Risk stratifier for sudden cardiac death beyond the left ventricular ejection fraction in Chagas cardiomyopathy

• Published in: Pacing and clinical electrophysiology Vol. 47; no. 2; pp. 312 - 320
• Main Authors: Pedrosa, Roberto Coury, Paulo do Vale Madeiro, João, Alberto, Alex C., Limeira, Gabriel A., Bragança Pereira, Basílio, Matos do Nascimento, Emília, Schlindwein, Fernando Soares, Ng, Gullien André
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.02.2024
• Subjects: Action potential; Aged; artificial intelligence; Cardiomyopathy; Chagas cardiomyopathy; Chagas Cardiomyopathy - complications; chagas disease; Cross-Sectional Studies; Death; Death, Sudden, Cardiac - epidemiology; Defibrillators, Implantable; EKG; Heart; Humans; implantable cardioverter defibrillators; Risk Assessment; Risk Factors; Sensitivity analysis; Stroke Volume - physiology; sudden cardiac death; Ventricle; Ventricular Function, Left; chagas disease; sudden cardiac death; artificial intelligence; Chagas cardiomyopathy; implantable cardioverter defibrillators
• ISSN: 0147-8389; 1540-8159
• DOI: 10.1111/pace.14908

Background Sudden cardiac death (SCD) risk markers are needed in Chagas cardiomyopathy (CC). Action potential duration restitution (APDR) dynamics is capable of extracting information on cardiac regional heterogeneity. This study intends to develop a patient‐specific variables‐based algorithm to predict SCD in the low‐intermediate subgroups of the Rassi risk score. Methods Cross‐sectional study of patients who underwent 24‐h Holter for research purposes between January 1992 and February 2017. From 4‐h ECG segment, RR series were generated and APDR dynamics metrics were calculated. Classification tree and sensitivity analysis were applied. As outcomes, SCD, SCD‐free and non‐cardiovascular death and 34 variables were included. Results Two hundred twenty‐one (129 in the group SCD‐free, 80 in the SCD group and 12 non‐cardiovascular death group) were analyzed. In the groups with and without SCD (209 patients), the median age was 66 years, 52% were female, the cardiac involvement was mild to moderate in 72% with a Rassi point median of 8 (IQ: 3 to 11). The SCD group had more ventricular remodeling and more ventricular electrical instability. The occurrence of a %beats QTend/TendQ ratio > 1 (AUC, 0.96 (95% CI 0.89–0.98) present in more than 56.7% of the 4‐h ECG segments was sufficient to identify patients of the SCD subgroup. Variables representing different stages of CC were also relevant in the model. Conclusion It is possible to use APDR dynamics as an adjuvant in the SCD risk assessment in a subgroup of patients with a high risk of SCD and a very low risk of non‐CV death with high power of discrimination.