Predictors of intracranial hemorrhage in patients with atrial fibrillation treated with oral anticoagulants: Insights from the GARFIELD-AF and ORBIT-AF registries.

Background: An unmet need exists to reliably predict the risk of intracranial hemorrhage (ICH) in patients with atrial fibrillation (AF) treated with oral anticoagulants (OACs).

Hypothesis: An externally validated model improves ICH risk stratification.

Methods: Independent factors associated with ICH were identified by Cox proportional hazard modeling, using pooled data from the GARFIELD-AF (Global Anticoagulant Registry in the FIELD-Atrial Fibrillation) and ORBIT-AF (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation) registries.

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

Aims: This study aimed to identify relationships in recently diagnosed atrial fibrillation (AF) patients with respect to anticoagulation status, use of guideline-directed medical therapy (GDMT) for comorbid cardiovascular conditions (co-GDMT), and clinical outcomes. The Global Anticoagulant Registry in the FIELD (GARFIELD)-AF is a prospective, international registry of patients with recently diagnosed non-valvular AF at risk of stroke (NCT01090362).

Methods And Results: Guideline-directed medical therapy was defined according to the European Society of Cardiology guidelines.

Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England.

Aims: The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England.

Methods And Results: Eligible participants (aged ≥30 years without AF diagnosis;  = 23 745) from six general practices in England were randomized into intervention and control arms. Intervention arm participants, identified by the algorithm as high risk of undiagnosed AF ( = 944), were invited for diagnostic testing ( = 256 consented); those who did not accept the invitation, and all control arm participants, were managed routinely.

Clinical outcomes of left atrial appendage occlusion versus direct oral anticoagulation in patients with atrial fibrillation and prior ischemic stroke: A propensity-score matched study.

Background: This propensity-score matched study investigated clinical outcomes associated with left atrial appendage occlusion (LAAO) versus direct oral anticoagulation (DOAC) in patients with AF and prior ischemic stroke.

Methods: AF patients enrolled in the Amulet Observational Study with a history of ischemic stroke and successful LAAO (n = 299) were compared with a propensity-score matched cohort of incident AF patients with prior ischemic stroke and treated by DOAC (n = 301). The control cohort was identified through the Danish National Patient Registries.

Clinical Outcomes Associated With Left Atrial Appendage Occlusion Versus Direct Oral Anticoagulation in Atrial Fibrillation.

Objectives: This study sought to investigate clinical outcomes associated with left atrial appendage occlusion (LAAO) versus direct oral anticoagulants (DOACs) in patients with high-risk atrial fibrillation (AF).

Background: LAAO has been shown to be noninferior to warfarin for stroke prevention in AF. However, anticoagulation with DOACs is now preferred over warfarin as thromboprophylaxis in AF.

The 4S-AF Scheme (Stroke Risk; Symptoms; Severity of Burden; Substrate): A Novel Approach to In-Depth Characterization (Rather than Classification) of Atrial Fibrillation.

Atrial fibrillation (AF) is a complex condition requiring holistic management with multiple treatment decisions about optimal thromboprophylaxis, symptom control (and prevention of AF progression), and identification and management of concomitant cardiovascular risk factors and comorbidity. Sometimes the information needed for treatment decisions is incomplete, as available classifications of AF mostly address a single domain of AF (or patient)-related characteristics. The most widely used classification of AF based on AF episode duration and temporal patterns (that is, the classification to first-diagnosed, paroxysmal, persistent/long-standing persistent, and permanent AF) has contributed to a better understanding of AF prevention and treatment but its limitations and the need for a multidimensional AF classification have been recognized as more complex treatment options became available.

New artificial intelligence prediction model using serial prothrombin time international normalized ratio measurements in atrial fibrillation patients on vitamin K antagonists: GARFIELD-AF.

Aims: Most clinical risk stratification models are based on measurement at a single time-point rather than serial measurements. Artificial intelligence (AI) is able to predict one-dimensional outcomes from multi-dimensional datasets. Using data from Global Anticoagulant Registry in the Field (GARFIELD)-AF registry, a new AI model was developed for predicting clinical outcomes in atrial fibrillation (AF) patients up to 1 year based on sequential measures of prothrombin time international normalized ratio (PT-INR) within 30 days of enrolment.

'Real-world' observational studies in arrhythmia research: data sources, methodology, and interpretation. A position document from European Heart Rhythm Association (EHRA), endorsed by Heart Rhythm Society (HRS), Asia-Pacific HRS (APHRS), and Latin America HRS (LAHRS).

The field of observational studies or "real world studies" is in rapid development with many new techniques introduced and increased understanding of traditional methods. For this reason the current paper provides an overview of current methods with focus on new techniques. Some highlights can be emphasized: We provide an overview of sources of data for observational studies.

Two-year outcomes of patients with newly diagnosed atrial fibrillation: results from GARFIELD-AF.

Aims: The relationship between outcomes and time after diagnosis for patients with non-valvular atrial fibrillation (NVAF) is poorly defined, especially beyond the first year.

Methods And Results: GARFIELD-AF is an ongoing, global observational study of adults with newly diagnosed NVAF. Two-year outcomes of 17 162 patients prospectively enrolled in GARFIELD-AF were analysed in light of baseline characteristics, risk profiles for stroke/systemic embolism (SE), and antithrombotic therapy.

Novel anticoagulants and antiplatelet agents; a guide for the urologist.

Novel oral anti-coagulants (NOACs) are increasingly being used in clinical practice and are set to almost entirely replace the vitamin K antagonists, such as warfarin, in the near future. Similarly, new antiplatelet agents are now regularly used in place of older agents, such as aspirin and clopidogrel. In an ageing population, with an increasing burden of complex comorbidities, urologists will frequently encounter patients who will be using such agents.

Does sex affect anticoagulant use for stroke prevention in nonvalvular atrial fibrillation? The prospective global anticoagulant registry in the FIELD-Atrial Fibrillation.

Background: Among patients with atrial fibrillation (AF), women are at higher risk of stroke than men. Using prospective cohort data from a large global population of patients with nonvalvular AF, we sought to identify any differences in the use of anticoagulants for stroke prevention in women and men.

Methods And Results: This was a prospective multicenter observational registry with 858 randomly selected sites in 30 countries.

A nonparametric approach to QT interval correction for heart rate.

We propose to use generalized additive models to fit the relationship between QT interval and RR (RR = 60/heart rate), and develop two new methods for correcting the QT for heart rate: the linear additive model and log-transformed linear additive model. The proposed methods are compared with six commonly used parametric models that were used in four clinical trial data sets and a simulated data set. The results show that the linear additive models provide the best fit for the vast majority of individual QT-RR profiles.