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Record W3110418780 · doi:10.1093/ehjci/ehaa946.0639

Permanent discontinuation of different anticoagulants in patients with atrial fibrillation and the impact on clinical outcome: data from the GARFIELD-AF registry

2020· article· en· W3110418780 on OpenAlexaff
Frank Cools, D. Johnson, Karen S. Pieper, A. John Camm, Jean‐Pierre Bassand, David Fitzmaurice, Keith A.A. Fox, Samuel Z. Goldhaber, Shinya Goto, Sylvia Haas, A. G. G. Turpie, Freek W.A. Verheugt, Frank Misselwitz, Gloria Kayani, A. K. Kakkar

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineDiscontinuationAtrial fibrillationStroke (engine)Internal medicineHazard ratioMyocardial infarctionCoronary artery diseaseRivaroxabanRisk factorRenal functionLower riskCardiologySurgeryWarfarinConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background Non-Vitamin K Antagonists (NOAC) are replacing vitamin K Antagonists (VKA) as first line oral anticoagulant therapy (OAC) in patients with non-valvular atrial fibrillation (NVAF). Discontinuation of OAC might put patients at increased risk. It was anticipated that patients who were on NOAC would discontinue OAC less. Purpose We compare the rates and impact on outcome of the discontinuation of NOAC and VKA using data from the GARFIELD-AF registry. Methods Patients included in GARFIELD-AF, had a new diagnosis of NVAF and at least 1 stroke risk factor. In this analysis 26,299 patients (VKA: 13,012; NOAC: 13,287) that received OAC were included. Permanent discontinuation was defined as stopping OAC for at least 7 consecutive days (whether or not restarted during follow-up). Marginal structural Cox proportional hazards models estimated the effect of discontinuation on death, cardiovascular (CV) death, non-haemorrhagic stroke + systemic embolism (NHS+SE), myocardial infarction (MI), or combined endpoints. Adjustments were made for both baseline factors and time dependent variables. Results Of all patients, 15.6% discontinued OAC (VKA: 15.4%; NOAC: 15.8%) over a median follow-up of 181 days (IQR: 359). Most discontinued early (67.0% of patients on VKA and 47.1% of patients on NOAC ≤4 months). Significantly higher discontinuation risk was seen with worsening kidney function, coronary artery disease, history of bleeding (baseline factors), as well as with all types of bleeding (time dependent factors). Lower discontinuation rates were seen with history of stroke/TIA, hypertension, increasing age, permanent AF (all p<0.01). Mean CHA2DS2-VASc score was 3 in all groups. Patients in both treatment arms who discontinued were at increased risk for death, NHS+SE, MI as well as combined endpoints of death/NHS+SE/MI, death/NHS+SE and a trend towards higher CV death (Figure 1). All interaction tests for the interaction of treatment and discontinuation had a p value >0.4. The association between discontinuation and outcomes did not change when a 30 day discontinuation window was used. Conclusion The rate of discontinuation in this study was 15.8% and comparable for VKA and NOAC over a 2-year follow-up. Discontinuation rates were the highest soon after the initiation of treatment. When VKA or NOAC was stopped for ≥7 consecutive days, the risk of NHS+SE, death, MI or any combined endpoints were significantly worse in both treatment arms. These data suggest that discontinuation of anticoagulant treatment with VKA or NOAC should be discouraged. HR of patients who discontinued OAC Funding Acknowledgement Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): The GARFIELD-AF registry is funded by an unrestricted research grant from Bayer AG.

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)0.005
metaresearch head score (Gemma)0.011
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.199
GPT teacher head0.407
Teacher spread0.208 · 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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Citations1
Published2020
Admission routes1
Has abstractyes

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