Search

Background While ventricular tachycardia (VT) in the setting of postmyocardial infarction left ventricular aneurysms (LVA) is not uncommonly encountered, there is a scarcity of data regarding the safety, efficacy, and outcomes of ablation of VT in this subset of patients. Methods Our study included consecutive patients aged 18 years or older with postmyocardial infarction LVA who presented to Mayo Clinic for catheter ablation of VT between 2002 and 2018. Results Of 34 patients, the mean age was 70.4 ± 9.1 years; 91% were male. Mean LVEF was 29 ± 9.7% and left ventricular end-diastolic dimension was 64.9 ± 6.6 mm. The site of the LVA was apical in 21 patients (62%). Fifteen patients (44%) presented with electrical storm or incessant VT. Nine patients (26%) had a history of intracardiac thrombus. All except for one patient had at least one VT originating from the aneurysm. The mean number of VTs was 2.9 ± 1.7. All patients underwent ablation at the site of the aneurysm. Ablation outside the aneurysm was performed in 13 patients (38%). Low-voltage fractionated potentials and/or late potentials at the aneurysmal site were present in all cases. Complete elimination of all VTs was achieved in 18 (53%), while the elimination of the clinical VT with continued inducibility of nonclinical VTs was achieved in a further 11 patients (32%). Two patients developed cardiac tamponade requiring pericardiocentesis. During a mean follow-up period of 2.3 ± 2.4 years, 11 patients (32%) experienced VT recurrence. Freedom from all-cause mortality at 1-year follow-up was 94%. Conclusion Radiofrequency catheter ablation targeting the aneurysmal site is a feasible and reasonably effective management strategy for clinical VTs in patients with postinfarction LVA.

Undiagnosed dilated cardiomyopathy (DC) can be asymptomatic or present as sudden cardiac death, therefore pre-emptively identifying and treating patients may be beneficial. Screening for DC with echocardiography is expensive and labor intensive and standard electrocardiography (ECG) is insensitive and non-specific. The performance and applicability of artificial intelligence-enabled electrocardiography (AI-ECG) for detection of DC is unknown. Diagnostic performance of an AI algorithm in determining reduced left ventricular ejection fraction (LVEF) was evaluated in a cohort that comprised of DC and normal LVEF control patients. DC patients and controls with 12-lead ECGs and a reference LVEF measured by echocardiography performed within 30 and 180 days of the ECG respectively were enrolled. The model was tested for its sensitivity, specificity, negative predictive (NPV) and positive predictive values (PPV) based on the prevalence of DC at 1% and 5%. The cohort consisted of 421 DC cases (60% males, 57±15 years, LVEF 28±11%) and 16,025 controls (49% males, age 69 ±16 years, LVEF 62±5%). For detection of LVEF≤45%, the area under the curve (AUC) was 0.955 with a sensitivity of 98.8% and specificity 44.8%. The NPV and PPV were 100% and 1.8% at a DC prevalence of 1% and 99.9% and 8.6% at a prevalence of 5%, respectively. In conclusion AI-ECG demonstrated high sensitivity and negative predictive value for detection of DC and could be used as a simple and cost-effective screening tool with implications for screening first degree relatives of DC patients.

Background We have demonstrated that a neural network is able to predict a person’s age from the electrocardiogram (ECG) [artificial intelligence (AI) ECG age]. However, some discrepancies were observed between ECG-derived and chronological ages. We assessed whether the difference between AI ECG and chronological age (Age-Gap) represents biological ageing and predicts long-term outcomes. Methods and results We previously developed a convolutional neural network to predict chronological age from ECGs. In this study, we used the network to analyse standard digital 12-lead ECGs in a cohort of 25 144 subjects ≥30 years who had primary care outpatient visits from 1997 to 2003. Subjects with coronary artery disease, stroke, and atrial fibrillation were excluded. We tested whether Age-Gap was correlated with total and cardiovascular mortality. Of 25 144 subjects tested (54% females, 95% Caucasian) followed for 12.4 ± 5.3 years, the mean chronological age was 53.7 ± 11.6 years and ECG-derived age was 54.6 ± 11 years (R2 = 0.79, P < 0.0001). The mean Age-Gap was small at 0.88 ± 7.4 years. Compared to those whose ECG-derived age was within 1 standard deviation (SD) of their chronological age, patients with Age-Gap ≥1 SD had higher all-cause and cardiovascular disease (CVD) mortality. Conversely, subjects whose Age-Gap was ≤1 SD had lower all-cause and CVD mortality. Results were unchanged after adjusting for CVD risk factors and other survival influencing factors. Conclusion The difference between AI ECG and chronological age is an independent predictor of all-cause and cardiovascular mortality. Discrepancies between these possibly reflect disease independent biological ageing.

Background: Voltage mapping is critical to define substrate during ablation. In ventricular tachycardia, abnormal potentials may be targets. However, wavefront of activation could impact local signal characteristics. This may be particularly true when comparing sinus rhythm versus paced rhythms. We sought to determine how activation wavefront impacts electrogram characteristics. Methods: Patients with ischemic cardiomyopathy, ventricular tachycardia, and without fascicular or bundle branch block were included. Point by point mapping was done and at each point, one was obtained during an atrial paced rhythm and one during a right ventricular paced rhythm. Signals were adjudicated after ablation to define late potentials, fractionated potentials, and quantify local voltage. Areas of abnormal voltage (defined as

IMPORTANCE: Ventricular tachycardia (VT) is associated with high mortality in patients with cardiac sarcoidosis (CS), and medical management of CS-associated VT is limited by high failure rates. The role of catheter ablation has been investigated in small, single-center studies. OBJECTIVE: To investigate outcomes associated with VT ablation in patients with CS. DESIGN, SETTING, AND PARTICIPANTS: This cohort study from the Cardiac Sarcoidosis Consortium registry (2003-2019) included 16 tertiary referral centers in the US, Europe, and Asia. A total of 158 consecutive patients with CS and VT were included (33% female; mean [SD] age, 52 [11] years; 53% with ejection fraction [EF]

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter–electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Objective This study sought to investigate incidence of left atrial appendage (LAA) triggers of atrial fibrillation (AF) and/or organized atrial tachycardias (OAT) in patients undergoing AF ablation and to evaluate outcomes after ablation. Background Although LAA isolation is being increasingly performed during AF ablation, the true incidence of LAA triggers for AF remains unclear. Methods All patients with LAA triggers of AF and/or OAT during AF ablation from 2001 to 2017 were included. LAA triggers were defined as atrial premature depolarizations from the LAA, which initiated sustained AF and/or OAT. Results Out of 7,129 patients undergoing AF ablation over 16 years, LAA triggers were observed in 21 (0.3%) subjects (age 60 ± 9 years; 57% males; 52% persistent AF). Twenty (95%) patients were undergoing repeat ablation. The LAA was the only nonpulmonary vein trigger in 3 patients; the remaining 18 patients had both LAA and other nonpulmonary vein triggers. LAA triggers were eliminated in all patients (focal ablation in 19 patients; LAA isolation in 2 patients). Twelve months after ablation, 47.6% remained free from recurrent arrhythmia. After overall follow-up of 5.0 ± 3.6 years (median: 3.7 years; interquartile range: 1.4 to 8.9 years), 38.1% were arrhythmia-free. All 3 patients with triggers limited to the LAA remained free of AF recurrence. One patient undergoing LAA isolation developed LAA thrombus during follow-up. Conclusions The incidence of true LAA triggers is very low (0.3%). Most patients with LAA triggers have additional nonpulmonary vein triggers, and despite elimination of LAA triggers, long-term arrhythmia recurrence rates remain high. Potential risks of empiric LAA isolation during AF ablation (especially first-time AF ablation) may outweigh benefits.

Atrial arrhythmias, including atrial tachycardia and atrial flutter, are not uncommon after prior ablation. Mechanisms for arrhythmogenesis may vary and include recurrent conduction through sites of ablation, leading to recurrence of prior ablated arrhythmias and creation of new substrate. Incidence of postablation atrial arrhythmias varies across studies and may relate to the approach to ablation, including extent of ablation performed, or to extent of substrate identified at the time of prior ablation and how that relates to the lesion set. In addition, postablation atrial arrhythmias may be more common in certain types of cardiomyopathy, including hypertrophic cardiomyopathy.

Introduction Autonomic modulation has been used as a therapy to control recurrent ventricular arrhythmia (VA). This study was to explore stellate ganglion block (SGB) effect on cardiac electrophysiologic properties and evaluate the long-term outcome of cardiac sympathetic denervation (CSD) for patients with recurrent VA and structural heart disease (SHD). Materials and methods Patients who had recurrent VA due to SHD were enrolled prospectively. Electrophysiologic study and ventricular tachycardia (VT) induction were performed before and after left and right SGB. VA burden and long-term outcomes were assessed for a separate patient group who underwent left or bilateral CSD for drug-refractory VA due to SHD. Results Electrophysiologic study of nine patients showed that baseline mean (SD) corrected sinus node recovery time (cSNRT) increased from 320.4 (73.3) ms to 402.9 (114.2) ms after left and 482.4 (95.7) ms after bilateral SGB (P = .03). SGB did not significantly change P-R, QRS, and Q-T intervals and ventricular effective refractory period, nor did the inducibility of VA. Nineteen patients underwent left (n = 14) or bilateral (n = 5) CSD. CSD reduced VA burden and appropriate ICD therapies from a median (interquartile range) of 2.5 (0.4-11.6) episodes weekly to 0.1 (0.0-2.4) episodes weekly at 6-month follow-up (P = .002). Three-year freedom from orthotopic heart transplant (OHT) and death was 52.6%. New York Heart Association functional class III/IV and VT rate less than 160 beats per minute were predictors of recurrent VA, OHT, and death. Conclusion SGB increased cSNRT without changing heart rate. CSD was more beneficial for patients with mild-to-moderate heart failure and faster VA.

The accurate differentiation of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular wide complex tachycardia (SWCT) remains problematic despite numerous manually-operated electrocardiogram (ECG) interpretation methods. We sought to create a new WCT differentiation method that could be automatically implemented by computerized ECG interpretation (CEI) software.In a two-part study, we developed and validated a logistic regression model (i.e. WCT Formula) that utilizes computerized measurements and computations derived from patients' paired WCT and subsequent baseline ECGs. In Part 1, a derivation cohort of paired WCT and baseline ECGs was examined to identify independent VT predictors to be incorporated into the WCT Formula. In Part 2, a separate validation cohort of paired WCT and baseline ECGs was used to prospectively evaluate the WCT Formula's diagnostic performance.The derivation cohort was comprised of 317 paired WCT (157 VT, 160 SWCT) and baseline ECGs. A logistic regression model (i.e. WCT Formula) incorporating WCT QRS duration (ms) (p 0.001), frontal percent amplitude change (%) (p 0.001), and horizontal percent amplitude change (%) (p 0.001) yielded effective WCT differentiation (AUC of 0.96). The validation cohort consisted of 284 paired WCT (116 VT, 168 SWCT) and baseline ECGs. The WCT Formula achieved favorable accuracy (91.5%) with strong sensitivity (89.7%) and specificity (92.9%) for VT.The WCT Formula is an example of how contemporary CEI software could be used to successfully differentiate WCTs. The incorporation of similar automated methods into CEI software may improve clinicians' ability to accurately distinguish VT and SWCT.

Objectives This study hypothesized that atrial fibrillation was associated with heart failure (HF) hospitalization, and that patients who received rhythm control therapy had a lower incidence of HF hospitalization and mortality. Background Atrial fibrillation is a known risk factor for HF hospitalization and mortality in patients with acquired heart disease. Although atrial arrhythmias are common in adults with tetralogy of Fallot (TOF), data about prevalence and outcomes of therapy for atrial fibrillation are very limited. Methods The MACHD (Mayo Adult Congenital Heart Disease) database was queried for adults with repaired TOF and documented atrial fibrillation from 1990 to 2017. Primary endpoint was HF hospitalization defined as admission for volume overload (pulmonary congestion and/or peripheral edema) requiring intravenous diuretics. Secondary endpoint was the effect of rhythm control therapy on HF hospitalization and all-cause mortality. Patients were divided into rhythm control and rate control groups based on the therapy initiated at the time of arrhythmia diagnosis. Results Of 415 patients, 27 (7%) had 42 HF hospitalizations. Of these 415 patients, 88 (21%) had atrial fibrillation at age 49 ± 13 years. Atrial fibrillation was an independent risk factor for HF hospitalization (adjusted hazard ratio: 2.67; 95% confidence interval: 1.04 to 7.34; p = 0.045). The 88 patients were divided into the rhythm control group (n = 61, 69%) and the rate control group (n = 27, 31%). The rate control group had higher unadjusted annual incidence of HF hospitalization (13% vs. 3%; p = 0.001) and all-cause mortality (11% vs. 4%; p = 0.002). Conclusions Atrial fibrillation was a risk factor for HF hospitalization and mortality in TOF patients, and rhythm control therapy was protective against these adverse events.

Aims: Previous data suggest ventricular high rate episodes (VHREs) on pacemakers are frequent and not associated with overall mortality on short term follow up. We sought to determine whether VHREs are associated with mortality, device upgrade, or change in ejection fraction on long term follow up. Methods: A single center, retrospective study was performed on 542 patients with permanent pacemakers followed between 2011 and 2013. Follow-up was extended to 2017 for determination of long term outcomes. “True” VHREs were defined as episodes adjudicated to be due to non-sustained ventricular tachycardia on review of electrograms and “false” VHREs were defined as supraventricular arrhythmias or noise. Results: VHRE occurred in 202(37.2%)/542 included patients. True VHRE was detected in 148(27.3%) while 54(10%) had false VHRE. The mean age of the population was 72 ± 15 years and 46% were women. Mean follow-up was 3.3 ± 1.4 years. The baseline characteristics of the true, false and no VHRE patients were similar. There was no difference in all-cause mortality between groups (27% mortality in true VHRE, 33% in false VHRE and 29% in no VHRE). Furthermore, there was no difference between groups with regards to any device upgrade (5% any upgrades in the VHRE, 9% in false VHRE and 5% in no VHRE.) On follow up, EF declined in all groups: −4% vs −2.4% vs −3.5% for true, false and no VHRE. Conclusion: VHRE are frequently encountered on remote monitoring of pacemakers and not associated with increased risk of mortality or need for downstream device upgrade. Keywords: Non-sustained ventricular tachycardia, Pacemakers, Remote monitoring, Mortality

Background Endocardial radiofrequency ablation of epicardial ganglionic plexus (GP) for atrial fibrillation (AF) is complicated by myocardial damage. Objectives We hypothesized that an epicardial approach with a novel nitinol catheter system capable of causing irreversible electroporation (IRE) with direct current (DC) could selectively and permanently destroy GP without collateral myocardial injury. Methods Acute studies and medium-term terminal studies (mean survival, 1137 days) were performed with seven dogs. In the acute studies, DC was used to target epicardial GP within the transverse sinus, oblique sinus, vein of Marshall, and right periaortic space. Successful electroporation was defined as the presence of ablative lesions in the GP without collateral myocardial damage. A four-point integer system was used to classify histologic changes in tissue harvested from the ablation sites. Atrial effective refractory period (AERP) was measured during the acute and medium-term studies. Results For six dogs in the medium-term studies, the postablation period was uneventful without complications. Lesions were successfully created at 20 of 21 sites (95.2%) with more than minimal myocardial damage in one dog. An increase in AERP occurred in both atria during the acute studies but was maintained only in the right atrium at medium-term follow-up (5032 milliseconds). No dog had damage to the esophagus, adjacent great arteries, or pulmonary veins. Conclusions This proof-of-concept study suggests that safe, effective, and selective epicardial ablation of GP can be performed with DC by IRE with minimal collateral myocardial damage.

Background: Data regarding ventricular tachycardia (VT) or premature ventricular complex (PVC) ablation following MVS is limited.) CA can be challenging given perivalvular substrate in the setting of mitral annuloplasty or prosthetic valves. Objective: To investigate the characteristics, safety, and outcomes of radiofrequency catheter ablation (CA) in patients with prior mitral valve surgery (MVS) and ventricular arrhythmias (VA). Methods: We identified consecutive patients with prior MVS who underwent CA for VT or PVC between January 2013- December 2018. We investigated the mechanism of arrhythmia, ablation approach, peri-operative complications, and outcomes. Results: In our cohort of 31 patients (77% men, mean age 62.3±10.8 years, left ventricular ejection fraction 39.2±13.9%) with prior MVS underwent CA (16 VT; 15 PVC). Access to the left ventricle was via transseptal approach in 17 patients, and a retrograde aortic approach was used in 13 patients. A combined transseptal and retrograde aortic approach was used in one patient, and a percutaneous epicardial approach was combined with trans-septal approach in 1patient. Heterogenous scar regions were present in 94% of VT patients and scar-related reentry was the dominant mechanism of VT. Clinical VA substrates involved the peri-mitral area in 6 patients with VT and 5 patients with PVC ablation. No procedure-related complications were reported. The overall recurrence-free rate at 1-year was 72.2%; 67% in the VT group and 78% in the PVC group. No arrhythmia-related death was documented on long-term follow-up. Conclusion: CA of VAs can be performed safely and effectively in patients with MVS

Background An artificial intelligence-augmented electrocardiogram (AI-ECG) can identify left ventricular systolic dysfunction (LVSD). We examined the accuracy of AI ECG for identification of LVSD (defined as LVEF ≤40% by transthoracic echocardiogram [TTE]) in cardiac intensive care unit (CICU) patients. Method We included unique Mayo Clinic CICU patients admitted from 2007 to 2018 who underwent AI-ECG and TTE within 7 days, at least one of which was during hospitalization. Discrimination of the AI-ECG for LVSD was determined using receiver-operator characteristic curve (AUC) values. Results We included 5680 patients with a mean age of 68 ± 15 years (37% females). Acute coronary syndrome (ACS) was present in 55%. LVSD was present in 34% of patients (mean LVEF 48 ± 16%). The AI-ECG had an AUC of 0.83 (95% confidence interval 0.82–0.84) for discrimination of LVSD. Using the optimal cut-off, the AI-ECG had 73%, specificity 78%, negative predictive value 85% and overall accuracy 76% for LVSD. AUC values were higher for patients aged Conclusions The AI-ECG algorithm had very good discrimination for LVSD in this critically-ill CICU cohort with a high prevalence of LVSD. Performance was better in younger male patients and those without ACS, highlighting those CICU patients in whom screening for LVSD using AI ECG may be more effective. The AI-ECG might potentially be useful for identification of LVSD in resource-limited settings when TTE is unavailable.

Background An artificial intelligence algorithm that detects age using the 12‐lead ECG has been suggested to signal “physiologic age.” This study aimed to investigate the association of peripheral microvascular endothelial function (PMEF) as an index of vascular aging, with accelerated physiologic aging gauged by ECG‐derived artificial intelligence–estimated age. Methods and Results This study included 531 patients who underwent ECG and a noninvasive PMEF assessment using reactive hyperemia peripheral arterial tonometry. Abnormal PMEF was defined as reactive hyperemia peripheral arterial tonometry index ≤2.0. Accelerated or delayed physiologic aging was calculated by the Δ age (ECG‐derived artificial intelligence–estimated age minus chronological age), and the association between Δ age and PMEF as well as its impact on composite major adverse cardiovascular events were investigated. Δ age was higher in patients with abnormal PMEF than in patients with normal PMEF (2.3±7.8 versus 0.5±7.7 years; P =0.01). Reactive hyperemia peripheral arterial tonometry index was negatively associated with Δ age after adjustment for cardiovascular risk factors (standardized β coefficient, –0.08; P =0.048). The highest quartile of Δ age was associated with an increased risk of major adverse cardiovascular events compared with the first quartile of Δ age in patients with abnormal PMEF, even after adjustment for cardiovascular risk factors (hazard ratio, 4.72; 95% CI, 1.24–17.91; P =0.02). Conclusions Vascular aging detected by endothelial function is associated with accelerated physiologic aging, as assessed by the artificial intelligence–ECG Δ age. Patients with endothelial dysfunction and the highest quartile of accelerated physiologic aging have a marked increase in risk for cardiovascular events.

The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosis in most acute and chronic cardiovascular conditions. While transthoracic echocardiography (TTE) remains the most common diagnostic tool to screen for LVSD, it is operator-dependent, time-consuming, effort-intensive, and relatively expensive. Recent work has demonstrated the ability of an artificial intelligence-augment ECG (AI-ECG) model to accurately predict LVSD in critical intensive care unit (CICU) patients. We demonstrate that the AI-ECG algorithm can maintain its performance in these patients with and without AF despite their clinical differences. An AI-ECG algorithm can serve as a non-invasive, inexpensive, and rapid screening tool for early detection of LVSD in resource-limited settings, and potentially expedite clinical decision making and guideline-directed therapies in the acute care setting.

Sarcoidosis is a multisystem inflammatory condition with occasional cardiac involvement (CS), which may be associated with risk of venous thromboembolism (VTE). As data on VTE in CS are sparse and corticosteroid therapy has not been previously examined, we aim to determine the association between CS, corticosteroid treatment for CS, and VTE. Patients referred to our institution with concern for sarcoidosis and underwent a positron emission tomography (PET) scan were retrospectively assessed. Chi-squared and multivariate regression analyses were conducted to determine the association between a diagnosis of sarcoidosis, CS, corticosteroid use, and VTE events. Six hundred and forty nine patients were split into 3 categories: 235 with no sarcoidosis (NS), 91 with extra-cardiac sarcoidosis only (ECS), and 323 with CS (isolated CS and/or CS with extra cardiac sarcoid). Thirty nine CS, 7 ECS, and 9 NS patients developed PE while 44 CS, 3 ECS, and 18 NS patients developed DVT. On multivariate regression, neither CS nor ECS was an independent risk factor for VTE (p0.05) but corticosteroid use was independently associated with VTE (HR 3.06, p = 0.007 for PE, HR 6.21, p0.0001 for DVT). On logistic regression analysis, corticosteroid dose was found to be independently associated with both PE (p = 0.001) and DVT (p = 0.007). Optimal threshold for defining VTE risk with corticosteroid therapy was a prednisone-equivalent dose of 17.5 mg. In conclusion, contrary to previous studies, this current study found that neither sarcoidosis nor CS is an independent risk factor for VTE. Rather, corticosteroid therapy was associated with an increased risk of VTE.

Background: A non-invasive, easy-to-access marker of accelerated cardiac ageing would provide novel insights into the mechanisms and aetiology of cardiovascular disease (CVD) as well as contribute to risk stratification of those who have not had a heart or circulatory event. Our hypothesis is that differences between an ECG-predicted and chronologic age of participants (δage) would reflect accelerated or decelerated cardiovascular ageing Methods: A convolutional neural network model trained on over 700,000 ECGs from the Mayo Clinic in the U.S.A was used to predict the age of 4,542 participants in the Know Your Heart study conducted in two cities in Russia (2015-2018). Thereafter, δage was used in linear regression models to assess associations with known CVD risk factors and markers of cardiac abnormalities. Results: The biomarker δage (mean: +5.32 years) was strongly and positively associated with established risk factors for CVD: blood pressure, body mass index (BMI), total cholesterol and smoking. Additionally, δage had strong independent positive associations with markers of structural cardiac abnormalities: N-terminal pro b-type natriuretic peptide (NT-proBNP), high sensitivity cardiac troponin T (hs-cTnT) and pulse wave velocity, a valid marker of vascular ageing. Conclusion: The difference between the ECG-age obtained from a convolutional neural network and chronologic age (δage) contains information about the level of exposure of an individual to established CVD risk factors and to markers of cardiac damage in a way that is consistent with it being a biomarker of accelerated cardiovascular (vascular) ageing. Further research is needed to explore whether these associations are seen in populations with different risks of CVD events, and to better understand the underlying mechanisms involved.

Background The prognosis of left ventricular noncompaction (LVNC) remains elusive despite its recognition as a clinical entity for >30 years. We sought to identify clinical and imaging characteristics and risk factors for mortality in patients with LVNC. Methods and Results 339 adults with LVNC seen between 2000 and 2016 were identified. LVNC was defined as end‐systolic noncompacted to compacted myocardial ratio >2 (Jenni criteria) and end‐diastolic trough of trabeculation‐to‐epicardium (X):peak of trabeculation‐to‐epicardium (Y) ratio 2.3 (Petersen criteria) by magnetic resonance imaging. Median age was 47.4 years, and 46% of patients were female. Left ventricular ejection fraction P Conclusions Overall survival is reduced in patients with LVNC compared with the expected survival of age‐ and sex‐matched US population. However, survival rate in those with preserved left ventricular ejection fraction and isolated apical noncompaction was comparable with that of the general population.

In this last decade, with further maturity of catheter ablation for AF, the multicenter CABANA trial demonstrated AF ablation to be safe, more effective compared to drugs, and likely having an early role in the CHF patient. Newer energy sources for accomplishing ablation with enhanced precision and safety are in their formative stages: particle beam radiation and electroporation advancing rapidly.

Background: High-sensitivity cardiac troponin (hs-cTn) assays quantify cTn in patients at very low concentrations. Myocyte injury due to ischemia or other pathologies cause blood levels to increase, which is prognostic. A noninvasive, rapid, broadly available, home-based test to detect hs-cTn increases would facilitate risk-stratification. Since myocyte injury is associated with ECG changes, we hypothesized an artificial intelligence ECG (AI-ECG) could non-invasively predict current or impending hs-cTnT elevations. Objective: To develop an AI-ECG convolutional neural network (CNN) to detect an abnormal hs-cTnT (5 th Gen cTnT, Roche Diagnostics) concentration using a 12-lead ECG, and a single lead ECG (lead I), which would enable smartphone, home-based detection. Methods: We developed single lead and 12-lead ECG CNNs to detect a) hs-cTnT concentrations that were at or above the 6ng/L limit that can be reported b) above the 99 th percentile upper limits of >15ng/L for men and >10ng/L for women. All ECGs were recorded within one hour of the hs-cTnT measurements. We used 73,012 ECG and hs-cTnT pairs from 47,542 unique patients to train the network, 9031 ECGs from 5,811 patients for internal validation to optimize hyperparameters, and 18,276 ECG and hs-cTnT pairs from 11,904 different patients as a holdout test set to determine the area under the receiver-operator curve (AUC). Results: The mean age was 63.9±17.5 years, and 30,348 of the 59,446 patients (51%) were male. Of the 91,288 hs-cTnT pairs 73,271 (80.2%) were above 6ng/L and 50,799 (55.6%) are above the 99 th percentile. In the test set, the AUC for the detection of a hs-cTnT level higher than 6ng/L was 0.88 using the 12 lead ECG and 0.834 with the single lead. For the detection of hs-cTnT level above of 99 th percentile, the 12 lead ECG AUC was 0.853 and the single lead was 0.806. Conclusion: The AI-ECG permits detection of levels of hs-cTnT consistent with myocardial injury. This may allow a home-based, non-invasive test that would be massively scalable and could further enhance rapid-risk stratification and patient triage with potentially significant cost reductions and enable novel triage strategies at sites without hs-cTn assays.

Background: Myocardial injury results in release of cardiac troponin (cTn) into the bloodstream, readily detected by high-sensitivity cTn (hs-cTn) assays. A noninvasive, rapid, home-based test to exclude acute myocardial injury at the time of the test and for the next 7 hours would help manage patients with suspected myocardial infarction. Since myocyte injury is associated with ECG changes, we hypothesized an artificial intelligence ECG (AI-ECG) could identify absence of injury. Objective: To train and test an AI-ECG convolutional neural network (CNN) to identify patients using a single ECG who are suspected of myocardial infarction who are low risk, with hs-cTn levels below the 99 th percentile at test time and for the subsequent 7 hours. Methods: A CNN tuned to identify the absence of a hs-cTnT (5 th Gen cTnT Roche Diagnostics) >15ng/L for men and >10ng/L for women was developed. All ECGs were recorded within one hour of the hs-cTnT assay. We used 73,012 ECGs and hs-cTnT pairs from 47,542 unique patients to train the network, 9031 ECGs from 5,811 patients for internal validation to optimize hyperparameters, and 11,904 ECGs with 21,191 hs-cTnT measurements up to 7 hours after the ECG, from 11,904 different patients as a holdout test set. Results: The mean age was 63.9±17.5 years, and 30,348 of the 59,446 patients (51%) were male. 5,852 patients (49.1%) had no elevation of hs-cTnT and 6,052 (50.9%) had an hs-cTnT above the 99 th percentile at baseline or within 7 hours of the test. Of the 11,904 patients in the test set, using a sensitive threshold, the 12 lead AI ECG identified 1037 patients (8.7%) likely to have a low risk for subsequent hs-cTnT increases > 99 th % (AUC 0.86), and the single lead ECG identified 685 patients. Of the 1037 low risk pts, 59 had an hs-cTnT > 99 th percentile within 7 hours. The mean maximum hs-cTnT among the 59 low-risk patients was 53 ng/L ± 92 vs 184 ng/L ± 1474 in the others. None of these low risk patients died within 14 days of the test. Conclusion: Use of the AI ECG to identify patients without cardiac injury at the time of the test and for 7 subsequent hours is feasible. This may permit rapid, point of care, home-based, bloodless, painless testing to exclude cardiac injury, facilitating care and management of patients with suspected ischemia.

Background Analysis of a 12-lead electrocardiogram (ECG) in sinus rhythm by artificial intelligence (AI) has demonstrated to identify the risk of underlying paroxysmal atrial fibrillation (AF) with reasonable accuracy in the overall population. Purpose This study investigates whether AI based ECG analysis can predict new AF development in patients with heart failure and preserved ejection fraction (HFpEF) without previous AF history, as well as predict AF burden in patients with AF history. Methods This retrospective cohort study includes 424 patients with HFpEF, consecutively admitted to receive treatment with intravenous diuretics for congestion. A previously validated AI algorithm that provides an AF risk score based on ECG analysis was applied in all subjects. Patients were stratified according to AF history: (1) no history; (2) paroxysmal AF; (3) persistent AF; or (4) permanent AF. In patients without AF history, the impact of AI-predicted AF risk on new AF development was assessed. In patients with previous AF episodes, the relationship between AI-predicted AF risk and AF burden as well as underlying echocardiography substrate was evaluated. Results Eighty-three patients had paroxysmal AF (19.5%), 48 persistent AF (11%), and 121 permanent AF (28.5%). AF patients were older, with lower body mass index and higher heart rate. Lower systolic blood pressure, larger left atrial volume index (LAVI), worse diastolic function, more tricuspid valve regurgitation, and more need for pacing were observed with increasing AF severity. In 172 patients without AF history followed for 979±875 days, 61 developed AF (35%) after a median time of 2,118 days. AI-predicted AF risk was associated with new-onset AF after adjustments for age, gender, systolic blood pressure, body mass index and LAVI [HR (95% CI) = 1.15 (1.04–1.28); P-value=0.007; figure]. Only 5/61 patients who developed AF during follow-up (8.2%) were anticoagulated at baseline. In patients with previous AF, the AI-predicted risk score increased significantly with AF burden (46±25% in paroxysmal AF, 59±22% in persistent AF, and 69±17% in permanent AF; P-value Conclusions An AI-predicted AF risk score based on ECG analysis was associated with AF burden in HFpEF patients and did independently predict new-onset AF in those without previous history. Time to new onset of atrial fibrillation Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Belgian American Educational Foundation (B.A.E.F.); Special Research Fund (BOF) of Hasselt University (Hasselt, Belgium)

Background Diastolic reserve decreases with aging. A recently developed artificial intelligence (AI) algorithm can predict age based on 12-lead electrocardiogram (ECG) analysis. Purpose This study aims to use a validated AI algorithm to assess cardiac senescence and investigate the impact of obesity on cardiac aging in heart failure with preserved ejection fraction (HFpEF). Methods This retrospective cohort study includes 403 patients with HFpEF, admitted for treatment with intravenous diuretics. ECG age was assessed by a convolutional neural network as previously validated. Patients were stratified according to the presence of obesity (body mass index >30 kg/m2) and ECG age was compared between groups. The relationship between ECG versus calendar age and structural/functional alterations on echocardiography, as well as the risk of atrial fibrillation (AF) development, was evaluated. Results In 253 (63%) obese patients with HFpEF, calendar age was 8 years younger compared with their non-obese counterparts, but ECG age was only 3 years younger. ECG minus calendar age was higher in obese patients (P-value Conclusions Obesity accelerates cardiac senescence in HFpEF as reflected by more pronounced diastolic dysfunction and a higher AF risk, which was identified from ECG analysis by a validated AI algorithm. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Belgian American Educational Foundation (B.A.E.F.); Special Research Fund (BOF) of Hasselt University (Hasselt, Belgium).

Background Artificial Intelligence (AI) algorithms enabled the detection of patients with paroxysmal atrial fibrillation (PAF) from a single normal sinus rhythm (NSR) ECG. Coronary microvascular dysfunction (CMD) is a precursor for coronary artery disease, which is a known risk factor for AF. Purpose The aim of this study is to examine the probability of PAF, according to AI-enabled algorithm estimation, in patients with CMD. Methods 1858 patients without persistent atrial fibrillation with signs and/or symptoms of ischemia and with non-obstructive CAD (9%; which is a pre-set cut-off found to have the highest accuracy of identifying patients with PAF (Area Under the Curve = 0.87). Results Mean age for patients was 51.2±12.4 and 66.3% were females. 835 (45%) were in G1, 39 (2%) in G2, 911 (49%) in G3, and 73 (4%) in G4. Compared to G1 and G2, G3 and G4 were older, had more diabetes and higher smoking rates (p Conclusion Patients with combined CMD have a significantly higher probability of having PAF based on an AI-enabled algorithm. Further research is warranted to know if patients with CMD would benefit from formal AF screening at the time of diagnosis. Funding Acknowledgement Type of funding source: None

Background An Artificial intelligence (AI)-enabled algorithm can provide an age estimate from a single standard resting ECG. The gap between AI-estimated age (ECG age) and chronological age (Age-Gap) has been associated with total and cardiovascular mortality. We hypothesized that coronary endothelial dysfunction (CED), an early feature of coronary atherosclerosis, is associated with physiological aging, as measured by ECG age. Purpose The aim of this study is to investigate the association of CED, a potential index of cardiac aging, and AI-estimated physiological aging. Methods 1902 patients with signs and/or symptoms of ischemia and with non-obstructive coronary artery disease ( Results Average chronological age was 50.9±12.5, ECG age was 54.1±11.6, 1261 (66%) were females. Compared to CED−, the CED+ group had more males and hyperlipidaemia (p Conclusion Abnormal coronary endothelial function is associated with an increased AI-estimated age which could indicate a higher physiological age. Funding Acknowledgement Type of funding source: None

Background We have demonstrated that artificial intelligence interpretation of ECGs (AI-ECG) can estimate an individual's physiologic age and that the gap between AI-ECG and chronologic age (Age-Gap) is associated with increased mortality. We hypothesized that Age-Gap would predict long-term atherosclerotic cardiovascular disease (ASCVD) and that Age-Gap would refine the ACC/AHA Pooled Cohort Equations' (PCE) predictive abilities. Methods Using the Rochester Epidemiology Project (REP) we evaluated a community-based cohort of consecutive patients seeking primary care between 1998–2000 and followed through March 2016. Inclusion criteria were age 40–79 and complete data to calculate PCE. We excluded those with known ASCVD, AF, HF or an event within 30 days of baseline.A neural network, trained, validated, and tested in an independent cohort of ∼ 500,000 independent patients, using 10-second digital samples of raw, 12 lead ECGs. PCE was categorized as low Results We included 24,793 patients (54% women, 95% Caucasian) with mean follow up of 12.6±5.1 years. 2,366 (9.5%) developed ASCVD events and 3,401 (13.7%) the expanded ASCVD. Mean chronologic age was 53.6±11.6 years and the AI-ECG age was 54.5±10.9 years, R2=0.7865, p20%) age and sex adjusted HR 6.90, 95% CI 1.98–24.08, p-value=0.0006, when comparing those older to younger by ECG respectively (Figure 1B). Conclusion The difference between physiologic AI-ECG age and chronologic age is associated with long-term ASCVD, and enhances current risk calculators (PCE) ability to identify high and low risk individuals. This may help identify individuals who should or should not be treated with newer, expensive risk-reducing therapies. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Mayo Clinic

Background Histologic evidence is required for a definitive diagnosis of cardiac sarcoidosis (CS) by published guidelines; however, the sporadic nature of the disease may produce false negative biopsy results, causing CS to be underdiagnosed. We sought to establish a clinical category of CS absent histologic findings. Methods Patients evaluated for CS were stratified into 3 groups: probable CS and definite CS based on Heart Rhythm Society (HRS) criteria and presumed CS, ie, patients without any histologic evidence of sarcoidosis, but with unexplained high-grade atrioventricular block or ventricular arrhythmia and findings suggestive of CS on either cardiac magnetic resonance imaging or positron emission tomography. The primary end point was hospitalization-free and overall survival at 10 years. Results A total of 383 patients were included in the study: 59, definite CS; 223, probable CS; and 101, presumed CS (62, isolated CS and 39, systemic CS). Compared with patients meeting HRS criteria for CS, patients with presumed CS had lower odds of New York Heart Association class III or IV symptoms (odds ratio [OR], 0.44 [95% CI, 0.23–0.83]; P = .01) but greater odds of previous ventricular tachycardia (OR, 2.4 [95% CI, 1.4–4.0]; P = .001) or history of resuscitated sudden cardiac arrest (OR, 2.9 [95% CI, 1.0–8.6]; P = .05). Hospitalization-free and overall survival were similar among groups (P = .51 and P = .71, respectively). Conclusions Clinical categorization of patients with presumed CS identified a high-risk cohort comparable to patients with histologic evidence of disease, although caution should be exercised in reaching this diagnosis without paying due diligence to the differential diagnosis.

Objective To validate an artificial intelligence–augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort. Methods We identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction ≤40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment. Results For detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004). Conclusion Artificial intelligence–augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD.

Background Right bundle‐branch block (RBBB) occurs in 0.2% to 1.3% of people and is considered a benign finding. However, some studies have suggested increased risk of cardiovascular morbidity and mortality. We sought to evaluate risk attributable to incidental RBBB in patients without prior diagnosis of cardiovascular disease (CVD). Methods and Results We reviewed the Mayo Clinic Integrated Stress Center database for exercise stress tests performed from 1993 to 2010. Patients with no known CVD—defined as absence of coronary disease, structural heart disease, heart failure, or cerebrovascular disease—were selected. Only Minnesota residents were included, all of whom had full mortality and outcomes data. There were 22 806 patients without CVD identified; 220 of whom (0.96%) had RBBB, followed for 6 to 23 years (mean 12.4±5.1). There were 8256 women (36.2%), mean age was 52±11 years; and 1837 deaths (8.05%), including 645 cardiovascular‐related deaths (2.83%), occurred over follow‐up. RBBB was predictive of all‐cause (hazard ratio [HR], 1.5; 95% CI, 1.1–2.0; P =0.0058) and cardiovascular‐related mortality (HR,1.7; 95% CI, 1.1–2.8; P =0.0178) after adjusting for age, sex, diabetes mellitus, hypertension, obesity, current and past history of smoking, and use of a heart rate‐lowering drug. Patients with RBBB exhibited more hypertension (34.1% versus 23.7%, P P P P Conclusions Patients with RBBB without CVD have increased risk of all‐cause mortality, cardiovascular‐related mortality, and lower exercise tolerance. These data suggest RBBB may be a marker of early CVD and merit further prospective evaluation.

Aims An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ventricular systolic dysfunction (LVSD). We sought to determine whether this AI-ECG algorithm could stratify mortality risk in cardiac intensive care unit (CICU) patients, independent of the presence of LVSD by transthoracic echocardiography (TTE). Methods and results We included 11 266 unique Mayo Clinic CICU patients admitted from 2007 to 2018 who underwent AI-ECG after CICU admission. Left ventricular ejection fraction (LVEF) data were extracted for patients with a TTE during hospitalization. Hospital mortality was analysed using multivariable logistic regression. Mean age was 68 ± 15 years, including 37% females. Higher AI-ECG probability of LVSD remained associated with higher hospital mortality [adjusted odds ratio (OR) 1.05 per 0.1 higher, 95% confidence interval (CI) 1.02–1.08, P = 0.003] after adjustment for LVEF, which itself was inversely related with the risk of hospital mortality (adjusted OR 0.96 per 5% higher, 95% CI 0.93–0.99, P = 0.02). Patients with available LVEF data (n = 8242) were divided based on the presence of predicted (by AI-ECG) vs. observed (by TTE) LVSD (defined as LVEF ≤ 35%), using TTE as the gold standard. A stepwise increase in hospital mortality was observed for patients with a true negative, false positive, false negative, and true positive AI-ECG. Conclusion The AI-ECG prediction of LVSD is associated with hospital mortality in CICU patients, affording risk stratification in addition to that provided by echocardiographic LVEF. Our results emphasize the prognostic value of electrocardiographic patterns reflecting underlying myocardial disease that are recognized by the AI-ECG.

Introduction Catheter ablation (CA) has emerged as the preferred modality of treatment for many cardiac arrhythmias. Anatomical sites of ablation are often located in close proximity to coronary arteries. However, the incidence of CA-related coronary injury has not been well studied. We sought to systematically evaluate all cases of CA-related coronary injuries. Methods and results A PubMed search was conducted from inception until May 1, 2017 using the keywords "coronary artery" and "ablation." We identified 2817 published articles of which 43 articles met our inclusion criteria representing 61 cases of coronary artery injury attributed to CA procedures from 1992 to 2017. Posteroseptal accessory pathway ablation was associated with the highest incidence of coronary injury (35.6% of cases), followed by cavotricuspid isthmus-dependent flutter (19.3%). The right coronary artery was the site of injury in over two-thirds of all reported cases. Coronary injury was detected intraprocedurally in about half of the cases (43.1%), whereas it was a delayed presentation in the other half. Coronary intervention was performed in a third of all cases (32.7%). There were a total of three deaths attributed to coronary artery injury. Conclusions Most (91.8%) coronary injuries are a result of anatomic proximity to the site of ablation. Awareness of the relation between coronary artery course and anatomical site of ablation could prevent myocardial damage and improve procedural safety.

Placement of an epicardial pacemaker system is often preferred over an endocardial system in patients who have undergone a Fontan operation, but data are limited on how these two systems perform over time in patients with Fontan palliation. We performed a retrospective review of adults with Fontan palliation who had pacemaker implantation and interrogation data at Mayo Clinic from 1994 to 2014. Lead parameters, pacing mode, and polarity were collected at the earliest device interrogation report. Clinic notes and device interrogation reports were reviewed at implantation, 6 months, and yearly after implantation to determine impedance, capture threshold (CT), and energy threshold (ET). There were 87 patients with 168 leads in the study cohort. The mean follow-up time was 7.7 years (6 months-19 years). There were 143 epicardial leads (57 atrial and 86 ventricular) and 25 endocardial leads (20 atrial and 5 ventricular). There was no difference in the baseline lead parameters between epicardial and endocardial leads for impedance (610 ± 259 versus 583 ± 156 Ω, p = 0.93), CT (2.0 ± 1.3 versus 1.8 ± 1.3 V, p = 0.28), or ET (7.1 ± 12.5 versus 6.8 ± 18.1 µJ, p = 0.29). Compared to endocardial leads, ventricular epicardial leads were associated with temporal decrease in impedance and increase in ET. Regarding clinical outcomes, epicardial leads had higher rates of failure but similar generator longevity in comparison to endocardial leads. Ventricular epicardial leads were associated with temporal decrease in impedance and increase in ET. Epicardial leads had a higher rate of failure but similar generator longevity compared to endocardial leads.

In patients with unexplained cardiomyopathy, electroanatomical mapping can identify abnormal tissue to target during electrophysiology-guided endomyocardial biopsy (EP-guided EMB). The objective of this study is to determine whether catheter ablation performed in the same setting as EP-guided EMB increases procedural risk. Sixty-seven patients (mean age 54.4 ± 13.8, 57% male) undergoing EP-guided EMB were included. Radiofrequency catheter ablation was performed in 17 patients (25%) for ventricular arrhythmias and in 2 (3%) for typical atrial flutter. Femoral arterial access was obtained in 90% ablation patients and 40% biopsy-only patients; vascular access complications were more common in the ablation group than in the EMB-only group (p = 0.02). There were no significant differences in rate of tricuspid regurgitation, thromboembolism, or pericardial effusion, whether procedural anticoagulation was used. In conclusion, catheter ablation and procedural anticoagulation can be combined with EP-guided EMB with an increased risk of vascular access complications, but no significant increase in intracardiac complications.

It is unknown whether systemic right ventricular (SRV) dysfunction confers increased risk for sudden death in congenitally corrected transposition of the great arteries (ccTGA). We sought to define risk of ventricular arrhythmias and sudden death attributable to systemic right ventricular dysfunction in ccTGA.The study cohort is comprised of adult patients with a diagnosis of ccTGA. Clinical information and clinical outcomes including ICD therapy, incidence of VT/VF, and cause of death were reviewed.129 patients with ccTGA were followed for 7.2 ± 3.4 years. Mean SRV ejection fraction (SRVEF) was 39% (n = 56 with an EF35%). Significant documented arrhythmia (sustained VT requiring defibrillation or cardiac arrest due to VT/VF) occurred in 13/56 patients (23%) with SRV EF35% compared with 2/73 (3%) with SRV EF35% (p 0.001). There was no significant difference in age at death, death from documented arrhythmia, or death from all cause between patients with SRV EF35% and35%. However, risk of sudden death was higher in patients with SRV EF35% (16% vs 1%, p = 0.002). The combined clinical endpoint of ICD therapy, clinically significant VT/VF, and sudden death was significantly higher in patients with SRV EF35% than in patients with SRV EF35%, independent of the presence of LV EF35% (p 0.001).Dysfunction of the systemic RV in ccTGA increases the risk of sudden death and clinically significant ventricular tachyarrhythmias. Further study is needed to determine if ventricular tachyarrhythmias comprise the primary cause of sudden death in these patients and if ICDs offer any significant mortality benefit.

Background: Recognition of rates and causes of hard, patient-centered outcomes of death and cerebrovascular events (CVEs) after heart rhythm disorder management (HRDM) procedures is an essential step for the development of quality improvement programs in electrophysiology laboratories. Our primary aim was to assess and characterize death and CVEs (stroke or transient ischemic attack) after HRDM procedures over a 17-year period. Methods: We performed a retrospective cohort study of all patients undergoing HRDM procedures between January 2000 and November 2016 at the Mayo Clinic. Patients from all 3 tertiary academic centers (Rochester, Phoenix, and Jacksonville) were included in the study. All in-hospital deaths and CVEs after HRDM procedures were identified and were further characterized as directly or indirectly related to the HRDM procedure. Subgroup analysis of death and CVE rates was performed for ablation, device implantation, electrophysiology study, lead extraction, and defibrillation threshold testing procedures. Results: A total of 48 913 patients (age, 65.7±6.6 years; 64% male) who underwent a total of 62 065 HRDM procedures were included in the study. The overall mortality and CVE rates in the cohort were 0.36% (95% confidence interval [CI], 0.31–0.42) and 0.12% (95% CI, 0.09–0.16), respectively. Patients undergoing lead extraction had the highest overall mortality rate at 1.9% (95% CI, 1.34–2.61) and CVE rate at 0.62% (95% CI, 0.32–1.07). Among patients undergoing HRDM procedures, 48% of deaths directly related to the HDRM procedure were among patients undergoing device implantation procedures. Overall, cardiac tamponade was the most frequent direct cause of death (40%), and infection was the most common indirect cause of death (29%). The overall 30-day mortality rate was 0.76%, with the highest being in lead extraction procedures (3.08%), followed by device implantation procedures (0.94%). Conclusions: Half of the deaths directly related to an HRDM procedure were among the patients undergoing device implantation procedures, with cardiac tamponade being the most common cause of death. This highlights the importance of the development of protocols for the quick identification and management of cardiac tamponade even in procedures typically believed to be lower risk such as device implantation.

Background Cardiac pacing can be challenging after a Fontan operation, and limited data exist regarding pacing in adult Fontan patients. The objectives of our study were to determine risk factors for pacing and occurrence of device-related complications (DRCs) and pacemaker reinterventions. Methods We performed a retrospective review of Fontan patients from 1994 through 2014. We defined DRCs as lead failure, lead recall, cardiac perforation, lead thrombus/vegetation, or device-related infection, and cardiovascular adverse events (CAEs) as venous thrombosis, stroke, death, or heart transplant. Pacemaker reintervention was defined as lead failure or recall. Results Of 439 patients, 166 (38%) had pacemakers implanted (79 during childhood; 87, adulthood); 114 patients (69%) received epicardial leads initially, and 52 (31%), endocardial leads. Pacing was initially atrial in 52 patients (31%); ventricular, 30 (18%); or dual chamber, 84 (51%). There were 37 reinterventions (1.9% per year) and 48 DRCs (2.4% per year). Pacemaker implantation during childhood was a risk factor for DRCs (hazard ratio, 2.01 [CI, 1.22-5.63]; P = .03). There were 70 CAEs (venous thrombosis, 5; stroke, 11; transplant, 8; and death, 46), yielding a rate of 3.5% per year. DRCs, CAEs, and reintervention rates were comparable for patients with epicardial or endocardial leads. Conclusions More than one-third of adult Fontan patients referred to Mayo Clinic had pacemaker implantation. Epicardial leads were associated with high rate of pacemaker reinterventions but similar DRC rates in comparison to endocardial leads.

The optimal management strategy for atrial tachyarrhythmia in the Fontan population is unknown.Retrospective review of 264 adult Fontan patients with atrial tachyarrhythmia evaluating 3 clinically adopted scenarios: antiarrhythmic drug (AAD) therapy, catheter ablation (CA), and Fontan conversion (FC). These patients were followed up at Mayo Clinic from 1994 to 2014. The study objective was to compare freedom from atrial tachyarrhythmia recurrence (AR) and occurrence of composite adverse events (stroke, heart failure hospitalization, death, or heart transplant) between treatment groups.The age of atrial tachyarrhythmia onset was 25 ± 4 years, time from Fontan operation was 13 ± 6 years, follow-up was 74 ± 18 months, atriopulmonary Fontan was 215 (81%), and atrial flutter/intra-atrial reentry tachycardia was 173 (65%). In those managed with AAD (n = 110), freedom from AR was 7% at 60 months. Catheter ablation (n = 31) was associated with an acute procedural success of 94%, and freedom from AR was 41% at 60 months. Fontan conversion (n = 33) resulted in a perioperative mortality of 3%, and freedom from AR was 51% at 60 months. Fontan conversion and CA were similar with regard to AR (P = .14) and significantly better compared with AAD (P.0001). Adverse events were found to occur more frequently in the patients with AR (P.0001) and the patients treated with AAD only (P.0001).Catheter ablation and FC operations are associated with less recurrence of atrial tachyarrhythmia compared with AAD. Atrial tachyarrhythmias are more likely to recur in patients with a longer history of the arrhythmia and are associated with more adverse events. Early referral to a specialty center for these interventions should be considered.

Introduction Obesity and aging are prominent risk factors for HFpEF. Obese versus non-obese patients are typically younger, but the effects of obesity on premature cardiac senescence remain insufficiently explained. Recent data suggest that cardiac senescence might be estimated from a 12-lead ECG by artificial intelligence (AI). Hypothesis Obese versus non-obese patients with HFpEF have true premature adverse cardiac remodeling, associated with diastolic dysfunction and a higher risk of atrial fibrillation (AF), which is reflected by faster ECG aging. Methods This retrospective cohort study of 408 patients with HFpEF, hospitalized for decompensation and treatment with intravenous loop diuretics, assessed ECG age upon admission with a previously validated AI algorithm. Differences in the relationship between chronological versus ECG age and underlying cardiac remodeling and function on echocardiography, as well AF risk, were evaluated and compared between obese versus non-obese patients. Age- and gender normalized echocardiography parameters were calculated according to regression equations determined from the PAVD study in Olmsted County (MN, US) Results Obese (n = 255) versus non-obese (n = 153) HFpEF patients were on average 9 years younger. ECG minus chronological age as surrogate for premature cardiac senescence was higher in the obese (P-value Conclusions Obesity is associated with older ECG compared to chronological age in HFpEF, which probably reflects premature cardiac senescence given its association with structural remodeling, more pronounced diastolic dysfunction, and a higher AF risk.

IntroductionThe application of brief high voltage electrical pulses to tissue can lead to an irreversible or reversible electroporation effect in a cell-specific manner. In the management of ventricular arrhythmias, the ability to target different tissue types, specifically cardiac conduction tissue (His-Purkinje System) vs. cardiac myocardium would be advantageous. We hypothesize that pulsed electric fields (PEFs) can be applied safely to the beating heart through a catheter-based approach, and we tested whether the superficial Purkinje cells can be targeted with PEFs without injury to underlying myocardial tissue.MethodsIn an acute (n = 5) and chronic canine model (n = 6), detailed electroanatomical mapping of the left ventricle identified electrical signals from myocardial and overlying Purkinje tissue. Electroporation was effected via percutaneous catheter-based Intracardiac bipolar current delivery in the anesthetized animal. Repeat Intracardiac electrical mapping of the heart was performed at acute and chronic time points; followed by histological analysis to assess effects.ResultsPEF demonstrated an acute dose-dependent functional effect on Purkinje, with titration of pulse duration and/or voltage associated with successful acute Purkinje damage. Electrical conduction in the insulated bundle of His (n = 2) and anterior fascicle bundle (n = 2), was not affected. At 30 days repeat cardiac mapping demonstrated resilient, normal electrical conduction throughout the targeted area with no significant change in myocardial amplitude (pre 5.9 ± 1.8 mV, 30 days 5.4 ± 1.2 mV, p = 0.92). Histopathological analysis confirmed acute Purkinje fiber targeting, with chronic studies showing normal Purkinje fibers, with minimal subendocardial myocardial fibrosis.ConclusionPEF provides a novel, safe method for non-thermal acute modulation of the Purkinje fibers without significant injury to the underlying myocardium. Future optimization of this energy delivery is required to optimize conditions so that selective electroporation can be utilized in humans the treatment of cardiac disease.

Introduction The ablation of outflow tract premature ventricular contractions (PVCs) is generally safe and effective. In some patients, successful ablation sites may not correlate with the earliest activation. We sought to evaluate mechanistic and anatomic relevance of the region below the left sinus of Valsalva in variable morphology outflow tract ventricular arrhythmias. Methods PVC cases where ablation was in the region inferior to the left sinus of Valsalva were identified. Procedural and demographic information and long-term outcomes were obtained. Cadaver dissections to evaluate regional anatomy were done as well. Results A total of 51 cases were included (age 53 ± 10; 37 [73%] males). Ablation was done for high PVC burden (>20%; mean 27% ± 8%) and presence of symptoms (73%) or ejection fraction less than 50% (78%). QRS morphology included either R wave (8; 16%), Rs (9; 18%), or rS (67%) in lead I, no precordial transition (40; 78%), V2 transition, (7; 14%), or V3 transition (4; 8%). In 31 (61%), the site just below the left coronary cusp was the earliest site, while the remainder had another site earlier. Ablation was acutely successful in 50 of 51 (98%). After 3 months, success was noted in 48 of 51 (94%). In two patients, repeat ablation in the same region resulted in durable suppression. Conclusion The cases presented emphasize the importance of a region centered below the left sinus of Valsalva, where multivariable morphology QRS may be successfully ablated. Consideration of mapping and ablation even when signals are late in this region may be warranted in previously failed ablation attempts or first-line evaluation.

Ventricular tachycardia ablation is a mainstay of treatment for patients with structural heart disease and ventricular arrhythmias but is often compromised by hemodynamic collapse. The decision on when, whether, and what to use for hemodynamic support depends on the clinical situation, the patient’s comorbidities, and the availability of appropriate equipment and staffing. Depending on the clinical situation, a specific circulatory support device might be optimal, as certain ones may impact approach to the procedure. While there is a paucity of data supporting routine use of circulatory support during cardiac ablation, in specific cases there may be utility due to the patient’s baseline status. Other considerations include the use of hemodynamic support during surgical ablation and in the peri-ablation period. This chapter reviews the indications for use, a structured clinical decision-making approach, and the different types of hemodynamic support available for use during ventricular arrhythmia ablation.

Background Hypertrophic cardiomyopathy (HCM) is an uncommon but important cause of sudden cardiac death. Objectives This study sought to develop an artificial intelligence approach for the detection of HCM based on 12-lead electrocardiography (ECG). Methods A convolutional neural network (CNN) was trained and validated using digital 12-lead ECG from 2,448 patients with a verified HCM diagnosis and 51,153 non-HCM age- and sex-matched control subjects. The ability of the CNN to detect HCM was then tested on a different dataset of 612 HCM and 12,788 control subjects. Results In the combined datasets, mean age was 54.8 ± 15.9 years for the HCM group and 57.5 ± 15.5 years for the control group. After training and validation, the area under the curve (AUC) of the CNN in the validation dataset was 0.95 (95% confidence interval [CI]: 0.94 to 0.97) at the optimal probability threshold of 11% for having HCM. When applying this probability threshold to the testing dataset, the CNN’s AUC was 0.96 (95% CI: 0.95 to 0.96) with sensitivity 87% and specificity 90%. In subgroup analyses, the AUC was 0.95 (95% CI: 0.94 to 0.97) among patients with left ventricular hypertrophy by ECG criteria and 0.95 (95% CI: 0.90 to 1.00) among patients with a normal ECG. The model performed particularly well in younger patients (sensitivity 95%, specificity 92%). In patients with HCM with and without sarcomeric mutations, the model-derived median probabilities for having HCM were 97% and 96%, respectively. Conclusions ECG-based detection of HCM by an artificial intelligence algorithm can be achieved with high diagnostic performance, particularly in younger patients. This model requires further refinement and external validation, but it may hold promise for HCM screening.

Background Cardiac sarcoidosis (CS) is an infiltrative inflammatory condition defined by infiltration of noncaseating granulomas into the heart. Based on the location of sarcoid lesion involvement, patients can present with symptoms of congestive heart failure, arrhythmias, and even sudden cardiac death. Purpose Diagnosis of CS has been somewhat challenging, with the Heart Rhythm Society (HRS) and Japanese Ministry of Health and Welfare (JMHW) being the 2 widely accepted diagnostic guidelines. Endomyocardial biopsy is the gold standard to prove definite CS but has a low sensitivity. Imaging studies have been helpful as non-invasive methods to diagnose probable CS but these can be logistically difficult and expensive. Thus, investigating for laboratory biomarkers that can act as both diagnostic and prognostic can be crucial in how we diagnose and manage CS in the future. Methods Patients meeting HRS for CS were evaluated at a single institution (n=217). Biomarkers of interest included angiotensin-converting enzyme (ACE), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), N-terminal pro B-type natriuretic peptide (NT-proBNP), troponin-T, 1,25 dihydroxyvitamin D (1,25-OHVit-D), and creatinine. Biomarkers were stratified by clinical variables of interest and their association with prognosis was examined. The primary endpoint was LVAD implantation, transplantation, or death. Results Mean values on presentation were: ACE 32.9±28, ESR 12±13, CRP 7.4±19, NT-proBNP 1630±2923, Troponin-T 0.03±0.1, 1,25-OHVit-D 55.5±20, and creatinine 1.12±0.3. None of the biomarkers differed by sex, definite or probable CS, or a history of immunosuppression. ACE levels were associated with the presence of cardiac fibrosis on cardiac MRI (mean difference 14.7, p=0.032). Troponin-T (p=0.006; HR 1.06 per 0.01 ng/mL), NT-proBNP (p=0.0003; HR 1.31 per 1,000 pg/mL), and creatinine (p=0.01; HR 4.02 per mg/dL) were each associated with the primary endpoint (52/217 patients). Biomarkers associated with long term outcomes in patients with cardiac sarcoidosis Biomarker Hazard ratio P value Troponin-T 1.06 (1.02–1.11)* 0.006 NT-pro BNP 1.31 (1.15–1.48)** 0.0003 Creatinine 4.02 (1.41–9.94)*** 0.01 *Per 0.01 ng/mL change; 99th percentile upper reference limit Conclusion Troponin-T, NT-proBNP, and creatinine at presentation predict outcomes in patients with CS. Further investigation on the utility of biomarkers for assessment of disease activity and treatment response is warranted.