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

Autor: Christopher Hamilton, Erick A. Perez-Alday, Eugene A. Park, Muammar M. Kabir, Larisa G. Tereshchenko, Jason Thomas
Rok vydání: 2018
Předmět:
Adult
Male
medicine.medical_specialty
Supine position
Adolescent
medicine.medical_treatment
Health Informatics
030204 cardiovascular system & hematology
Logistic regression
QT interval
Article
Electrocardiography
Young Adult
03 medical and health sciences
QRS complex
0302 clinical medicine
Internal medicine
Humans
Medicine
Diagnosis
Computer-Assisted
Prospective Studies
cardiovascular diseases
030212 general & internal medicine
Lead (electronics)
Aged
Aged
80 and over
Ejection fraction
Anthropometry
Receiver operating characteristic
business.industry
Arrhythmias
Cardiac
Signal Processing
Computer-Assisted
Middle Aged
Implantable cardioverter-defibrillator
Defibrillators
Implantable
Computer Science Applications
Cross-Sectional Studies
ROC Curve
Cardiology
Regression Analysis
Female
business
Zdroj: Computers in Biology and Medicine. 102:242-250
ISSN: 0010-4825
Popis: 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.
Databáze: OpenAIRE
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