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BackgroundSmartphone ownership and mobile app use are steadily increasing in individuals of diverse racial and ethnic backgrounds living in the United States. Growing adoption of technology creates a perfect opportunity for digital health interventions to increase access to health care. To successfully implement digital health interventions and engage users, intervention development should be guided by user input, which is best achieved by the process of co-design. Digital health interventions co-designed with the active engagement of users have the potential to increase the uptake of guideline recommendations, which can reduce morbidity and mortality and advance health equity. ObjectiveWe aimed to co-design a digital health intervention for patients with atrial fibrillation, the most common cardiac arrhythmia, with patient, caregiver, and clinician feedback and to describe our approach to human-centered design for building digital health interventions. MethodsWe conducted virtual meetings with patients with atrial fibrillation (n=8), their caregivers, and clinicians (n=8). We used the following 7 steps in our co-design process: step 1, a virtual meeting focused on defining challenges and empathizing with problems that are faced in daily life by individuals with atrial fibrillation and clinicians; step 2, a virtual meeting focused on ideation and brainstorming the top challenges identified during the first meeting; step 3, individualized onboarding of patients with an existing minimally viable version of the atrial fibrillation app; step 4, virtual prototyping of the top 3 ideas generated during ideation; step 5, further ranking by the study investigators and engineers of the ideas that were generated during ideation but were not chosen as top-3 solutions to be prototyped in step 4; step 6, ongoing engineering work to incorporate top-priority features in the app; and step 7, obtaining further feedback from patients and testing the atrial fibrillation digital health intervention in a pilot clinical study. ResultsThe top challenges identified by patients and caregivers included addressing risk factor modification, medication adherence, and guidance during atrial fibrillation episodes. Challenges identified by clinicians were complementary and included patient education, addressing modifiable atrial fibrillation risk factors, and remote atrial fibrillation episode management. Patients brainstormed more than 30 ideas to address the top challenges, and the clinicians generated more than 20 ideas. Ranking of the ideas informed several novel or modified features aligned with the Theory of Health Behavior Change, features that were geared toward risk factor modification; patient education; rhythm, symptom, and trigger correlation for remote atrial fibrillation management; and social support. ConclusionsWe co-designed an atrial fibrillation digital health intervention in partnership with patients, caregivers, and clinicians by virtually engaging in collaborative creation through the design process. We summarize our experience and describe a flexible approach to human-centered design for digital health intervention development that can guide innovative clinical investigators.

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.

BACKGROUND: Post-myocardial infarction (MI) structural remodeling is characterized by left ventricular dilatation, fibrosis, and hypertrophy of the non-infarcted myocardium. OBJECTIVE: The goal of our study was to quantify post-MI electrical remodeling by measuring the sum absolute QRST integral (SAI QRST). We hypothesized that adverse electrical remodeling predicts outcomes in MADIT II study participants. METHODS: Baseline orthogonal ECGs of 750 MADIT II study participants (448 [59.7%] ICD arm) were analyzed. SAI QRST was measured as the arithmetic sum of absolute QRST integrals over all three orthogonal ECG leads. The primary endpoint was defined as sudden cardiac death (SCD) or sustained ventricular tachycardia (VT)/ventricular fibrillation (VF) with appropriate ICD therapies. All-cause mortality served as a secondary endpoint. RESULTS: Adverse electrical remodeling in post-MI patients was characterized by wide QRS, increased magnitudes of spatial QRS and T vectors, J-point deviation, and QTc prolongation. In multivariable Cox regression analysis after adjustment for age, QRS duration, atrial fibrillation, New York Heart Association heart failure class and blood urea nitrogen, SAI QRST predicted SCD/VT/VF (HR 1.33 per 100 mV*ms (95%CI 1.11-1.59); P = 0.002), and all-cause death (HR 1.27 per 100 mV*ms (95%CI 1.03-1.55), P = 0.022) in both arms. No interaction with therapy arm and bundle branch block (BBB) status was found. CONCLUSIONS: In MADIT II patients, increased SAI QRST is associated with increased risk of sustained VT/VF with appropriate ICD therapies and all-cause death in both ICD and in conventional medical therapy arms, and in patients with and without BBB. Further studies of SAI QRST are warranted.

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

Abstract Background: Recent studies suggest that left atrial (LA) late gadolinium enhancement (LGE) can quantify the underlying tissue remodeling that harbors atrial fibrillation (AF). However, quantification of LA-LGE requires labor-intensive magnetic resonance imaging acquisition and postprocessing at experienced centers. LA intra-atrial dyssynchrony assessment is an emerging imaging technique that predicts AF recurrence after catheter ablation. We hypothesized that 1) LA intra-atrial dyssynchrony is associated with LA-LGE in patients with AF and 2) LA intra-atrial dyssynchrony is greater in patients with persistent AF than in those with paroxysmal AF. Method: We conducted a cross-sectional study comparing LA intra-atrial dyssynchrony and LA-LGE in 146 patients with a history of AF (60.0 ± 10.0 years, 30.1% nonparoxysmal AF) who underwent pre-AF ablation cardiac magnetic resonance (CMR) in sinus rhythm. Using tissue-tracking CMR, we measured the LA longitudinal strain in two- and four-chamber views. We defined intra-atrial dyssynchrony as the standard deviation (SD) of the time to peak longitudinal strain (SD-TPS, in %) and the SD of the time to the peak pre-atrial contraction strain corrected by the cycle length (SD-TPSpreA, in %). We used the image intensity ratio (IIR) to quantify LA-LGE. Results: Intra-atrial dyssynchrony analysis took 5 ± 9 minutes per case. Multivariable analysis showed that LA intra-atrial dyssynchrony was independently associated with LA-LGE. In addition, LA intra-atrial dyssynchrony was significantly greater in patients with persistent AF than those with paroxysmal AF. In contrast, there was no significant difference in LA-LGE between patients with persistent and paroxysmal AF. LA intra-atrial dyssynchrony showed excellent reproducibility and its analysis was less time-consuming (5 ± 9 minutes) than the LA-LGE (60 ± 20 minutes). Conclusion: LA Intra-atrial dyssynchrony is a quick and reproducible index that is independently associated with LA-LGE to reflect the underlying tissue remodeling.

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.