Asymptomatic atrial fibrillation

Predicting impaired cardiopulmonary exercise capacity in patients with atrial fibrillation using a simple echocardiographic marker

BACKGROUND

Exercise intolerance is a common symptom associated with atrial fibrillation (AF). However, echocardiographic markers that can predict impaired exercise capacity are lacking.

OBJECTIVE

This study aimed to investigate the association between echocardiographic parameters and exercise capacity assessed by cardiopulmonary exercise testing in patients with AF.

METHODS

This single-center prospective study enrolled patients with AF who underwent echocardiography and cardiopulmonary exercise testing to evaluate exercise capacity at a tertiary center for AF management from 2020 to 2022. Patients with valvular heart disease, reduced left ventricular ejection fraction, or documented cardiomyopathy were excluded.

RESULTS

Of the 188 patients, 134 (71.2%) exhibited impaired exercise capacity (peak oxygen consumption ≤85%), including 4 (2.1%) having poor exercise capacity (peak oxygen consumption <50%). Echocardiographic findings revealed that these patients had an enlarged left atrial end-systolic diameter (LA); smaller left ventricular end-diastolic diameter (LVEDD); and increased relative wall thickness, tricuspid regurgitation velocity, and LA/LVEDD and E/e' ratios. In addition, they exhibited lower peak systolic velocity of the mitral annulus and LA reservoir strain. In the multivariate regression model, LA/LVEDD remained the only significant echocardiographic parameter after adjustment for age, sex, and body mass index (P = .020). This significance persisted even after incorporation of heart rate reserve, N-terminal pro-B-type natriuretic peptide level, and beta-blocker use into the model.

CONCLUSION

In patients with AF, LA/LVEDD is strongly associated with exercise capacity. Further follow-up and validation are necessary to clarify its clinical implications in patient care.

Assessing the impact of atrial fibrillation self-care interventions: A systematic review

This systematic review evaluates the efficacy of self-care interventions for atrial fibrillation (AF), focusing on strategies for maintenance, monitoring, and management applied individually or in combination. Adhering to the 2020 PRISMA guidelines, the search strategy spanned literature from 2005 to 2023, utilizing keywords and subject headings for "atrial fibrillation" and "self-care" combined with the Boolean operator AND. The databases searched included Medline, Embase, and CINAHL. The initial search, conducted on February 17, 2021, and updated on May 16, 2023, identified 5160 articles, from which 2864 unique titles and abstracts were screened. After abstract screening, 163 articles were reviewed in full text, resulting in 27 articles being selected for data extraction; these studies comprised both observational and randomized controlled trial designs. A key finding in our analysis reveals that self-care interventions, whether singular, dual, or integrated across all three components, resulted in significant improvements across patient-reported, clinical, and healthcare utilization outcomes compared to usual care. Educational interventions, often supported by in-person sessions or telephone follow-ups, emerged as a crucial element of effective AF self-care. Additionally, the integration of mobile and web-based technologies alongside personalized education showed promise in enhancing outcomes, although their full potential remains underexplored. This review highlights the importance of incorporating comprehensive, theory-informed self-care interventions into routine clinical practice and underscores the need for ongoing innovation and the implementation of evidence-based strategies. The integration of education and technology in AF self-care aligns with the recommendations of leading health organizations, advocating for patient-centered, technology-enhanced approaches to meet the evolving needs of the AF population.

Differences in Iron Kinetics during Cardiac Load between Patients with Atrial Fibrillation and Those with Sinus Rhythm

INTRODUCTION

The prevalence of atrial fibrillation (AF) increases with age. Although most AF cases are caused by irregular electrical impulses near the pulmonary vein, not all elderly individuals develop AF. Moreover, risk factors such as hypertension and diabetes do not always lead to AF, even in severe conditions such as pneumonia. We aimed to examine iron kinetics, including ferritin, in patients with AF and individuals in normal sinus rhythm (NSR) using peripheral blood samples.

METHODS

This case-control study included 178 patients who visited the outpatient clinic of a cardiovascular and arrhythmia specialist at the National Center for Geriatrics and Gerontology between August and October 2023. Patients with missing iron-related blood tests and those with pacemaker implantation were excluded. Iron parameters (ferritin, free iron, transferrin saturation) were compared between AF (n = 53) and NSR (n = 125) groups.

RESULTS

The AF group had higher log brain natriuretic peptide (BNP) levels, indicating increased cardiac load (AF 2.18 vs. NSR 1.53). However, there were no significant differences in iron parameters between the AF and NSR groups. After matching for age, sex, and coronary artery disease, the AF group showed an increasing trend in ferritin and a decreasing trend in free iron with BNP elevation, suggesting chronic inflammation. In contrast, the NSR group showed no significant changes in iron parameters with BNP elevation.

CONCLUSION

Patients with AF are more likely to have elevated ferritin levels and decreased free iron levels during cardiac overload. Thus, they are more likely to present with chronic inflammation associated with cardiac overload in AF. Future studies should investigate the mechanisms underlying this phenomenon and its implications for AF treatment.

Diastolic Dysfunction and Atrial Fibrillation: Recognition, Interplay, and Management

Diastolic dysfunction occurs when the left ventricle loses its ability to relax normally, impairing ventricular filling during diastole. This most commonly occurs as a pathological sequela of left ventricular hypertrophy and remodeling due to chronic hypertension and/or age-related sclerotic changes of the aortic valve. This can subsequently deteriorate to diastolic heart failure or heart failure with preserved ejection fraction. There is a substantive interplay between atrial fibrillation and diastolic dysfunction, as atrial fibrillation can cause, exacerbate, or be a direct result of diastolic dysfunction and vice versa. In this review, we first independently define diastolic heart failure and atrial fibrillation while discussing the diagnostic guidelines, which encompass various modalities such as medical history, electrocardiography, echocardiography, and laboratory tests. We subsequently examine their interplay and pathophysiological links drawing on recent evidence in the literature. Finally, we discuss management approaches, including pharmacological interventions targeting rate and rhythm control, diuretics, and addressing comorbidities.

Enhancing ECG signal classification through pre-trained stacked-CNN embeddings: a transfer learning approach

Rapid and accurate electrocardiogram (ECG) signal classification is crucial in high-stakes healthcare settings. However, existing computational models often struggle to balance high performance with computational efficiency. This study introduces an innovative computational framework that combines transfer learning with traditional machine learning to optimize ECG classification. We use a pre-trained Stacked Convolutional Neural Network (SCNN) to generate high-dimensional feature embeddings, which are then evaluated by an array of machine learning classifiers. Our models demonstrate exceptional performance, particularly when utilizing embeddings from SCNNs trained on diverse datasets. This underscores the importance of data diversity in improving classifier discrimination. Notably, Multilayer Perceptrons (MLPs) stand out for their ability to balance computational efficiency with strong performance, achieving test F1-scores of 0.94 and 1.00 in multi-class and binary tasks on the CinC2017 dataset, and 0.85 and 0.99 on the CPSC2018 dataset. Our approach consistently outperforms existing methods, setting new benchmarks in ECG classification. The synergy between deep learning-based feature extraction and traditional machine learning through transfer learning offers a robust, efficient, and adaptable strategy for ECG classification, addressing a critical research gap and laying the groundwork for future advancements in this crucial healthcare field.

Sensitivity and specificity of handheld one lead ECG detecting atrial fibrillation in an outpatient clinic setting

AIMS

To validate the sensitivity and specificity of the Zenicor One handheld ECG device for detection of atrial fibrillation in an outpatient clinical setting.

METHODS AND RESULTS

Patients attending outpatient clinics at Danderyd Hospital (n = 220) were examined with one lead handheld ECG immediately after standard care 12‑lead ECG recording. Twelve recordings were excluded (atrial flutter or pacing) or missing. The recordings were dichotomously categorized as "atrial fibrillation" or "not atrial fibrillation" by two senior cardiologists. In cases of diverging interpretations, a third senior cardiologist had the deciding vote. Sensitivity and specificity in diagnosing atrial fibrillation was calculated with 12‑lead ECG as gold standard. Sensitivity and specificity for diagnosis of atrial fibrillation with one lead handheld ECG and 12‑lead ECG as gold standard was 98% and 99% respectively.

CONCLUSION

In a health-care outpatient setting, Zenicor One handheld ECG had high sensitivity and specificity for detection of atrial fibrillation when compared with 12‑lead ECG.

The influence of cardiac arrhythmias on the detection of heartbeats in the photoplethysmogram: benchmarking open-source algorithms

Objective.Cardiac arrhythmias are a leading cause of mortality worldwide. Wearable devices based on photoplethysmography give the opportunity to screen large populations, hence allowing for an earlier detection of pathological rhythms that might reduce the risks of complications and medical costs. While most of beat detection algorithms have been evaluated on normal sinus rhythm or atrial fibrillation recordings, the performance of these algorithms in patients with other cardiac arrhythmias, such as ventricular tachycardia or bigeminy, remain unknown to date.Approach. ThePPG-beatsopen-source framework, developed by Charlton and colleagues, evaluates the performance of the beat detectors namedQPPG,MSPTDandABDamong others. We applied thePPG-beatsframework on two newly acquired datasets, one containing seven different types of cardiac arrhythmia in hospital settings, and another dataset including two cardiac arrhythmias in ambulatory settings.Main Results. In a clinical setting, theQPPGbeat detector performed best on atrial fibrillation (with a medianF1score of 94.4%), atrial flutter (95.2%), atrial tachycardia (87.0%), sinus rhythm (97.7%), ventricular tachycardia (83.9%) and was ranked 2nd for bigeminy (75.7%) behindABDdetector (76.1%). In an ambulatory setting, theMSPTDbeat detector performed best on normal sinus rhythm (94.6%), and theQPPGdetector on atrial fibrillation (91.6%) and bigeminy (80.0%).Significance. Overall, the PPG beat detectorsQPPG,MSPTDandABDconsistently achieved higher performances than other detectors. However, the detection of beats from wrist-PPG signals is compromised in presence of bigeminy or ventricular tachycardia.

Detection of Atrial Fibrillation Episodes based on 3D Algebraic Relationships between Cardiac Intervals

In this study, the notion of perfect matrices of Lagrange differences is employed to detect atrial fibrillation episodes based on three ECG parameters (JT interval, QRS interval, RR interval). The case study comprised 8 healthy individuals and 7 unhealthy individuals, and the mean and standard deviation of age was 65.84 ± 1.4 years, height was 1.75 ± 0.12 m, and weight was 79.4 ± 0.9 kg. Initially, it was demonstrated that the sensitivity of algebraic relationships between cardiac intervals increases when the dimension of the perfect matrices of Lagrange differences is extended from two to three. The baseline dataset was established using statistical algorithms for classification by means of the developed decision support system. The classification helps to determine whether the new incoming candidate has indications of atrial fibrillation or not. The application of probability distribution graphs and semi-gauge indicator techniques aided in visualizing the categorization of the new candidates. Though the study's data are limited, this work provides a strong foundation for (1) validating the sensitivity of the perfect matrices of Lagrange differences, (2) establishing a robust baseline dataset for supervised classification, and (3) classifying new incoming candidates within the classification framework. From a clinical standpoint, the developed approach assists in the early detection of atrial fibrillation in an individual.

Atrial Fibrillation Detection With an Analog Smartwatch: Prospective Clinical Study and Algorithm Validation

BACKGROUND

Atrial fibrillation affects approximately 4% of the world's population and is one of the major causes of stroke, heart failure, sudden death, and cardiovascular morbidity. It can be difficult to diagnose when asymptomatic or in the paroxysmal stage, and its natural history is not well understood. New wearables and connected devices offer an opportunity to improve on this situation.

OBJECTIVE

We aimed to validate an algorithm for the automatic detection of atrial fibrillation from a single-lead electrocardiogram taken with a smartwatch.

METHODS

Eligible patients were recruited from 4 sites in Paris, France. Electrocardiograms (12-lead reference and single lead) were captured simultaneously. The electrocardiograms were reviewed by independent, blinded board-certified cardiologists. The sensitivity and specificity of the algorithm to detect atrial fibrillation and normal sinus rhythm were calculated. The quality of single-lead electrocardiograms (visibility and polarity of waves, interval durations, heart rate) was assessed in comparison with the gold standard (12-lead electrocardiogram).

RESULTS

A total of 262 patients (atrial fibrillation: n=100, age: mean 74.3 years, SD 12.3; normal sinus rhythm: n=113, age: 61.8 years, SD 14.3; other arrhythmia: n=45, 66.9 years, SD 15.2; unreadable electrocardiograms: n=4) were included in the final analysis; 6.9% (18/262) were classified as Noise by the algorithm. Excluding other arrhythmias and Noise, the sensitivity for atrial fibrillation detection was 0.963 (95% CI lower bound 0.894), and the specificity was 1.000 (95% CI lower bound 0.967). Visibility and polarity accuracies were similar (1-lead electrocardiogram: P waves: 96.9%, QRS complexes: 99.2%, T waves: 91.2%; 12-lead electrocardiogram: P waves: 100%, QRS complexes: 98.8%, T waves: 99.5%). P-wave visibility accuracy was 99% (99/100) for patients with atrial fibrillation and 95.7% (155/162) for patients with normal sinus rhythm, other arrhythmias, and unreadable electrocardiograms. The absolute values of the mean differences in PR duration and QRS width were <3 ms, and more than 97% were <40 ms. The mean difference between the heart rates from the 1-lead electrocardiogram calculated by the algorithm and those calculated by cardiologists was 0.55 bpm.

CONCLUSIONS

The algorithm demonstrated great diagnostic performance for atrial fibrillation detection. The smartwatch's single-lead electrocardiogram also demonstrated good quality for physician use in daily routine care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04351386; http://clinicaltrials.gov/ct2/show/NCT04351386.

Real-time realizable mobile imaging photoplethysmography

Photoplethysmography imaging (PPGI) sensors have attracted a significant amount of attention as they enable the remote monitoring of heart rates (HRs) and thus do not require any additional devices to be worn on fingers or wrists. In this study, we mounted PPGI sensors on a robot for active and autonomous HR (R-AAH) estimation. We proposed an algorithm that provides accurate HR estimation, which can be performed in real time using vision and robot manipulation algorithms. By simplifying the extraction of facial skin images using saturation (S) values in the HSV color space, and selecting pixels based on the most frequent S value within the face image, we achieved a reliable HR assessment. The results of the proposed algorithm using the R-AAH method were evaluated by rigorous comparison with the results of existing algorithms on the UBFC-RPPG dataset (n = 42). The proposed algorithm yielded an average absolute error (AAE) of 0.71 beats per minute (bpm). The developed algorithm is simple, with a processing time of less than 1 s (275 ms for an 8-s window). The algorithm was further validated on our own dataset (BAMI-RPPG dataset [n = 14]) with an AAE of 0.82 bpm.

Machine learning-based identification of risk-factor signatures for undiagnosed atrial fibrillation in primary prevention and post-stroke in clinical practice

AIMS

Atrial fibrillation (AF) carries a substantial risk of ischemic stroke and other complications, and estimates suggest that over a third of cases remain undiagnosed. AF detection is particularly pressing in stroke survivors. To tailor AF screening efforts, we explored German health claims data for routinely available predictors of incident AF in primary care and post-stroke using machine learning methods.

METHODS AND RESULTS

We combined AF predictors in patients over 45 years of age using claims data in the InGef database (n = 1 476 391) for (i) incident AF and (ii) AF post-stroke, using machine learning techniques. Between 2013-2016, new-onset AF was diagnosed in 98 958 patients (6.7%). Published risk factors for AF including male sex, hypertension, heart failure, valvular heart disease, and chronic kidney disease were confirmed. Component-wise gradient boosting identified additional predictors for AF from ICD-codes available in ambulatory care. The area under the curve (AUC) of the final, condensed model consisting of 13 predictors, was 0.829 (95% confidence interval (CI) 0.826-0.833) in the internal validation, and 0.755 (95% CI 0.603-0.890) in a prospective validation cohort (n = 661). The AUC for post-stroke AF was of 0.67 (95% CI 0.651-0.689) in the internal validation data set, and 0.766 (95% CI 0.731-0.800) in the prospective clinical cohort.

CONCLUSION

ICD-coded clinical variables selected by machine learning can improve the identification of patients at risk of newly diagnosed AF. Using this readily available, automatically coded information can target AF screening efforts to identify high-risk populations in primary care and stroke survivors.

The Asymptomatic Patient with Atrial Fibrillation, previously reported in some but now found in many

Investigators in Japan evaluated echocardiographic and hemodynamic findings in patients with paroxysmal atrial fibrillation, comparing the findings of asymptomatic patients with patients who had symptomatic atrial fibrillation. Transseptal measurements of left atrial pressure were obtained. The multivariate analysis showed that patients with asymptomatic atrial fibrillation had significantly lower E/e on echo and lower rates of change of peak LA pressure in sinus rhythm or with high right atrial pacing. Patients with asymptomatic atrial fibrillation have preserved diastolic function and significantly less increase in LA pressure during atrial fibrillation. Although asymptomatic atrial fibrillation has generally been shown to be present in approximately 25% of patients with atrial fibrillation, new technologies of digital monitoring have revealed documentation of an increased number of patients with asymptomatic atrial fibrillation. This article is protected by copyright. All rights reserved.

Recent Advances in Materials and Flexible Sensors for Arrhythmia Detection

Arrhythmias are one of the leading causes of death in the United States, and their early detection is essential for patient wellness. However, traditional arrhythmia diagnosis by expert evaluation from intermittent clinical examinations is time-consuming and often lacks quantitative data. Modern wearable sensors and machine learning algorithms have attempted to alleviate this problem by providing continuous monitoring and real-time arrhythmia detection. However, current devices are still largely limited by the fundamental mismatch between skin and sensor, giving way to motion artifacts. Additionally, the desirable qualities of flexibility, robustness, breathability, adhesiveness, stretchability, and durability cannot all be met at once. Flexible sensors have improved upon the current clinical arrhythmia detection methods by following the topography of skin and reducing the natural interface mismatch between cardiac monitoring sensors and human skin. Flexible bioelectric, optoelectronic, ultrasonic, and mechanoelectrical sensors have been demonstrated to provide essential information about heart-rate variability, which is crucial in detecting and classifying arrhythmias. In this review, we analyze the current trends in flexible wearable sensors for cardiac monitoring and the efficacy of these devices for arrhythmia detection.

Enhancing Healthcare Access-Smartphone Apps in Arrhythmia Screening: Viewpoint

Atrial fibrillation is the most commonly reported arrhythmia and, if undiagnosed or untreated, may lead to thromboembolic events. It is therefore desirable to provide screening to patients in order to detect atrial arrhythmias. Specific mobile apps and accessory devices, such as smartphones and smartwatches, may play a significant role in monitoring heart rhythm in populations at high risk of arrhythmia. These apps are becoming increasingly common among patients and professionals as a part of mobile health. The rapid development of mobile health solutions may revolutionize approaches to arrhythmia screening. In this viewpoint paper, we assess the availability of smartphone and smartwatch apps and evaluate their efficacy for monitoring heart rhythm and arrhythmia detection. The findings obtained so far suggest they are on the right track to improving the efficacy of early detection of atrial fibrillation, thus lowering the risk of stroke and reducing the economic burden placed on public health.

Perception of atrial fibrillation in dependence of neuroticism

OBJECTIVE

Atrial fibrillation (AF) is associated with a varying symptom burden, which ranges from completely unawareness to disabling conditions. The present cross-sectional study tried to assess if neuroticism is associated with a greater degree of perception of AF related symptoms.

METHODS

162 patients who were considered for catheter ablation of AF were included. AF related symptom burden was quantified according to the European Heart Rhythm Association (EHRA) score. Personality traits were assessed using the Big Five personality traits (5BT).

RESULTS

Female patients reported higher symptom burden. Higher EHRA scores were furthermore associated with treatment with antiarrhythmic agents, digitalis, direct oral anticoagulants (DOAC), and antidepressant treatment, as well as suffering from heart failure or chronic kidney disease. Neuroticism showed a positive correlation to AF related symptom burden with significantly higher neuroticism scores in patients with higher EHRA scores (Rho = 0.41; 95%CI 0.26 to 0.53; p < .001), while no association was demonstrated for the other four personality traits. Multiple linear regression analysis revealed neuroticism as strongest independent predictor for symptomatic AF, followed by treatment with antiarrhythmic agents and DOAC.

CONCLUSIONS

Perception of AF related symptoms is a multifactorial process, which in our cohort was independently associated with neuroticism. Patients with higher symptom burden were also more likely to receive antiarrhythmic agents and DOAC, as well as antidepressants.

TRIAL REGISTRATION

German registry for clinical studies (DRKS), DRKS00019007.

The symptom experience of early and late treatment seekers before an atrial fibrillation diagnosis

BACKGROUND

Atrial fibrillation is a complex condition associated with a broad spectrum of symptoms, coupled with variability in the frequency, duration and severity of symptoms. Early treatment seeking is important to reduce the risk of stroke, heart failure and dementia. Despite the increasing prevalence, there remains a limited understanding of the symptom experience prior to an atrial fibrillation diagnosis, and how these experiences influence treatment-related decisions and time frames.

AIMS

This qualitative study aimed to explore the symptom experiences of patients receiving an early diagnosis of less than 48 hours and a late diagnosis of 48 hours or more after symptom awareness.

METHODS

Twenty-six adults were interviewed guided by the symptom experience model. The symptom checklist was used to probe patient's symptoms further. Data were analysed using a two-step approach to thematic analysis utilising concepts from the symptom experience model.

RESULTS

The two groups differed in their perception, evaluation and response to symptoms. The early diagnosis group (n = 6) experienced traumatic, severe and persistent symptoms, evoking concern and urgent treatment seeking. Conversely, the late diagnosis group (n = 20) reported more vague, paroxysmal symptoms that were readily ignored, self-theorised as non-illness related, and engaged in non-treatment strategies. Healthy self-perceptions, past experiences, atrial fibrillation knowledge and healthcare provider interactions influenced early or late treatment seeking.

CONCLUSION

For many, the atrial fibrillation pre-diagnosis was a tumultuous period, requiring prolonged periods to recognise symptoms and formulate treatment-seeking responses. This study may promote future research and strategies aimed at facilitating the early identification and response to symptoms among atrial fibrillation patients.

Risk factors and outcomes of new-onset atrial fibrillation in patients hospitalized in an internal medicine ward: a case-control study

Atrial fibrillation (AF) is a frequent pathology in Internal Medicine departments. The aim of our study was to identify the risk factors associated with the development of new-onset AF during hospitalization and to evaluate its outcome as in-hospital mortality. We conducted a retrospective case-control study on a cohort of 14,179 patients admitted to an internal medicine department. We included in the study the patients who did not have an anamnestic history of AF, who presented a sinus rhythm at the time of admission and who developed a new-onset AF during hospitalization. For each of these cases, two controls were enrolled who were not affected by AF. The patients included in the study were 588, including 196 cases and 392 controls. Patients who developed AF during hospitalization had significantly more comorbidity than controls. The most frequent causes for hospitalization were sepsis, significantly higher in the case group. From the results of the multivariate analysis, the factors related independently to the development of AF were the presence of a number of comorbidities ≥ 3 (OR = 1.52; p = 0.017), sepsis as a reason of hospitalization (OR = 2, 16; p = 0.001) and glycemic value at the admission ≥ 130 mg/dL (OR = 1.44; p = 0.047). Both the length of hospital stay and in-hospital mortality were higher in the group of patients who developed AF, with a statistically significant difference compared to controls (p < 0.001).

Photoplethysmography based atrial fibrillation detection: a review

Atrial fibrillation (AF) is a cardiac rhythm disorder associated with increased morbidity and mortality. It is the leading risk factor for cardioembolic stroke and its early detection is crucial in both primary and secondary stroke prevention. Continuous monitoring of cardiac rhythm is today possible thanks to consumer-grade wearable devices, enabling transformative diagnostic and patient management tools. Such monitoring is possible using low-cost easy-to-implement optical sensors that today equip the majority of wearables. These sensors record blood volume variations-a technology known as photoplethysmography (PPG)-from which the heart rate and other physiological parameters can be extracted to inform about user activity, fitness, sleep, and health. Recently, new wearable devices were introduced as being capable of AF detection, evidenced by large prospective trials in some cases. Such devices would allow for early screening of AF and initiation of therapy to prevent stroke. This review is a summary of a body of work on AF detection using PPG. A thorough account of the signal processing, machine learning, and deep learning approaches used in these studies is presented, followed by a discussion of their limitations and challenges towards clinical applications.

The prevalence of atrial fibrillation on 48-hour ambulatory electrocardiography in African Americans compared to Whites: The Atherosclerosis Risk in Communities (ARIC) study

BACKGROUND

A lower prevalence of atrial fibrillation (AF), but paradoxically higher burden of cardiovascular disease risk factors, has been observed among African Americans compared to Whites in studies of AF identified by mostly 12-lead electrocardiograms (ECGs) and clinically.

METHODS

We performed 48-hour ambulatory electrocardiography (aECG) in a biracial sample of 1,193 participants in the Atherosclerosis Risk in Communities (ARIC) (mean age = 78 years, 62% African Americans, 64% female). Atrial fibrillation was identified from aECG, study visit ECGs, and discharge codes from cohort hospitalizations. We used covariate-adjusted logistic regression to estimate prevalence odds ratios (ORs) for AF in African Americans versus Whites, with adjustment for sampling and nonresponse.

RESULTS

African Americans were more likely than Whites to have hypertension and diabetes but less likely to have coronary heart disease. The prevalence of AF detected by aECG or ARIC study ECG (adjusted for age and coronary heart disease) was lower in African Americans than Whites (2.7% vs 5.0%). White men had a higher (although not significant) AF prevalence of 7.8% compared to the other race and gender groups at 2.3%-2.8%. The adjusted OR for AF was 0.49 (0.24-0.99) comparing African Americans to Whites. Findings were similar when AF was defined to include prior AF hospitalizations (OR = 0.42, 0.25-0.72). There were no significant differences by race for asymptomatic or paroxysmal AF.

CONCLUSIONS

Atrial fibrillation was less prevalent in African American than white older adults, regardless of detection method. Although overall detection of new AF cases with aECG was low, future studies should consider longer-term monitoring to characterize AF by race.

Role of Geriatric Syndromes in the Management of Atrial Fibrillation in Older Adults: A Narrative Review

OBJECTIVES

Atrial fibrillation (AF) is common in older adults and associated with increased risk of cardiovascular events including thromboembolism. However, less is known about its association with noncardiovascular events, especially geriatric syndromes and conditions such as dementia, depression, impaired physical function, polypharmacy, falls, and poor quality of life. This review aims to help healthcare professionals integrate the special needs of older adults into their management of AF.

DESIGN

Nonsystematic review. A literature search on published articles on AF and geriatric syndromes and conditions was performed using the electronic databases MEDLINE, EMBASE and SCOPUS, and DARE until December 2017. Non-English articles were excluded.

SETTINGS AND PARTICIPANTS

Older adults with and without AF from different settings.

MEASURES

Various cognitive, mood, and functional measurements were used in these studies. In studies regarding polypharmacy, the Beers or PRISCUS criteria were used to identify inappropriate medications. In quality of life measurements studies, instruments like Medical Outcomes Study Short Form 36 and Atrial Fibrillation Quality of Life questionnaire were used.

RESULTS

This literature review finds that AF has a substantial association with geriatric syndromes and conditions and that AF is a risk factor for the development of geriatric syndromes and conditions. Evidence is limited regarding the potential benefit of long-term treatment of AF in lowering the risk of developing geriatric syndromes and conditions.

CONCLUSIONS/IMPLICATIONS

Considering the impact of AF on cardiovascular outcomes and geriatric syndromes and conditions in older adults, healthcare professionals need to consider these complex dynamics while managing AF in older adults. An individual approach to AF management is needed in older adults with multiple comorbidity and polypharmacy that may help lower the risk of disease-disease, disease-drug, and drug-drug interactions. Special consideration needs to be given to patients' cognitive and functional impairment and ability to adhere to therapy.

Atrial Fibrillation Symptom Perception

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with a significantly increased risk of ischemic stroke, heart failure, and death. AF is a heterogenous disease both in terms of the pathophysiologic mechanisms that lead to the disease, and in terms of symptom presentation. Although most patients with AF perceive symptoms, their symptom experience is highly variable. The purpose of this paper is to review the: 1) epidemiology and pathophysiology of AF, 2) symptoms associated with AF, and 3) implications for clinical practice based on disparate symptom perception.

Characteristics and outcomes of atrial fibrillation patients with or without specific symptoms: results from the PREFER in AF registry

Aims

Atrial fibrillation (AF) is a common condition that is a major cause of stroke. A significant proportion of patients with AF are not classically symptomatic at diagnosis or soon after diagnosis. There is little information comparing their characteristics, treatment, and outcomes of patients with symptoms, which predominate in clinical trials to those without.

Methods and results

We analysed data from the Prevention of Thromboembolic Events-European Registry in Atrial Fibrillation. This was a prospective, real-world registry with a 12-month follow-up that included AF patients aged 18 years and over. Patients were divided into those with and without AF symptoms using the European Heart Rhythm Association (EHRA) score (Category I vs. Categories II-IV). Of the 6196 patients (mean age 72 years) with EHRA scores available, 501 (8.1%) were asymptomatic. A lower proportion of asymptomatic patients was female (22.8 vs. 41.2%), with less noted to have heart failure and coronary artery disease (P < 0.01 for all). There were no differences in terms of the prevalence of diabetes, obesity, or prior stroke. Asymptomatic patients had a lower CHA2DS2-VASc score (2.9 ± 1.7 vs. 3.4 ± 1.8; P < 0.01) and HAS-BLED score (1.8 ± 1.1 vs. 2.1 ± 1.2; P < 0.01). During the 1-year follow-up, adverse events occurred at similar frequencies in asymptomatic and symptomatic patients (1.6 vs. 0.8% for ischaemic stroke; P = 0.061; 1.4 vs. 1.3% for transient ischaemic attack; P = 0.840). Patients with higher CHA2DS2-VASc and HAS-BLED scores experienced more events, independent of symptoms. Antithrombotic therapy was comparable for both groups at baseline and at follow-up.

Conclusions

The similar clinical characteristics and frequency of adverse events between asymptomatic and symptomatic AF patients revives the question of whether screening programmes to detect people with asymptomatic AF are worthwhile, particularly in those aged 65 and over potentially likely to have clinical and economic benefits from anticoagulants. This evidence may be informative if clinicians may not be comfortable participating in future clinical trials, leaving asymptomatic patients with AF and high stroke risk without anticoagulation.

Left ventricular torsional parameters before and after atrial fibrillation ablation: a velocity vector imaging study

BACKGROUND AND AIM

Effects of atrial fibrillation (AF) and its ablative treatment on LV torsion have not yet been fully investigated. This study aimed to examine whether AF patterns of LV contraction and its ablative correction can exert a significant impact on LV torsion by velocity vector imaging (VVI).

METHODS

This case-control study conducted in Rajaie Cardiovascular, Medical and Research Center between October 2012 and June 2013. Study participants were 30 consecutive patients with symptomatic paroxysmal AF who met the inclusion criteria. The control group included 24 healthy participants with no history of cardiovascular disease. All individuals were in sinus rhythm at the time of echocardiography before and after the ablation procedure. Two-dimensional (2D) and Doppler echocardiography on a commercially available ultrasound system was performed for all the patients. Scanning was done by a wide-band ultrasound transducer with the frequency range between 2.5-3.5 MHz. The two short-axis views at basal and apical levels were subsequently processed off-line by VVI XStrain software. In order for data analysis, SPSS 16 utilized using paired and independent t-test. p-value ≤0.05 was considered significant.

RESULTS

LV torsion (°/cm) mean ± SD was significantly lower in paroxysmal AF patients before ablation (0.8±0.3) than the control group (1.5±0.4) (p<0.001) and increased significantly after ablation (1.1±0.5) compared with before ablation (p=0.004), but still significantly lower than the control group (p=0.003). LV Twist, twist rate and untwist rate mean ± SD were significantly lower in paroxysmal AF patients before ablation than the control group and increased significantly after ablation compared with before ablation, but still significantly lower than the control group.

CONCLUSION

Subclinical LV dysfunction may be detected in paroxysmal AF rhythm by measuring torsional parameters through VVI which improves after AF ablation.

Detection of atrial fibrillation using an earlobe photoplethysmographic sensor

Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world, associated with increased risk of thromboembolic events and an increased mortality rate. In addition, a significant portion of AF patients are asymptomatic. Current AF diagnostic methods, often including a body surface electrocardiogram or implantable loop recorder, are both expensive and invasive and offer limited access within the general community.

OBJECTIVE

We tested the feasibility of the detection of AF using a photoplethysmographic signal acquired from an inexpensive, non-invasive earlobe photoplethysmographic sensor. This technology can be implemented into wearable devices and would enable continuous cardiac monitoring capabilities, greatly improving the rate of asymptomatic AF detection.

APPROACH

We conducted a clinical study of patients going through electrical cardioversion for AF treatment. Photoplethysmographic recordings were taken from these AF patients before and after their cardioversion procedure, along with recordings from a healthy control group. Using these recordings, cardiac beats were identified and the inter-systolic interval was calculated. The inter-systolic interval was used to calculate four parameters to quantify the heart rate variability indicative of AF. Receiver operating characteristic curves were used to calculate discriminant thresholds between the AF and non-AF cohorts.

MAIN RESULTS

The parameter with the greatest discriminant capability resulted in a sensitivity and specificity of 90.9%. These results are comparable to expensive ECG-based and invasive implantable loop recorder AF detection methods.

SIGNIFICANCE

These results demonstrate that using a non-invasive earlobe photoplethysmographic signal is a viable and inexpensive alternative to ECG-based AF detection methods, and an alternative that could be invaluable in detecting subclinical AF.

Should We Perform Catheter Ablation for Asymptomatic Atrial Fibrillation?

Since the original description of atrial fibrillation ablation, numerous studies have demonstrated the superiority of catheter ablation over pharmacological therapy for maintenance of sinus rhythm in patients with both paroxysmal and persistent atrial fibrillation. However, to date, no randomized studies have been powered to demonstrate a mortality or stroke reduction benefit of rhythm control with catheter ablation over a rate control strategy. The results of such ongoing studies are not expected until 2018 or 2019. Thus, the only indication for atrial fibrillation ablation in recent guidelines has been the presence of symptoms. However, up to 40% of an atrial fibrillation population may be asymptomatic. In 2017, in the absence of randomized studies, are there nevertheless data that support atrial fibrillation ablation in asymptomatic patients?

First Diagnosis of Atrial Fibrillation at the Time of Stroke

BACKGROUND

Atrial fibrillation (AF) is a major cause of ischemic stroke. Individuals with undiagnosed AF lack the stroke protection afforded by oral anticoagulants. We obtained a contemporary estimate of the percentage of AF patients newly diagnosed at the time of stroke.

METHODS

We identified patients admitted to the Massachusetts General Hospital (MGH) from January 1, 2010 to December 31, 2013 with acute ischemic stroke and either previously or newly diagnosed AF using hospital stroke registry data and stroke and AF ICD-9 code searches of hospital databases. Reviewers categorized AF as previously known or newly diagnosed, and collected comorbidity and outcome data. To confirm AF as newly diagnosed, we searched patients' pre-event electronic medical records (EMRs) for AF terms.

RESULTS

AF was considered newly diagnosed in 156/856 patients (18%; 95% CI 16-21). In 136/156 cases, AF was diagnosed using 12-lead EKG, telemetry, or rhythm strips. New AF strokes had a median NIH stroke scale of 12; 60% had mRankin ≥3 at discharge, including 15% deaths. Pre-stroke CHA2DS2-VASc score was ≥2 in 89%. About half (76/156) had prior records in the MGH EMR. Evidence of pre-stroke AF, often peri-procedural, was found in 8/76, but the AF diagnosis was not carried forward.

CONCLUSIONS

In this contemporary cohort, nearly one in 5 AF-related strokes occurred without a pre-stroke AF diagnosis. AF was readily diagnosed using standard rhythm monitoring. The vast majority of patients with newly diagnosed AF were at high enough pre-stroke risk to merit anticoagulation. In conclusion, our findings support screening for AF before stroke. Patients with past transient AF may merit more intensive screening.

Atrial fibrillation burden and atrial fibrillation type: Clinical significance and impact on the risk of stroke and decision making for long-term anticoagulation

Atrial fibrillation (AF) is a common arrhythmia increasing the risk of morbidity and adverse outcomes (stroke, heart failure, death). AF is found in 1-2% of the general population, with increasing prevalence with aging. Its exact epidemiological profile is incomplete and underestimated, because 10-40% of AF patients (particularly the elderly) can be asymptomatic ("clinically silent or subclinical AF"), with occasional electrocardiographic diagnosis. The research interest on silent AF has increased by the evidence that its outcome is no less severe, in terms of risks of stroke and death, than that for symptomatic patients. Data collected from more than 18,000 patients indicate that cardiac implantable electrical devices (CIEDs) are validated tools for detecting silent AF and measuring the time spent in AF, defined as "AF burden." A maximum daily AF burden of ≥5-6min, but particularly ≥1h, is associated with a significant increase in the risk of stroke, and may be clinically relevant to improve current risk stratification based on risk scores and for "personalizing" prescription of oral anticoagulants. An in-depth study of the temporal relationship between AF and ischemic stroke showed that data from CIEDs reveal a complex scenario, by which AF is certainly a risk factor for cardioembolic stroke, with a cause-effect relationship related to atrial thrombi, but can also be a simple "marker of risk," with a noncausal association with stroke. In such cases, stroke is possibly related to atheroemboli from the aorta, the carotid arteries, or other sources.

Accurate, Automated Detection of Atrial Fibrillation in Ambulatory Recordings

A highly accurate, automated algorithm would facilitate cost-effective screening for asymptomatic atrial fibrillation. This study analyzed a new algorithm and compared it to existing techniques. The incremental benefit of each step in refinement of the algorithm was measured, and the algorithm was compared to other methods using the Physionet atrial fibrillation and normal sinus rhythm databases. When analyzing segments of 21 RR intervals or less, the algorithm had a significantly higher area under the receiver operating characteristic curve (AUC) than the other algorithms tested. At analysis segment sizes of up to 101 RR intervals, the algorithm continued to have a higher AUC than any of the other methods tested, although the difference from the second best other algorithm was no longer significant, with an AUC of 0.9992 with a 95% confidence interval (CI) of 0.9986-0.9998, vs. 0.9986 (CI 0.9978-0.9994). With identical per-subject sensitivity, per-subject specificity of the current algorithm was superior to the other tested algorithms even at 101 RR intervals, with no false positives (CI 0.0-0.8%) vs. 5.3% false positives for the second best algorithm (CI 3.4-7.9%). The described algorithm shows great promise for automated screening for atrial fibrillation by reducing false positives requiring manual review, while maintaining high sensitivity.

Are implantable cardiac monitors the 'gold standard' for atrial fibrillation detection? A prospective randomized trial comparing atrial fibrillation monitoring using implantable cardiac monitors and DDDRP permanent pacemakers in post atrial fibrillation ablation patients

AIMS

Implantable devices are widely accepted, but not proven, to be the most reliable monitoring method to assess atrial fibrillation (AF) therapies. We compared REVEAL(®)XT implantable cardiac monitors (ICMs) and permanent pacemakers (PPMs).

METHODS AND RESULTS

Fifty patients with paroxysmal AF were randomized to ICM or PPM implant 6 weeks prior to pulmonary vein isolation. Permanent pacemakers were programmed to monitoring only (ODO). Device downloads were performed at 0, 3, 6, 9, and 12 months. All patients underwent 7-day external loop recorder. Device ECGs and EGMs were compared for AF burden. A total of 20 744 and 11 238 arrhythmia episodes were identified in the ICM and PPM groups, respectively. Correct identification of AF was significantly better in the PPM group (97 vs. 55% P < 0.001). In the ICM group, 26% of ECGs were un-interpretable. Sensitivity and specificity for each episode of AF was significantly better in the PPM group (100 vs. 79% and 98 vs. 66%, respectively, P < 0.001). The positive predictive value for the detection of any AF was significantly better in the PPM than the ICM (100 vs. 58%, P = 0.03). The negative predictive value for the absence of all AF was not significantly different between the PPM and ICM (100% vs. 92%, P = 0.76).

CONCLUSION

Permanent pacemakers Holters are the most accurate method of evaluating arrhythmia burden and the therapeutic efficacy of novel AF therapies. ICM has a high degree of artefact, which reduces its specifity and sensitivity. Despite the deficiencies of ICM monitoring the negative predictive value of the ICM is satisfactory if zero AF burden is the aim of therapy.

Prevalence of atrial fibrillation in patients with high CHADS2- and CHA2DS2VASc-scores: anticoagulate or monitor high-risk patients?

Background

In patients with known atrial fibrillation (AF) different scores are utilized to estimate the risk of thromboembolic events and guide oral anticoagulation. Diagnosis of AF strongly depends on the duration of electrocardiogram monitoring. The aim of this study was to use established scores to predict the prevalence of AF.

Methods

The CHADS₂- (Congestive Heart failure, hypertension, Age >75 years, Diabetes, Stroke [doubled]) and CHA₂DS₂VASc-score (Congestive Heart failure, hypertension, Age ≥75 years [doubled], Diabetes, Stroke [doubled], Vascular disease, Age 65–74 years, Sex category [female sex]) was calculated in 150,408 consecutive patients, referred to the University Hospital of Rostock between 2007 and 2012. All factors constituting these scores and a history of AF were prospectively documented with the ICD-10 admission codes.

Results

Mean age of our study population was 67.6 ± 13.6 years with a mean CHADS₂-score of 1.65 ± 0.92 and CHA₂DS₂VASc-score of 3.04 ± 1.42. AF was prevalent in 15.9% of the participants. The prevalence of AF increased significantly with every CHADS₂- and CHA₂DS₂VASc-score point up to 54.2% in CHADS₂-score of 6 and 71.4% in CHA₂DS₂VASc-score of 9 (P < 0.001).

Conclusion

The prevalence of AF increases with increasing CHADS₂- and CHA₂DS₂VASc-score. In intermediate scores intensified monitoring may be recommended. In high scores, thromboembolic complications occurred irrespective of the presence of AF and anticoagulant therapy may be initiated irrespective of documented AF.

Accuracy of patient perception of their prevailing rhythm: a comparative analysis of monitor data and questionnaire responses in patients with atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) guidelines recommend that symptom relief be a primary goal in management. However, patient perception of their prevailing rhythm is often inaccurate, complicating symptom-targeted treatment.

OBJECTIVE

The purpose of this study was to evaluate the accuracy of patient perception of their prevailing rhythm and identify factors that predict inaccuracies.

METHODS

Demographic and health status data were captured by questionnaires for 458 outpatients with documented AF. AF burden (%) was captured by 1-week continuous heart monitors. Patients estimated the length and frequency of their AF episodes by completing the AF Symptom Severity questionnaire. Patient reports were compared to AF burden, and outliers were identified and broken into 2 groups: patients with AF burden <10% who indicated near-continuous AF (overestimators) and patients with AF burden >90% who estimated little to no AF (underestimators). Multinomial logistic regression was used to identify predictors of inaccuracies (over- or underestimators).

RESULTS

By continuous monitor, 15% of patients were found to be over- or underestimators. Persistent AF, female sex, older age, anxiety, and depression were predictive of inaccurate patient perception. Persistent AF, female sex, and older age were predictive of underestimating, while mood disorders (anxiety and depression) were predictive of overestimating. The prevalence of underestimators was nearly twice that of overestimators.

CONCLUSION

Sex, age, and mood disorders are among factors that lead to inaccurate patient perception of their prevailing rhythm in patients with AF. Such modulating factors should be considered when evaluating treatment strategies. Consideration should be given to more liberal use of heart monitors in these patient populations to better target therapy.

Epidemiology of atrial fibrillation: European perspective

In the last 20 years, atrial fibrillation (AF) has become one of the most important public health problems and a significant cause of increasing health care costs in western countries. The prevalence of AF is increasing due to our greater ability to treat chronic cardiac and noncardiac diseases, and the improved ability to suspect and diagnose AF. At the present time, the prevalence of AF (2%) is double that reported in the last decade. The prevalence of AF varies with age and sex. AF is present in 0.12%–0.16% of those younger than 49 years, in 3.7%–4.2% of those aged 60–70 years, and in 10%–17% of those aged 80 years or older. In addition, it occurs more frequently in males, with a male to female ratio of 1.2:1. The incidence of AF ranges between 0.21 and 0.41 per 1,000 person/years. Permanent AF occurs in approximately 50% of patients, and paroxysmal and persistent AF in 25% each. AF is frequently associated with cardiac disease and comorbidities. The most common concomitant diseases are coronary artery disease, valvular heart disease, and cardiomyopathy. The most common comorbidities are hypertension, diabetes, heart failure, chronic obstructive pulmonary disease, renal failure, stroke, and cognitive disturbance. Paroxysmal AF occurs in younger patients and with a reduced burden of both cardiac disease and comorbidities. Generally, the history of AF is long, burdened by frequent recurrences, and associated with symptoms (in two thirds of patients). Patients with AF have a five-fold and two-fold higher risk of stroke and death, respectively. We estimate that the number of patients with AF in 2030 in Europe will be 14–17 million and the number of new cases of AF per year at 120,000–215,000. Given that AF is associated with significant morbidity and mortality, this increasing number of individuals with AF will have major public health implications.

Current practice for diagnosis and management of silent atrial fibrillation: results of the European Heart Rhythm Association survey

Although it is well known that silent atrial fibrillation (AF) is associated with morbidity and mortality rates similar to those of symptomatic AF, no specific strategy for screening and management of this form of AF has been advocated. The purpose of this survey was to identify current practices for the diagnosis and management of silent AF. This survey is based on an electronic questionnaire sent to the European Heart Rhythm Association Research Network partners. Responses were received from 33 centres in 16 countries. The preferred screening methods for silent AF in patients with rhythm control by pharmacological therapy was 12-lead electrocardiogram (ECG) at outpatient visits (31.3%) and periodical 24 h Holter ECG recordings (34.4%), while after pulmonary vein isolation the corresponding figures were 6.3 and 65.6%, respectively. No consensus has been reached concerning the therapeutic approach for such patients. Most responders preferred rate control over rhythm control in patients with silent AF, although some favoured pulmonary vein isolation in young patients. However, oral anticoagulant therapy in patients at high thromboembolic risk was considered mandatory by most, provided that at least one episode of silent AF was documented, without recommending further investigations. The results of this survey have confirmed that there is currently no consensus regarding the screening and management of patients with silent AF and that clinical practice is not always consistent with the few existing evidence-based recommendations.

Predictive value of atrial high-rate episodes for arterial stiffness and endothelial dysfunction in dual-chamber pacemaker patients

BACKGROUND

Various pacing studies have demonstrated an association between right ventricular pacing (RVp) and atrial fibrillation (AF), even after preserving atrioventricular (AV) synchrony. We aimed to assess the interaction between arterial stiffness, endothelial function and atrial high-rate episodes (AHRE) in patients with dual-chamber pacemakers.

METHODS

We studied 101 patients with dual-chamber pacemakers incorporated with sophisticated AF detection and therapy algorithms. Macrovascular endothelial dysfunction (ED) was measured by the relative change in aortic augmentation index (AIx), using carotid artery applanation tonometry in response to inhaled salbutamol and sublingual glyceryl trinitrate. Microvascular ED was measured by cutaneous laser Doppler flowmetry (LDF) in response to acetylcholine (Ach, endothelium dependent) and sodium nitroprusside (SNP, endothelium independent). Arterial stiffness was measured using carotid-femoral pulse wave velocity (PWVcf). 'Reservoir pressure' (Pr, MATLAB) describes the aortic 'cushioning' properties.

RESULTS

Mean age of the cohort was 72.1 ± 10.8 years; men (n = 69) 68.3%. Of 101 dual-chamber pacemaker patients, 23.8% (n = 24) had AHRE detected on the baseline pacemaker interrogation. PP, PWVcf and Pr were significantly higher in patients with AHRE compared with those without AHRE. The change in AIx with salbutamol (∆% AIx Sal) and acetylcholine-induced changes in LDF (Δ%LDF Ach) were lower in patients with AHRE compared with those without AHRE. In patients with AHRE, significant correlations were observed between%Vp and Δ%LDF Ach (P = 0.03) as well as between PP and Δ%LDF Ach (P = 0.05). On multivariate analysis, PP, Pr, PWVcf and ∆% AIx Sal remained as independent predictors of AHRE.

CONCLUSION

In patients with dual-chamber pacemakers, both higher arterial stiffness and greater endothelial dysfunction independently predicted AHRE, irrespective of the degree (or mode) of pacing. Arterial stiffness and endothelial dysfunction may potentially contribute to the perpetuation of atrial arrhythmias beyond the adverse effects of ventricular pacing alone.

Immediate and medium-term outcomes of cryoballoon-based pulmonary vein isolation in patients with paroxysmal and persistent atrial fibrillation: single-centre experience

BACKGROUND

Pulmonary vein (PV) isolation with cryoballoon is a recently developed technique for the treatment of atrial fibrillation (AF) with acceptable mid-term results in terms of the success and safety. The purpose of our study is to identify the periprocedural complications, mid-term success rates and predictors of recurrence after AF ablation with cryoballoon.

METHOD

A total of 236 patients (54% male, mean age 54.6 ± 10.45 years and 79.6% paroxysmal AF) with symptomatic AF underwent PV isolation with cryoballoon due to failure with ≥1 antiarrhythmic drug previously. Procedural success, complications and follow-up data were defined according to recent guidelines.

RESULTS

Acute procedural success rate was 99.5%. Mean procedural and fluoroscopy times were 72.5 ± 5.3 and 14 ± 3.5 min. At a median of 18 (6-27) months follow-up, 80.8% of paroxysmal AF patients and 50.0% of persistent AF patients were free from AF recurrence. In multivariate regression analysis, body mass index (BMI) (hazard ratio (HR), 1.35; 95% confidence interval (CI), 1.18-2.93, p = 0.001), smoking (HR, 2.12; 95% CI, 1.36-6.67, p < 0.001), non-paroxysmal AF (HR, 1.26; 95% CI, 1.12-2.56, p = 0.024), duration of AF (HR, 1.42; 95% CI, 1.18-2.61, p = 0.015), left atrium (LA) diameter (HR, 2.42; 95% CI, 1.64-5.88, p < 0.001) and early AF recurrence (HR, 4.88; 95% CI, 2.86-35.6, p < 0.001) were independent predictors of AF recurrence following cryoablation.

CONCLUSION

Our results showed that AF ablation with cryoballoon is effective and safe. Non-paroxysmal AF, duration of AF, smoking, BMI, LA diameter and early recurrence were found to be the most powerful predictors and could be helpful to select patients for appropriate therapeutic strategy.

The burden of atrial fibrillation in the Netherlands

BACKGROUND

Atrial fibrillation (AF) is the most common sustained atrial arrhythmia and it is independently associated with an increased morbidity and mortality. As a result of the high prevalence of AF, the economic and clinical impact of the disease is substantial. This study describes the economic and clinical impact of AF in the Netherlands.

METHODS

Epidemiological data on AF in the Netherlands were projected on population estimates of the Netherlands in 2009 and combined with data on the cost of AF and its interventions.

RESULTS

Overall prevalence of AF in the Netherlands is 5.5% in the population over 55 years, corresponding to about 250,000 AF patients. The prevalence increases with age, and the mean age of AF patients is 69.3 years. Incidence of AF in the Netherlands varies with age, from 1188 new cases in the age group of 55 to 59 up to 7074 new cases in the age group 75 to 79. Total new cases amounts to 45,085 patients per year in the Netherlands. Total costs of AF in the Netherlands are <euro> 583 million, of which the majority (70%) were accounted for by hospitalisations and in-hospital procedures. Pharmacotherapeutic management of AF totalled <euro> 17 million in the Netherlands in 2009.

DISCUSSION

AF is a serious disease with a high clinical and economic burden, especially due to hospitalisations as a result of cardiovascular events. The number of patients with AF in the Netherlands is considerable and will increase with the ageing population in the future.

Long-term success and follow-up after atrial fibrillation ablation

Atrial fibrillation (AF) is the most prevalent sustained arrhythmia in clinical practice. It is associated with significant morbidity and mortality and has been identified as an independent risk factor for ischemic stroke and thromboembolic events. Catheter ablation has become an established rhythm control therapy in patients with highly symptomatic drug-refractory AF. The definition of ablation success remains controversial since current symptom-based or intermittent electrocardiogram monitoring strategies fail to sufficiently disclose rhythm outcome. This failure is mainly related to the high incidence of asymptomatic AF recurrences, the unpredictable nature of arrhythmia relapses, and the poor correlation of symptoms and AF episodes. There is a clear correlation between the intensity of the monitoring strategy and the sensitivity for it to detect arrhythmia recurrences. Furthermore, several clinical studies assessing the long-term efficacy of catheter ablation procedures have reported late AF recurrences in patients who were initially considered responders to catheter ablation. In certain subsets of patients, precise long-term monitoring may help to guide therapy, e.g. patients in whom withdrawal of antithrombotic therapy may be considered if they are free of arrhythmia recurrences. Recently, sub-cutaneous implantable cardiac monitors (ICM) have been introduced for prolonged and continuous rhythm monitoring. The performance of a leadless ICM equipped with a dedicated AF detection algorithm has recently been assessed in a clinical trial demonstrating a high sensitivity and overall accuracy for identifying patients with AF. The clinical impact of ICM-based follow-up strategies, however, has to be evaluated in prospective clinical trials.