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Real world data (RWD) refers to healthcare information that is routinely collected in electronic healthcare records (EHR), hospital and pharmacy records, patient and disease registries, and health insurance databases. The collection and analysis of this vast amount of data is an important complement to that obtained from conventional randomised controlled trials (RCT). Real world data has been used for healthcare quality improvements, to conduct clinical trials, to support drug and device development, and to inform medical guidelines. The utility of RWD may be facilitated by common data models, which standardise format and content, and allow data from different health systems to be analysed together.The European Society of Cardiology (ESC) supports the use of RWD in collaboration with national cardiac societies, regulatory authorities, and industry to encourage continuous quality of care improvements at the hospital and country level, to conduct registry-based randomised clinical trials (R-RCT) and to facilitate safety surveillance of novel drugs and devices.The European Medicines Agency (EMA) is developing systems and processes to enable the use of RWD that can help in trial planning, defining clinical contexts, and enhancing outcome assessments. RWD can also contribute to the measurement of the impact of regulatory actions, such as contraindications or restriction of indications by looking at medicines use patterns over time across European Member States. A number of other initiatives from the European Commission and the EMA are underway to strengthen the EU's health security framework, and foster the collection and utilisation of RWD.

Heart failure with preserved ejection fraction (HFpEF) and AF are two common cardiovascular conditions that are inextricably linked to each other’s development and progression, often in multimorbid patients. Current management is often directed to specific components of each disease without considering their joint impact on diagnosis, treatment and prognosis. The result for patients is suboptimal on all three levels, restricting clinicians from preventing major adverse events, including death, which occurs in 20% of patients at 2 years and in 45% at 4 years. New trial evidence and reanalysis of prior trials are providing a glimmer of hope that adverse outcomes can be reduced in those with concurrent HFpEF and AF. This will require a restructuring of care to integrate heart failure and AF teams, alongside those that manage comorbidities. Parallel commencement and non-sequential uptitration of therapeutics across different domains will be vital to ensure that all patients benefit at a personal level, based on their own needs and priorities.

Background:\ud Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess multiple and higher-dimension interactions of comorbidities, and define clusters of β-blocker efficacy in patients with sinus rhythm and atrial fibrillation.\ud Methods:\ud Neural network-based variational autoencoders and hierarchical clustering were applied to pooled individual patient data from nine double-blind, randomised, placebo-controlled trials of β blockers. All-cause mortality during median 1·3 years of follow-up was assessed by intention to treat, stratified by electrocardiographic heart rhythm. The number of clusters and dimensions was determined objectively, with results validated using a leave-one-trial-out approach. This study was prospectively registered with ClinicalTrials.gov (NCT00832442) and the PROSPERO database of systematic reviews (CRD42014010012).\ud Findings:\ud 15 659 patients with heart failure and LVEF of less than 50% were included, with median age 65 years (IQR 56–72) and LVEF 27% (IQR 21–33). 3708 (24%) patients were women. In sinus rhythm (n=12 822), most clusters demonstrated a consistent overall mortality benefit from β blockers, with odds ratios (ORs) ranging from 0·54 to 0·74. One cluster in sinus rhythm of older patients with less severe symptoms showed no significant efficacy (OR 0·86, 95% CI 0·67–1·10; p=0·22). In atrial fibrillation (n=2837), four of five clusters were consistent with the overall neutral effect of β blockers versus placebo (OR 0·92, 0·77–1·10; p=0·37). One cluster of younger atrial fibrillation patients at lower mortality risk but similar LVEF to average had a statistically significant reduction in mortality with β blockers (OR 0·57, 0·35–0·93; p=0·023). The robustness and consistency of clustering was confirmed for all models (p

Rebecca Persson,1 Todd Sponholtz,1 Catherine Vasilakis-Scaramozza,1 Katrina Wilcox Hagberg,1 Tim Williams,2 Dipak Kotecha,3 Puja Myles,2 Susan S Jick1,4 1Epidemiology, Boston Collaborative Drug Surveillance Program, Lexington, MA, USA; 2Clinical Practice Research Datalink, Medicines and Healthcare Products Regulatory Agency, London, UK; 3Institute of Cardiovascular Sciences, University of Birmingham & University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; 4Epidemiology, Boston University School of Public Health, Boston, MA, USACorrespondence: Susan S Jick Email sjick@bu.eduBackground: Validation studies of the Clinical Practice Research Datalink (CPRD) Aurum database in the UK are critical for making decisions about its suitability and validity for research purposes.Objective: To examine data source agreement of myocardial infarction (MI) diagnoses recorded in CPRD Aurum compared with linked Hospital Episode Statistics (HES) data. This comparison provides information on CPRD Aurum data correctness (accuracy, validity) and completeness (presence, missingness).Methods: Patients with MI diagnoses recorded in either data source were selected from a random sample of 50,000 patients in CPRD Aurum with HES linkage (1997– 2017). Correctness was defined as the proportion of MI cases in CPRD Aurum with a concordant MI diagnosis recorded in HES or with strong supporting evidence in either data source. Completeness was defined as the proportion of patients with primary HES-coded MIs with strong supporting evidence that were also present in CPRD Aurum.Results: There were 1260 patients with MI recorded in the CPRD Aurum sample. The overall correctness of the recorded MI diagnoses was 94%: 986 patients (78%) had concordant diagnoses in HES within 90 days; 123 (10%) were concordant with HES, but with an inconclusive date and another 71 (6%) had strong supporting evidence for being a true MI case. There were 1125 patients with MI recorded in HES primary diagnosis fields with strong supporting evidence in either data source. Of these, 880 (78%) were present in CPRD Aurum, with completeness somewhat higher in more recent years.Conclusion: MI diagnoses recorded in CPRD Aurum were highly likely to be correct, supporting its use in clinical research studies. Completeness was lower, indicating the need for data linkage for some studies.Keywords: clinical practice research datalink, CPRD Aurum, data validation, data completeness, data quality

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Background Machine learning (ML) is increasingly used in research for subtype definition and risk prediction, particularly in cardiovascular diseases. No existing ML models are routinely used for cardiovascular disease management, and their phase of clinical utility is unknown, partly due to a lack of clear criteria. We evaluated ML for subtype definition and risk prediction in heart failure (HF), acute coronary syndromes (ACS) and atrial fibrillation (AF). Methods For ML studies of subtype definition and risk prediction, we conducted a systematic review in HF, ACS and AF, using PubMed, MEDLINE and Web of Science from January 2000 until December 2019. By adapting published criteria for diagnostic and prognostic studies, we developed a seven-domain, ML-specific checklist. Results Of 5918 studies identified, 97 were included. Across studies for subtype definition (n = 40) and risk prediction (n = 57), there was variation in data source, population size (median 606 and median 6769), clinical setting (outpatient, inpatient, different departments), number of covariates (median 19 and median 48) and ML methods. All studies were single disease, most were North American (n = 61/97) and only 14 studies combined definition and risk prediction. Subtype definition and risk prediction studies respectively had limitations in development (e.g. 15.0% and 78.9% of studies related to patient benefit; 15.0% and 15.8% had low patient selection bias), validation (12.5% and 5.3% externally validated) and impact (32.5% and 91.2% improved outcome prediction; no effectiveness or cost-effectiveness evaluations). Conclusions Studies of ML in HF, ACS and AF are limited by number and type of included covariates, ML methods, population size, country, clinical setting and focus on single diseases, not overlap or multimorbidity. Clinical utility and implementation rely on improvements in development, validation and impact, facilitated by simple checklists. We provide clear steps prior to safe implementation of machine learning in clinical practice for cardiovascular diseases and other disease areas.

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.

BackgroundImproving the efficiency of clinical trials is key to their continued importance in directing evidence-based patient care. Digital innovations, in particular the use of electronic healthcare records (EHR), allow for large-scale screening and follow-up of participants. However, it is critical these developments are accompanied by robust and transparent methods that can support high quality and high clinical value research.MethodsThe DaRe2THINK trial includes a series of novel processes, including nationwide pseudonymised pre-screening of the primary care EHR across England, digital enrolment, remote e-consent, and ‘no-visit’ follow-up by linking all primary and secondary care health data with patient-reported outcomes.FindingsDaRe2THINK is a pragmatic, healthcare-embedded randomised trial testing whether earlier use of direct oral anticoagulants in patients with prior or current atrial fibrillation can prevent thromboembolic events and cognitive decline (www.birmingham.ac.uk/dare2think). This paper outlines the systematic approach and methodology employed to define patient information and outcome events. This includes transparency on all medical code lists and phenotypes used in the trial across a variety of national data sources, including Clinical Practice Research Datalink Aurum (primary care), Hospital Episode Statistics (secondary care) and the Office for National Statistics (mortality).InterpretationCo-designed by a patient and public involvement team, DaRe2THINK presents an opportunity to transform the approach to randomised trials in the setting of routine healthcare, providing high-quality evidence generation in populations representative of the community at-risk.

The validity and reproducibility of systolic function assessment in patients with atrial fibrillation (AF) using cardiac magnetic resonance, echocardiography, nuclear imaging and computed tomography is unknown. A prospectively-registered systematic review was performed, including 24 published studies with patients in AF at the time of imaging and reporting validity or reproducibility data on left ventricular systolic parameters (PROSPERO: CRD42018091674). Data extraction and risk of bias were performed by 2 investigators independently and synthesized qualitatively. In 3 cardiac magnetic resonance studies (40 AF patients), left ventricular ejection fraction and stroke volume measurements correlated highly with catheter angiography (r ≥0.85), and intra- and/or interobserver variability were low. From 3 nuclear studies (171 AF patients), there were no external validation assessments but intra and/or interobserver and intersession variability were low. In 18 echocardiography studies (2,566 AF patients), 2 studies showed high external validity of global longitudinal strain and tissue Doppler s' with angiography-derived dP/dt (r ≥0.88). Global longitudinal strain and myocardial performance index were both associated with adverse cardiovascular events. Reproducibility of echocardiography was better when selecting an index-beat (where 2 preceding R-to-R intervals are similar) compared to averaging of consecutive beats. There were no studies relating to computed tomography. Most studies were small and biased by selection of patients with good quality images, limiting clinical extrapolation of results. The validity of systolic function measurements in patients with AF remains unclear due to the paucity of good-quality data.

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.

Europace : the European journal of pacing, arrhythmias and cardiac electrophysiology euac062 (2022). doi:10.1093/europace/euac062, Published by Oxford Univ. Press, Oxford

Background Fabry disease (FD) is a treatable X-linked condition leading to progressive cardiac disease, arrhythmia and premature death. We aimed to increase awareness of the arrhythmogenicity of Fabry cardiomyopathy, by comparing device usage in patients with Fabry cardiomyopathy and sarcomeric HCM. All Fabry patients with an implantable cardioverter defibrillator (ICD) implanted in the UK over a 17 year period were included. A comparator group of HCM patients, with primary prevention ICD implantation, were captured from a regional registry database. Results Indications for ICD in FD varied with 72% implanted for primary prevention based on multiple potential risk factors. In FD and HCM primary prevention devices, arrhythmia occurred more frequently in FD over shorter follow-up (HR 4.2, p p = 0.002). Immediate shock therapy for sustained VT was also more common (HR 2.5, p p = 0.004, NSVT: HR 3.1, p Conclusion This study demonstrates arrhythmia burden and ICD usage in FD is high, suggesting that Fabry cardiomyopathy may be more ‘arrhythmogenic’ than previously thought. Existing risk models cannot be mutually applicable and further research is needed to provide clarity in managing Fabry patients with cardiac involvement.

Aims: To provide robust data on mortality in patients with atrial fibrillation (AF) and heart failure (HF), accounting for differences in mode of death using post-mortem information. Methods and Results: Retrospective cohort of 1009 patients admitted to a Romanian hospital between 2014-2017, with mean age 73±11 years, 47% women, NYHA class 3.0±0.9, left ventricular ejection fraction (LVEF) 40.1±11.0% and 100% anticoagulated. The primary outcome was mortality during 1.5±0.9 years follow-up, of which 291 (29%) died. Post-mortems were performed in 186 (64%) of patients. Baseline factors associated with mortality were dependent on the cause of death. HF-related death in 136 (47%) was associated with higher NYHA class (hazard ratio [HR] 2.45 per one class increase, 95% CI 1.73-3.46; p Conclusions: Supported by post-mortem data, the cause of death in AF and HF patients is heterogeneous, and the relationships with typical markers of mortality are critically dependent on mode of death. The poor prognosis in this group demands further attention to improve management beyond anticoagulation.

Background Intravenous (IV) beta-blockers are commonly used to manage patients with acute atrial fibrillation (AF) and atrial flutter (AFl). Important pharmacodynamic differences exist amongst beta-blockers, and the choice of beta-blocker or other therapy is often not evidence-based. Purpose Systematic review and meta-analysis of randomised controlled trials (RCTs) in the setting of acute AF/AFl to assess the efficacy and safety of IV beta-blockers against other pharmacological interventions (diltiazem, verapamil, digoxin, anti-arrhythmic drugs or placebo). Methods Prospectively registered (PROSPERO: CRD42020204772). MEDLINE, EMBASE and Cochrane Register were searched from inception to August 2020. The primary outcomes were reduction in heart rate and proportion of patients achieving study-defined target heart rate. Secondary outcomes included conversion to sinus rhythm and incidence of adverse events. Beta-blockers were divided according to beta-1 adrenoreceptor selectivity. Meta-analysis was performed to calculate risk ratios (RR) and standardised mean differences (SMD) using random-effects, and fixed-effects within beta-1 subgroups. Results From 5974 studies, 12 RCTs were included with variable risk of bias, encompassing 1152 participants with mean age 62 years, 38% women and baseline heart rate 137 beats/minute. With high heterogeneity (I2=87%; p Conclusion There is no difference between IV beta-blockers overall and other medications for the control of acute AF/AFl, although better efficacy was shown for beta-blockers with higher beta-1 selectivity. IV beta-blockers were as safe as comparator agents, with the exception of non-selective beta-blockers. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Independent systematic review commissioned by Amomed Pharma. Target heart rate and hypotension events

Echocardiography plays an essential role in the diagnosis and assessment of cardiovascular disease. Measurements derived from echocardiography are also used to determine the severity of disease, its progression over time, and to aid in the choice of optimal therapy. It is therefore clinically important that echocardiographic measurements be reproducible, repeatable, and reliable. There are a variety of statistical tests available to assess these parameters, and in this article the authors summarize those available for use by echocardiographers to improve their clinical practice. Correlation coefficients, linear regression, Bland-Altman plots, and the coefficient of variation are explored, along with their limitations. The authors also provide an online tool for the easy calculation of these statistics in the clinical environment (www.birmingham.ac.uk/echo). Quantifying and enhancing the reproducibility of echocardiography has important potential to improve the value of echocardiography as the basis for good clinical decision-making.

BACKGROUND: Many patients with heart failure (HF) are treated with warfarin or non-vitamin K oral anticoagulants (NOACs). Randomized outcome-driven comparisons of different anticoagulant strategies in HF are lacking. Data from international, government-mandated registries may be useful in understanding the real-life use of various anticoagulants and how they are linked to outcomes.STUDY QUESTION: To assess 2015 annual all-cause mortality, myocardial infarction, and stroke rates co-reported for warfarin and NOACs in subjects with and without HF in the US Food and Drug Administration Adverse Event Reporting System (FAERS) database.STUDY DESIGN: We extracted and examined outcome cases in subjects with HF and on warfarin, dabigatran, rivaroxaban, apixaban, or edoxaban and stratified these according to anticoagulants.MEASURES AND OUTCOMES: Annual all-cause mortality, myocardial infarction, and stroke in FAERS.ANALYSIS METHOD: Odds ratio (OR) and χ(Equation is included in full-text article.)for oral anticoagulants from FAERS with and without HF among complete primary reports issued in 2015.RESULTS: FAERS reported 137,026 HF cases, with death co-reported in 42,942 (31.3%). In total, 11,278 (8.2%) HF patients were treated with anticoagulants, with more prescribed warfarin (n = 8260) than all NOACs combined (n = 3018). Very few reports for edoxaban were available. Warfarin consistently displayed a signal for excess adverse events compared to NOACs: OR (95% confidence interval) for the composite of mortality, myocardial infarction, and stroke were 1.91 (1.76-2.07) versus apixaban, 1.92 (1.81-2.03) versus dabigatran, 4.09 (3.38-4.37) versus rivaroxaban, and 2.64 (2.53-2.76) versus all NOACs combined (all P < 0.001). Warfarin, compared to all NOACs combined, demonstrated higher rates of all-cause mortality [OR = 2.69 (95% confidence interval, 2.49-2.90)], myocardial infarction [5.30 (4.17-6.74)], stroke [OR = 8.85 (6.61-11.84)], and ischemic stroke [OR = 12.73 (8.87-18.27); all P < 0.001].CONCLUSIONS: Annual 2015 FAERS profiles in HF patients reveal that warfarin was numerically dominant. Warfarin was associated with higher risk of death, myocardial infarction, and stroke compared to NOACs. These observational data provide real-world insight into a potential safety benefit of NOACs over warfarin in the setting of HF.

AimsTo evaluate population-based electronic health record (EHR) definitions of atrial fibrillation (AF) and valvular heart disease (VHD) subtypes, time trends in prevalence and prognosis.Methods and resultsA total of 76 019 individuals with AF were identified in England in 1998–2010 in the CALIBER resource, linking primary and secondary care EHR. An algorithm was created, implemented, and refined to identify 18 VHD subtypes using 406 diagnosis, procedure, and prescription codes. Cox models were used to investigate associations with a composite endpoint of incident stroke (ischaemic, haemorrhagic, and unspecified), systemic embolism (SSE), and all-cause mortality. Among individuals with AF, the prevalence of AF with concomitant VHD increased from 11.4% (527/4613) in 1998 to 17.6% (7014/39 868) in 2010 and also in individuals aged over 65 years. Those with mechanical valves, mitral stenosis (MS), or aortic stenosis had highest risk of clinical events compared to AF patients with no VHD, in relative [hazard ratio (95% confidence interval): 1.13 (1.02–1.24), 1.20 (1.05–1.36), and 1.27 (1.19–1.37), respectively] and absolute (excess risk: 2.04, 4.20, and 6.37 per 100 person-years, respectively) terms. Of the 95.2% of individuals with indication for warfarin (men and women with CHA2DS2-VASc ≥1 and ≥2, respectively), only 21.8% had a prescription 90 days prior to the study.ConclusionPrevalence of VHD among individuals with AF increased from 1998 to 2010. Atrial fibrillation associated with aortic stenosis, MS, or mechanical valves (compared to AF without VHD) was associated with an excess absolute risk of stroke, SSE, and mortality, but anticoagulation was underused in the pre-direct oral anticoagulant (DOAC) era, highlighting need for urgent clarity regarding DOACs in AF and concomitant VHD.

Background Atrial fibrillation (AF) is the arrhythmia most commonly diagnosed in clinical practice. It is associated with significant morbidity and mortality. Prevalence of AF and complications of AF, estimated by hospitalisations, have increased dramatically in the last decade. Being able to predict AF would allow tailoring of management strategies and a focus on primary or secondary prevention. Models predicting recurrent AF would have particular clinical use for the selection of rhythm control therapy. There are existing prognostic models which combine several predictors or risk factors to generate an individualised estimate of risk of AF. The aim of this systematic review is to summarise and compare model performance measures and predictive accuracy across different models and populations at risk of developing incident or recurrent AF. Methods Methods tailored to systematic reviews of prognostic models will be used for study identification, risk of bias assessment and synthesis. Studies will be eligible for inclusion where they report an internally or externally validated model. The quality of studies reporting a prognostic model will be assessed using the Prediction Study Risk Of Bias Assessment Tool (PROBAST). Studies will be narratively described and included variables and predictive accuracy compared across different models and populations. Meta-analysis of model performance measures for models validated in similar populations will be considered where possible. Discussion To the best of our knowledge, this will be the first systematic review to collate evidence from all studies reporting on validated prognostic models, or on the impact of such models, in any population at risk of incident or recurrent AF. The review may identify models which are suitable for impact assessment in clinical practice. Should gaps in the evidence be identified, research recommendations relating to model development, validation or impact assessment will be made. Findings will be considered in the context of any models already used in clinical practice, and the extent to which these have been validated. Systematic review registration PROSPERO (CRD42018111649).

Importance: There is little evidence to support selection of heart rate control therapy in patients with permanent atrial fibrillation, in particular those with coexisting heart failure. Objective: To compare low-dose digoxin with bisoprolol (a β-blocker). Design, Setting, and Participants: Randomized, open-label, blinded end-point clinical trial including 160 patients aged 60 years or older with permanent atrial fibrillation (defined as no plan to restore sinus rhythm) and dyspnea classified as New York Heart Association class II or higher. Patients were recruited from 3 hospitals and primary care practices in England from 2016 through 2018; last follow-up occurred in October 2019. Interventions: Digoxin (n = 80; dose range, 62.5-250 μg/d; mean dose, 161 μg/d) or bisoprolol (n = 80; dose range, 1.25-15 mg/d; mean dose, 3.2 mg/d). Main Outcomes and Measures: The primary end point was patient-reported quality of life using the 36-Item Short Form Health Survey physical component summary score (SF-36 PCS) at 6 months (higher scores are better; range, 0-100), with a minimal clinically important difference of 0.5 SD. There were 17 secondary end points (including resting heart rate, modified European Heart Rhythm Association [EHRA] symptom classification, and N-terminal pro-brain natriuretic peptide [NT-proBNP] level) at 6 months, 20 end points at 12 months, and adverse event (AE) reporting. Results: Among 160 patients (mean age, 76 [SD, 8] years; 74 [46%] women; mean baseline heart rate, 100/min [SD, 18/min]), 145 (91%) completed the trial and 150 (94%) were included in the analysis for the primary outcome. There was no significant difference in the primary outcome of normalized SF-36 PCS at 6 months (mean, 31.9 [SD, 11.7] for digoxin vs 29.7 [11.4] for bisoprolol; adjusted mean difference, 1.4 [95% CI, −1.1 to 3.8]; P = .28). Of the 17 secondary outcomes at 6 months, there were no significant between-group differences for 16 outcomes, including resting heart rate (a mean of 76.9/min [SD, 12.1/min] with digoxin vs a mean of 74.8/min [SD, 11.6/min] with bisoprolol; difference, 1.5/min [95% CI, −2.0 to 5.1/min]; P = .40). The modified EHRA class was significantly different between groups at 6 months; 53% of patients in the digoxin group reported a 2-class improvement vs 9% of patients in the bisoprolol group (adjusted odds ratio, 10.3 [95% CI, 4.0 to 26.6]; P Conclusions and Relevance: Among patients with permanent atrial fibrillation and symptoms of heart failure treated with low-dose digoxin or bisoprolol, there was no statistically significant difference in quality of life at 6 months. These findings support potentially basing decisions about treatment on other end points.

Deterministic approaches using iterative optimisation have been historically successful in diffeomorphic image registration (DiffIR). Although these approaches are highly accurate, they typically carry a significant computational burden. Recent developments in stochastic approaches based on deep learning have achieved sub-second runtimes for DiffIR with competitive registration accuracy, offering a fast alternative to conventional iterative methods. In this paper, we attempt to reduce this difference in speed whilst retaining the performance advantage of iterative approaches in DiffIR. We first propose a simple iterative scheme that functionally composes intermediate non-stationary velocity fields to handle large deformations in images whilst guaranteeing diffeomorphisms in the resultant deformation. We then propose a convex optimisation model that uses a regularisation term of arbitrary order to impose smoothness on these velocity fields and solve this model with a fast algorithm that combines Nesterov gradient descent and the alternating direction method of multipliers (ADMM). Finally, we leverage the computational power of GPU to implement this accelerated ADMM solver on a 3D cardiac MRI dataset, further reducing runtime to less than 2 seconds. In addition to producing strictly diffeomorphic deformations, our methods outperform both state-of-the-art deep learning-based and iterative DiffIR approaches in terms of dice and Hausdorff scores, with speed approaching the inference time of deep learning-based methods., Accepted to MICCAI 2021

Background: Transparent and robust real-world evidence sources are increasingly important for global health, including cardiovascular (CV) diseases. We aimed to identify global real-world data (RWD) sources for heart failure (HF), acute coronary syndrome (ACS), and atrial fibrillation (AF). Methods: We conducted a systematic review of publications with RWD pertaining to HF, ACS, and AF (2010–2018), generating a list of unique data sources. Metadata were extracted based on the source type (e.g., electronic health records, genomics, and clinical data), study design, population size, clinical characteristics, follow-up duration, outcomes, and assessment of data availability for future studies and linkage. Results: Overall, 11,889 publications were retrieved for HF, 10,729 for ACS, and 6,262 for AF. From these, 322 (HF), 287 (ACS), and 220 (AF) data sources were selected for detailed review. The majority of data sources had near complete data on demographic variables (HF: 94%, ACS: 99%, and AF: 100%) and considerable data on comorbidities (HF: 77%, ACS: 93%, and AF: 97%). The least reported data categories were drug codes (HF, ACS, and AF: 10%) and caregiver involvement (HF: 6%, ACS: 1%, and AF: 1%). Only a minority of data sources provided information on access to data for other researchers (11%) or whether data could be linked to other data sources to maximize clinical impact (20%). The list and metadata for the RWD sources are publicly available at www.escardio.org/bigdata. Conclusions: This review has created a comprehensive resource of CV data sources, providing new avenues to improve future real-world research and to achieve better patient outcomes.

Introduction: The impact of the sympathetic nervous system (SNS) modulation on the risk of heart failure (HF) outside of ß1 receptor blockade remains controversial. Methods: We performed a two-sample Mendelian randomization (MR) study using common independent genetic variants located in the cis region of genes encoding the 9 SNS receptors (α1 A, B, D, α2 A, B, C and ß 1, 2 and 3) that were associated at genome-wide significance (P-value ≤ 5х10 –8 ) with blood pressure (BP) and/or heart rate (HR) in published genome-wide association studies (GWAS) available for BP and HR. Variants were filtered out by Linkage Disequilibrium clumping (LD R 2 > 0.1) and based on their minor allele frequency (MAF < 0.01). The effects of selected variants on the genetic risk of HF were extracted from a GWAS of HF from the HERMES consortium, based on a non-overlapping sample population. MR estimates were obtained using the Wald estimator for a single variant or the inverse variance weighted method for multiple variants. Results: 542,362 controls and 40,805 HF cases were evaluated. Independent variants in genes encoding 4 SNS receptors associated with BP or HR were identified as follows: α1A (diastolic BP), α2B (diastolic BP and HR), ß1 and ß2 (diastolic and systolic BP). MR analysis of α1A and ß1, weighted by their effects on diastolic BP, estimated an association with a higher risk of HF, while α2B variants were associated with a lower risk. We found no evidence for an effect of ß2. A similar relationship with systolic BP was found for ß1 and ß2. HR increasing effect of α2B variants was associated with a decreased odd of HF. Conclusions: Mindful of pleiotropic effects, these findings are consistent with the known benefits of ß1 blockade in HF and support a similar role for α1A blockade; conversely, they suggest a detrimental lowering effect of BP and HR through α2B modulation that deserves further studies. No evidence for a role of ß2 in HF was found.

Background Although observational studies have suggested an association between elevated blood pressure (BP) and increased risk of atrial fibrillation (AF), randomised evidence on the effects of pharmacological blood pressure lowering on the risk of new-onset AF remains limited. Purpose To investigate the effects of pharmacological BP lowering on the risk of AF overall and stratified by baseline risk of AF and by drug class. Methods We extracted individual participant data from trials with over 1,000 person-years of follow-up that had randomly assigned patients to different classes of BP-lowering drugs, BP-lowering drugs vs placebo, or to more vs less intensive BP-lowering regimens. We investigated the effects of BP lowering on the risk of new-onset AF using fixed-effect one-stage individual participant data meta-analyses based on Cox proportional hazards models stratified by trial. Results Twenty-one trials were included with a total of 194,041 patients, in whom 6,357 new-onset and 516 recurrent AF events were recorded. The hazard ratio for new-onset AF was 1.01, 95% CI [0.95–1.07] per each 5-mmHg reduction in systolic BP, and meta-regression suggested that treatment effects were similar irrespective of the intensity of systolic BP reduction. Patients were overall at low risk of AF at baseline (median 2.3%, IQR [1.2–3.4%] at 5 years), and there was no evidence of heterogeneity in treatment effects across thirds of risk and 10-mmHg strata of baseline systolic BP (Figure). There was also no clear evidence that treatment effects differed between drug classes when renin-angiotensin-aldosterone system inhibitors and calcium channel blockers were compared with placebo and/or standard treatment. Conclusion In a low-risk population, pharmacological BP lowering did not reduce the risk of new-onset AF. Further research is needed to understand whether the effects would be different in high-risk individuals, and to better clarify the existence of class-specific effects. Figure 1. Forest plot Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): British Heart Foundation

Introduction Echocardiography is essential for the management of patients with atrial fibrillation (AF), but current methods are time consuming and lack any evidence of reproducibility. Purpose To compare conventional averaging of consecutive beats with an index beat approach, where systolic and diastolic measurements are taken once after two prior beats with a similar RR interval (not more than 60 ms difference). Methods Transthoracic echocardiography was performed using a standardized and blinded protocol in patients enrolled into the RAte control Therapy Evaluation in permanent AF randomised controlled trial (RATE-AF; NCT02391337). AF was confirmed in all patients with a preceding 12-lead ECG. A minimum of 30-beat loops were recorded. Left ventricular function was determined using the recommended averaging of 5 and 10 beats and using the index beat method, with observers blinded to clinical details. Complete loops were used to calculate the within-beat coefficient of variation (CV) and intraclass correlation coefficient (ICC) for Simpson's biplane left ventricular ejection fraction (LVEF), global longitudinal strain (GLS) and filling pressure (E/e'). Results 160 patients (median age 75 years (IQR 69–82); 46% female) were included, with median heart rate 100 beats/min (IQR 86–112). For LVEF, the index beat had the lowest CV of 32% compared to 51% for 5 consecutive beats and 53% for 10 consecutive beats (p Conclusion Index beat determination of left ventricular function improves reproducibility, saves time and does not compromise validity compared to conventional quantification in patients with heart failure and AF. After independent validation, the index beat method should be adopted into routine clinical practice. Comparison for measurement of E/e' Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Institute of Health Research UK

Introduction Early diagnosis of atrial fibrillation (AF) is essential to reduce complications such as stroke, and improve patient quality of life. Novel screening techniques using smartphone camera photoplethysmography (PPG) can be used for AF detection, but their clinical applicability remains unclear. Purpose To assess the diagnostic accuracy of smartphone PPG compared to conventional ECG for AF detection. Methods We performed a systematic review of MEDLINE, EMBASE, Cochrane library, and other databases (1980-October 2019), including any study or abstract where smartphone finger-tip PPG was compared with a reference ECG (1, 3 or 12-lead). Outcomes were sensitivity (SE), specificity (SP), positive and negative predictive value (PPV; NPV) and overall accuracy. Bivariate hierarchical random effects meta-analysis was performed for studies with confidence intervals for SE and SP, and funnel plots were used to identify publication bias. Study quality was assessed using the established QUADAS-2 tool by two independent graders. Results 1350 publications were screened, of which 17 studies were included in the systematic review (7 full text publications and 10 abstracts), providing 21 comparisons of accuracy for AF detection. Most studies were based in secondary care and small (range n=33 to 1095), with a total of 5469 participants including 1384 with AF. Only 4 studies were multicentre. Smartphone applications used were Cardiio Rhythm, Fibricheck, Preventicus and Heartbeats, with 7 studies not specifying the tool used. Overall SE and SP for AF detection were high, ranging from 76 to 100%, and 85 to 100% respectively. PPV ranged from 54 to 100% and NPV from 77 to 100%, with overall accuracy between 61 and 99%. The meta-analysis included 12 comparisons from 10 studies (n=2714; 936 with AF). The pooled SE was 93% (95% CI 90–96%) and SP 97% (95% CI 95–99%); Figure 1A. QUADAS-2 assessment demonstrated poor quality of studies overall, with a high or unclear risk of bias in at least one domain for all studies. There was clear evidence of publication bias; Figure 1B. Conclusions PPG offers the potential for large scale, non-invasive, patient-led screening of AF. However, current evidence is limited to biased, low quality studies often with unrealistic results for AF detection. These are insufficient to advise clinicians on the true value of current smartphone PPG technology. Figure 1. Meta-analysis & publication bias Funding Acknowledgement Type of funding source: Public grant(s) – EU funding. Main funding source(s): BigData@Heart EU/EFPIA IMI 116074.

AimsTo establish the extent and impact of symptoms in patients with atrial fibrillation (AF), the importance of different aspects of quality of life (QoL), and how we should assess wellbeing.MethodsFocus groups of patients with symptomatic permanent AF in a trial of heart rate control; the RATE-AF trial randomised 160 patients aged ≥60 years with permanent AF and at least NYHA class II dyspnoea to either digoxin or beta-blockers. Patient and public representatives led the focus groups and performed all data acquisition and analysis, using thematic approaches to interpret patient views about QoL and its measurement.ResultsSubstantial impairment of health-related QoL was noted in 160 trial patients, with impact on all domains apart from mental health. Eight women and 11 men aged 61–87 years participated in the focus groups. Common themes were a lack of information from healthcare professionals about AF, a lack of focus on QoL in consultations, and a sense of frustration, isolation and reduced confidence. There was marked variability in symptoms in individual patients, with some describing severe impact on activities of daily living, and profound interaction with comorbidities such as arthritis. Day-to-day variation in QoL and difficulty in attributing symptom burden to AF or other comorbidities led to challenges in questionnaire completion. Consensus was reached that collecting both general and AF-specific QoL would be useful in routine practice, along with participation in peer support, which was empowering for the patients.ConclusionsThe impact of comorbidities is poorly appreciated in the context of AF, with considerable variability in QoL that requires both generic and AF-specific assessment. Improvement in QoL should direct the appraisal, and reappraisal, of treatment decisions for patients with permanent AF.

Aims: To establish the extent and impact of symptoms in patients with atrial fibrillation (AF), the importance of different aspects of quality of life (QoL), and how we should assess wellbeing. Methods: Focus groups of patients with symptomatic permanent AF in a trial of heart rate control; the RATE-AF trial randomised 160 patients aged ≥60 years with permanent AF and at least NYHA class II dyspnoea to either digoxin or beta-blockers. Patient and public representatives led the focus groups and performed all data acquisition and analysis, using thematic approaches to interpret patient views about QoL and its measurement. Results: Substantial impairment of health-related QoL was noted in 160 trial patients, with impact on all domains apart from mental health. Eight women and 11 men aged 61–87 years participated in the focus groups. Common themes were a lack of information from healthcare professionals about AF, a lack of focus on QoL in consultations, and a sense of frustration, isolation, and reduced confidence. There was marked variability in symptoms in individual patients, with some describing severe impact on activities of daily living, and profound interaction with comorbidities such as arthritis. Day-to-day variation in QoL and difficulty in attributing symptom burden to AF or other comorbidities led to challenges in questionnaire completion. Consensus was reached that collecting both general and AF-specific QoL would be useful in routine practice, along with participation in peer support, which was empowering for the patients. Conclusions: The impact of comorbidities is poorly appreciated in the context of AF, with considerable variability in QoL that requires both generic and AF-specific assessment. Improvement in QoL should direct the appraisal, and reappraisal, of treatment decisions for patients with permanent AF.

Introduction Echocardiography is essential for the management of patients with atrial fibrillation (AF), but current methods are time consuming and lack any evidence of reproducibility. Purpose To compare conventional averaging of consecutive beats with an index beat approach, where systolic and diastolic measurements are taken once after two prior beats with a similar RR interval (not more than 60 ms difference). Methods Transthoracic echocardiography was performed using a standardized and blinded protocol in patients enrolled into the RAte control Therapy Evaluation in permanent AF randomised controlled trial (RATE-AF; NCT02391337). AF was confirmed in all patients with a preceding 12-lead ECG. A minimum of 30-beat loops were recorded. Left ventricular function was determined using the recommended averaging of 5 and 10 beats and using the index beat method, with observers blinded to clinical details. Complete loops were used to calculate the within-beat coefficient of variation (CV) and intraclass correlation coefficient (ICC) for Simpson’s biplane left ventricular ejection fraction (LVEF), global longitudinal strain (GLS) and filling pressure (E/e’). Results 160 patients (median age 75 years (IQR 69-82); 46% female) were included, with median heart rate 100 beats/min (IQR 86-112). For LVEF, the index beat had the lowest CV of 32% compared to 51% for 5 consecutive beats and 53% for 10 consecutive beats (p Conclusion Index beat determination of left ventricular function improves reproducibility, saves time and does not compromise validity compared to conventional quantification in patients with heart failure and AF. After independent validation, the index beat method should be adopted into routine clinical practice. Conflict of Interest Nothing to declare