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

被引:1
作者
Pedrosa, Roberto Coury [1 ]
Madeiro, Joao Paulo do Vale [2 ]
Alberto, Alex C. [3 ]
Limeira, Gabriel A. [4 ]
Pereira, Basilio de Braganca [5 ,6 ]
do Nascimento, Emilia Matos [7 ]
Schlindwein, Fernando Soares [8 ,9 ]
Ng, Gullien Andre [10 ]
机构
[1] Univ Fed Rio de Janeiro, Clementino Fraga Filho Univ Hosp, Edson Saad Heart Inst, Cardiol Dept, Rio De Janeiro, Brazil
[2] Univ Fed Ceara, Dept Comp Sci, Fortaleza, Ceara, Brazil
[3] Fed Ctr Technol Educ Celso Suckow da Fonseca, Rio De Janeiro, Brazil
[4] Univ Fed Rio de Janeiro, Rio De Janeiro, Brazil
[5] Univ Fed Rio de Janeiro, Sch Med, Rio De Janeiro, Brazil
[6] Edson Saad Heart Inst, Rio De Janeiro, Brazil
[7] Univ Estado Rio De Janeiro, Rio De Janeiro, Brazil
[8] Univ Leicester, Sch Engn, Leicester, Leics, England
[9] Univ Leicester, NIHR Leicester Biomed Res Ctr, Leicester, Leics, England
[10] Univ Leicester, NIHR Leicester Biomed Res Ctr, Dept Cardiovasc Sci, Leicester, Leics, England
来源
PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY | 2024年 / 47卷 / 02期
关键词
artificial intelligence; Chagas cardiomyopathy; chagas disease; implantable cardioverter defibrillators; sudden cardiac death; DISEASE; CLASSIFICATION; SCORE;
D O I
10.1111/pace.14908
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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. From4-h ECGsegment, RRseries 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-hECGsegments 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.
引用
收藏
页码:312 / 320
页数:9
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