Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association.

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

Competing risks of monomorphic vs. non-monomorphic ventricular arrhythmias in primary prevention implantable cardioverter-defibrillator recipients: Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) study.

AIMS: Ablation of monomorphic ventricular tachycardia (MMVT) has been shown to reduce shock frequency and improve survival. We aimed to compare cause-specific risk factors for MMVT and polymorphic ventricular tachycardia (PVT)/ventricular fibrillation (VF) and to develop predictive models. METHODS AND RESULTS: The multicentre retrospective cohort study included 2668 patients (age 63.1 ± 13.0 years; 23% female; 78% white; 43% non-ischaemic cardiomyopathy; left ventricular ejection fraction 28.2 ± 11.1%). Cox models were adjusted for demographic characteristics, heart failure severity and treatment, device programming, and electrocardiogram metrics. Global electrical heterogeneity was measured by spatial QRS-T angle (QRSTa), spatial ventricular gradient elevation (SVGel), azimuth, magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). We compared the out-of-sample performance of the lasso and elastic net for Cox proportional hazards and the Fine-Gray competing risk model. During a median follow-up of 4 years, 359 patients experienced their first sustained MMVT with appropriate implantable cardioverter-defibrillator (ICD) therapy, and 129 patients had their first PVT/VF with appropriate ICD shock. The risk of MMVT was associated with wider QRSTa [hazard ratio (HR) 1.16; 95% confidence interval (CI) 1.01-1.34], larger SVGel (HR 1.17; 95% CI 1.05-1.30), and smaller SVGmag (HR 0.74; 95% CI 0.63-0.86) and SAIQRST (HR 0.84; 95% CI 0.71-0.99). The best-performing 3-year competing risk Fine-Gray model for MMVT [time-dependent area under the receiver operating characteristic curve (ROC(t)AUC) 0.728; 95% CI 0.668-0.788] identified high-risk (> 50%) patients with 75% sensitivity and 65% specificity, and PVT/VF prediction model had ROC(t)AUC 0.915 (95% CI 0.868-0.962), both satisfactory calibration. CONCLUSION: We developed and validated models to predict the competing risks of MMVT or PVT/VF that could inform procedural planning and future randomized controlled trials of prophylactic ventricular tachycardia ablation. CLINICAL TRIAL REGISTRATION: URL:www.clinicaltrials.gov Unique identifier:NCT03210883.

Ambient circulation surrounding an ablation catheter tip affects ablation lesion characteristics.

INTRODUCTION: The association between ambient circulating environments (CEs) and ablation lesions has been largely underexplored. METHODS: Viable bovine myocardium was placed in a saline bath in an ex vivo endocardial model. Radiofrequency (RF) ablation was performed using three different ablation catheters: 3.5 mm open irrigated (OI), 4, and 8 mm. Variable flow rates of surrounding bath fluids were applied to simulate standard flow, high flow, and no flow. For in vivo epicardial ablation, 24 rats underwent a single OI ablation and performed with circulating saline (30 ml/min; n = 12), versus those immersed in saline without circulation (n = 12). RESULTS: High flow reduced ablation lesion volumes for all three catheters. In no-flow endocardial CE, both 4 mm and OI catheters produced smaller lesions compared with standard flow. However, the 8 mm catheter produced the largest lesions in a no-flow CE. Ablation performed in an in vivo model with CE resulted in smaller lesions compared with ablation performed in a no-flow environment. No statistically significant differences in steam pops were found among the groups. CONCLUSION: A higher endocardial CE flow can decrease RF effectiveness. Cardiac tissue subjected to no endocardial CE flow may also limit RF for 4 mm catheters, but not for OI catheters; these findings may have implications for RF ablation safety and efficacy, especially in the epicardial space without circulating fluid or in the endocardium under varying flow conditions.

Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography.

BACKGROUND: Structural changes in the left atrium (LA) modestly predict outcomes in patients undergoing catheter ablation for atrial fibrillation (AF). Machine learning (ML) is a promising approach to personalize AF management strategies and improve predictive risk models after catheter ablation by integrating atrial geometry from cardiac computed tomography (CT) scans and patient-specific clinical data. We hypothesized that ML approaches based on a patient's specific data can identify responders to AF ablation. METHODS: Consecutive patients undergoing AF ablation, who had preprocedural CT scans, demographics, and 1-year follow-up data, were included in the study for a retrospective analysis. The inputs of models were CT-derived morphological features from left atrial segmentation (including the shape, volume of the LA, LA appendage, and pulmonary vein ostia) along with deep features learned directly from raw CT images, and clinical data. These were merged intelligently in a framework to learn their individual importance and produce the optimal classification. RESULTS: Three hundred twenty-one patients (64.2 ± 10.6 years, 69% male, 40% paroxysmal AF) were analyzed. Post 10-fold nested cross-validation, the model trained to intelligently merge and learn appropriate weights for clinical, morphological, and imaging data (AUC 0.821) outperformed those trained solely on clinical data (AUC 0.626), morphological (AUC 0.659), or imaging data (AUC 0.764). CONCLUSION: Our ML approach provides an end-to-end automated technique to predict AF ablation outcomes using deep learning from CT images, derived structural properties of LA, augmented by incorporation of clinical data in a merged ML framework. This can help develop personalized strategies for patient selection in invasive management of AF.

Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside. OBJECTIVE: To develop computational phenotypes of patients with ischemic cardiomyopathy, by training then interpreting machine learning of ventricular monophasic action potentials (MAPs) to reveal phenotypes that predict long-term outcomes. METHODS AND RESULTS: We recorded 5706 ventricular MAPs in 42 patients with coronary artery disease and left ventricular ejection fraction ≤40% during steady-state pacing. Patients were randomly allocated to independent training and testing cohorts in a 70:30 ratio, repeated K=10-fold. Support vector machines and convolutional neural networks were trained to 2 end points: (1) sustained VT/VF or (2) mortality at 3 years. Support vector machines provided superior classification. For patient-level predictions, we computed personalized MAP scores as the proportion of MAP beats predicting each end point. Patient-level predictions in independent test cohorts yielded c-statistics of 0.90 for sustained VT/VF (95% CI, 0.76-1.00) and 0.91 for mortality (95% CI, 0.83-1.00) and were the most significant multivariate predictors. Interpreting trained support vector machine revealed MAP morphologies that, using in silico modeling, revealed higher L-type calcium current or sodium-calcium exchanger as predominant phenotypes for VT/VF. CONCLUSIONS: Machine learning of action potential recordings in patients revealed novel phenotypes for long-term outcomes in ischemic cardiomyopathy. Such computational phenotypes provide an approach which may reveal cellular mechanisms for clinical outcomes and could be applied to other conditions.

The digital journey: 25 years of digital development in electrophysiology from an Europace perspective.

AIMS: Over the past 25 years there has been a substantial development in the field of digital electrophysiology (EP) and in parallel a substantial increase in publications on digital cardiology.In this celebratory paper, we provide an overview of the digital field by highlighting publications from the field focusing on the EP Europace journal. RESULTS: In this journey across the past quarter of a century we follow the development of digital tools commonly used in the clinic spanning from the initiation of digital clinics through the early days of telemonitoring, to wearables, mobile applications, and the use of fully virtual clinics. We then provide a chronicle of the field of artificial intelligence, a regulatory perspective, and at the end of our journey provide a future outlook for digital EP. CONCLUSION: Over the past 25 years Europace has published a substantial number of papers on digital EP, with a marked expansion in digital publications in recent years.

Reduction in long-term mortality using remote device monitoring in a large real-world population of patients with implantable defibrillators.

AIMS: Remote monitoring (RM) for implantable cardioverter-defibrillators (ICDs) is advocated for the potential of early detection of disease progression and device dysfunction. While studies have examined the effect of RM on clinical outcomes in carefully selected populations of heart failure patients implanted with ICDs from a single vendor, there is a paucity of data in real-world patients. We aimed to assess the long-term effect of RM in a representative ICD population using real-world data. METHODS AND RESULTS: This is an observational retrospective longitudinal study of 1004 patients implanted with an ICD or cardiac resynchronization therapy device (CRT-D) from all device vendors between 2010 and 2021. Patients started on RM (N = 403) within 90 days following de novo device implantation and yearly in-office visits were compared with patients with only bi-yearly in-office follow-up (non-RM, N = 601). In a propensity score matched cohort of 430 patients (mean age 61.4 ± 14.3 years, 26.7% female), all-cause mortality at 4-year was 12.6% in the RM and 27.7% in the non-RM group [hazard ratio (HR) 0.52, 95% confidence interval (CI) 0.32-0.82; P = 0.005]. No difference in inappropriate ICD-therapy (HR 1.90, 95% CI 0.86-4.21; P = 0.122) was observed. The risk of appropriate ICD-therapy (HR 1.71, 95% CI 1.07-2.74; P = 0.026) was higher in the RM group. CONCLUSION: Remote monitoring was associated with a reduction in long-term all-cause and cardiac mortality compared with traditional office visits in a real-world ICD population.

Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms.

AIMS: There is a clinical spectrum for atrial tachyarrhythmias wherein most patients with atrial tachycardia (AT) and some with atrial fibrillation (AF) respond to ablation, while others do not. It is undefined if this clinical spectrum has pathophysiological signatures. This study aims to test the hypothesis that the size of spatial regions showing repetitive synchronized electrogram (EGM) shapes over time reveals a spectrum from AT, to AF patients who respond acutely to ablation, to AF patients without acute response. METHODS AND RESULTS: We studied n = 160 patients (35% women, 65.0 ± 10.4 years) of whom (i) n = 75 had AF terminated by ablation propensity matched to (ii) n = 75 without AF termination and (iii) n = 10 with AT. All patients had mapping by 64-pole baskets to identify areas of repetitive activity (REACT) to correlate unipolar EGMs in shape over time. Synchronized regions (REACT) were largest in AT, smaller in AF termination, and smallest in non-termination cohorts (0.63 ± 0.15, 0.37 ± 0.22, and 0.22 ± 0.18, P < 0.001). Area under the curve for predicting AF termination in hold-out cohorts was 0.72 ± 0.03. Simulations showed that lower REACT represented greater variability in clinical EGM timing and shape. Unsupervised machine learning of REACT and extensive (50) clinical variables yielded four clusters of increasing risk for AF termination (P < 0.01, χ2), which were more predictive than clinical profiles alone (P < 0.001). CONCLUSION: The area of synchronized EGMs within the atrium reveals a spectrum of clinical response in atrial tachyarrhythmias. These fundamental EGM properties, which do not reflect any predetermined mechanism or mapping technology, predict outcome and offer a platform to compare mapping tools and mechanisms between AF patient groups.

Arrhythmias including atrial fibrillation and congenital heart disease in Kleefstra syndrome: a possible epigenetic link.

AIMS: Kleefstra syndrome (KS), often diagnosed in early childhood, is a rare genetic disorder due to haploinsufficiency of EHMT1 and is characterized by neuromuscular and intellectual developmental abnormalities. Although congenital heart disease (CHD) is common, the prevalence of arrhythmias and CHD subtypes in KS is unknown. METHODS AND RESULTS: Inspired by a novel case series of KS patients with atrial tachyarrhythmias in the USA, we evaluate the two largest known KS registries for arrhythmias and CHD: Radboudumc (50 patients) based on health record review at Radboud University Medical Center in the Netherlands and GenIDA (163 patients) based on worldwide surveys of patient families. Three KS patients (aged 17-25 years) presented with atrial tachyarrhythmias without manifest CHD. In the international KS registries, the median [interquartile range (IQR)] age was considerably younger: GenIDA/Radboudumc at 10/13.5 (12/13) years, respectively. Both registries had a 40% prevalence of cardiovascular abnormalities, the majority being CHD, including septal defects, vascular malformations, and valvular disease. Interestingly, 4 (8%) patients in the Radboudumc registry reported arrhythmias without CHD, including one atrial fibrillation (AF), two with supraventricular tachycardias, and one with non-sustained ventricular tachycardia. The GenIDA registry reported one patient with AF and another with chronic ectopic atrial tachycardia (AT). In total, atrial tachyarrhythmias were noted in six young KS patients (6/213 or 3%) with at least four (three AF and one AT) without structural heart disease. CONCLUSION: In addition to a high prevalence of CHD, evolving data reveal early-onset atrial tachyarrhythmias in young KS patients, including AF, even in the absence of structural heart disease.

Optimizing patient selection for primary prevention implantable cardioverter-defibrillator implantation: utilizing multimodal machine learning to assess risk of implantable cardioverter-defibrillator non-benefit.

AIMS: Left ventricular ejection fraction (LVEF) is suboptimal as a sole marker for predicting sudden cardiac death (SCD). Machine learning (ML) provides new opportunities for personalized predictions using complex, multimodal data. This study aimed to determine if risk stratification for implantable cardioverter-defibrillator (ICD) implantation can be improved by ML models that combine clinical variables with 12-lead electrocardiograms (ECG) time-series features. METHODS AND RESULTS: A multicentre study of 1010 patients (64.9 ± 10.8 years, 26.8% female) with ischaemic, dilated, or non-ischaemic cardiomyopathy, and LVEF ≤ 35% implanted with an ICD between 2007 and 2021 for primary prevention of SCD in two academic hospitals was performed. For each patient, a raw 12-lead, 10-s ECG was obtained within 90 days before ICD implantation, and clinical details were collected. Supervised ML models were trained and validated on a development cohort (n = 550) from Hospital A to predict ICD non-arrhythmic mortality at three-year follow-up (i.e. mortality without prior appropriate ICD-therapy). Model performance was evaluated on an external patient cohort from Hospital B (n = 460). At three-year follow-up, 16.0% of patients had died, with 72.8% meeting criteria for non-arrhythmic mortality. Extreme gradient boosting models identified patients with non-arrhythmic mortality with an area under the receiver operating characteristic curve (AUROC) of 0.90 [95% confidence intervals (CI) 0.80-1.00] during internal validation. In the external cohort, the AUROC was 0.79 (95% CI 0.75-0.84). CONCLUSIONS: ML models combining ECG time-series features and clinical variables were able to predict non-arrhythmic mortality within three years after device implantation in a primary prevention population, with robust performance in an independent cohort.

Perpendicular catheter orientation during papillary muscle ablation results in larger, deeper lesions.

INTRODUCTION: Ablation of papillary muscles (PMs) for refractory ventricular arrhythmias can often be challenging. The catheter approach and orientation during ablation may affect optimal radiofrequency (RF) delivery. Yet, no previous study investigated the association between catheter orientation and PM lesion size. We evaluated ablation lesion characteristics with various catheter orientations relative to the PM tissue during open irrigated ablation, using a standardized, experimental setting. METHODS: Viable bovine PM was positioned on a load cell in a circulating saline bath. RF ablation was performed over PM tissue at 50 W, with the open irrigated catheter positioned either perpendicular or parallel to the PM surface. Applied force was 10 g. Ablation lesions were sectioned and underwent quantitative morphometric analysis. RESULTS: A catheter position oriented directly perpendicular to the PM tissue resulted in the largest ablation lesion volumes and depths compared with ablation with the catheter parallel to PM tissue (75.26 ± 8.40 mm3 vs. 34.04 ± 2.91 mm3 , p < .001) and (3.33 ± 0.18 mm vs. 2.24 ± 0.10 mm, p < .001), respectively. There were no significant differences in initial impedance, peak voltage, peak current, or overall decrease in impedance among groups. Parallel catheter orientation resulted in higher peak temperature (41.33 ± 0.28°C vs. 40.28 ± 0.24°C, p = .003), yet, there were no steam pops in either group. CONCLUSION: For PM ablation, catheter orientation perpendicular to the PM tissue achieves more effective and larger ablation lesions, with greater lesion depth. This may have implications for the chosen ventricular access approach, the type of catheter used, consideration for remote navigation, and steerable sheaths.

Breath variability increases in the minutes preceding obstructive sleep apneic events.

PURPOSE: It is unclear if there is a consistent signature in breath patterns prior to an impending obstructive apneic event in patients with sleep-disordered breathing (SDB). OBJECTIVE: To use continuous recordings of ambient sound in sleep using a smartphone to track auditory signatures of breaths and measure their regularity preceding apneic events. METHODS: We studied 50 patients evaluated for SDB in whom sound was recorded using smartphones concurrently with polysomnography (PSG). Whole-night sound files were analyzed for time and frequency domain analyses of breath periodicity during periods of normal and sleep-disordered breathing. RESULTS: Fifty patients (44% women, 42.0 ± 9.4 years old, BMI 32.8 ± 10.8 kg/m2) recorded sound, of whom 30 were diagnosed with OSA and 20 were not. We analyzed a total of 497 apneic (≥10 s) and 481 non-apneic intervals, confirmed by PSG. Interbreath intervals were 3.75 ± 0.62 s for 1 min in quiet breathing, with SD 1.11 ± 0.48 s that increased to 4.16 ± 3.06 s in successive 60-s epochs up to apnea (p < 0.001). Interbreath SD in the 60 s immediately preceding apnea was higher than the SD in random non-apneic periods (p < 0.01, ANOVA). Interbreath SD ≥1.49 s gave 87.3% sensitivity and 86.5% specificity for predicting apnea in the next minute (c-statistic 0.94). CONCLUSIONS: Breaths increase in variability minutes before proven obstructive apnea in patients with suspected SDB. These results suggest that it may be possible to predict and thus potentially avert apneic events and provide insights into events leading to SDB. TRIAL REGISTRATION: NCT03288376, clinicaltrials.org.

Continuous ablation improves lesion maturation compared with intermittent ablation strategies.

BACKGROUND: Interrupted ablation is increasingly proposed as part of high-power short-duration radiofrequency ablation (RFA) strategies and may also result from loss of contact from respiratory patterns or cardiac motion. To study the extent that ablation interruption affects lesions. METHODS: In ex vivo and in vivo experiments, lesion characteristics and tissue temperatures were compared between continuous (group 1) and interrupted (groups 2 and 3) RFA with equal total ablation duration and contact force. Extended duration ablation lesions were also characterized from 1 to 5 minutes. RESULTS: In the ex vivo study, continuous RFA (group 1) produced larger total lesion volumes compared with each interrupted ablation lesion group (273.8 ± 36.5 vs 205.1 ± 34.2 vs 174.3 ± 32.3 mm3 , all P < .001). Peak temperatures for group 1 were higher at 3 and 5 mm than groups 2 and 3. In vivo, continuous ablation resulted in larger lesions, greater lesion depths, and higher tissue temperatures. Longer ablation durations created larger lesion volumes and increased lesion depths. However, after 3 minutes of ablation, the rate of lesion volume, and depth formation decreased. CONCLUSIONS: Continuous RFA delivery resulted in larger and deeper lesions with higher tissue temperatures compared with interrupted ablation. This study may have implications for high-power short duration ablation strategies, motivates strategies to reduce variations in ablation delivery, and provides an upper limit for ablation duration beyond which power delivery has diminishing returns.

Termination of persistent atrial fibrillation by ablating sites that control large atrial areas.

AIMS: Persistent atrial fibrillation (AF) has been explained by multiple mechanisms which, while they conflict, all agree that more disorganized AF is more difficult to treat than organized AF. We hypothesized that persistent AF consists of interacting organized areas which may enlarge, shrink or coalesce, and that patients whose AF areas enlarge by ablation are more likely to respond to therapy. METHODS AND RESULTS: We mapped vectorial propagation in persistent AF using wavefront fields (WFF), constructed from raw unipolar electrograms at 64-pole basket catheters, during ablation until termination (Group 1, N = 20 patients) or cardioversion (Group 2, N = 20 patients). Wavefront field mapping of patients (age 61.1 ± 13.2 years, left atrium 47.1 ± 6.9 mm) at baseline showed 4.6 ± 1.0 organized areas, each separated by disorganization. Ablation of sites that led to termination controlled larger organized area than competing sites (44.1 ± 11.1% vs. 22.4 ± 7.0%, P < 0.001). In Group 1, ablation progressively enlarged unablated areas (rising from 32.2 ± 15.7% to 44.1 ± 11.1% of mapped atrium, P < 0.0001). In Group 2, organized areas did not enlarge but contracted during ablation (23.6 ± 6.3% to 15.2 ± 5.6%, P < 0.0001). CONCLUSION: Mapping wavefront vectors in persistent AF revealed competing organized areas. Ablation that progressively enlarged remaining areas was acutely successful, and sites where ablation terminated AF were surrounded by large organized areas. Patients in whom large organized areas did not emerge during ablation did not exhibit AF termination. Further studies should define how fibrillatory activity is organized within such areas and whether this approach can guide ablation.

Novel three-dimensional imaging approach for cryoballoon navigation and confirmation of pulmonary vein occlusion.

BACKGROUND: Cryoballoon apposition is crucial for durable pulmonary vein isolation (PVI) in atrial fibrillation, yet the balloon is difficult to visualize by conventional mapping systems, and pulmonary venography may miss small or out-of-plane leaks. We report a novel imaging system that offers real-time 3D navigation of the cryoballoon within atrial anatomy that may circumvent these issues. METHODS AND RESULTS: A novel overlay guidance system (OGS) registers already-acquired segmented atrial cardiac tomography (CT) with fluoroscopy, enabling real-time visualization of the cryoballoon within tomographic left atrial imaging during PVI. Phantom experiments in a patient-specific 3D printed left atrium showed feasibility for confirming PV apposition and leaks. We applied OGS prospectively to 68 PVs during PVI in 17 patients. The cryoballoon was successfully reconstructed in all cases, and its apposition was compared to concurrent PV venography. The OGS uncovered leaks undetected by venography in nine veins (eight cases), which enabled repositioning, confirming apposition in remaining 68 veins. Concordance of OGS to venography was 83.8% (χ2 , P < .01) CONCLUSIONS: We report a new system for real-time imaging of cryoballoon catheters to ensure PV apposition within the tomography of the left atrium. While providing high concordance with other imaging modalities for confirming balloon apposition or leak, the system also identified leaks missed by venography. Future studies should determine if this tool can provide a new reference for cryoballoon positioning.

Deep learning for cardiovascular medicine: a practical primer.

Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via multi-layered neural networks. Deep learning has accelerated by recent advances in computer hardware and algorithms and is increasingly applied in e-commerce, finance, and voice and image recognition to learn and classify complex datasets. The current medical literature shows both strengths and limitations of DL. Strengths of DL include its ability to automate medical image interpretation, enhance clinical decision-making, identify novel phenotypes, and select better treatment pathways in complex diseases. Deep learning may be well-suited to cardiovascular medicine in which haemodynamic and electrophysiological indices are increasingly captured on a continuous basis by wearable devices as well as image segmentation in cardiac imaging. However, DL also has significant weaknesses including difficulties in interpreting its models (the 'black-box' criticism), its need for extensive adjudicated ('labelled') data in training, lack of standardization in design, lack of data-efficiency in training, limited applicability to clinical trials, and other factors. Thus, the optimal clinical application of DL requires careful formulation of solvable problems, selection of most appropriate DL algorithms and data, and balanced interpretation of results. This review synthesizes the current state of DL for cardiovascular clinicians and investigators, and provides technical context to appreciate the promise, pitfalls, near-term challenges, and opportunities for this exciting new area.

Transient outward K+ current can strongly modulate action potential duration and initiate alternans in the human atrium.

Efforts to identify the mechanisms for the initiation and maintenance of human atrial fibrillation (AF) often focus on changes in specific elements of the atrial "substrate," i.e., its electrophysiological properties and/or structural components. We used experimentally validated mathematical models of the human atrial myocyte action potential (AP), both at baseline in sinus rhythm (SR) and in the setting of chronic AF, to identify significant contributions of the Ca2+-independent transient outward K+ current ( Ito) to electrophysiological instability and arrhythmia initiation. First, we explored whether changes in the recovery or restitution of the AP duration (APD) and/or its dynamic stability (alternans) can be modulated by Ito. Recent reports have identified disease-dependent spatial differences in expression levels of the specific K+ channel α-subunits that underlie Ito in the left atrium. Therefore, we studied the functional consequences of this by deletion of 50% of native Ito (Kv4.3) and its replacement with Kv1.4. Interestingly, significant changes in the short-term stability of the human atrial AP waveform were revealed. Specifically, this K+ channel isoform switch produced discontinuities in the initial slope of the APD restitution curve and appearance of APD alternans. This pattern of in silico results resembles some of the changes observed in high-resolution clinical electrophysiological recordings. Important insights into mechanisms for these changes emerged from known biophysical properties (reactivation kinetics) of Kv1.4 versus those of Kv4.3. These results suggest new approaches for pharmacological management of AF, based on molecular properties of specific K+ isoforms and their changed expression during progressive disease. NEW & NOTEWORTHY Clinical studies identify oscillations (alternans) in action potential (AP) duration as a predictor for atrial fibrillation (AF). The abbreviated AP in AF also involves changes in K+ currents and early repolarization of the AP. Our simulations illustrate how substitution of Kv1.4 for the native current, Kv4.3, alters the AP waveform and enhances alternans. Knowledge of this "isoform switch" and related dynamics in the AF substrate may guide new approaches for detection and management of AF.

Secular trends in success rate of catheter ablation for atrial fibrillation: The SMASH-AF cohort.

BACKGROUND: Approaches, tools, and technologies for atrial fibrillation (AF) ablation have evolved significantly since its inception. We sought to characterize secular trends in AF ablation success rates. METHODS: We performed a systematic review and meta-analysis of AF ablation from January 1, 1990, to August 1, 2016, searching PubMed, Scopus, and Cochrane databases. Major exclusion criteria were insufficient outcome reporting and ablation strategies that were not prespecified and uniform. We stratified treatment arms by AF type (paroxysmal AF; nonparoxysmal AF) and analyzed single-procedure outcomes. Multivariate meta-regressions analyzed effects of study, patient, and procedure characteristics on success rate trends. Registered in PROSPERO (CRD42016036549). RESULTS: A total of 180 trials and observational studies with 28,118 patients met inclusion. For paroxysmal AF ablation studies, unadjusted success rate summary estimates ranged from 73.1% in 2003 to 77.1% in 2016, increasing by 0.9%/year (95% CI 0.4%-1.4%; P = .001; I2 = 90%). After controlling for study design and patient demographics, rate of improvement in success rate summary estimate increased (1.6%/year; 95% CI 0.9%-2.2%; P = .001; I2 = 87%). For nonparoxysmal AF ablation studies, unadjusted success rate summary estimates ranged from 70.0% in 2010 to 64.3% in 2016 (1.1%/year; 95% CI -1.3% to 3.5%; P = .37; I2 = 85%), with no improvement in multivariate analyses. CONCLUSIONS: Despite substantial research investment and health care expenditure, improvements in AF ablation success rates have been incremental. Meaningful improvements may require major paradigm or technology changes, and evaluation of clinical outcomes such as mortality and quality of life may prove to be important going forward.

Urinary tract infection after catheter ablation of atrial fibrillation.

BACKGROUND: Urinary tract infection (UTI) is common after surgical procedures and a quality improvement target. For non-surgical procedures such as catheter ablation of atrial fibrillation (AF), UTI risk has not been characterized. We sought to determine incidence and risk factors of UTI after AF ablation and risk variation across sites. METHODS: Using Marketscan commercial claims databases, we performed a retrospective cohort study of patients who underwent AF ablation from 2007 to 2011. The primary outcome was UTI diagnosis within 30 days after ablation. We performed multivariate analyses to determine risk factors for UTI and risk of sepsis within 30 days after ablation with UTI as the predictor variable. Median odds ratio was used to quantify UTI site variation. RESULTS: Among 21 091 patients (age 59.2 ± 10.9; 29.1% female; CHA2 DS2 -VASc 2.0 ± 1.6), 622 (2.9%) were diagnosed with UTI within 30 days. In multivariate analyses, UTI was independently associated with age, female sex, prior UTI, and general anesthesia (all P < .01). UTI diagnosis was associated with a substantial increased risk of sepsis within 30 days (5.0% vs. 0.3%; odds ratio 17.5; 95% confidence interval [CI] 10.8-28.2; P < .0001). Among 416 sites, 211 had at least one UTI. Among these 211 sites, the incidence of postablation UTI ranged from 0.7 to 26.7% (median: 5.4%; Interquartile Range (IQR): 3.0-7.1%; 95th percentile: 14.3%; median odds ratio: 1.45; 95% CI 1.41-1.50). CONCLUSIONS: UTI after AF ablation is not uncommon and varies substantially across sites. Consideration of UTI as a quality measure and interventions targeted at high-risk patients or sites warrant consideration.

Comparison of phase mapping and electrogram-based driver mapping for catheter ablation in atrial fibrillation.

INTRODUCTION: Adjunctive driver-guided ablation in addition to pulmonary vein isolation has been proposed as a strategy to improve procedural success and outcomes for various populations with atrial fibrillation (AF). First, this study aimed to evaluate the different mapping techniques for driver/rotor identification and second to evaluate the benefits of driver/rotor-guided ablation in patients with paroxysmal and persistent AF (PerAF). METHODS: We searched the electronic database in PubMed using the keywords "atrial fibrillation," "rotor," "rotational driver," "atrial fibrillation source," and "drivers" for both randomized controlled trials and observational controlled trials. Clinical studies reporting efficacy or safety outcomes of driver-guided ablation for paroxysmal AF or (PerAF) were identified. We performed subgroup analyses comparing different driver mapping methods in patients with PerAF. The odds ratios (ORs) with random effects were analyzed. RESULTS: Out of 175 published articles, seven met the inclusion criteria, of which two were randomized controlled trials, one was quasiexperimental study, and four observational studies (three case-controlled studies and one cross-sectional study). Overall, adjunctive driver-guided ablation was associated with higher rates of acute AF termination (OR: 4.62, 95% confidence interval [CI]: 2.12-10.08; P < 0.001), lower recurrence of any atrial arrhythmia (OR: 0.44, 95% CI: 0.30-0.065; P < 0.001), and comparable complication incidence. CONCLUSIONS: Adjunctive driver-guided catheter ablation suggested an increased freedom from AF/AT relative to conventional strategies, irrespective of the mapping techniques. Furthermore, phase mapping appears to be superior to electrogram-based driver mapping in PerAF ablation.