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Hybrid ablation combines thoracoscopic epicardial ablation with percutaneous catheter based endocardial ablation for the treatment of AF. The purpose of this study was to evaluate the safety and efficacy of hybrid ablation surgery for the treatment of atrial fibrillation (AF), and to compare outcomes of unilateral vs bilateral thoracoscopic epicardial ablation. Patients with documented AF who underwent hybrid ablation were followed post-operatively for major events. Major events were classified into 2 categories consisting of (1) safety, comprising all-cause mortality and major morbidities, and (2) efficacy, which included recurrence of atrial arrhythmia, cessation of antiarrhythmic drugs (AAD), and completeness of lesion set. A total of 84 consecutive patients were consented for hybrid ablation. Patients presented with an average AF duration of 85.9 months before hybrid ablation. 80 patients underwent successful thoracoscopic epicardial ablation. At 1-year, 87% (60/69) of patients were free from AF and 73% (50/69) were free from AF and off AAD. 63 patients completed both epicardial and endocardial hybrid ablation with posterior wall isolation achieved in 89% (56/63) of patients. Unilateral epicardial ablation was associated with significantly shorter hospital length of stay compared to bilateral surgical approached (3.9 vs 6.7 days, p = 0.002) with no difference in freedom from AF between groups at 1 year. Hybrid ablation for atrial fibrillation is effective for patients at high risk for recurrence after catheter ablation. The unilateral surgical approach may be associated with shorter hospital stay with no appreciable effect on procedure success rates.

Shared decision making (SDM) may result in treatment plans that best reflect the goals and wishes of patients, increasing patient satisfaction with the decision-making process. There is a knowledge gap to support the use of decision aids in SDM for anticoagulation therapy in patients with atrial fibrillation (AF). We describe the development and testing of a new decision aid, including a multicenter, randomized, controlled, 2-arm, open-label ENHANCE-AF clinical trial (Engaging Patients to Help Achieve Increased Patient Choice and Engagement for AF Stroke Prevention) to evaluate its effectiveness in 1,200 participants.Participants will be randomized to either usual care or to a SDM pathway incorporating a digital tool designed to simplify the complex concepts surrounding AF in conjunction with a clinician tool and a non-clinician navigator to guide the participants through each step of the tool. The participant-determined primary outcome for this study is the Decisional Conflict Scale, measured at 1 month after the index visit during which a decision was made regarding anticoagulation use. Secondary outcomes at both 1 and 6 months will include other decision making related scales as well as participant and clinician satisfaction, oral anticoagulation adherence, and a composite rate of major bleeding, death, stroke, or transient ischemic attack. The study will be conducted at four sites selected for their ability to enroll participants of varying racial and ethnic backgrounds, health literacy, and language skills. Participants will be followed in the study for 6 months.The results of the ENHANCE-AF trial will determine whether a decision aid facilitates high quality shared decision making in anticoagulation discussions for stroke reduction in AF. An improved shared decision-making experience may allow patients to make decisions better aligned with their personal values and preferences, while improving overall AF care.

AimsThere 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 resultsWe 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).ConclusionThe 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.

Background Shared decision-making (SDM) is an approach in which patients and clinicians act as partners in making medical decisions. Patients receive the information needed to decide and are encouraged to balance risks, benefits, and preferences. Informative materials are vital to SDM. Atrial fibrillation (AF) is the most common cardiac arrhythmia and responsible for 10% of ischemic strokes, however 1/3 of patients are not on appropriate anticoagulation. Decision sharing may facilitate treatment acceptance, improving outcomes. Aims To develop a framework of the components needed to create novel SDM tools and to provide practical examples through a case-study of stroke prevention in AF. Methods We analyze the design values of a web-based SDM tool created to better inform AF patients about anticoagulation. The tool was developed in partnership with patient advocates, multi-disciplinary investigators, and private design firms. It was refined through iterative, recursive testing in patients with AF. Its effectiveness is being evaluated in a multisite clinical trial led by Stanford University and sponsored by the American Heart Association. Findings The main components considered when creating the Stanford AFib tool included: design and software; content identification; information delivery; inclusive communication, user engagement; patient feedback; clinician experience; and anticipation of implementation and dissemination. We also highlight the ethical principles underlying SDM; matters of diversity and inclusion, linguistic variety, accessibility, and health literacy. The Stanford AFib Guide patient tool is available at: https://afibguide.com and the clinician tool at https://afibguide.com/clinician. Conclusion Attention to a range of vital development and design factors can facilitate tool adoption and information acquisition by diverse cultural, educational, and socioeconomic subpopulations. With thoughtful design, digital tools may decrease decision regret and improve treatment outcomes across many decision-making situations in healthcare.

Despite the global COVID-19 pandemic, during the past 2 years, there have been numerous advances in our understanding of arrhythmia mechanisms and diagnosis and in new therapies. We increased our understanding of risk factors and mechanisms of atrial arrhythmias, the prediction of atrial arrhythmias, response to treatment, and outcomes using machine learning and artificial intelligence. There have been new technologies and techniques for atrial fibrillation ablation, including pulsed field ablation. There have been new randomized trials in atrial fibrillation ablation, giving insight about rhythm control, and long-term outcomes. There have been advances in our understanding of treatment of inherited disorders such as catecholaminergic polymorphic ventricular tachycardia. We have gained new insights into the recurrence of ventricular arrhythmias in the setting of various conditions such as myocarditis and inherited cardiomyopathic disorders. Novel computational approaches may help predict occurrence of ventricular arrhythmias and localize arrhythmias to guide ablation. There are further advances in our understanding of noninvasive radiotherapy. We have increased our understanding of the role of His bundle pacing and left bundle branch area pacing to maintain synchronous ventricular activation. There have also been significant advances in the defibrillators, cardiac resynchronization therapy, remote monitoring, and infection prevention. There have been advances in our understanding of the pathways and mechanisms involved in atrial and ventricular arrhythmogenesis.

Tyrosine kinase inhibitors (TKIs) have been increasingly used as first-line therapy in hematologic and solid-organ malignancies. Multiple TKIs have been linked with the development of cardiovascular complications, especially atrial arrhythmias, but data on ventricular arrhythmias (VAs) is scarce.Herein we describe five detailed cases of VAs related to TKI use in patients with varied baseline cardiovascular risk factors between 2019 and 2022 at three centers. Individual chart review was conducted retrospectively.Patient ages ranged from 43 to 83 years. Three patients were on Bruton's TKI (2 ibrutinib and 1 zanubrutinib) at the time of VAs; other TKIs involved were afatinib and dasatinib. Three patients had a high burden of non-sustained ventricular tachycardia (NSVT) requiring interventions, whereas two patients had sustained VAs. While all patients in our case series had significant improvement in VA burden after TKI cessation, two patients required new long-term antiarrhythmic drug therapy, and one had an implantable defibrillator cardioverter (ICD) placed due to persistent VAs after cessation of TKI therapy. One patient reinitiated TKI therapy after control of arrhythmia was achieved with antiarrhythmic drug therapy.Given the expanding long-term use of TKIs among a growing population of cancer patients, it is critical to acknowledge the association of TKIs with cardiovascular complications such as VAs, to characterize those at risk, and deploy preventive and therapeutic measures to avoid such complications and interference with oncologic therapy. Further efforts are warranted to develop monitoring protocols and optimal treatment strategies for TKI-induced VAs.

Background: Machine learning is a promising approach to personalize atrial fibrillation management strategies for patients after catheter ablation. Prior atrial fibrillation ablation outcome prediction studies applied classical machine learning methods to hand-crafted clinical scores, and none have leveraged intracardiac electrograms or 12-lead surface electrocardiograms for outcome prediction. We hypothesized that (1) machine learning models trained on electrograms or electrocardiogram (ECG) signals can perform better at predicting patient outcomes after atrial fibrillation ablation than existing clinical scores and (2) multimodal fusion of electrogram, ECG, and clinical features can further improve the prediction of patient outcomes. Methods: Consecutive patients who underwent catheter ablation between 2015 and 2017 with panoramic left atrial electrogram before ablation and clinical follow-up for at least 1 year following ablation were included. Convolutional neural network and a novel multimodal fusion framework were developed for predicting 1-year atrial fibrillation recurrence after catheter ablation from electrogram, ECG signals, and clinical features. The models were trained and validated using 10-fold cross-validation on patient-level splits. Results: One hundred fifty-six patients (64.5±10.5 years, 74% male, 42% paroxysmal) were analyzed. Using electrogram signals alone, the convolutional neural network achieved an area under the receiver operating characteristics curve (AUROC) of 0.731, outperforming the existing APPLE scores (AUROC=0.644) and CHA2DS2-VASc scores (AUROC=0.650). Similarly using 12-lead ECG alone, the convolutional neural network achieved an AUROC of 0.767. Combining electrogram, ECG, and clinical features, the fusion model achieved an AUROC of 0.859, outperforming single and dual modality models. Conclusions: Deep neural networks trained on electrogram or ECG signals improved the prediction of catheter ablation outcome compared with existing clinical scores, and fusion of electrogram, ECG, and clinical features further improved the prediction. This suggests the promise of using machine learning to help treatment planning for patients after catheter ablation.

Background. The Stanford Biodesign Faculty Fellows program was established in 2014 to train Stanford Medical and Engineering faculty in a repeatable innovation process for health technology translation while also being compatible with the busy clinical schedules of surgical faculty members. Methods. Since 2014, 62 faculty members have completed the fellowship with 42% (n = 26) coming from 14 surgical subspecialties. This eight-month, needs-based innovation program covers topics from identifying unmet health-related needs, to inventing new technology, developing plans for intellectual property (IP), regulatory, reimbursement, and business models to advance the technologies toward patient care. Results/Conclusion. Intake and exit survey results from three years of program participants (n = 36) indicate that the fellowship is a valuable hands-on educational program capable of improving awareness and experience with skill sets required for health technology innovation and entrepreneurship.

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.

Coronavirus disease 2019 (COVID-19) has presented substantial challenges to patient care and impacted healthcare delivery, including cardiac electrophysiology practice throughout the globe. Based upon the undetermined course and regional variability of the pandemic, there is uncertainty as to how and when to resume and deliver electrophysiology services for patients with arrhythmia. This joint document from representatives of the Heart Rhythm Society, American Heart Association, and American College of Cardiology seeks to provide guidance for clinicians and institutions reestablishing safe electrophysiological care. To achieve this aim, we address regional and local COVID-19 disease status, the role of viral screening and serological testing, return-to-work considerations for exposed or infected health care workers, risk stratification and management strategies based on COVID-19 disease burden, institutional preparedness for resumption of elective procedures, patient preparation and communication, prioritization of procedures, and development of outpatient and periprocedural care pathways.

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 mm(3), 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.

BACKGROUND Limited studies are available on the clinical significance of left ventricular (LV) lead polarity in patients undergoing cardiac resynchronization therapy (CRT), with a recent study suggesting better outcomes with LV true bipolar pacing. OBJECTIVE We aimed to determine whether true bipolar LV pacing is associated with reduced mortality in a large, real-life CRT cohort, followed by remote monitoring. METHODS We analyzed de-identified device data from CRT patients followed by the Boston Scientific LATITUDE remote monitoring database system. Patients with LV bipolar leads paced between the LV ring and LV tip were identified as true bipolar and those with LV bipolar leads paced between LV tip or LV ring and right ventricular (RV) coil were identified as extended bipolar. Patients with unipolar leads were identified as unipolar. RESULTS Of the 59 046 patients included in the study, 2927 had unipolar pacing, 34 390 had extended bipolar pacing, and 21 729 had true bipolar pacing. LV true bipolar pacing was associated with a significant 30% lower risk of all-cause mortality as compared to unipolar pacing (hazards ratio [HR] = 0.70, 95% CI: 0.62-0.79, P

BACKGROUND: Surgical ablation for atrial fibrillation (AF) can be effective, yet has mixed results. It is unclear which endocardial lesions delivered as part of hybrid therapy‚ will best augment surgical lesion sets in individual patients. We addressed this question by systematically mapping AF endocardially after surgical ablation and relating findings to early recurrence, then performing tailored endocardial ablation as part of hybrid therapy. METHODS: We studied 81 consecutive patients undergoing epicardial surgical ablation (stage 1 hybrid), of whom 64 proceeded to endocardial catheter mapping and ablation (stage 2). Stage 2 comprised high-density mapping of pulmonary vein (PV) or posterior wall (PW) reconnections, low-voltage zones (LVZs), and potential localized AF drivers. We related findings to postsurgical recurrence of AF. RESULTS: Mapping at stage 2 revealed PW isolation reconnection in 59.4%, PV isolation reconnection in 28.1%, and LVZ in 42.2% of patients. Postsurgical recurrence of AF occurred in 36 patients (56.3%), particularly those with long-standing persistent AF ( P =0.017), but had no relationship to reconnection of PVs ( P =0.53) or PW isolation ( P =0.75) when compared with those without postsurgical recurrence of AF. LVZs were more common in patients with postsurgical recurrence of AF ( P =0.002), long-standing persistent AF ( P =0.002), advanced age ( P =0.03), and elevated CHA 2 DS 2 -VASc ( P =0.046). AF mapping revealed 4.4±2.7 localized focal/rotational sites near and also remote from PV or PW reconnection. After ablation at patient-specific targets, arrhythmia freedom at 1 year was 81.0% including and 73.0% excluding previously ineffective antiarrhythmic medications. CONCLUSIONS: After surgical ablation, AF may recur by several modes particularly related to localized mechanisms near low voltage zones, recovery of posterior wall or pulmonary vein isolation, or other sustaining mechanisms. LVZs are more common in patients at high clinical risk for recurrence. Patient-specific targeting of these mechanisms yields excellent long-term outcomes from hybrid ablation.

Shared decision making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.

Introduction: Women, ethnic, and racial group representation in clinical trials is low or uncertain in various fields of medicine. Hypothesis: Ethnic/racial information is underreported in atrial fibrillation clinical Trials. Methods: We systematically reviewed 85 randomized atrial fibrillation clinical trials (RCT), published with results on ClinicalTrials.gov, encompassing 2,546,351 participants from January 2011 to May 2021. We determined the representation of women and ethnic/racial groups, and the frequency of information reporting. Results: All of the studies reported gender information; women represented 33.73% of the participants. Only 56.5% (48/75) reported racial/ethnic data. The distribution of the participants were 87% White and 5.1% Black. Data on Latinx were reported in 38% (33/85) of RCTs and represented 5% of reported samples. Only 3.8% of participants were Asian and reported in 34 studies. Ethnic and racial group underrepresentation and underreporting were observed in trials involving device/procedure as well as drug therapy, with more underrepresentation and underreporting observed in drug therapy trials (Table). Conclusions: Gender reporting is consistent for all RCTs but with women representing only one-third of participants. However, the ethnic and racial characteristics, particularly in drug therapy trials, are underreported. In RCTs that report ethnic and racial data, Black and Latinx patients are underrepresented compared to their proportion in the overall population. These limitations may significantly impact the generalizability of the RCT results.

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% (χ(2), 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.

Catheter ablation has brought major advances in the management of patients with atrial fibrillation (AF). As evidenced by multiple randomized trials, AF catheter ablation can reduce the risk of recurrent AF and improve quality of life. In some studies, AF ablation significantly reduced cardiovascular hospitalizations. Despite the existing data on AF catheter ablation, numerous knowledge gaps remain concerning this intervention. This report is based on a recent virtual workshop convened by the National Heart, Lung, and Blood Institute to identify key research opportunities in AF ablation. We outline knowledge gaps related to emerging technologies, the relationship between cardiac structure and function and the success of AF ablation in patient subgroups in whom clinical benefit from ablation varies, and potential platforms to advance clinical research in this area. This report also considers the potential value and challenges of a sham ablation randomized trial. Prioritized research opportunities are identified and highlighted to empower relevant stakeholders to collaborate in designing and conducting effective, cost-efficient, and transformative research to optimize the use and outcomes of AF ablation.