Effects of Glucagon-Like Peptide-1 Receptor Agonists on Atrial Fibrillation Recurrence After Catheter Ablation.

BACKGROUND: Relationship between glucagon-like peptide-1 receptor agonist (GLP-1 RA) use prior to atrial fibrillation (AF) ablation and subsequent AF recurrence is not well-understood. OBJECTIVES: This study investigated the effects of GLP-1 RA use within 1 year before ablation and its association with AF recurrence and associated outcomes. METHODS: The TriNetX research database was used to identify patients aged ≥18 years undergoing AF ablation (2014-2023). Patients were categorized into 2 groups, and propensity score matching (1:1) between preablation GLP-1 RA users and nonusers was performed based on demographics, comorbidities, body mass index, laboratory tests, AF subtype, and medications. Primary outcome was composite of cardioversion, new antiarrhythmic drug therapy, or repeat AF ablation after a 3-month blanking period following the index ablation. Additional outcomes included ischemic stroke, all-cause hospitalization, and mortality during 12-month follow-up period. RESULTS: After 1:1 propensity score matching, the study cohort comprised 1,625 GLP-1 RA users and 1,625 matched GLP-1 RA nonusers. Preablation GLP-1 RA therapy was not associated with a lower risk of cardioversion, new AAD therapy, and repeat AF ablation after the index procedure (HR: 1.04 [95% CI: 0.92-1.19]; log-rank P = 0.51). Furthermore, the risk of ischemic stroke, all-cause hospitalization, and mortality during the 12-month follow-up period did not differ between the 2 groups. CONCLUSIONS: These findings suggest that preprocedural use of GLP-1 RAs is not associated with a reduced risk of AF recurrence or associated adverse outcomes following ablation, and underscore the need for future research to determine whether these agents improve outcome in AF patients.

Association of pre-left ventricular assist device defibrillator shocks for ventricular arrhythmia with clinical outcomes after left ventricular assist device implantation.

Background: Implantable cardioverter-defibrillation (ICD) shocks after left ventricular assist device therapy (LVAD) are associated with adverse clinical outcomes. Little is known about the association of pre-LVAD ICD shocks on post-LVAD clinical outcomes and whether LVAD therapy affects the prevalence of ICD shocks. Objectives: The purpose of this study was to determine whether pre-LVAD ICD shocks are associated with adverse clinical outcomes post-LVAD and to compare the prevalence of ICD shocks before and after LVAD therapy. Methods: Patients 18 years or older with continuous-flow LVADs and ICDs were retrospectively identified within the University of Pittsburgh Medical Center system from 2006-2020. We analyzed the association between appropriate ICD shocks within 1 year pre-LVAD with a primary composite outcome of death, stroke, and pump thrombosis and secondary outcomes of post-LVAD ICD shocks and ICD shock hospitalizations. Results: Among 309 individuals, average age was 57 ± 12 years, 87% were male, 80% had ischemic cardiomyopathy, and 42% were bridge to transplantation. Seventy-one patients (23%) experienced pre-LVAD shocks, and 69 (22%) experienced post-LVAD shocks. The overall prevalence of shocks pre-LVAD and post-LVAD were not different. Pre-LVAD ICD shocks were not associated with the composite outcome. Pre-LVAD ICD shocks were found to predict post-LVAD shocks (hazard ratio [HR] 5.7; 95% confidence interval [CI] 3.42-9.48; P <.0001) and hospitalizations related to ICD shocks from ventricular arrhythmia (HR 10.34; 95% CI 4.1-25.7; P <.0001). Conclusion: Pre-LVAD ICD shocks predicted post-LVAD ICD shocks and hospitalizations but were not associated with the composite outcome of death, pump thrombosis, or stroke at 1 year. The prevalence of appropriate ICD shocks was similar before and after LVAD implantation in the entire cohort.

Cardiovascular Hospitalizations and Resource Use Following Atrial Fibrillation Ablation.

Background Over the next few years, atrial fibrillation (AF)-related morbidity and costs will increase significantly. Thus, it is prudent to examine the impact of AF treatment on health care resource use. This study examined the impact of AF ablation on hospitalization, length of stay, and resource use for patients undergoing AF ablation in a multihospital system. Methods and Results In an observational analysis, outcomes of total, cardiovascular, and AF hospitalizations, emergency department visits, and length of stay were compared for 3417 patients between 12 months before and 24 months following AF ablation. Use of electrical cardioversions and antiarrhythmic use were also compared 1 year before to 2 years after AF ablation. There were fewer total (0.7±1.3 versus 0.3±0.7; P<0.001), cardiovascular (0.7±1.2 versus 0.2±0.6; P<0.001), and AF (0.6±1.1 versus 0.1±0.3; P<0.001) hospitalizations and emergency department visits (0.8±2.1 versus 0.4±0.9; P<0.001) per patient-year for the 2 years following AF ablation compared with 1 year before. Average length of stay per patient-year (1.4±7.9 versus 3.6±5.3 days; P<0.0001), the percentage of patients on antiarrhythmic therapy (21.2% versus 58.5%; P<0.0001), and those undergoing electrical cardioversions (16.1% versus 28.1%; P<0.0001) were lower 2 years following AF ablation versus 1 year before. Conclusions We noted a decrease in total, cardiovascular, and AF hospitalizations and health care resource use during the 2-year period after index AF ablation, compared with the 1 year before. AF ablation may portend a decline in patient morbidity and health care costs.

Safety and efficacy of left bundle branch area pacing compared with right ventricular pacing in patients with bradyarrhythmia and conduction system disorders: Systematic review and meta-analysis.

BACKGROUND: Right Ventricular Pacing (RVP) may have detrimental effects in ventricular function. Left Bundle Branch Area Pacing (LBBAP) is a new pacing strategy that appears to have better results. The aim of this systematic review and meta-analysis is to compare the safety and efficacy of LBBAP vs RVP in patients with bradyarrhythmia and conduction system disorders. METHODS: MEDLINE, EMBASE and Pubmed databases were searched for studies comparing LBBAP with RVP. Outcomes were all-cause mortality, atrial fibrillation (AF) occurrence, heart failure hospitalizations (HFH) and complications. QRS duration, mechanical synchrony and LVEF changes were also assessed. Pairwise meta-analysis was conducted using random and fixed effects models. RESULTS: Twenty-five trials with 4250 patients (2127 LBBAP) were included in the analysis. LBBAP was associated with lower risk for HFH (RR:0.33, CI 95%:0.21 to 0.50; p < 0.001), all-cause mortality (RR:0.52 CI 95%:0.34 to 0.80; p = 0.003), and AF occurrence (RR:0.43 CI 95%:0.27 to 0.68; p < 0.001) than RVP. Lead related complications were not different between the two groups (p = 0.780). QRSd was shorter in the LBBAP group at follow-up (WMD: -32.20 msec, CI 95%: -40.70 to -23.71; p < 0.001) and LBBAP achieved better intraventricular mechanical synchrony than RVP (SMD: -1.77, CI 95%: -2.45 to -1.09; p < 0.001). LBBAP had similar pacing thresholds (p = 0.860) and higher R wave amplitudes (p = 0.009) than RVP. CONCLUSIONS: LBBAP has better clinical outcomes, preserves ventricular electrical and mechanical synchrony and has excellent pacing parameters, with no difference in complications compared to RVP.

Relative Contribution of Atrial Fibrillation to Outcomes of Patients With Cardiomyopathy Based on Severity of Left Ventricular Dysfunction.

In patients with left ventricular (LV) dysfunction, the risk of death or heart failure hospitalizations (HFHs) increases with worsening ejection fraction (EF). Whether the relative contribution of atrial fibrillation (AF) to outcomes is more pronounced in patients with worse EF is not confirmed. The present study aimed to investigate the relative influence of AF on the outcome of cardiomyopathy patients by severity of LV dysfunction. In this observational study, data from 18,003 patients with EF ≤50% seen at a large academic institution between 2011 and 2017 were analyzed. Patients were stratified by EF quartiles (EF<25%, 25%≤EF<35%, 35%≤EF<40%, and EF≥40%, for quartiles 1, 2, 3, and 4, respectively). and followed to the end point of death or HFH. Outcomes of AF versus non-AF patients were compared within each EF quartile. During a median follow-up of 3.35 years, 8,037 patients (45%) died and 7,271 (40%) had at least 1 HFH. Rates of HFH and all-cause mortality increased as EF decreased. The hazard ratios (HRs) of death or HFH for AF versus non-AF patients increased steadily with increasing EF (HR of 1.22, 1.27, 1.45, 1.50 for quartiles 1, 2, 3, and 4, respectively, p = 0.045) driven primarily by the risk of HFH (HR of 1.26, 1.45, 1.59, 1.69 for quartiles 1, 2, 3, and 4, respectively, p = 0.045). In conclusion, in patients with LV dysfunction, the detrimental influence of AF on the risk of HFH is more pronounced in those with more preserved EF. Mitigation strategies for AF with the goal of decreasing HFH may be more impactful in patients with more preserved LV function.

Ventricular conduction abnormality in patients with mild to moderate cardiomyopathy.

BACKGROUND: In mild-to-moderate cardiomyopathy, cardiac resynchronization therapy (CRT) is indicated in patients with high burden of right ventricular pacing but not in those with intrinsic ventricular conduction abnormalities. HYPOTHESIS: We hypothesized that CRT positively impacts outcomes of patients with intrinsic ventricular conduction delay and left ventricular ejection fraction (LVEF) of 36%-50%. METHODS: Of 18 003 patients with LVEF ≤ 50%, 5966 (33%) patients had mild-to-moderate cardiomyopathy, of whom 1741 (29%) have a QRS duration ≥120 ms. Patients were followed to the endpoints of death and heart failure (HF) hospitalization. Outcomes were compared between patients with narrow versus wide QRS. RESULTS: Of the 1741 patients with mild-to-moderate cardiomyopathy and wide QRS duration, only 68 (4%) were implanted with a CRT device. Over a median follow-up of 3.35 years, 849 (51%) died and 1004 (58%) had a HF hospitalization. The adjusted risk of death (hazard ratio (HR) = 1.11, p = 0.046) and of death or HF hospitalization (HR = 1.10, p = 0.037) were significantly higher in patients with wide versus narrow QRS duration. In patients with wide QRS complex, CRT was associated with reduction in the adjusted risk of death (HR = 0.47, p = 0.020) and of death or HF hospitalization (HR = 0.58, p = 0.008). CONCLUSIONS: Patients with mild-to-moderate cardiomyopathy and wide QRS duration are rarely implanted with CRT devices and have worse outcomes compared to those with narrow QRS. Randomized trials are needed to examine if CRT has salutary effects in this population.

Impact of a dedicated center for atrial fibrillation on resource utilization and costs.

BACKGROUND: Atrial fibrillation (AF) affects millions of Americans each year and can lead to high levels of resource utilization through emergency department (ED) visits and inpatient stays. HYPOTHESIS: We hypothesized that referral of patients to a dedicated Center for AF from the ED would reduce costs of care. METHODS: The University of Pittsburgh Center for AF serves as a rapid referral center for patients with AF to avoid unnecessary inpatient admissions and provide specialized care. Patients that presented to the ED with AF and met prespecified criteria were directed to rapid outpatient follow-up instead of inpatient admission. The primary outcome of interest was 30-day total costs. Secondary outcomes included outpatient costs, inpatient costs, 90-day costs, and inpatient stay characteristics. RESULTS: We identified 96 patients (median age 65, 38% women) referred to the center for AF for a new diagnosis of AF between October 2017 and December 2019 and matched 96 control patients. After 30 days of follow-up, patients referred to the center for AF had a lower average cost ($619 vs. $1252, p < 0.001) compared to controls, driven by lower costs of ED care tempered by slightly higher outpatient costs. Thirty-day admissions and lengths of stay were also lower. These differences were persistent at 90 days. CONCLUSION: Directing patients with AF that present to the ED to follow-up at a dedicated Center for AF significantly reduced overall costs, while reducing subsequent inpatient admissions and total lengths of stay in the hospital.

"Failing kidneys in a failing planet; CKD of unknown origin".

The 'alarm clock' for human beings in the era of climate medicine has rung. Original diseases have appeared, that could not be explained and attributed to common causes, which are suggested to be linked to global warming and environmental factors. Such an indolent disease is the chronic kidney disease of unknown cause (CKDu), introduced also as Mesoamerican or Uddanam nephropathy. Scientists equate the climate impact on kidneys with the canary in the coal mine; coal miners used to carry caged canaries with them, so that if poisonous gases, such as methane or carbon monoxide leaked into the mine-shaft, the gases would kill the canary before killing the miners; similarly, kidneys are injured before devastating and lethal complications occur in humans. In some regions of Central America, the deaths due to chronic kidney disease increased by 177% with a death toll being as high as over 20,000. It was first documented in animals that periodic heat and dehydration have a major role in causing chronic kidney disease. Based on that observation, it is advocated that young male agricultural workers in Central America and South Asia, develop renal disease by getting exposed to extreme heat repeatedly. The clinico-pathological characteristics of this type of kidney injury, do not belong to an existing classification, even though a form of tubulo-interstitial renal disease has been proposed. In this review, we will discuss about CKDu, its epidemiology and pathophysiological mechanisms, clinical presentation and diagnostic biomarkers and examine potential therapeutic options.

Guideline-Directed Medical Therapy and the Risk of Death in Primary Prevention Defibrillator Recipients.

BACKGROUND: Contemporary guideline-directed medical therapy (GDMT) confers a significant mortality benefit for patients with heart failure with reduced ejection fraction (HFrEF), as compared to GDMT prevalent at the time of landmark primary prevention implantable cardioverter-defibrillator (ICD) trials. The impact of modern era GDMT on survival in this population is unknown. OBJECTIVES: This study sought to investigate the impact of number of GDMT medications prescribed for HFrEF on all-cause mortality in recipients of primary prevention ICD. METHODS: A cohort of 4,972 recipients with primary prevention ICD (n = 3,210) or cardiac resynchronization therapy-defibrillator (CRT-D) (n = 1,762) was studied. The association of number of GDMT medications prescribed at the time of device implantation and all-cause mortality at 2 years post implantation was examined. RESULTS: In our primary prevention cohort, 5%, 20%, 52%, and 23% of patients were prescribed 0, 1, 2, or 3-4 GDMT medications, respectively. After risk adjustment for age, sex, ejection fraction, body mass index, the Elixhauser comorbidity score, the type of cardiomyopathy, and the year of device implantation, each additional GDMT conferred a reduction in the risk of death of 36% in recipients of ICD (HR: 0.64; P < 0.001) and 30% in recipients of CRT-D (HR: 0.70; P < 0.001). CONCLUSIONS: A higher number of prescribed GDMT medications is associated with an incremental 1-year survival in recipients of primary prevention ICD with or without CRT. Initiation of maximum number of tolerated GDMT medications should therefore be the goal for all patients with HFrEF. In the setting of robust GDMT, the risk versus benefit of a primary prevention ICD warrants re-examination in future studies.

Real-Time Prediction of Mortality, Cardiac Arrest, and Thromboembolic Complications in Hospitalized Patients With COVID-19.

Background: COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease. Objectives: The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19. Methods: Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed. Results: Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively. Conclusions: The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.

Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart.

Sudden cardiac death from arrhythmia is a major cause of mortality worldwide. Here, we develop a novel deep learning (DL) approach that blends neural networks and survival analysis to predict patient-specific survival curves from contrast-enhanced cardiac magnetic resonance images and clinical covariates for patients with ischemic heart disease. The DL-predicted survival curves offer accurate predictions at times up to 10 years and allow for estimation of uncertainty in predictions. The performance of this learning architecture was evaluated on multi-center internal validation data and tested on an independent test set, achieving concordance index of 0.83 and 0.74, and 10-year integrated Brier score of 0.12 and 0.14. We demonstrate that our DL approach with only raw cardiac images as input outperforms standard survival models constructed using clinical covariates. This technology has the potential to transform clinical decision-making by offering accurate and generalizable predictions of patient-specific survival probabilities of arrhythmic death over time.

Predictors of Hospital Admissions for Ventricular Arrhythmia or Cardiac Arrest in Patients With Cardiomyopathy.

Although ventricular dysfunction is associated with the occurrence of ventricular arrhythmia (VA), most patients with cardiomyopathy do not experience VA. We therefore investigated other predictors of VA in a large contemporary cohort of patients with cardiomyopathy. All patients at a large academic medical system with left ventricular ejection fraction (LVEF) ≤50% were enrolled at the time of first documented low LVEF. Predictors of hospital admission for VA were examined using multivariable Cox models. The incidence of implantable defibrillator (ICD) placement was also examined. A total of 18,003 patients were enrolled. Over a median follow-up of 3.35 years, 389 patients (2.2%) were admitted for VA (304 of 12,037 [2.5%] among patients with LVEF ≤35% vs 85 of 5,966 [1.4%] among those with LVEF 36% to 50%). Predictors of VA hospitalization included lower LVEF (hazard ratio (HR) = 1.43 per 10% decrease, p <0.001), the presence of an ICD at baseline (HR = 1.63, p = 0.010), higher blood glucose (HR = 1.02 per 10 mg/100 ml increase, p = 0.050), the presence of end-stage renal disease (HR = 3.59, p <0.001), and the presence of liver cirrhosis (HR = 1.93, p = 0.013). During follow-up, 626 patients were implanted with a new ICD. In addition to being admitted with VA, a lower LVEF and a history of coronary artery disease or heart failure were the main predictors of ICD therapy in this population. In conclusion, in addition to more severe cardiomyopathy and the presence of an implanted ICD, metabolic derangements on initial contact are independent predictors of hospital admissions for VA in patients with cardiomyopathy. Noncardiac co-morbidities play an important role in stratifying patients with cardiomyopathy for their risk of VA or cardiac arrest.

Spatial dispersion analysis of LGE-CMR for prediction of ventricular arrhythmias in patients with cardiac sarcoidosis.

BACKGROUND: Patients with cardiac sarcoidosis (CS) are at increased risk of life-threatening ventricular arrhythmias (VA). Current approaches to risk stratification have limited predictive value. OBJECTIVES: To assess the utility of spatial dispersion analysis of late gadolinium enhancement cardiac magnetic resonance (LGE-CMR), as a quantitative measure of myocardial tissue heterogeneity, in risk stratifying patients with CS for VA and death. METHODS: Sixty two patients with CS underwent LGE-CMR. LGE images were segmented and dispersion maps of the left and right ventricles were generated as follows. Based on signal intensity (SI), each pixel was categorized as abnormal (SI ≥3SD above the mean), intermediate (SI 1-3 SD above the mean) or normal (SI <1SD above the mean); and each pixel was then assigned a value of 0 to 8 based on the number of adjacent pixels of a different category. Average dispersion score was calculated for each patient. The primary endpoint was VA during follow up. The composite of VA or death was assessed as a secondary endpoint. RESULTS: During 4.7 ± 3.5 years of follow up, six patients had VA, and five without documented VA died. Average dispersion score was significantly higher in patients with VA versus those without (0.87 ± 0.08 vs. 0.71 ± 0.16; p = .002) and in patients with events versus those without (0.83 ± 0.08 vs. 0.70 ± 0.16; p = .003). Patients at higher tertiles of dispersion score had a higher incidence of VA (p = .03) and the composite of VA or death (p = .01). CONCLUSIONS: Increased substrate heterogeneity, quantified by spatial dispersion analysis of LGE-CMR, may be helpful in risk-stratifying patients with CS for adverse events, including life-threatening arrhythmias.

Assessment of an ECG-Based System for Localizing Ventricular Arrhythmias in Patients With Structural Heart Disease.

Background We have previously developed an intraprocedural automatic arrhythmia-origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3-lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system. Methods and Results In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120-ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient-specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P=0.895). Conclusions The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.

Characterization of the Electrophysiologic Remodeling of Patients With Ischemic Cardiomyopathy by Clinical Measurements and Computer Simulations Coupled With Machine Learning.

RATIONALE: Patients 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. OBJECTIVES: To 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 RESULTS: We 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. CONCLUSION: Myocardial 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.

Prospective Multicenter Assessment of a New Intraprocedural Automated System for Localizing Idiopathic Ventricular Arrhythmia Origins.

OBJECTIVES: The objective of this study was to present a new system, the Automatic Arrhythmia Origin Localization (AAOL) system, which used incomplete electroanatomic mapping (EAM) for localization of idiopathic ventricular arrhythmia (IVA) origin on the patient-specific geometry of left ventricular, right ventricular, and neighboring vessels. The study assessed the accuracy of the system in localizing IVA source sites on cardiac structures where pace mapping is challenging. BACKGROUND: An intraprocedural automated site of origin localization system was previously developed to identify the origin of early left ventricular activation by using 12-lead electrocardiograms (ECGs). However, it has limitations, as it could not identify the site of origin in the right ventricle and relied on acquiring a complete EAM. METHODS: Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The new system combined 3-lead (III, V2, and V6) 120-ms QRS integrals and patient-specific EAM geometry with pace mapping to predict the site of earliest ventricular activation. The predicted site was projected onto EAM geometry. RESULTS: Twenty-three IVA origin sites were clinically identified by activation mapping and/or pace mapping (8, right ventricle; 15, left ventricle, including 8 from the posteromedial papillary muscle, 2 from the aortic root, and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs. CONCLUSIONS: The new intraprocedural AAOL system achieved accurate localization of IVA origin in ventricles and neighboring vessels, which could facilitate ablation procedures for patients with IVAs.

Feasibility study shows concordance between image-based virtual-heart ablation targets and predicted ECG-based arrhythmia exit-sites.

INTRODUCTION: We recently developed two noninvasive methodologies to help guide VT ablation: population-derived automated VT exit localization (PAVEL) and virtual-heart arrhythmia ablation targeting (VAAT). We hypothesized that while very different in their nature, limitations, and type of ablation targets (substrate-based vs. clinical VT), the image-based VAAT and the ECG-based PAVEL technologies would be spatially concordant in their predictions. OBJECTIVE: The objective is to test this hypothesis in ischemic cardiomyopathy patients in a retrospective feasibility study. METHODS: Four post-infarct patients who underwent LV VT ablation and had pre-procedural LGE-CMRs were enrolled. Virtual hearts with patient-specific scar and border zone identified potential VTs and ablation targets. Patient-specific PAVEL based on a population-derived statistical method localized VT exit sites onto a patient-specific 238-triangle LV endocardial surface. RESULTS: Ten induced VTs were analyzed and 9-exit sites were localized by PAVEL onto the patient-specific LV endocardial surface. All nine predicted VT exit sites were in the scar border zone defined by voltage mapping and spatially correlated with successful clinical lesions. There were 2.3 ± 1.9 VTs per patient in the models. All five VAAT lesions fell within regions ablated clinically. VAAT targets correlated well with 6 PAVEL-predicted VT exit sites. The distance between the center of the predicted VT-exit-site triangle and nearest corresponding VAAT ablation lesion was 10.7 ± 7.3 mm. CONCLUSIONS: VAAT targets are concordant with the patient-specific PAVEL-predicted VT exit sites. These findings support investigation into combining these two complementary technologies as a noninvasive, clinical tool for targeting clinically induced VTs and regions likely to harbor potential VTs.

Personalized Digital-Heart Technology for Ventricular Tachycardia Ablation Targeting in Hearts With Infiltrating Adiposity.

BACKGROUND: Infiltrating adipose tissue (inFAT) is a newly recognized proarrhythmic substrate for postinfarct ventricular tachycardias (VT) identifiable on contrast-enhanced computed tomography. This study presents novel digital-heart technology that incorporates inFAT from contrast-enhanced computed tomography to noninvasively predict VT ablation targets and assesses the capability of the technology by comparing its predictions with VT ablation procedure data from patients with ischemic cardiomyopathy. METHODS: Digital-heart models reflecting patient-specific inFAT distributions were reconstructed from contrast-enhanced computed tomography. The digital-heart identification of fat-based ablation targeting (DIFAT) technology evaluated the rapid-pacing-induced VTs in each personalized inFAT-based substrate. DIFAT targets that render the inFAT substrate noninducible to VT, including VTs that arise postablation, were determined. DIFAT predictions were compared with corresponding clinical ablations to assess the capabilities of the technology. RESULTS: DIFAT was developed and applied retrospectively to 29 ischemic cardiomyopathy patients with contrast-enhanced computed tomography. DIFAT ablation volumes were significantly less than the estimated clinical ablation volumes (1.87±0.35 versus 7.05±0.88 cm3, P<0.0005). DIFAT targets overlapped with clinical ablations in 79% of patients, mostly in the apex (72%) and inferior/inferolateral (74%). In 3 patients, DIFAT targets colocalized with redo ablations delivered years after the index procedure. CONCLUSIONS: DIFAT is a novel digital-heart technology for individualized VT ablation guidance designed to eliminate VT inducibility following initial ablation. DIFAT predictions colocalized well with clinical ablation locations but provided significantly smaller lesions. DIFAT also predicted VTs targeted in redo procedures years later. As DIFAT uses widely accessible computed tomography, its integration into clinical workflows may augment therapeutic precision and reduce redo procedures.