The utility of routine clinical 12-lead ECG in assessing eligibility for subcutaneous implantable cardioverter defibrillator

Jason A. Thomas, Erick Andres Perez-Alday, Christopher Hamilton, Muammar M. Kabir, Eugene A. Park, Larisa Tereshchenko

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    Abstract

    Introduction: The subcutaneous implantable cardioverter-defibrillator (S-ICD) is a life-saving device. Recording of a specialized 3-lead electrocardiogram (ECG) is required for S-ICD eligibility assessment. The goals of this study were: (1) evaluate the effect of ECG filtering on S-ICD eligibility, and (2) simplify S-ICD eligibility assessment by development of an S-ICD ineligibility prediction tool, which utilizes the widely available routine 12-lead ECG. Methods and results: Prospective cross-sectional study participants [n = 68; 54% male; 94% white, with wide ranges of age (18–81 y), body mass index (19–53), QRS duration (66–150 ms), and left ventricular ejection fraction (37–77%)] underwent 12-lead supine, 3-lead supine and standing ECG recording. All 3-lead ECG recordings were assessed using the standard S-ICD pre-implantation ECG morphology screening. Backward, stepwise, logistic regression was used to build a model for 12-lead prediction of S-ICD eligibility. Select electrocardiogram waves and complexes: QRS, R-, S–, and T-amplitudes on all 12 leads, averaged QT interval, QRS duration, and R/T ratio in the lead with the largest T wave (R/Tmax) were included as predictors. The effect of ECG filtering on ECG morphology was evaluated. A total of 9 participants (13%) failed S-ICD screening prior to filtering. Filtering at 3–40 Hz, similar to the S-ICD default, reduced S-ICD ineligibility to 4%. A regression model that included RII, SII-aVL, TI, II, aVL, aVF, V3-V6, and R/Tmax perfectly predicted S-ICD eligibility, with an Area Under the Receiver Operating Characteristic Curve of 1.0. Conclusion: Routine clinical 12-lead ECG can be used to predict S-ICD eligibility. ECG filtering may improve S-ICD eligibility.

    Original languageEnglish (US)
    JournalComputers in Biology and Medicine
    DOIs
    StateAccepted/In press - Jan 1 2018

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    Keywords

    • Electrocardiogram
    • Eligibility
    • Subcutaneous ICD

    ASJC Scopus subject areas

    • Computer Science Applications
    • Health Informatics

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