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Record W2973841278 · doi:10.1016/j.jacc.2019.07.065

Major Bleeding in Patients With Coronary or Peripheral Artery Disease Treated With Rivaroxaban Plus Aspirin

2019· article· en· W2973841278 on OpenAlexaff
John W. Eikelboom, Jackie Bosch, Stuart J. Connolly, Olga Shestakovska, Gilles R. Dagenais, Robert G. Hart, Darryl P. Leong, Martin O’Donnell, Keith A.A. Fox, Deepak L. Bhatt, John A. Cairns, Christoph Tasto, Scott D. Berkowitz, Nancy Cook Bruns, Eva Muehlhofer, Rafael Díaz, Aldo P. Maggioni, Salim Yusuf

Bibliographic record

VenueJournal of the American College of Cardiology · 2019
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsUniversity of British ColumbiaInstitut universitaire de cardiologie et de pneumologie de QuébecHamilton Health SciencesPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsMedicineRivaroxabanAspirinCoronary artery diseaseInternal medicineHemostasisThrombosisHazard ratioAdverse effectGastroenterologySurgeryAnesthesiaWarfarinAtrial fibrillationConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: In patients with coronary or peripheral artery disease, the combination of rivaroxaban 2.5 mg twice daily and aspirin 100 mg once daily compared with aspirin 100 mg once daily reduced major adverse cardiovascular events and mortality and increased bleeding. OBJECTIVES: This study sought to explore the effects of the combination of rivaroxaban and aspirin compared with aspirin on sites, timing, severity, and management of bleeding in the COMPASS (Cardiovascular Outcomes for People Using Anticoagulation Strategies) study. METHODS: This study reports, by treatment group, the number and proportion of patients; hazard rate ratios for bleeding according to site and severity; the timing of bleeding using landmark analyses; and the number and proportion of patients who received blood products and other hemostatic treatments. RESULTS: Of 27,395 patients enrolled (mean age 68 years, 22% women), 18,278 were randomized to the combination of rivaroxaban and aspirin or to aspirin alone and followed for a mean of 23 months. Compared with aspirin alone, the combination increased modified International Society on Thrombosis and Hemostasis major bleeding (288 of 9,152 [3.1%] vs. 170 of 9,126 [1.9%]), (HR: 1.70; 95% CI: 1.40 to 2.05; p < 0.001), International Society on Thrombosis and Hemostasis major bleeding (206 of 9,152 [2.3%] vs. 116 of 9,126 [1.3%]), (HR: 1.78; 95% CI: 1.41 to 2.23; p < 0.0001), and minor bleeding (838 of 9,152 [9.2%] vs. 503 of 9,126 [5.5%]), (HR: 1.70; 95% CI 1.52 to 1.90; p < 0.0001); the combination also increased the need for any red cell transfusion (87 of 9,152 [1.0%] vs. 44 of 9,126 [0.5%]), (HR: 1.97; 95% CI 1.37 to 2.83, p = 0.0002). The gastrointestinal (GI) tract was the most common site of increased major bleeding (140 of 9,152 [1.5%] vs. 65 of 9,126 [0.7%]), (HR: 2.15; 95% CI: 1.60 to 2.89; p < 0.001), and the increase in bleeding was predominantly in the first year after randomization. Approximately one-third of major GI bleeding was gastric or duodenal, one-third was colonic or rectal, and one-third was from an unknown GI site. The study investigators reported that approximately three-quarters of major bleeding episodes were of mild or moderate intensity. A similar proportion of patients in each treatment group who experienced major bleeding received platelets, clotting factors, or other hemostatic agents. CONCLUSIONS: The combination of rivaroxaban and aspirin compared with aspirin alone increased major bleeding, mainly from the GI tract. Most excess bleeding occurred during the first year after randomization, was of mild or moderate intensity, and was managed with conventional supportive therapy. (Rivaroxaban for the Prevention of Major Cardiovascular Events in Coronary or Peripheral Artery Disease [COMPASS]; 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.219
Teacher spread0.212 · 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 teacher head, 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

Citations45
Published2019
Admission routes1
Has abstractyes

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