Eligibility for Subcutaneous Implantable Cardioverter Defibrillator in Congenital Heart Disease

Abstract

Background: The goals of this study were: assess left-and right-sided subcutaneous implantable cardioverter-defibrillator (SICD) eligibility in adult congenital heart disease (ACHD) patients, use machine learning to predict SICD eligibility in ACHD patients, and transform 12-lead ECG to S-ICD 3-lead ECG, and vice versa. Methods: ACHD outpatients (n=101; age 42±14 y; 52% female; 85% white; left ventricular ejection fraction (LVEF) 56±9%) were enrolled in a prospective study. Supine and standing 12-lead ECG was recorded simultaneously with a right- and left-sided S-ICD 3-lead ECG. Peak-to-peak QRS and T amplitudes, RR, PR, QT, QTc, QRS intervals, Tmax, and R/Tmax (31 predictor variables) were tested. Model selection, training, and testing were performed using supine ECG datasets. Validation was performed using standing ECG datasets and out-of-sample non-ACHD population (n=68; age 54±16 y; 54% female; 94% white; LVEF 61±8%). Results: A 40% of participants were ineligible for S-ICD. Tetralogy of Fallot patients passed right-sided screening (57%) more often than left-sided (21%; McNemar's χ2 P=0.025). The ridge model demonstrated the best cross-validation function. Validation of the ridge models was satisfactory for standing left-sided [ROC AUC 0.687 (95%CI 0.582-0.791)] and right-sided [ROC AUC 0.655(95%CI 0.549-0.762)] SICD eligibility prediction. Out-of-sample validation in the non-ACHD population yielded a 100% sensitivity of the pre-selected threshold for the elastic net model. Validation of the transformation matrices showed satisfactory agreement (<0.1 mV difference). Conclusion: Nearly half of the contemporary ACHD population is ineligible for S-ICD. Machine-learning prediction of SICD eligibility can be used for screening of SICD candidates. Clinical Trial Registration: URL: www.clinicaltrials.gov Unique identifier: NCT03209726

To the editor: S‐ICD eligibility in adult congenital heart disease

“…Mathematically, it is not possible to achieve the reported 83% rate of eligibility per written findings, but, instead, figure 1 provides results more consistent with previous studies. [2][3][4] The authors 1 did not discuss possible reasons for disagreement of their findings with previous studies. It is essential to discuss the limitations of the study in order for the reader to gain perspective of the study.The methods included the use of an automated Boston-Scientific screening test.…”

“…The limitations in the study design and conduct could at least partially explain the difference in the reported results with other studies. [2][3][4] Also, the study 1 raised questions about the appropriateness of utilized statistical analyses. For appropriate paired comparison of S-ICD ineligibility in different positions (standing and supine) on the left and right sides, McNemar's χ 2 statistic has to be used.…”

“…Recently, Wang et al 2 observed important sex differences in S-ICD eligibility and showed that female ACHD patients had a nearly 6-fold greater odds of S-ICD eligibility. Sex differences in clinical characteristics and outcomes in the ACHD population are insufficiently studied, and any available data contribute to the knowledge base.…”

“…Similar to the discussed study, previous studies of S-ICD eligibility in ACHD are relatively small. [2][3][4][5] To summarize research evidence, future systematic reviews and meta-analyses will likely be needed. An accurate, detailed, and reproducible methods and results have the greatest impact on what new studies can expand on in the ACHD population.…”

Digitizing ECG image: new fully automated method and open-source software code

“…For the development and validation of the algorithm, we used the data of clinical studies conducted at the Oregon Health & Science University (OHSU), with available both (1) digitally recorded ECGs and (2) printed on paper ECGs. [11][12][13][14] All studies were approved by the OHSU Institutional Review Board, and all participants signed informed consent before entering the study.…”