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Record W4391028843 · doi:10.1161/jaha.123.031586

Primary and Secondary Cardiovascular and Kidney Prevention With Canagliflozin: Insights From the CANVAS Program and CREDENCE Trial

2024· article· en· W4391028843 on OpenAlexafffund
Abhinav Sharma, Amir Razaghizad, Abdulaziz Joury, Adeera Levin, Harpreet S. Bajaj, G.B. John Mancini, Norman C. Wong, April Slee, Fernando G. Ang, Wally Rapattoni, Brendon L. Neuen, Clare Arnott, Vlado Perkovic, Kenneth W. Mahaffey

Bibliographic record

VenueJournal of the American Heart Association · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsBrampton Civic HospitalBC Innovation CouncilUniversity of British ColumbiaUniversity of CalgaryMcGill University Health Centre
FundersNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of HealthIdorsia PharmaceuticalsIngham Institute for Applied Medical ResearchAstellas PharmaSanofiKidney Foundation of CanadaKowa CompanyGilead SciencesPfizerNational Institute of Diabetes and Digestive and Kidney DiseasesAmgenEli Lilly and CompanyAstraZenecaNovo NordiskVerily Life SciencesCanadian Institutes of Health ResearchUniversity of WashingtonAmerican Heart Association
KeywordsCanagliflozinMedicineKidney diseaseInternal medicineDiabetes mellitusType 2 diabetesHazard ratioProportional hazards modelEmpagliflozinPlaceboClinical trialEndocrinologyConfidence intervalPathology

Abstract

fetched live from OpenAlex

Background This study evaluated the effects of canagliflozin in patients with type 2 diabetes with and without prevalent cardiovascular disease (secondary and primary prevention). Methods and Results This was a pooled participant‐level analysis of the CANVAS (Canagliflozin Cardiovascular Assessment Study) Program and CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) trial. The CANVAS Program included participants with type 2 diabetes at elevated cardiovascular risk, whereas the CREDENCE trial included participants with type 2 diabetes and albuminuric chronic kidney disease. Hazard ratios (HRs) with interaction terms were obtained from Cox regression models to estimate relative risk reduction with canagliflozin versus placebo across the primary and secondary prevention groups. We analyzed 5616 (38.9%) and 8804 (61.1%) individuals in the primary and secondary prevention subgroups, respectively. Primary versus secondary prevention participants were on average younger (62.2 versus 63.8 years of age) and more often women (42% versus 31%). Canagliflozin reduced the risk of major adverse cardiovascular events (HR, 0.84 [95% CI, 0.76–0.94]) consistently across primary and secondary prevention subgroups ( P interaction =0.86). Similarly, no treatment effect heterogeneity was observed with canagliflozin for hospitalization for heart failure, cardiovascular death, end‐stage kidney disease, or all‐cause mortality (all P interaction >0.5). Conclusions Canagliflozin reduced cardiovascular and kidney outcomes with no statistical evidence of heterogeneity for the treatment effect across the primary and secondary prevention subgroups in the CANVAS Program and CREDENCE trial. Although studies on the optimal implementation of canagliflozin within these populations are warranted, these results reinforce canagliflozin's role in cardiorenal prevention and treatment in individuals with type 2 diabetes. Registration URL: https://www.clinicaltrials.gov ; Unique identifiers: NCT01032629, NCT01989754, NCT02065791.

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)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.009
GPT teacher head0.246
Teacher spread0.238 · 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 designObservational
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

Citations7
Published2024
Admission routes2
Has abstractyes

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