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Record W2709730559 · doi:10.1093/ehjci/eux141.009

P281Baseline characteristics of patients with atrial fibrillation with and without comorbid heart failure: the GLORIA-AF registry

2017· article· en· W2709730559 on OpenAlexaff
SJ. Dubner, Huisman Mv, HC Diener, Jonathan L. Halperin, KJ Rothman, Ma Cs, Kristina Zint, Lionel Riou França, Shihai Lu, Christine Teutsch, Miney Paquette, GYH Lip

Bibliographic record

VenueEP Europace · 2017
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsBoehringer Ingelheim (Canada)
Fundersnot available
KeywordsMedicineAtrial fibrillationHeart failureCardiologyInternal medicine

Abstract

fetched live from OpenAlex

On behalf of: GLORIA-AF Investigators Funding Acknowledgements: The study was funded by Boehringer Ingelheim. Introduction: Heart failure (HF) and atrial fibrillation (AF) are among the most common cardiovascular conditions and frequently co-exist. There is ample evidence that AF and HF both have deleterious effects, and together they increase the risk of thromboembolic events more than additively. GLORIA-AF is a global registry programme of newly diagnosed non-valvular AF patients at risk of stroke, consecutively enrolled irrespective of antithrombotic treatment prescribed. Purpose: This analysis of patients enrolled in phase II of GLORIA-AF (which started after approval of dabigatran in the respective countries) aimed to compare baseline characteristics, comorbid diseases and co-medications in the subset with HF vs those without HF (NYHA class II–IV or ejection fraction ≤40%). Methods: Eligible patients were those who completed a baseline visit in phase II. Results: A total of 15,092 patients were included in the full baseline set. After excluding 149 due to missing data, 3647 AF patients were diagnosed with comorbid HF, while 11,296 did not have comorbid HF. There were regional differences in the prevalence of HF: 19.7% in North America, 23.4% in Europe, 27.3% in Asia, 30.3% in the Middle East/South Africa and 32.4% in Latin America. When compared with those without HF, patients with HF were more likely to be symptomatic; have a history of persistent or permanent AF, coronary artery disease or myocardial infarction; and have a CHA2DS2VASc score ≥2. There were no appreciable differences in the proportion of patients ≥75 years, and those with HAS BLED score ≥3 between the two groups (Figure). The use of antihypertensive, HF and antiarrhythmic medications was higher among HF patients: beta blockers (70.5 vs 56.9%, respectively), diuretics (67.4 vs 29.5%), digoxin (22.0 vs 8.0%), other antiarrhythmic drugs (8.9 vs 4.1%), angiotensin-converting enzyme inhibitors (45.1 vs 27.2%) and angiotensin receptor blockers (23.3 vs 24.9%). Overall anticoagulant treatment patterns were similar between patients with and without HF. Anticoagulant treatment was administered to 81.5% of patients with HF (non-vitamin K antagonist [VKA] oral anticoagulants [NOAC] 46.6% and VKA 34.9%) and 79.5% with no HF (NOAC 48.0% and VKA 31.5%) with regional differences. Conclusions: This analysis provides additional insights among newly diagnosed patients with non-valvular AF who have a comorbid diagnosis of HF. Such patients are more likely to have symptomatic and persistent/permanent AF. Regional differences were observed with more patients in Asia, the Middle East and Latin America with an HF diagnosis than counterparts in North America or Europe. Abstract P281 Figure.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.290
Teacher spread0.264 · 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
Published2017
Admission routes1
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