Disturbed atrial metabolism, shear stress, and cardiac load contribute to atrial fibrillation after ablation: AXAFA biomolecule study.

AIMS: Different disease processes can combine to cause atrial fibrillation (AF). Their contribution to recurrent AF after ablation in patients is not known. Cardiovascular processes associated with recurrent AF after AF ablation were determined by quantifying biomolecules related to inflammation, metabolism, proliferation, fibrosis, shear stress, atrial pressure, and others in the AXAFA biomolecule study. METHODS AND RESULTS: Twelve circulating cardiovascular biomolecules (ANGPT2, BMP10, CA125, hsCRP, ESM1, FABP3, FGF23, GDF15, IGFBP7, IL6, NT-proBNP, and hsTnT) were quantified in plasma samples obtained prior to a first AF ablation using high-throughput, high-precision assays. Cox regression was used to identify biomolecules associated with recurrent AF during the first 3 months after AF ablation. In 433 patients (64 years [58, 70]; 33% women), baseline concentrations of ANGPT2, BMP10, hsCRP, FGF23, FABP3, GDF15, and NT-proBNP were elevated in patients with recurrent AF (120/433; 28%). After adjustment for 11 clinical features and randomized treatment, elevated NT-proBNP [hazard ratio (HR) 1.58, 95% confidence interval (1.29, 1.94)], ANGPT2 [HR 1.37, (1.12, 1.67)], and BMP10 [HR 1.24 (1.02, 1.51)] remained associated with recurrent AF. Concentrations of ANGPT2, BMP10, and NT-proBNP decreased in patients who remained arrhythmia free, but not in patients with recurrent AF, highlighting their connection to AF. The other eight biomarkers showed unchanged concentrations. CONCLUSION: Elevated concentrations of ANGPT2, BMP10, and NT-proBNP are associated with recurrent AF after a first AF ablation, suggesting that processes linked to disturbed cardiomyocyte metabolism, altered atrial shear stress, and increased load contribute to AF after AF ablation in patients.

SARS-CoV-2 infection is associated with anti-desmoglein 2 autoantibody detection.

Post-acute cardiac sequelae, following SARS-CoV-2 infection, are well recognized as complications of COVID-19. We have previously shown the persistence of autoantibodies against antigens in skin, muscle, and heart in individuals following severe COVID-19; the most common staining on skin tissue displayed an inter-cellular cement pattern consistent with antibodies against desmosomal proteins. Desmosomes play a critical role in maintaining the structural integrity of tissues. For this reason, we analyzed desmosomal protein levels and the presence of anti-desmoglein (DSG) 1, 2, and 3 antibodies in acute and convalescent sera from patients with COVID-19 of differing clinical severity. We find increased levels of DSG2 protein in sera from acute COVID-19 patients. Furthermore, we find that DSG2 autoantibody levels are increased significantly in convalescent sera following severe COVID-19 but not in hospitalized patients recovering from influenza infection or healthy controls. Levels of autoantibody in sera from patients with severe COVID-19 were comparable to levels in patients with non-COVID-19-associated cardiac disease, potentially identifying DSG2 autoantibodies as a novel biomarker for cardiac damage. To determine if there was any association between severe COVID-19 and DSG2, we stained post-mortem cardiac tissue from patients who died from COVID-19 infection. This confirmed DSG2 protein within the intercalated discs and disruption of the intercalated disc between cardiomyocytes in patients who died from COVID-19. Our results reveal the potential for DSG2 protein and autoimmunity to DSG2 to contribute to unexpected pathologies associated with COVID-19 infection.

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference.

Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.

Quantification of fibroblast growth factor 23 and N-terminal pro-B-type natriuretic peptide to identify patients with atrial fibrillation using a high-throughput platform: A validation study.

BACKGROUND: Large-scale screening for atrial fibrillation (AF) requires reliable methods to identify at-risk populations. Using an experimental semi-quantitative biomarker assay, B-type natriuretic peptide (BNP) and fibroblast growth factor 23 (FGF23) were recently identified as the most suitable biomarkers for detecting AF in combination with simple morphometric parameters (age, sex, and body mass index [BMI]). In this study, we validated the AF model using standardised, high-throughput, high-sensitivity biomarker assays. METHODS AND FINDINGS: For this study, 1,625 consecutive patients with either (1) diagnosed AF or (2) sinus rhythm with CHA2DS2-VASc score of 2 or more were recruited from a large teaching hospital in Birmingham, West Midlands, UK, between September 2014 and February 2018. Seven-day ambulatory ECG monitoring excluded silent AF. Patients with tachyarrhythmias apart from AF and incomplete cases were excluded. AF was diagnosed according to current clinical guidelines and confirmed by ECG. We developed a high-throughput, high-sensitivity assay for FGF23, quantified plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and FGF23, and compared results to the previously used multibiomarker research assay. Data were fitted to the previously derived model, adjusting for differences in measurement platforms and known confounders (heart failure and chronic kidney disease). In 1,084 patients (46% with AF; median [Q1, Q3] age 70 [60, 78] years, median [Q1, Q3] BMI 28.8 [25.1, 32.8] kg/m2, 59% males), patients with AF had higher concentrations of NT-proBNP (median [Q1, Q3] per 100 pg/ml: with AF 12.00 [4.19, 30.15], without AF 4.25 [1.17, 15.70]; p < 0.001) and FGF23 (median [Q1, Q3] per 100 pg/ml: with AF 1.93 [1.30, 4.16], without AF 1.55 [1.04, 2.62]; p < 0.001). Univariate associations remained after adjusting for heart failure and estimated glomerular filtration rate, known confounders of NT-proBNP and FGF23. The fitted model yielded a C-statistic of 0.688 (95% CI 0.656, 0.719), almost identical to that of the derived model (C-statistic 0.691; 95% CI 0.638, 0.744). The key limitation is that this validation was performed in a cohort that is very similar demographically to the one used in model development, calling for further external validation. CONCLUSIONS: Age, sex, and BMI combined with elevated NT-proBNP and elevated FGF23, quantified on a high-throughput platform, reliably identify patients with AF. TRIAL REGISTRATION: Registry IRAS ID 97753 Health Research Authority (HRA), United Kingdom.

Dynamic risk assessment to improve quality of care in patients with atrial fibrillation: the 7th AFNET/EHRA Consensus Conference.

AIMS: The risk of developing atrial fibrillation (AF) and its complications continues to increase, despite good progress in preventing AF-related strokes. METHODS AND RESULTS: This article summarizes the outcomes of the 7th Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA) held in Lisbon in March 2019. Sixty-five international AF specialists met to present new data and find consensus on pressing issues in AF prevention, management and future research to improve care for patients with AF and prevent AF-related complications. This article is the main outcome of an interactive, iterative discussion between breakout specialist groups and the meeting plenary. AF patients have dynamic risk profiles requiring repeated assessment and risk-based therapy stratification to optimize quality of care. Interrogation of deeply phenotyped datasets with outcomes will lead to a better understanding of the cardiac and systemic effects of AF, interacting with comorbidities and predisposing factors, enabling stratified therapy. New proposals include an algorithm for the acute management of patients with AF and heart failure, a call for a refined, data-driven assessment of stroke risk, suggestions for anticoagulation use in special populations, and a call for rhythm control therapy selection based on risk of AF recurrence. CONCLUSION: The remaining morbidity and mortality in patients with AF needs better characterization. Likely drivers of the remaining AF-related problems are AF burden, potentially treatable by rhythm control therapy, and concomitant conditions, potentially treatable by treating these conditions. Identifying the drivers of AF-related complications holds promise for stratified therapy.

Mobile Apps to Improve Medication Adherence in Cardiovascular Disease: Systematic Review and Meta-analysis.

BACKGROUND: Adherence rates of preventative medication for cardiovascular disease (CVD) have been reported as 57%, and approximately 9% of all CVD events in Europe are attributable to poor medication adherence. Mobile health technologies, particularly mobile apps, have the potential to improve medication adherence and clinical outcomes. OBJECTIVE: The objective of this study is to assess the effects of mobile health care apps on medication adherence and health-related outcomes in patients with CVD. This study also evaluates apps' functionality and usability and the involvement of health care professionals in their use. METHODS: Electronic databases (MEDLINE [Ovid], PubMed Central, Cochrane Library, CINAHL Plus, PsycINFO [Ovid], Embase [Ovid], and Google Scholar) were searched for randomized controlled trials (RCTs) to investigate app-based interventions aimed at improving medication adherence in patients with CVD. RCTs published in English from inception to January 2020 were reviewed. The Cochrane risk of bias tool was used to assess the included studies. Meta-analysis was performed for clinical outcomes and medication adherence, with meta-regression analysis used to evaluate the impact of app intervention duration on medication adherence. RESULTS: This study included 16 RCTs published within the last 6 years. In total, 12 RCTs reported medication adherence as the primary outcome, which is the most commonly self-reported adherence. The duration of the interventions ranged from 1 to 12 months, and sample sizes ranged from 24 to 412. Medication adherence rates showed statistically significant improvements in 9 RCTs when compared with the control, and meta-analysis of the 6 RCTs reporting continuous data showed a significant overall effect in favor of the app intervention (mean difference 0.90, 95% CI 0.03-1.78) with a high statistical heterogeneity (I2=93.32%). Moreover, 9 RCTs assessed clinical outcomes and reported an improvement in systolic blood pressure, diastolic blood pressure, total cholesterol, and low-density lipoprotein cholesterol levels in the intervention arm. Meta-analysis of these clinical outcomes from 6 RCTs favored app interventions, but none were significant. In the 7 trials evaluating app usability, all were found to be acceptable. There was a great variation in the app characteristics. A total of 10 RCTs involved health care professionals, mainly physicians and nurses, in the app-based interventions. The apps had mixed functionality: 2 used education, 7 delivered reminders, and 7 provided reminders in combination with educational support. CONCLUSIONS: Apps tended to increase medication adherence, but interventions varied widely in design, content, and delivery. Apps have an acceptable degree of usability; yet the app characteristics conferring usability and effectiveness are ill-defined. Future large-scale studies should focus on identifying the essential active components of successful apps. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42019121385; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=121385.

Predicting recurrent atrial fibrillation after catheter ablation: a systematic review of prognostic models.

AIMS: We assessed the performance of modelsf (risk scores) for predicting recurrence of atrial fibrillation (AF) in patients who have undergone catheter ablation. METHODS AND RESULTS: Systematic searches of bibliographic databases were conducted (November 2018). Studies were eligible for inclusion if they reported the development, validation, or impact assessment of a model for predicting AF recurrence after ablation. Model performance (discrimination and calibration) measures were extracted. The Prediction Study Risk of Bias Assessment Tool (PROBAST) was used to assess risk of bias. Meta-analysis was not feasible due to clinical and methodological differences between studies, but c-statistics were presented in forest plots. Thirty-three studies developing or validating 13 models were included; eight studies compared two or more models. Common model variables were left atrial parameters, type of AF, and age. Model discriminatory ability was highly variable and no model had consistently poor or good performance. Most studies did not assess model calibration. The main risk of bias concern was the lack of internal validation which may have resulted in overly optimistic and/or biased model performance estimates. No model impact studies were identified. CONCLUSION: Our systematic review suggests that clinical risk prediction of AF after ablation has potential, but there remains a need for robust evaluation of risk factors and development of risk scores.

Sex differences in catheter ablation of atrial fibrillation: results from AXAFA-AFNET 5.

AIMS: Study sex-differences in efficacy and safety of atrial fibrillation (AF) ablation. METHODS AND RESULTS: We assessed first AF ablation outcomes on continuous anticoagulation in 633 patients [209 (33%) women and 424 (67%) men] in a pre-specified subgroup analysis of the AXAFA-AFNET 5 trial. We compared the primary outcome (death, stroke or transient ischaemic attack, or major bleeding) and secondary outcomes [change in quality of life (QoL) and cognitive function] 3 months after ablation. Women were older (66 vs. 63 years, P < 0.001), more often symptomatic, had lower QoL and a longer history of AF. No sex differences in ablation procedure were found. Women stayed in hospital longer than men (2.1 ± 2.3 vs. 1.6 ± 1.3 days, P = 0.004). The primary outcome occurred in 19 (9.1%) women and 26 (6.1%) men, P = 0.19. Women experienced more bleeding events requiring medical attention (5.7% vs. 2.1%, P = 0.03), while rates of tamponade (1.0% vs. 1.2%) or intracranial haemorrhage (0.5% vs. 0%) did not differ. Improvement in QoL after ablation was similar between the sexes [12-item Short Form Health Survey (SF-12) physical 5.1% and 5.9%, P = 0.26; and SF-12 mental 3.7% and 1.6%, P = 0.17]. At baseline, mild cognitive impairment according to the Montreal Cognitive Assessment (MoCA) was present in 65 (32%) women and 123 (30%) men and declined to 23% for both sexes at end of follow-up. CONCLUSION: Women and men experience similar improvement in QoL and MoCA score after AF ablation on continuous anticoagulation. Longer hospital stay, a trend towards more nuisance bleeds, and a lower overall QoL in women were the main differences observed.

Predictors of recurrence of atrial fibrillation within the first 3 months after ablation.

AIMS: Freedom from atrial fibrillation (AF) at 1 year can be achieved in 50-70% of patients undergoing catheter ablation. Recurrent AF early after ablation most commonly terminates spontaneously without further interventional treatment but is associated with later recurrent AF. The aim of this investigation is to identify clinical and procedural factors associated with recurrence of AF early after ablation. METHODS AND RESULTS: We retrospectively analysed data for recurrence of AF within the first 3 months after catheter ablation from the randomized controlled AXAFA-AFNET 5 trial, which demonstrated that continuous anticoagulation with apixaban is as safe and as effective compared to vitamin K antagonists in 678 patients undergoing first AF ablation. The primary outcome of first recurrent AF within 90 days was observed in 163 (28%) patients, in which 78 (48%) patients experienced an event within the first 14 days post-ablation. After multivariable adjustment, a history of stroke/transient ischaemic attack [hazard ratio (HR) 1.54, 95% confidence interval (CI) 0.93-2.6; P = 0.11], coronary artery disease (HR 1.85, 95% CI 1.20-2.86; P = 0.005), cardioversion during ablation (HR 1.78, 95% CI 1.26-2.49; P = 0.001), and an age:sex interaction for older women (HR 1.01, 95% CI 1.00-1.01; P = 0.04) were associated with recurrent AF. The P-wave duration at follow-up was significantly longer for patients with AF recurrence (129 ± 31 ms vs. 122 ± 22 ms in patients without AF, P = 0.03). CONCLUSION: Half of all early AF recurrences within the first 3 months post-ablation occurred within the first 14 days post-ablation. Vascular disease and cardioversion during the procedure are strong predictors of recurrent AF. P-wave duration at follow-up was longer in patients with recurrent AF. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT02227550.

Data-driven discovery and validation of circulating blood-based biomarkers associated with prevalent atrial fibrillation.

AIMS: Undetected atrial fibrillation (AF) is a major health concern. Blood biomarkers associated with AF could simplify patient selection for screening and further inform ongoing research towards stratified prevention and treatment of AF. METHODS AND RESULTS: Forty common cardiovascular biomarkers were quantified in 638 consecutive patients referred to hospital [mean ± standard deviation age 70 ± 12 years, 398 (62%) male, 294 (46%) with AF] with known AF or ≥2 CHA2DS2-VASc risk factors. Paroxysmal or silent AF was ruled out by 7-day ECG monitoring. Logistic regression with forward selection and machine learning algorithms were used to determine clinical risk factors, imaging parameters, and biomarkers associated with AF. Atrial fibrillation was significantly associated with age [bootstrapped odds ratio (OR) per year = 1.060, 95% confidence interval (1.04-1.10); P = 0.001], male sex [OR = 2.022 (1.28-3.56); P = 0.008], body mass index [BMI, OR per unit = 1.060 (1.02-1.12); P = 0.003], elevated brain natriuretic peptide [BNP, OR per fold change = 1.293 (1.11-1.63); P = 0.002], elevated fibroblast growth factor-23 [FGF-23, OR = 1.667 (1.36-2.34); P = 0.001], and reduced TNF-related apoptosis-induced ligand-receptor 2 [TRAIL-R2, OR = 0.242 (0.14-0.32); P = 0.001], but not other biomarkers. Biomarkers improved the prediction of AF compared with clinical risk factors alone (net reclassification improvement = 0.178; P < 0.001). Both logistic regression and machine learning predicted AF well during validation [area under the receiver-operator curve = 0.684 (0.62-0.75) and 0.697 (0.63-0.76), respectively]. CONCLUSION: Three simple clinical risk factors (age, sex, and BMI) and two biomarkers (elevated BNP and elevated FGF-23) identify patients with AF. Further research is warranted to elucidate FGF-23 dependent mechanisms of AF.

Development and external validation of predictive models for prevalent and recurrent atrial fibrillation: a protocol for the analysis of the CATCH ME combined dataset.

BACKGROUND: Atrial fibrillation (AF) is caused by different mechanisms but current treatment strategies do not target these mechanisms. Stratified therapy based on mechanistic drivers and biomarkers of AF have the potential to improve AF prevention and management outcomes. We will integrate mechanistic insights with known pathophysiological drivers of AF in models predicting recurrent AF and prevalent AF to test hypotheses related to AF mechanisms and response to rhythm control therapy. METHODS: We will harmonise and combine baseline and outcome data from 12 studies collected by six centres from the United Kingdom, Germany, France, Spain, and the Netherlands which assess prevalent AF or recurrent AF. A Delphi process and statistical selection will be used to identify candidate clinical predictors. Prediction models will be developed in patients with AF for AF recurrence and AF-related outcomes, and in patients with or without AF at baseline for prevalent AF. Models will be used to test mechanistic hypotheses and investigate the predictive value of plasma biomarkers. DISCUSSION: This retrospective, harmonised, individual patient data analysis will use information from 12 datasets collected in five European countries. It is envisioned that the outcome of this analysis would provide a greater understanding of the factors associated with recurrent and prevalent AF, potentially allowing development of stratified approaches to prevention and therapy management.

European Society of Cardiology smartphone and tablet applications for patients with atrial fibrillation and their health care providers.

We are in the midst of a digital revolution in health care, although the application of new and useful technology in routine clinical practice is variable. The Characterizing Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly (CATCH ME) Consortium, in collaboration with the European Society of Cardiology (ESC), has funded the creation of two applications (apps) in atrial fibrillation (AF) for use in smartphones and tablets. The patient app aims to enhance patient education, improve communication between patients and health care professionals, and encourage active patient involvement in the management of their condition. The health care professional app is designed as an interactive management tool incorporating the new ESC Practice Guidelines on AF and supported by the European Heart Rhythm Association (EHRA), with the aim of improving best practice approaches for the care of patients with AF. Both stand-alone apps are now freely available for Android and iOS devices though the Google Play, Amazon, and Apple stores. In this article, we outline the rationale for the design and implementation of these apps. Our objective is to demonstrate the value of integrating novel digital technology into clinical practice, with the potential for patient engagement, optimization of pharmacological and interventional therapy in AF, and ultimately to improve patient outcomes.

Integrating new approaches to atrial fibrillation management: the 6th AFNET/EHRA Consensus Conference.

There are major challenges ahead for clinicians treating patients with atrial fibrillation (AF). The population with AF is expected to expand considerably and yet, apart from anticoagulation, therapies used in AF have not been shown to consistently impact on mortality or reduce adverse cardiovascular events. New approaches to AF management, including the use of novel technologies and structured, integrated care, have the potential to enhance clinical phenotyping or result in better treatment selection and stratified therapy. Here, we report the outcomes of the 6th Consensus Conference of the Atrial Fibrillation Network (AFNET) and the European Heart Rhythm Association (EHRA), held at the European Society of Cardiology Heart House in Sophia Antipolis, France, 17-19 January 2017. Sixty-two global specialists in AF and 13 industry partners met to develop innovative solutions based on new approaches to screening and diagnosis, enhancing integration of AF care, developing clinical pathways for treating complex patients, improving stroke prevention strategies, and better patient selection for heart rate and rhythm control. Ultimately, these approaches can lead to better outcomes for patients with AF.

Pilot study to evaluate the use of remote patient monitoring to guide the timing of valve intervention in patients with severe asymptomatic aortic stenosis (APRAISE-AS): study protocol for a randomised controlled trial delivered in two tertiary cardiac centres in the UK.

INTRODUCTION: Aortic stenosis (AS) is common affecting >13% of adults over the age of 75 years. In people who develop symptoms, without valve replacement, prognosis is dismal with mortality as high as 50% at 1 year. In asymptomatic patients, the timing of valve intervention is less well defined and a strategy of watchful waiting is recommended. Many, however, may develop symptoms and attribute this to age related decline, rather than worsening AS. Timely intervention in asymptomatic severe AS is critical, since delayed intervention often results in poor outcomes. Proactive surveillance of symptoms, quality of life and functional capacity should enable timely identification of people who will benefit from aortic valve replacement. There are no data however, to support the clinical and cost effectiveness of such an approach in a healthcare setting in the UK. The aim of this pilot trial is to test the feasibility of a full-scale randomised controlled trial (RCT) to determine the utility of proactive surveillance in people with asymptomatic severe AS to guide the timing of intervention. METHODS AND ANALYSIS: APRAISE-AS is a multi-centre, non-blinded, two-arm, parallel group randomised controlled trial of up to 66 participants aged >18 years with asymptomatic severe AS. Participants will be randomised to either standard care or standard care supplemented with the APRAISE-AS intervention. Primary outcomes will capture; adherence to and participant acceptability of the intervention, recruitment and retention rates, and completeness of data collection. The findings will be used to inform the sample size and most appropriate outcome measure(s) for a full-scale RCT and health economic evaluation. ETHICS AND DISSEMINATION: Ethical approval was granted by the Black Country REC, reference: 22/WM/0214. Results will be submitted for publication in peer-reviewed journals and disseminated at local, regional and national meetings where appropriate. TRIAL REGISTRATION NUMBER: ISRCTN19413194 registered on 14.07.2023.

Blood-based cardiometabolic phenotypes in atrial fibrillation and their associated risk: EAST-AFNET 4 biomolecule study.

AIMS: Atrial fibrillation (AF) and concomitant cardiometabolic disease processes interact and combine to lead to adverse events, such as stroke, heart failure, myocardial infarction, and cardiovascular death. Circulating biomolecules provide quantifiable proxies for cardiometabolic disease processes. The aim of this study was to test whether biomolecule combinations can define phenotypes in patients with AF. METHODS AND RESULTS: This pre-specified analysis of the EAST-AFNET 4 biomolecule study assigned patients to clusters using polytomous variable latent-class analysis based on baseline concentrations of 13 precisely quantified biomolecules potentially reflecting ageing, cardiac fibrosis, metabolic dysfunction, oxidative stress, cardiac load, endothelial dysfunction, and inflammation. In each cluster, rates of cardiovascular death, stroke, or hospitalization for heart failure or acute coronary syndrome, the primary outcome of EAST-AFNET 4, were calculated and compared between clusters over median 5.1 years follow-up. Findings were independently validated in a prospective cohort of 748 patients with AF (BBC-AF; median follow-up 2.9 years).Unsupervised biomolecule analysis assigned 1586 patients (71 years old, 46% women) into four clusters. The highest risk cluster was dominated by elevated bone morphogenetic protein 10, insulin-like growth factor-binding protein 7, N-terminal pro-B-type natriuretic peptide, angiopoietin 2, and growth differentiation factor 15. Patients in the lowest risk cluster showed low concentrations of these biomolecules. Two intermediate-risk clusters differed by high or low concentrations of C-reactive protein, interleukin-6, and D-dimer. Patients in the highest risk cluster had a five-fold higher cardiovascular event rate than patients in the low-risk cluster. Early rhythm control was effective across clusters (Pinteraction = 0.63). Sensitivity analyses and external validation in BBC-AF replicated clusters and risk gradients. CONCLUSION: Biomolecule concentrations identify cardiometabolic subphenotypes in patients with AF at high and low cardiovascular risk.

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions.

Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation.

Heart Failure, Female Sex, and Atrial Fibrillation Are the Main Drivers of Human Atrial Cardiomyopathy: Results From the CATCH ME Consortium.

BACKGROUND: Atrial cardiomyopathy (atCM) is an emerging prognostic factor in cardiovascular disease. Fibrotic remodeling, cardiomyocyte hypertrophy, and capillary density are hallmarks of atCM. The contribution of etiological factors and atrial fibrillation (AF) to the development of differential atCM phenotypes has not been quantified. This study aimed to evaluate the association between histological features of atCM and the clinical phenotype. METHODS AND RESULTS: We examined left atrial (LA, n=95) and right atrial (RA, n=76) appendages from a European cohort of patients undergoing cardiac surgery. Quantification of histological atCM features was performed following wheat germ agglutinin/CD31/vimentin staining. The contributions of AF, heart failure, sex, and age to histological characteristics were determined with multiple linear regression models. Persistent AF was associated with increased endomysial fibrosis (LA: +1.13±0.47 µm, P=0.038; RA: +0.94±0.38 µm, P=0.041), whereas total extracellular matrix content was not. Men had larger cardiomyocytes (LA: +1.92±0.72 µm, P<0.001), while women had more endomysial fibrosis (LA: +0.99±0.56 µm, P=0.003). Patients with heart failure showed more endomysial fibrosis (LA: +1.85±0.48 µm, P<0.001) and extracellular matrix content (LA: +3.07±1.29%, P=0.016), and a higher capillary density (LA: +0.13±0.06, P=0.007) and size (LA: +0.46±0.22 µm, P=0.044). Fuzzy k-means clustering of histological features identified 2 subtypes of atCM: 1 characterized by enhanced endomysial fibrosis (LA: +3.17 µm, P<0.001; RA: +2.86 µm, P<0.001), extracellular matrix content (LA: +3.53%, P<0.001; RA: +6.40%, P<0.001) and fibroblast density (LA: +4.38%, P<0.001), and 1 characterized by cardiomyocyte hypertrophy (LA: +1.16 µm, P=0.008; RA: +2.58 µm, P<0.001). Patients with fibrotic atCM were more frequently female (LA: odds ratio [OR], 1.33, P=0.002; RA: OR, 1.54, P=0.004), with persistent AF (LA: OR, 1.22, P=0.036) or heart failure (LA: OR, 1.62, P<0.001). Hypertrophic features were more common in men (LA: OR=1.33, P=0.002; RA: OR, 1.54, P=0.004). CONCLUSIONS: Fibrotic atCM is associated with female sex, persistent AF, and heart failure, while hypertrophic features are more common in men.

The efficacy of a task model approach to ADL rehabilitation in stroke apraxia and action disorganisation syndrome: A randomised controlled trial.

BACKGROUND: Apraxia and action disorganization syndrome (AADS) after stroke can disrupt activities of daily living (ADL). Occupational therapy has been effective in improving ADL performance, however, inclusion of multiple tasks means it is unclear which therapy elements contribute to improvement. We evaluated the efficacy of a task model approach to ADL rehabilitation, comparing training in making a cup of tea with a stepping training control condition. METHODS: Of the 29 stroke survivors with AADS who participated in this cross-over randomized controlled feasibility trial, 25 were included in analysis [44% females; mean(SD) age = 71.1(7.8) years; years post-stroke = 4.6(3.3)]. Participants attended five 1-hour weekly tea making training sessions in which progress was monitored and feedback given using a computer-based system which implemented a Markov Decision Process (MDP) task model. In a control condition, participants received five 1-hour weekly stepping sessions. RESULTS: Compared to stepping training, tea making training reduced errors across 4 different tea types. The time taken to make a cup of tea was reduced so the improvement in accuracy was not due to a speed-accuracy trade-off. No improvement linked to tea making training was evident in a complex tea preparation task (making two different cups of tea simultaneously), indicating a lack of generalisation in the training. CONCLUSIONS: The clearly specified but flexible training protocol, together with information on the distribution of errors, provide pointers for further refinement of task model approaches to ADL rehabilitation. It is recommended that the approach be tested under errorless learning conditions with more impaired patients in future research. TRIAL REGISTRATION: Retrospectively registered at ClinicalTrials.gov on 5th August 2019 [NCT04044911] https://clinicaltrials.gov/ct2/show/NCT04044911?term=Cogwatch&rank=1.

Interactions Between Atrial Fibrillation and Natriuretic Peptide in Predicting Heart Failure Hospitalization or Cardiovascular Death.

Background Natriuretic peptides are routinely quantified to diagnose heart failure (HF). Their concentrations are also elevated in atrial fibrillation (AF). To clarify their value in predicting future cardiovascular events, we measured natriuretic peptides in unselected patients with cardiovascular conditions and related their concentrations to AF and HF status and outcomes. Methods and Results Consecutive patients with cardiovascular conditions presenting to a large teaching hospital underwent clinical assessment, 7-day ECG monitoring, and echocardiography to diagnose AF and HF. NT-proBNP (N-terminal pro-B-type natriuretic peptide) was centrally quantified. Based on a literature review, four NT-proBNP groups were defined (<300, 300-999, 1000-1999, and ≥2000 pg/mL). Clinical characteristics and NT-proBNP concentrations were related to HF hospitalization or cardiovascular death. Follow-up data were available in 1616 of 1621 patients (99.7%) and analysis performed at 2.5 years (median age, 70 [interquartile range, 60-78] years; 40% women). HF hospitalization or cardiovascular death increased from 36 of 488 (3.2/100 person-years) in patients with neither AF nor HF, to 55 of 354 (7.1/100 person-years) in patients with AF only, 92 of 369 (12.1/100 person-years) in patients with HF only, and 128 of 405 (17.7/100 person-years) in patients with AF plus HF (P<0.001). Higher NT-proBNP concentrations predicted the outcome in patients with AF only (C-statistic, 0.82; 95% CI, 0.77-0.86; P <0.001) and in other phenotype groups (C-statistic in AF plus HF, 0.66; [95% CI, 0.61-0.70]; P <0.001). Conclusions Elevated NT-proBNP concentrations predict future HF events in patients with AF irrespective of the presence of HF, encouraging routine quantification of NT-proBNP in the assessment of patients with AF.

Detection of unknown atrial fibrillation by prolonged ECG monitoring in an all-comer patient cohort and association with clinical and Holter variables.

OBJECTIVES: Prolonged ECG monitoring is clinically useful to detect unknown atrial fibrillation (AF) in stroke survivors. The diagnostic yield of prolonged ECG monitoring in other patient populations is less well characterised. We therefore studied the diagnostic yield of prolonged Holter ECG monitoring for AF in an unselected patient cohort referred from primary care or seen in a teaching hospital. METHODS: We analysed consecutive 7-day ECG recordings in unselected patients referred from different medical specialities and assessed AF detection rates by indication, age and comorbidities. RESULTS: Seven-day Holter ECGs (median monitoring 127.5 hours, IQR 116 to 152) were recorded in 476 patients (mean age 54.6 (SD 17.0) years, 55.9% female) without previously known AF, requested to evaluate palpitations (n=241), syncope (n=99), stroke or transient ischaemic attack (n=75), dizziness (n=29) or episodic chest pain (n=32). AF was newly detected in 42/476 (8.8%) patients. Oral anticoagulation was initiated in 40/42 (95.2%) patients with newly detected AF. Multivariate logistic regression, adjusted for age, sex and monitoring duration found four clinical parameters to be associated with newly detected AF: hypertension OR=2.54, (1.08 to 8.61) (adjusted OR (95% CI)), p=0.034; previous stroke or TIA OR=4.14 (1.81 to 13.01), p=0.001; left-sided valvular heart disease OR=5.07 (2.48 to 18.70), p<0.001 and palpitations OR=2.86, (1.33 to 10.44), p=0.015. CONCLUSIONS: Open multispeciality access to prolonged ECG monitoring, for example, as part of integrated, cross-sector AF care, can accelerate diagnosis of AF and increase adequate use of oral anticoagulation, especially in older and symptomatic patients with comorbidities.