Prakash, Shisheer Havangi

Background: Patients with systemic right ventricle (sRV), including congenitally corrected transposition of great arteries (cc-TGA) and dextro-transposition of great arteries (d-TGA) post-atrial switch procedure are at risk of sudden cardiac death due to ventricular arrhythmias (VA). While programmed ventricular stimulation (PVS) can help with risk stratification in certain patients with congenital heart disease, its role in sRV is unknown. Objective: To study the diagnostic value of electrophysiology study (EPS) in predicting VAs in patients with sRV. Methods: EPS was performed in 53 patients with sRV at Mayo Clinic from 1994 to 2021. Patients with a history of sustained VA or cardiac arrest were excluded (n=19). The incidence of sustained VA (sudden cardiac death, sustained ventricular tachycardia [VT] or appropriate implantable cardioverter-defibrillator [ICD] therapy) was evaluated in the remaining 34 patients. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of EPS in predicting VAs is reported. Results: The mean age at EPS was 36.2±11.6 years, 21 (61.8%) were male, 21 (61.8%) had d-TGA and mean sRV ejection fraction was 31.3±10.8%. Indication for EPS was supraventricular tachycardias (n=15, 44.1%), syncope/palpitations (n=9, 26.5%) and non-sustained VT (n=6, 17.6%). 13/34 (38.2%) patients had inducible sustained VA, (5 [38.5%] with monomorphic VT and 8 [61.5%] with polymorphic VT/VF). Treatments included ICD implantation in all 13 patients and ablation in one patient. During a mean follow-up of 8±5.4 years, one patient with a positive PVS (inducible polymorphic VT) experienced sustained VT secondary to atrial flutter with 1:1 conduction. The sensitivity of PVS was 100%, specificity was 63.6%, PPV 7.7%, and NPV 100%. Conclusion: In this retrospective cohort of patients with sRV, polymorphic VT was the most commonly observed VA during PVS. The predictive value of a positive PVS was low in this cohort, and larger studies are needed to better define the role of EPS in risk stratification. Patients with negative EPS did not have future VAs recognizing that the overall event rate is low. Further multicenter research with a larger sample is required to develop predictive models to identify those at risk of VAs.

Introduction: The incidence and risk factors for atrial arrhythmia (AA) [atrial fibrillation (AF) and atrial flutter (AFL)] in adults with systemic right ventricle (SRV), specifically congenitally corrected-TGA (cc-TGA) and D-TGA palliated with atrial switch procedures, is not well understood. This study aims to better define these risks. Methods: Adults with SRV presenting to the Mayo Clinic between 1971 and 2022 were identified. Clinical characteristics, ECG and echocardiographic parameters were recorded at first evaluation. Sustained AA (> 30s) incidence at follow-up was documented using ECG. Cox regression analysis identified associations of incident AA. Results: Among 447 patients with SRV (mean age 34.7±14.8, 55.9% male, cc-TGA n=247; D-TGA post-atrial baffle n=200), AA was documented in 231 (51.6%) at a mean age of 37.5±18.8y. Isolated AF was observed in 88 (38.1%), isolated AFL in 71 (30.7%), and both AF and AFL in 72 (31.2%) patients. Univariate analysis showed significant predictors of AA as: age (HR:1.03, p<0.001), male sex (HR:1.49, p=0.026), NYHA class≥2 (HR:1.98, p<0.001), ventricular pacing (HR:1.64, p=0.019), QRS duration (HR:1.008, p<0.001), SRV enlargement (HR:1.73, p=0.01), SRV ejection fraction (HR:0.979,p=0.012), left atrial enlargement (HR:1.947, p=0.006), hypertension (HR:1.57, p=0.047), CKD (HR:0.991, p=0.021), and obesity (HR:1.66, p=0.023). In multivariable analysis, age (HR:1.032, p<0.001) and QRS duration (HR:1.007, p=0.013) were significant predictors of AA. Kaplan Meier analysis of time from first evaluation to incidence of AA is shown in the figure. AA was associated with heart failure in 56 (26.7%) patients. During 11.2±10.5 years of follow-up, mortality occurred in 50 (21.6%) with AA and 19 (8.8%) without AA. Conclusion: Atrial arrhythmia occurred in more than half of patients with SRV, predominantly in the third decade of life. Significant associations of AA included advancing age, longer QRS duration, enlargement of pulmonary venous atrium, reduced SRV function, hypertension and obesity. AA was associated with heart failure in one-fourth of patients and higher mortality. Close monitoring and early intervention in patients with risk factors may help mitigate the development of AA.

Introduction: Ebstein's anomaly (EA) is associated with ECG signature of right bundle branch block (RBBB). Patients with EA also have high incidence of accessory pathways (AP) and it has been hypothesized that the absence of RBBB on ECG may be associated with a higher prevalence of AP. This study aims to assess the prevalence of RBBB in patients with EA and examine the correlation between its absence and the presence of AP. Methods: Adults (age>18 years) with EA, identified using the Mayo Adult Congenital Heart Disease registry, were divided into 3 groups based on the QRS morphology of their first ECG. Those with prior AP ablation were excluded. The demographic characteristics, baseline ECG data, echocardiographic parameters and EP study data were retrospectively collected and compared between the three groups using Chi-square or ANOVA test as appropriate. Results: Of 596 patients with EA, 358(60.06%) patients had a RBBB, bifascicular block or an incomplete RBBB (group1) ; 18 (3.02%) patients had either a LBBB , ventricular pre-excitation, isolated left anterior or posterior fascicular block (group 2); and 220 (36.92%) patients had normal QRS (group 3). The characteristics of these groups are compared in the table. Patients with RBBB had larger RV size, reduced RV systolic function and higher likelihood of tricuspid valve surgery. EP study was performed in 51 (14%), 3 (17%) and 51 (23%) patients in groups 1, 2,and 3 respectively. One or more APs were noted in 11/51 (22%) and 14/51 (30%) patients with RBBB and normal QRS respectively (p=0.18). Additionally, in patients who did not undergo an EP study, supraventricular tachycardia was documented in 39/307 (13%), 2/15(13%) and 13/169 patients (8%) in group 1,2 and 3 respectively during followup . Conclusion: In a large cohort of adults with EA in a tertiary referral center, greater than one-third of patients had a normal QRS complex without RBBB. However, EP study did not reveal a significant difference in the prevalence of accessory pathways between patients with and without RBBB. In EA, the absence of RBBB may not increase the risk of an underlying accessory pathway.

Background Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in adults using a 12‐lead ECG; however, its efficacy in children is uncertain. We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. Methods and Results We identified 10 142 unique pediatric patients (age≤18) with a 10‐second, 12‐lead surface ECG within 14 days of a transthoracic echocardiogram, performed between 2002 and 2022. LVSD was defined quantitatively by left ventricular ejection fraction (LVEF). RVSD was defined semiquantitatively. Novel pediatric models for LVEF ≤35% and LVEF <50% achieved excellent test areas under the curve of 0.93 (95% CI, 0.89–0.98) and 0.88 (95% CI, 0.83–0.94) respectively. The model to detect LVEF <50% had a sensitivity of 0.85, specificity of 0.80, positive predictive value of 0.095, and negative predictive value of 0.995. In comparison, the previously validated adult data‐derived model for LVEF <35% achieved an area under the curve of 0.87 (95% CI, 0.84–0.90) for LVEF ≤35% in children. A novel pediatric model for any RVSD detection reached a test area under the curve of 0.90 (0.87–0.94). Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.