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Comparative effectiveness of NOAC vs VKA in patients representing common clinical challenges: results from the GARFIELD-AF registry

2021· article· en· W3207809452 on OpenAlexaff
Saverio Virdone, Jelle C L Himmelreich, Karen S. Pieper, A. John Camm, Jean‐Pierre Bassand, Keith A.A. Fox, David Fitzmaurice, Samuel Z. Goldhaber, Shinya Goto, Sylvia Haas, Gloria Kayani, Frank Misselwitz, Alexander G. G. Turpie, Freek W.A. Verheugt, A.K. Kakkar

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAtrial fibrillationVitamin K antagonistClinical trialInternal medicineVitamin kMajor bleedingPropensity score matchingRivaroxabanStroke (engine)WarfarinIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Large phase III trials of non-valvular atrial fibrillation (AF) patients have shown a favourable risk-to-benefit ratio with Non-Vitamin K antagonist oral anticoagulants (NOAC) compared to Vitamin K antagonists (VKA). Although the results of these trials are directly applicable to many AF patients, important subsets of patients were under-represented. Thus, there remains uncertainty about the safety and effectiveness of NOAC therapy in common challenging scenarios. Purpose The main purpose of this study is to quantify and compare the impact of NOAC vs VKA in settings where clinical uncertainty still exists and represents a considerable proportion of AF patients in clinical practice. Methods The analysis was conducted in patients enrolled in the largest AF multinational prospective registry (the Global Anticoagulant Registry in the FIELD–Atrial Fibrillation, GARFIELD-AF). We evaluated the effectiveness and safety of NOAC compared to VKA in three groups of patients representing common clinical challenges (CCC): 1) elderly patients (i.e. age ≥75), 2) increased bleeding risk (i.e. HAS-BLED ≥3 or prior bleeding), and 3) renal impairment (i.e. CKD stages II to IV). We applied a propensity score using an overlap weighting scheme to obtain unbiased estimates of the treatment effect within each CCC group. Weights were applied to Cox proportional hazards models to estimate the effects of the NOAC vs VKA comparison on the occurrence of death, non-haemorrhagic stroke/SE and major bleeding within 2 years of enrolment. Results Comparative effectiveness of NOAC vs VKA was assessed in 8607 elderly patients, 1711 with increased bleeding risk, and 4460 with renal impairment. The proportion of anticoagulated patients was low in patients with increased bleeding risk (59%), while in the other two CCC groups the corresponding proportion was close to the one in the overall population (72%). Among anticoagulated patients, NOAC were prescribed to 50–55% of patients in the CCC groups. Patients with a high risk of bleeding and impaired kidney function were less likely to be prescribed NOAC instead of VKA compared with the overall anticoagulated population (−5.4% and −4.7%, respectively). Propensity-weighted hazard ratios for all-cause mortality favored NOAC (vs VKA) in all three CCC groups: 0.86 (95% CI: 0.74–0.99) for elderly patients, 0.73 (0.53–1.00) for patients with increased bleeding risk, and 0.80 (0.65–0.98) for patients with renal impairment (Figure). Conclusion In the selected common challenging scenarios of AF patients, there were significant mortality reductions in favor of NOACs compared to VKAs. These observations suggest that NOACs are safe and effective in patients who are elderly, at increased bleeding risk, or renally impaired. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This study was supported by an unrestricted research grant from Bayer AG, Berlin, Germany, to TRI, London, UK, which sponsors the GARFIELD-AF registry. The work is supported by KANTOR CHARITABLE FOUNDATION for the Kantor-Kakkar Global Centre for Thrombosis Science.

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)0.018
metaresearch head score (Gemma)0.035
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 score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.258
GPT teacher head0.430
Teacher spread0.172 · 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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