Design and Implementation of an Electronic Health Record-Integrated Hypertension Management Application.

BACKGROUND: High blood pressure affects approximately 116 million adults in the United States. It is the leading risk factor for death and disability across the world. Unfortunately, over the past decade, hypertension control rates have decreased across the United States. Prediction models and clinical studies have shown that reducing clinician inertia alone is sufficient to reach the target of ≥80% blood pressure control. Digital health tools containing evidence-based algorithms that are able to reduce clinician inertia are a good fit for turning the tide in blood pressure control, but careful consideration should be taken in the design process to integrate digital health interventions into the clinical workflow. METHODS: We describe the development of a provider-facing hypertension management platform. We enumerate key steps of the development process, including needs finding, clinical workflow analysis, treatment algorithm creation, platform design and electronic health record integration. We interviewed and surveyed 5 Stanford clinicians from primary care, cardiology, and their clinical care team members (including nurses, advanced practice providers, medical assistants) to identify needs and break down the steps of clinician workflow analysis. The application design and development stage were aided by a team of approximately 15 specialists in the fields of primary care, hypertension, bioinformatics, and software development. CONCLUSIONS: Digital monitoring holds immense potential for revolutionizing chronic disease management. Our team developed a hypertension management platform at an academic medical center to address some of the top barriers to adoption and achieving clinical outcomes. The frameworks and processes described in this article may be used for the development of a diverse range of digital health tools in the cardiovascular space.

Comparative arrhythmia patterns among patients on tyrosine kinase inhibitors.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) are widely used in the treatment of hematologic malignancies. Limited studies have shown an association between treatment-limiting arrhythmias and TKI, particularly ibrutinib, a Bruton's tyrosine kinase (BTK) inhibitor. We sought to comprehensively assess the arrhythmia burden in patients receiving ibrutinib vs non-BTK TKI vs non-TKI therapies. METHODS: We performed a retrospective analysis of consecutive patients who received long-term cardiac event monitors while on ibrutinib, non-BTK TKIs, or non-TKI therapy for a hematologic malignancy between 2014 and 2022. RESULTS: One hundred ninety-three patients with hematologic malignancies were included (ibrutinib = 72, non-BTK TKI = 46, non-TKI therapy = 75). The average duration of TKI therapy was 32 months in the ibrutinib group vs 64 months in the non-BTK TKI group (p = 0.003). The ibrutinib group had a higher prevalence of atrial fibrillation (n = 32 [44%]) compared to the non-BTK TKI (n = 7 [15%], p = 0.001) and non-TKI (n = 15 [20%], p = 0.002) groups. Similarly, the prevalence of non-sustained ventricular tachycardia was higher in the ibrutinib group (n = 31, 43%) than the non-BTK TKI (n = 8 [17%], p = 0.004) and non-TKI groups (n = 20 [27%], p = 0.04). TKI therapy was held in 25% (n = 18) of patients on ibrutinib vs 4% (n = 2) on non-BTK TKIs (p = 0.005) secondary to arrhythmias. CONCLUSIONS: In this large retrospective analysis of patients with hematologic malignancies, patients receiving ibrutinib had a higher prevalence of atrial and ventricular arrhythmias compared to those receiving other TKI, with a higher rate of treatment interruption due to arrhythmias.

Electrophysiological mapping of the epicardium via 3D-printed flexible arrays.

Cardiac electrophysiology mapping and ablation are widely used to treat heart rhythm disorders such as atrial fibrillation (AF) and ventricular tachycardia (VT). Here, we describe an approach for rapid production of three dimensional (3D)-printed mapping devices derived from magnetic resonance imaging. The mapping devices are equipped with flexible electronic arrays that are shaped to match the epicardial contours of the atria and ventricle and allow for epicardial electrical mapping procedures. We validate that these flexible arrays provide high-resolution mapping of epicardial signals in vivo using porcine models of AF and myocardial infarction. Specifically, global coverage of the epicardial surface allows for mapping and ablation of myocardial substrate and the capture of premature ventricular complexes with precise spatial-temporal resolution. We further show, as proof-of-concept, the localization of sites of VT by means of beat-to-beat whole-chamber ventricular mapping of ex vivo Langendorff-perfused human hearts.

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.

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.

Design and development of a digital shared decision-making tool for stroke prevention in atrial fibrillation.

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.

Worldwide survey on implantation of and outcomes for conduction system pacing with His bundle and left bundle branch area pacing leads.

BACKGROUND: Adoption and outcomes for conduction system pacing (CSP), which includes His bundle pacing (HBP) or left bundle branch area pacing (LBBAP), in real-world settings are incompletely understood. We sought to describe real-world adoption of CSP lead implantation and subsequent outcomes. METHODS: We performed an online cross-sectional survey on the implantation and outcomes associated with CSP, between November 15, 2020, and February 15, 2021. We described survey responses and reported HBP and LBBAP outcomes for bradycardia pacing and cardiac resynchronization CRT indications, separately. RESULTS: The analysis cohort included 140 institutions, located on 5 continents, who contributed data to the worldwide survey on CSP. Of these, 127 institutions (90.7%) reported experience implanting CSP leads. CSP and overall device implantation volumes were reported by 84 institutions. In 2019, the median proportion of device implants with CSP, HBP, and/or LBBAP leads attempted were 4.4% (interquartile range [IQR], 1.9-12.5%; range, 0.4-100%), 3.3% (IQR, 1.3-7.1%; range, 0.2-87.0%), and 2.5% (IQR, 0.5-24.0%; range, 0.1-55.6%), respectively. For bradycardia pacing indications, HBP leads, as compared to LBBAP leads, had higher reported implant threshold (median [IQR]: 1.5 V [1.3-2.0 V] vs 0.8 V [0.6-1.0 V], p = 0.0008) and lower ventricular sensing (median [IQR]: 4.0 mV [3.0-5.0 mV] vs. 10.0 mV [7.0-12.0 mV], p < 0.0001). CONCLUSION: In conclusion, CSP lead implantation has been broadly adopted but has yet to become the default approach at most surveyed institutions. As the indications and data for CSP continue to evolve, strategies to educate and promote CSP lead implantation at institutions without CSP lead implantation experience would be necessary.

Tyrosine kinase inhibitor-associated ventricular arrhythmias: a case series and review of literature.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Randomized Clinical Trial to Evaluate an Atrial Fibrillation Stroke Prevention Shared Decision-Making Pathway.

Background Oral anticoagulation reduces stroke and disability in atrial fibrillation (AF) but is underused. We evaluated the effects of a novel patient-clinician shared decision-making (SDM) tool in reducing oral anticoagulation patient's decisional conflict as compared with usual care. Methods and Results We designed and evaluated a new digital decision aid in a multicenter, randomized, comparative effectiveness trial, ENHANCE-AF (Engaging Patients to Help Achieve Increased Patient Choice and Engagement for AF Stroke Prevention). The digital AF shared decision-making toolkit was developed using patient-centered design with clear health communication principles (eg, meaningful images, limited text). Available in English and Spanish, the toolkit included the following: (1) a brief animated video; (2) interactive questions with answers; (3) a quiz to check on understanding; (4) a worksheet to be used by the patient during the encounter; and (5) an online guide for clinicians. The study population included English or Spanish speakers with nonvalvular AF and a CHA2DS2-VASc stroke score ≥1 for men or ≥2 for women. Participants were randomized in a 1:1 ratio to either usual care or the shared decision-making toolkit. The primary end point was the validated 16-item Decision Conflict Scale at 1 month. Secondary outcomes included Decision Conflict Scale at 6 months and the 10-item Decision Regret Scale at 1 and 6 months as well as a weighted average of Mann-Whitney U-statistics for both the Decision Conflict Scale and the Decision Regret Scale. A total of 1001 participants were enrolled and followed at 5 different sites in the United States between December 18, 2019, and August 17, 2022. The mean patient age was 69±10 years (40% women, 16.9% Black, 4.5% Hispanic, 3.6% Asian), and 50% of participants had CHA2DS2-VASc scores ≥3 (men) or ≥4 (women). The primary end point at 1 month showed a clinically meaningful reduction in decisional conflict: a 7-point difference in median scores between the 2 arms (16.4 versus 9.4; Mann-Whitney U-statistics=0.550; P=0.007). For the secondary end point of 1-month Decision Regret Scale, the difference in median scores between arms was 5 points in the direction of less decisional regret (P=0.078). The treatment effects lessened over time: at 6 months the difference in medians was 4.7 points for Decision Conflict Scale (P=0.060) and 0 points for Decision Regret Scale (P=0.35). Conclusions Implementation of a novel shared decision-making toolkit (afibguide.com; afibguide.com/clinician) achieved significantly lower decisional conflict compared with usual care in patients with AF. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04096781.

Hybrid Ablation for Atrial Fibrillation: Safety & Efficacy of Unilateral Epicardial Access.

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.

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.

Advances in Cardiac Electrophysiology.

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.

Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes.

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.

Mapping Atrial Fibrillation After Surgical Therapy to Guide Endocardial Ablation.

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 CHA2DS2-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.

The ENHANCE-AF clinical trial to evaluate an atrial fibrillation shared decision-making pathway: Rationale and study design.

INTRODUCTION: 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. METHODS: 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. CONCLUSIONS: 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.