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Record W3108116011 · doi:10.1093/ehjci/ehaa946.0631

Guideline-directed medical therapies for comorbidities among patients with atrial fibrillation: results from GARFIELD-AF

2020· article· en· W3108116011 on OpenAlexaff
A. John Camm, Jan Steffel, Saverio Virdone, Jean‐Pierre Bassand, David Fitzmaurice, Keith A.A. Fox, Samuel Z. Goldhaber, Shinya Goto, Sylvia Haas, Alexander G. G. Turpie, Freek W.A. Verheugt, Frank Misselwitz, Gloria Kayani, Karen S. Pieper, A. K. Kakkar

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAtrial fibrillationGuidelineInternal medicineStroke (engine)Diabetes mellitusPopulationCoronary artery diseaseCardiologySurgeryPathology

Abstract

fetched live from OpenAlex

Abstract Introduction The GARFIELD-AF registry is a prospective, multicentre, observational study of adults with recently diagnosed non-valvular atrial fibrillation (AF) and at least one risk factor for stroke. In GARFIELD-AF the absolute risk reduction of mortality associated with anticoagulation is far greater than the apparent absolute risk reduction in (ischemic) stroke. One potential explanation is improved treatment, with the use of comprehensive guideline-directed medical therapies (GDMT), in patients with AF receiving oral anticoagulant (OAC) therapy. The objectives were to identify the potential relationships between anticoagulation status, GDMT use and clinical outcomes. Methods Use of GDMT was determined on the basis of published European Society for Cardiology guidelines operative between 2010 and 2016. We explored the use of GDMT in patients enrolled in GARFIELD-AF (March 2010-Aug 2016) with CHA2DS2-VASc ≥2 and with one or more of five comorbidities–coronary artery disease, diabetes mellitus, heart failure, hypertension and peripheral vascular disease. Association between GDMT use and clinical outcomes events was evaluated with Cox-proportional hazards models. The models included stratification by all possible combinations of the five comorbidities used to define GDMT eligibility. Results The study population comprised of 39,946 patients who had one or more comorbidities (3238 [8.1%] received none of the GDMT, 17,398 [43.6%] received some, and 19,310 [48.3%] received all of the GDMT for which they were eligible). Patients on OAC tended to receive all the GDMTs more frequently compared to patients on no OAC (50.2% vs 44.8%, respectively). Comprehensive GDMT was associated with a lower risk of all-cause mortality (HR: 0.89 [0.80–0.99]) and non-cardiovascular mortality (0.80 [0.68–0.95]) compared to inadequate or no GDMT but was not associated with a lower risk of stroke (HR: 1.04 (0.88–1.24)] (Figure). The effect of OAC was beneficial for mortality and stroke risk whether receiving comprehensive GDMT or not. Conclusion OAC therapy is associated with a lower risk of all-cause mortality, non-cardiovascular mortality and stroke/SE in comparison with no OAC, irrespective of GDMT use in patients with CHA2DS2-VASc ≥2. Although the use of GDMT is associated with a significant reduction in mortality, there is little evidence that this explains the decrease in mortality with the use of OAC. GDMT use at two years of follow-up 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)0.002
metaresearch head score (Gemma)0.006
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.087
GPT teacher head0.326
Teacher spread0.239 · 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
Published2020
Admission routes1
Has abstractyes

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