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Record W2749380187 · doi:10.1056/nejmoa1709118

Rivaroxaban with or without Aspirin in Stable Cardiovascular Disease

2017· article· en· W2749380187 on OpenAlexaff
John W. Eikelboom, Stuart J. Connolly, Jackie Bosch, Gilles R. Dagenais, Robert G. Hart, Olga Shestakovska, Rafael Díaz, Marco Alings, Eva Lonn, Sonia S. Anand, Petr Widimský, Masatsugu Hori, Álvaro Avezum, Leopoldo Soares Piegas, Kelley R. Branch, Jeffrey L. Probstfield, Deepak L. Bhatt, Jun Zhu, Yan Liang, Aldo P. Maggioni, Patricio López‐Jaramillo, Martin O’Donnell, Ajay K. Kakkar, Keith A.A. Fox, Alexander Parkhomenko, Georg Ertl, Stefan Störk, Mátyás Keltai, Lars Rydén, Nana Pogosova, Antonio L Dans, Fernando Laņas, Patrick Commerford, Christian Torp‐Pedersen, Peter Verhamme, Dragoş Vinereanu, Jae‐Hyung Kim, Andrew M. Tonkin, Basil S. Lewis, Camilo Félix, Khalid Yusoff, Philippe Gabríel Steg, Kaj Metsärinne, Nancy Cook Bruns, Frank Misselwitz, Edmond Chen, Darryl P. Leong, Salim Yusuf

Bibliographic record

VenueNew England Journal of Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersDaiichi Sankyo EuropeLEO PharmaServierNovo NordiskAstellas PharmaFresenius Medical Care North AmericaEisaiBelvoir Media GroupIronwood Pharmaceuticals, IncorporatedAgence Nationale de la RechercheRegado BiosciencesAstraZenecaAmarin CorporationBoston Scientific CorporationMassachusetts Medical SocietyRegeneron PharmaceuticalsCleveland ClinicBristol-Myers SquibbEli Lilly and CompanyCSL BehringUniversity College LondonBayer HealthCareSanofiGlaxoSmithKlineAmgenPfizerU.S. Department of Veterans Affairs
KeywordsRivaroxabanAspirinMedicineDiseaseInternal medicineCardiologyIntensive care medicineAtrial fibrillationWarfarin

Abstract

fetched live from OpenAlex

BACKGROUND: We evaluated whether rivaroxaban alone or in combination with aspirin would be more effective than aspirin alone for secondary cardiovascular prevention. METHODS: In this double-blind trial, we randomly assigned 27,395 participants with stable atherosclerotic vascular disease to receive rivaroxaban (2.5 mg twice daily) plus aspirin (100 mg once daily), rivaroxaban (5 mg twice daily), or aspirin (100 mg once daily). The primary outcome was a composite of cardiovascular death, stroke, or myocardial infarction. The study was stopped for superiority of the rivaroxaban-plus-aspirin group after a mean follow-up of 23 months. RESULTS: The primary outcome occurred in fewer patients in the rivaroxaban-plus-aspirin group than in the aspirin-alone group (379 patients [4.1%] vs. 496 patients [5.4%]; hazard ratio, 0.76; 95% confidence interval [CI], 0.66 to 0.86; P<0.001; z=-4.126), but major bleeding events occurred in more patients in the rivaroxaban-plus-aspirin group (288 patients [3.1%] vs. 170 patients [1.9%]; hazard ratio, 1.70; 95% CI, 1.40 to 2.05; P<0.001). There was no significant difference in intracranial or fatal bleeding between these two groups. There were 313 deaths (3.4%) in the rivaroxaban-plus-aspirin group as compared with 378 (4.1%) in the aspirin-alone group (hazard ratio, 0.82; 95% CI, 0.71 to 0.96; P=0.01; threshold P value for significance, 0.0025). The primary outcome did not occur in significantly fewer patients in the rivaroxaban-alone group than in the aspirin-alone group, but major bleeding events occurred in more patients in the rivaroxaban-alone group. CONCLUSIONS: Among patients with stable atherosclerotic vascular disease, those assigned to rivaroxaban (2.5 mg twice daily) plus aspirin had better cardiovascular outcomes and more major bleeding events than those assigned to aspirin alone. Rivaroxaban (5 mg twice daily) alone did not result in better cardiovascular outcomes than aspirin alone and resulted in more major bleeding events. (Funded by Bayer; COMPASS ClinicalTrials.gov number, NCT01776424 .).

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)0.004
metaresearch head score (Gemma)0.004
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: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.084
GPT teacher head0.342
Teacher spread0.258 · 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".

Quick stats

Citations2,412
Published2017
Admission routes1
Has abstractyes

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