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Abstract The rapid growth in consumer-facing mobile and sensor technologies has created tremendous opportunities for patient-driven personalized health management. The diagnosis and management of cardiac arrhythmias are particularly well suited to benefit from these easily accessible consumer health technologies. In particular, smartphone-based and wrist-worn wearable electrocardiogram (ECG) and photoplethysmography (PPG) technology can facilitate relatively inexpensive, long-term rhythm monitoring. Here we review the practical utility of the currently available and emerging mobile health technologies relevant to cardiac arrhythmia care. We discuss the applications of these tools, which vary with respect to diagnostic performance, target populations, and indications. We also highlight that requirements for successful integration into clinical practice require adaptations to regulatory approval, data management, electronic medical record integration, quality oversight, and efforts to minimize the additional burden to health care professionals.

Cardiovascular disease is the leading cause of morbidity and mortality in patients with autoimmune rheumatic diseases. Much of this may be attributed to systemic inflammation resulting in coronary atherosclerosis and myocarditis. Cardiac magnetic resonance imaging is the gold standard for the evaluation of cardiac structure and function, including tissue characterization, which allows for detection of myocardial edema, inflammation, and fibrosis. Advances in parametric mapping and coronary flow reserve measurement techniques have the potential to change the diagnosis, risk stratification, and management of patients with autoimmune rheumatic diseases. We provide an overview of the current evidence and suggest potential future roles for the use of comprehensive cardiac magnetic resonance in patients with autoimmune rheumatic diseases in the field of cardio-rheumatology.

Background Heart failure (HF) has been increasing in prevalence, and a need exists for biomarkers with improved predictive and prognostic ability. GDF‐15 (growth differentiation factor‐15) is a novel biomarker associated with HF mortality, but no serial studies of GDF‐15 have been conducted. This study aimed to investigate the association between GDF‐15 levels over time and the occurrence of ventricular arrhythmias, HF hospitalizations, and all‐cause mortality. Methods and Results We used a retrospective case–control design to analyze 148 patients with ischemic and nonischemic cardiomyopathies and primary prevention implantable cardioverter‐defibrillator (ICD) from the PROSe‐ICD (Prospective Observational Study of the ICD in Sudden Cardiac Death Prevention) cohort. Patients had blood drawn every 6 months and after each appropriate ICD therapy and were followed for a median follow‐up of 4.6 years, between 2005 to 2019. We compared serum GDF‐15 levels within ±90 days of an event among those with a ventricular tachycardia/fibrillation event requiring ICD therapies and those hospitalized for decompensated HF. A comparator/control group comprised patients with GDF‐15 levels available during 2‐year follow‐up periods without events. Median follow‐up was 4.6 years in the 148 patients studied (mean age 58±12, 27% women). The HF cohort had greater median GDF‐15 values within 90 days (1797 pg/mL) and 30 days (2039 pg/mL) compared with the control group (1062 pg/mL, both P

BackgroundCardiac arrhythmias are associated with increased maternal morbidity. There are limited data on trends of arrhythmias among women hospitalized for delivery.Materials and methodsWe used the National Inpatient Sample (NIS) database to identify delivery hospitalizations for individuals aged 18–49 years between 2009 to 2019 and utilized coding data from the 9th and 10th editions of the International Classification of Diseases to identify supraventricular tachycardias (SVT), atrial fibrillation (AF), atrial flutter, ventricular tachycardia (VT), and ventricular fibrillation (VF). Arrhythmia trends were analyzed by age, race-ethnicity, hospital setting, and hospital geographic regions. Multivariable logistic regression was used to evaluate the association of demographic, clinical, and socioeconomic characteristics with arrhythmias.ResultsAmong 41,576,442 delivery hospitalizations, the most common arrhythmia was SVT (53%), followed by AF (31%) and VT (13%). The prevalence of arrhythmia among delivery hospitalizations increased between 2009 and 2019. Age > 35 years and Black race were associated with a higher arrhythmia burden. Factors associated with an increased risk of arrhythmias included valvular disease (OR: 12.77; 95% C1:1.98–13.61), heart failure (OR:7.13; 95% CI: 6.49–7.83), prior myocardial infarction (OR: 5.41, 95% CI: 4.01–7.30), peripheral vascular disease (OR: 3.19, 95% CI: 2.51–4.06), hypertension (OR: 2.18; 95% CI: 2.07–2.28), and obesity (OR 1.69; 95% CI: 1.63–1.76). Delivery hospitalizations complicated by arrhythmias compared with those with no arrhythmias had a higher proportion of all-cause in-hospital mortality (0.95% vs. 0.01%), cardiogenic shock (0.48% vs. 0.00%), preeclampsia (6.96% vs. 3.58%), and preterm labor (2.95% vs. 2.41%) (all p < 0.0001).ConclusionPregnant individuals with age > 35 years, obesity, hypertension, valvular heart disease, or severe pulmonary disease are more likely to have an arrhythmia history or an arrhythmia during a delivery hospitalization. Delivery hospitalizations with a history of arrhythmia are more likely to be complicated by all-cause in-hospital mortality, cardiovascular, and adverse pregnancy outcomes (APOs). These data highlight the increased risk associated with pregnancies among individuals with arrhythmias.

Background: Right ventricular (RV) dysfunction and late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR) are associated with ventricular arrhythmias (VA) and mortality in cardiac sarcoidosis (CS). However, image resolution limits the detection of RV LGE. Global longitudinal RV strain (RVS) correlates to RV scar on electroanatomical mapping and RV function. Objective: We evaluated the association between RVS on CMR and VA/death (combined-primary-endpoint (CPE)) in patients with CS. Methods: RVS and RV LGE on MRI were retrospectively compared to variables known to predict outcomes in 66 patients with CS. Outcomes were obtained from electronic medical records and implantable cardioverter defibrillator (ICD) interrogations over median [IQR] 3.7[1.7, 6.3] years. Cox proportional hazard models were used to evaluate survival. Harrell's C-statistic was used to compare variables in risk prediction models. Results: 62.1 % of patients were male, with a mean age [SD] of 52.3 [9.6] years and left ventricular ejection fraction (LVEF) of 51.1[17.5]%. 9 patients with the primary endpoint were more likely to be Caucasian (p = 0.01) with prior VAs (p = 0.002), be on anti-arrhythmic drugs (p = 0.001) with an ICD (p = 0.002). In multivariable analyses adjusted for age, race, and history of VA, RVS (1.18 [1.05–1.31], p = 0.004), RV EDVI (1.08[1.01, 1.14], p = 0.02), and LV LGE (1.07[1.00, 1.13], p = 0.04) predicted the CPE. Risk prediction models including RVS (Cstatistic 0.94), outperformed those including RV and LV LGE (0.89–0.92). Conclusion: RVS on CMR was the best predictor of VA and mortality in CS.

Abstract Background Patients receiving dialysis face a high risk of cardiovascular disease, arrhythmia and sudden cardiac death. Few patients, however, are aware of this risk. Implantable cardiac monitors are currently available for clinical use and can continuously monitor cardiac rhythms without the need for transvenous leads. Our goal was to gauge patients’ and family members’ perceptions of these risks and to identify their concerns about cardiac monitors. Methods Two 90-minute focus groups were conducted: one with patients receiving in-center hemodialysis and one with their family members. Trained moderators assessed: (1) knowledge of cardiovascular disease; (2) cardiovascular disease risk in dialysis; (3) risk of death due to cardiovascular disease; (4) best ways to convey this risk to patients/families; and (5) concerns about cardiac monitors. The sessions were audiotaped, transcribed, and independently analyzed by two reviewers to identify core themes. Emblematic quotations were chosen to illustrate the final themes. Results Nine adult patients and three family members participated. Patients felt education was inadequate and had little knowledge of arrhythmias. Patients’/families’ concerns regarding cardiac monitors were related to adverse effects, the notification process, and cosmetic effects. Patients/families felt that nephrologists, not dialysis staff, would be the best source for education. Conclusions The preliminary data from this small study population suggest that patients/families are not well aware of the high risk of arrhythmia and sudden cardiac death in dialysis. Further investigation is required to gauge this awareness among patients/families and to assess their impressions of implantable cardiac monitors for arrhythmia detection and management.

Abstract Frequent premature ventricular contractions (PVCs) can induce cardiomyopathy (PVC CM). We sought to use cardiac magnetic resonance imaging (CMR) to quantify changes in cardiac structure and function of cardiomyopathy patients following catheter ablation for PVCs. Patients undergoing PVC ablation at the Johns Hopkins Hospital with pre-procedural CMR from 2010 to 2018 were included in this study. CMR Images were analyzed to collect information on cardiac structure and function as well as to quantify scar. Of the total 51 included patients, PVC CM (LVEF

Sudden cardiac death (SCD) is a leading cause of mortality, comprising approximately half of all deaths from cardiovascular disease. In the US, the majority of SCD (85%) occurs in patients with ischemic cardiomyopathy (ICM) and a subset in patients with non-ischemic cardiomyopathy (NICM), who tend to be younger and whose risk of mortality is less clearly delineated than in ischemic cardiomyopathies. The conventional means of SCD risk stratification has been the determination of the ejection fraction (EF), typically via echocardiography, which is currently a means of determining candidacy for primary prevention in the form of implantable cardiac defibrillators (ICDs). Advanced cardiac imaging methods such as cardiac magnetic resonance imaging (CMR), single-photon emission computerized tomography (SPECT) and positron emission tomography (PET), and computed tomography (CT) have emerged as promising and non-invasive means of risk stratification for sudden death through their characterization of the underlying myocardial substrate that predisposes to SCD. Late gadolinium enhancement (LGE) on CMR detects myocardial scar, which can inform ICD decision-making. Overall scar burden, region-specific scar burden, and scar heterogeneity have all been studied in risk stratification. PET and SPECT are nuclear methods that determine myocardial viability and innervation, as well as inflammation. CT can be used for assessment of myocardial fat and its association with reentrant circuits. Emerging methodologies include the development of “virtual hearts” using complex electrophysiologic modeling derived from CMR to attempt to predict arrhythmic susceptibility. Recent developments have paired novel machine learning (ML) algorithms with established imaging techniques to improve predictive performance. The use of advanced imaging to augment risk stratification for sudden death is increasingly well-established and may soon have an expanded role in clinical decision-making. ML could help shift this paradigm further by advancing variable discovery and data analysis.

Background: An estimated 1 million patients require cardiac implantable electronic devices (CIEDs) but go without annually. This disparity exists in low-to-middle-income nations largely owing to the cost of CIED hardware. Humanitarian reuse of CIEDs has been shown to be safe and feasible. However, recent publications have raised concern that promotion of CIED reuse may foster a CIED “black market,” to the dismay of manufacturers, regulators, and clinicians alike. Objective: To determine if unregulated CIED sales for potential human use is a real issue by investigating unregulated public online CIED sale listings in the United States of America. Methods: An observational study was undertaken over 6 months using multiple internet search engines from May 1 to November 1, 2019. We cataloged usable CIEDs (still in packaging, manufactured

Cardiac sarcoidosis (CS) is an increasingly recognized cause of heart failure and arrhythmia. Historically challenging to identify, particularly in the absence of extracardiac sarcoidosis, diagnosis of CS has improved with advancements in cardiac imaging. Recognition as well as management may require interpretation of multiple imaging modalities. Echocardiography may serve as an initial screening study for cardiac involvement in patients with systemic sarcoidosis. Cardiac magnetic resonance imaging (CMR) provides information on diagnosis as well as risk stratification, particularly for ventricular arrhythmia in the setting of late gadolinium enhancement. More recently, 18F-fluorodeoxyglucose position emission tomography (FDG-PET) has assumed a valuable role in the diagnosis and longitudinal management of patients with CS, allowing for the assessment of response to treatment. Hybrid FDG-PET/CT may also be used in the evaluation of extracardiac inflammation, permitting the identification of biopsy sites for diagnostic confirmation. Herein we examine the approach to diagnosis and management of CS using multimodality imaging via a case-based review.

RationalePatients with ischemic cardiomyopathy (ICMP) are at high risk for malignant arrhythmias, largely due to electrophysiological remodeling of the non-infarcted myocardium. The electrophysiological properties of the non-infarcted myocardium of patients with ICMP remain largely unknown.ObjectivesTo assess the pro-arrhythmic behavior of non-infarcted myocardium in ICMP patients and couple computational simulations with machine learning to establish a methodology for the development of disease-specific action potential models based on clinically measured action potential duration restitution (APDR) data.Methods and ResultsWe enrolled 22 patients undergoing left-sided ablation (10 ICMP) and compared APDRs between ICMP and structurally normal left ventricles (SNLVs). APDRs were clinically assessed with a decremental pacing protocol. Using genetic algorithms (GAs), we constructed populations of action potential models that incorporate the cohort-specific APDRs. The variability in the populations of ICMP and SNLV models was captured by clustering models based on their similarity using unsupervised machine learning. The pro-arrhythmic potential of ICMP and SNLV models was assessed in cell- and tissue-level simulations. Clinical measurements established that ICMP patients have a steeper APDR slope compared to SNLV (by 38%, p < 0.01). In cell-level simulations, APD alternans were induced in ICMP models at a longer cycle length compared to SNLV models (385–400 vs 355 ms). In tissue-level simulations, ICMP models were more susceptible for sustained functional re-entry compared to SNLV models.ConclusionMyocardial remodeling in ICMP patients is manifested as a steeper APDR compared to SNLV, which underlies the greater arrhythmogenic propensity in these patients, as demonstrated by cell- and tissue-level simulations using action potential models developed by GAs from clinical measurements. The methodology presented here captures the uncertainty inherent to GAs model development and provides a blueprint for use in future studies aimed at evaluating electrophysiological remodeling resulting from other cardiac diseases.

Background: Abnormalities on cardiac imaging (cardiac magnetic resonance imaging [CMR] or positron emission tomography [PET]), left ventricular ejection fraction (LVEF), and electrophysiology study (EPS) all predict ventricular arrhythmias (VA) in patients with cardiac sarcoidosis (CS). We sought to assess the utility of EPS in patients with CS and abnormal cardiac imaging, focusing on those with LVEF >35%. Methods: We identified all patients treated at our institution from 2000 to 2017 who: 1.) had probable or definite CS; 2.) had either late gadolinium enhancement (LGE) on CMR or abnormal 18-flourodeoxyglucose (FDG) uptake on PET, and 3.) had undergone EPS. The primary endpoint was VA during follow up. Results: Twenty five patients were included, of whom 10 (40%) had positive EPS. During a mean follow-up of 4.8 +/− 3.4 years, 11 (44%) patients had VA. The positive predictive value (PPV) of EPS for VA was 100% and the negative predictive value (NPV) of EPS for VA was 93%. Among 12 patients with LVEF >35% and no prior VA, the PPV of EPS for VA was 100% and the NPV of EPS for VA was 90%. Conclusion: EPS may help with risk stratification in patients with CS and abnormal imaging, especially those without conventional indications for ICD placement. Among patients with LVEF >35% and no history of prior VA, a negative EPS has good positive and negative predictive value for future VA events. Keywords: Cardiac sarcoidosis, Ventricular arrhythmia, Sudden cardiac death, Electrophysiology study, Implantable cardioverter defibrillator

Focal impulse and rotor mapping (FIRM) involves intracardiac detection and catheter ablation of re-entrant drivers (RDs), some of which may contribute to arrhythmia perpetuation in persistent atrial fibrillation (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) has the potential to non-invasively identify all areas of the fibrotic substrate where RDs could potentially be sustained, including locations where RDs may not manifest during mapped AF episodes. The objective of this study was to carry out multi-modal assessment of the arrhythmogenic propensity of the fibrotic substrate in PsAF patients by comparing locations of RD-harboring regions found in simulations and detected by FIRM (RDsim and RDFIRM) and analyze implications for ablation strategies predicated on targeting RDs. For 11 PsAF patients who underwent pre-procedure LGE-MRI and FIRM-guided ablation, we retrospectively simulated AF in individualized atrial models, with geometry and fibrosis distribution reconstructed from pre-ablation LGE-MRI scans, and identified RDsim sites. Regions harboring RDsim and RDFIRM were compared. RDsim were found in 38 atrial regions (median [inter-quartile range (IQR)] = 4 [3; 4] per model). RDFIRM were identified and subsequently ablated in 24 atrial regions (2 [1; 3] per patient), which was significantly fewer than the number of RDsim-harboring regions in corresponding models (p < 0.05). Computational modeling predicted RDsim in 20 of 24 (83%) atrial regions identified as RDFIRM-harboring during clinical mapping. In a large number of cases, we uncovered RDsim-harboring regions in which RDFIRM were never observed (18/22 regions that differed between the two modalities; 82%); we termed such cases “latent” RDsim sites. During follow-up (230 [180; 326] days), AF recurrence occurred in 7/11 (64%) individuals. Interestingly, latent RDsim sites were observed in all seven computational models corresponding to patients who experienced recurrent AF (2 [2; 2] per patient); in contrast, latent RDsim sites were only discovered in two of four patients who were free from AF during follow-up (0.5 [0; 1.5] per patient; p < 0.05 vs. patients with AF recurrence). We conclude that substrate-based ablation based on computational modeling could improve outcomes.

Persistent atrial fibrillation (AF) can be viewed as disintegrated patterns of information transmission by action potential across the communication network consisting of nodes linked by functional connectivity. To test the hypothesis that ablation of persistent AF is associated with improvement in both local and global connectivity within the communication networks, we analyzed multi-electrode basket catheter electrograms of 22 consecutive patients (63.5 ± 9.7 years, 78% male) during persistent AF before and after the focal impulse and rotor modulation-guided ablation. Eight patients (36%) developed recurrence within 6 months after ablation. We defined communication networks of AF by nodes (cardiac tissue adjacent to each electrode) and edges (mutual information between pairs of nodes). To evaluate patient-specific parameters of communication, thresholds of mutual information were applied to preserve 10% to 30% of the strongest edges. There was no significant difference in network parameters between both atria at baseline. Ablation effectively rewired the communication network of persistent AF to improve the overall connectivity. In addition, successful ablation improved local connectivity by increasing the average clustering coefficient, and also improved global connectivity by decreasing the characteristic path length. As a result, successful ablation improved the efficiency and robustness of the communication network by increasing the small-world index. These changes were not observed in patients with AF recurrence. Furthermore, a significant increase in the small-world index after ablation was associated with synchronization of the rhythm by acute AF termination. In conclusion, successful ablation rewires communication networks during persistent AF, making it more robust, efficient, and easier to synchronize. Quantitative analysis of communication networks provides not only a mechanistic insight that AF may be sustained by spatially localized sources and global connectivity, but also patient-specific metrics that could serve as a valid endpoint for therapeutic interventions.