CV death; hospitalization for heart failure [HHF], and the composite of CV death or HHF), kidney outcomes (end-stage kidney disease [ESKD], doubling of serum creatinine [dSCr], and the composite of ESKD or dSCr), and all-cause mortality were assessed in participants with T2DM with or without a history of CVD. Results Among the 14,543 participants from the pooled CANVAS Program (N=10,142) and CREDENCE trial (N=4401), 5667 (39%; canagliflozin, n=3128; placebo, n=2539) were in the primary prevention group and 8876 (61%; canagliflozin, n=4869; placebo, n=4007) were in the secondary prevention group. Baseline characteristics of participants in each group were generally similar. Across both primary and secondary prevention participants, no heterogeneity in the relative risk reduction of CV outcomes, kidney outcomes, and all-cause mortality with canagliflozin versus placebo was observed (all P interaction >0.624; Figures 1 and 2). The benefits of canagliflozin on MACE and the composite of CV death or HHF were observed as early as 6 months into treatment in both subgroups of participants and were sustained throughout the study. Conclusions In this pooled analysis of patient-level data from the CANVAS Program and CREDENCE trial, treatment with canagliflozin demonstrated early benefits and was associated with reduced risk of CV outcomes, kidney outcomes, and all-cause mortality, with similar results across primary and secondary prevention participants with T2DM. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Janssen, Inc.

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)0.018
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.019
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.268
Teacher spread0.248 · 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 designMeta-analysis
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

Citations2
Published2022
Admission routes1
Has abstractyes

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