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Assessing the applicability and outcomes of the COMPASS trial a large cohort of atherosclerotic disease patients

2021· article· en· W4386660583 on OpenAlexaff
Robert C. Welsh, Douglas C. Dover, M. Sean McMurtry, Kevin R. Bainey, Finlay A. McAlister, Padma Kaul

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsUniversity of AlbertaCanadian VIGOUR Centre
Fundersnot available
KeywordsMedicineMaceRivaroxabanMyocardial infarctionStroke (engine)Internal medicineHazard ratioCohortPopulationCoronary artery diseaseWarfarinPhysical therapySurgeryPercutaneous coronary interventionConfidence intervalAtrial fibrillation

Abstract

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Abstract Background Atherosclerotic Cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality worldwide with substantial impact on health care resources. Rivaroxaban 2.5 mg twice daily with low dose ASA reduced death, myocardial infarction and stroke compared to ASA alone in stable ASCVD patients studied in the COMPASS trial. Purpose To assess the applicability and potential outcomes of applying the COMPASS antithrombotic strategy in a population-based cohort of patients with ASCVD. Methods All patients with a new diagnosis of ASCVD identified during hospital admission or outpatient medical encounters using validated case definitions from 2008–2019 were included. We determined the proportion who met COMPASS eligibility criteria (Eligible), the proportion who met inclusion criteria but had exclusion criteria (Excluded), and the proportion who did not meet inclusion criteria (Ineligible). Primary outcomes of interest were CV death, myocardial infarction, and stroke (MACE), with secondary outcomes all cause death, CV hospitalization, PAD intervention, amputation, and all bleeding which were followed to end of study. Results Of 226,446 new ASCVD patients in the 11 years studied, 73% had coronary artery disease, 17% had peripheral artery disease including cerebral and peripheral vascular disease (PAD), and 10% had both. Of the 364,442 prevalent cases, 27% met COMPASS eligibility criteria, another 42% met inclusion criteria but would have been excluded and 31% were Ineligible. The main reasons for exclusion were high bleeding risk characteristics in 69% and concomitant medical therapy (CYP3A4 inducers 30%, oral anticoagulants 28%, and dual antiplatelet therapy 7%). The MACE event rates were approximately twice as high in the excluded group as those deemed COMPASS eligible (figures 1). COMPASS eligible patients in our cohort exhibited event rates similar to the ASA arm of COMPASS (figure 2). The other event rates per 100 person-years for Eligible, Excluded, and Ineligible patients respectively were: all-cause death 4.6, 10.6, 1.2,; CV hospitalization 4.8, 8.8, 3.0; PAD intervention 0.6, 0.6, 0.1; and all bleeding 1.9, 4.3, 1.1. If the COMPASS antithrombotic strategy of Rivaroxaban 2.5 twice daily with low dose ASA was given to patients deemed eligible in this population, there would have been a potential reduction of 87 MACE events, 34 CV death, 25 MI, 24 stroke, and 12 amputations per 10,000 patient years of treatment. Conclusion In a population of 4.4 million persons, there are approximately 20,000 incident ASCVD patients diagnosed yearly. Approximately 70% of patients with ASCVD in the real-world met COMPASS inclusion criteria, although more than half would be excluded due to high-bleed risk characteristics or concomitant medical therapy. Implementing the COMPASS antithrombotic strategy would result in substantial reduction in CV death and MACE events. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Bayer MACE by COMPASS eligibilityEvent rates compared to COMPASS ASA

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)0.012
metaresearch head score (Gemma)0.018
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.311
Teacher spread0.280 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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