Chung, Mina K.

Despite advances in cardiovascular care and improved outcomes, fragmented healthcare systems, nonequitable access to health care, and nonuniform and unbiased collection and access to healthcare data have exacerbated disparities in healthcare provision and further delayed the technological-enabled implementation of precision medicine. Precision medicine relies on a foundation of accurate and valid omics and phenomics that can be harnessed at scale from electronic health records. Big data approaches in noncardiovascular healthcare domains have helped improve efficiency and expedite the development of novel therapeutics; therefore, applying such an approach to cardiovascular precision medicine is an opportunity to further advance the field. Several endeavors, including the American Heart Association Precision Medicine platform and public-private partnerships (such as BigData@Heart in Europe), as well as cloud-based platforms, such as Terra used for the National Institutes of Health All of Us, are attempting to temporally and ontologically harmonize data. This state-of-the-art review summarizes best practices used in cardiovascular genomic and precision medicine and provides recommendations for systems’ requirements that could enhance and accelerate the integration of these platforms.

Abstract Atrial fibrillation (AF) is a globally prevalent cardiac arrhythmia with significant genetic underpinnings, as highlighted by recent large-scale genetic studies. A prominent clinical and genetic overlap exists between AF, heritable ventricular cardiomyopathies, and arrhythmia syndromes, underlining the potential of AF as an early indicator of severe ventricular disease in younger individuals. Indeed, several recent studies have demonstrated meaningful yields of rare pathogenic variants among early-onset AF patients (∼4%–11%), most notably for cardiomyopathy genes in which rare variants are considered clinically actionable. Genetic testing thus presents a promising opportunity to identify monogenetic defects linked to AF and inherited cardiac conditions, such as cardiomyopathy, and may contribute to prognosis and management in early-onset AF patients. A first step towards recognizing this monogenic contribution was taken with the Class IIb recommendation for genetic testing in AF patients aged 45 years or younger by the 2023 American College of Cardiology/American Heart Association guidelines for AF. By identifying pathogenic genetic variants known to underlie inherited cardiomyopathies and arrhythmia syndromes, a personalized care pathway can be developed, encompassing more tailored screening, cascade testing, and potentially genotype-informed prognosis and preventive measures. However, this can only be ensured by frameworks that are developed and supported by all stakeholders. Ambiguity in test results such as variants of uncertain significance remain a major challenge and as many as ∼60% of people with early-onset AF might carry such variants. Patient education (including pretest counselling), training of genetic teams, selection of high-confidence genes, and careful reporting are strategies to mitigate this. Further challenges to implementation include financial barriers, insurability issues, workforce limitations, and the need for standardized definitions in a fast-moving field. Moreover, the prevailing genetic evidence largely rests on European descent populations, underscoring the need for diverse research cohorts and international collaboration. Embracing these challenges and the potential of genetic testing may improve AF care. However, further research—mechanistic, translational, and clinical—is urgently needed.

AbstractCardiac physiologic pacing (CPP), encompassing cardiac resynchronization therapy (CRT) and conduction system pacing (CSP), has emerged as a pacing therapy strategy that may mitigate or prevent the development of heart failure (HF) in patients with ventricular dyssynchrony or pacing‐induced cardiomyopathy. This clinical practice guideline is intended to provide guidance on indications for CRT for HF therapy and CPP in patients with pacemaker indications or HF, patient selection, pre‐procedure evaluation and preparation, implant procedure management, follow‐up evaluation and optimization of CPP response, and use in pediatric populations. Gaps in knowledge, pointing to new directions for future research, are also identified.

Sinus tachycardia (ST) is ubiquitous, but its presence outside of normal physiological triggers in otherwise healthy individuals remains a commonly encountered phenomenon in medical practice. In many cases, ST can be readily explained by a current medical condition that precipitates an increase in the sinus rate, but ST at rest without physiological triggers may also represent a spectrum of normal. In other cases, ST may not have an easily explainable cause but may represent serious underlying pathology and can be associated with intolerable symptoms. The classification of ST, consideration of possible etiologies, as well as the decisions of when and how to intervene can be difficult. ST can be classified as secondary to a specific, usually treatable, medical condition (eg, pulmonary embolism, anemia, infection, or hyperthyroidism) or be related to several incompletely defined conditions (eg, inappropriate ST, postural tachycardia syndrome, mast cell disorder, or post-COVID syndrome). While cardiologists and cardiac electrophysiologists often evaluate patients with symptoms associated with persistent or paroxysmal ST, an optimal approach remains uncertain. Due to the many possible conditions associated with ST, and an overlap in medical specialists who see these patients, the inclusion of experts in different fields is essential for a more comprehensive understanding. This article is unique in that it was composed by international experts in Neurology, Psychology, Autonomic Medicine, Allergy and Immunology, Exercise Physiology, Pulmonology and Critical Care Medicine, Endocrinology, Cardiology, and Cardiac Electrophysiology in the hope that it will facilitate a more complete understanding and thereby result in the better care of patients with ST.

Oral anticoagulants (OACs) are medications commonly used in patients with atrial fibrillation and other cardiovascular conditions. Both warfarin and direct oral anticoagulants are susceptible to drug-drug interactions (DDIs). DDIs are an important cause of adverse drug reactions and exact a large toll on the health care system. DDI for warfarin mainly involve moderate to strong inhibitors/inducers of cytochrome P450 (CYP) 2C9, which is responsible for the elimination of the more potent S-isomer of warfarin. However, inhibitor/inducers of CYP3A4 and CYP1A2 may also cause DDI with warfarin. Recognition of these precipitating agents along with increased frequency of monitoring when these agents are initiated or discontinued will minimize the impact of warfarin DDI. Direct oral anticoagulants are mainly affected by medications strongly affecting the permeability glycoprotein (P-gp), and to a lesser extent, strong CYP3A4 inhibitors/inducers. Dabigatran and edoxaban are affected by P-gp modulation. Strong inducers of CYP3A4 or P-gp should be avoided in all patients taking direct oral anticoagulant unless previously proven to be otherwise safe. Simultaneous strong CYP3A4 and P-gp inhibitors should be avoided in patients taking apixaban and rivaroxaban. Concomitant antiplatelet/anticoagulant use confers additive risk for bleeding, but their combination is unavoidable in many cases. Minimizing duration of concomitant anticoagulant/antiplatelet therapy as indicated by evidence-based clinical guidelines is the best way to reduce the risk of bleeding.

Antiarrhythmic drugs (AAD) play an important role in the management of arrhythmias. Drug interactions involving AAD are common in clinical practice. As AADs have a narrow therapeutic window, both pharmacokinetic as well as pharmacodynamic interactions involving AAD can result in serious adverse drug reactions ranging from arrhythmia recurrence, failure of device-based therapy, and heart failure, to death. Pharmacokinetic drug interactions frequently involve the inhibition of key metabolic pathways, resulting in accumulation of a substrate drug. Additionally, over the past 2 decades, the P-gp (permeability glycoprotein) has been increasingly cited as a significant source of drug interactions. Pharmacodynamic drug interactions involving AADs commonly involve additive QT prolongation. Amiodarone, quinidine, and dofetilide are AADs with numerous and clinically significant drug interactions. Recent studies have also demonstrated increased morbidity and mortality with the use of digoxin and other AAD which interact with P-gp. QT prolongation is an important pharmacodynamic interaction involving mainly Vaughan-Williams class III AAD as many commonly used drug classes, such as macrolide antibiotics, fluoroquinolone antibiotics, antipsychotics, and antiemetics prolong the QT interval. Whenever possible, serious drug-drug interactions involving AAD should be avoided. If unavoidable, patients will require closer monitoring and the concomitant use of interacting agents should be minimized. Increasing awareness of drug interactions among clinicians will significantly improve patient safety for patients with arrhythmias.

There is a growing appreciation for differences in epidemiology, treatment, and outcomes of cardiovascular conditions by sex. Historically, cardiovascular clinical trials have under-represented females, but findings have nonetheless been applied to clinical care in a sex-agnostic manner. Thus, much of the collective knowledge about sex-specific cardiovascular outcomes result from post hoc and secondary analyses. In some cases, these investigations have revealed important sex-based differences with implications for optimizing care for female patients with arrhythmias. This review explores the available evidence related to cardiac arrhythmia care among females, with emphasis on areas in which important sex differences are known or suggested. Considerations related to improving female enrollment in clinical trials as a way to establish more robust clinical evidence for the treatment of females are discussed. Areas of remaining evidence gaps are provided, and recommendations for areas of future research and specific action items are suggested. The overarching goal is to improve appreciation for sex-based differences in cardiac arrhythmia care as 1 component of a comprehensive plan to optimize arrhythmia care for all patients.

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.

While published guidelines are useful in the care of patients with long-QT syndrome, it can be difficult to decide how to apply the guidelines to individual patients, particularly those with intermediate risk. We explored the diversity of opinion among 24 clinicians with expertise in long-QT syndrome. Experts from various regions and institutions were presented with 4 challenging clinical scenarios and asked to provide commentary emphasizing why they would make their treatment recommendations. All 24 authors were asked to vote on case-specific questions so as to demonstrate the degree of consensus or divergence of opinion. Of 24 authors, 23 voted and 1 abstained. Details of voting results with commentary are presented. There was consensus on several key points, particularly on the importance of the diagnostic evaluation and of β-blocker use. There was diversity of opinion about the appropriate use of other therapeutic measures in intermediate-risk individuals. Significant gaps in knowledge were identified.

Background: While NKX2-5 plays pivotal roles in human cardiac development and disease, no ChIP-Seq studies of NKX2-5 in human cardiac tissues currently exist, resulting in an incomplete understanding of its direct gene targets. Modern computational methods which identify binding sites using transcription factor motif and tissue-specific experimental data can help to fill this knowledge gap. Objective: To use computational methods to identify likely NKX2-5 binding sites and downstream gene targets using human heart-specific experimental data. Methods: Human cardiomyocyte DNAse hypersensitivity data (2 replicates) were downloaded from the Encyclopedia of DNA Elements (ENCODE) database. The position weight matrix (PWM) representing the transcription factor motif of NKX2-5 was obtained from JASPAR. We applied the Protein Interaction Quantification (PIQ) algorithm to detect NKX2-5 binding sites using the PWM and DNAse hypersensitivity data as inputs. RNA-Seq data from 108 human heart-specific samples (atrial appendages and left ventricles) were downloaded from the Genotype-Tissue Expression (GTEx) database. Protein-coding genes significantly expressed in the heart (RPKM <= 1 based on the GTEx RNA-Seq data) that were within 100kb of the predicted binding sites were then identified. Pathway analysis of these genes was performed using Ingenuity Pathway Analysis (IPA). Results: 1283 binding sites for NKX2-5 were discovered by PIQ. Of 12698 protein-coding, heart-expressed genes, 625 were within 100kb of these binding sites. The identified genes were highly enriched in physiologic categories like “Vasculogenesis” and “Development of Cardiovascular Tissue” (p = 2.36x10-9 and 2.31x10-8 respectively). Notable genes included: cardiac transcription factors (MEF2A, TBX20); growth factors (TGFB2, BMP2); muscle and ion channel function (ACTA2, BIN1), and; calcium signaling (CALM2, CAMK2D). Conclusion: By using computational analyses of transcription factor motif and human heart-specific experimental data, we have identified candidate downstream targets of NKX2-5. Future work will include validation studies in an external cohort and analysis of associations between these candidate genes and cardiac disease.