Literature DB >> 21723240

High-frequency powers hidden within QRS complex as an additional predictor of lethal ventricular arrhythmias to ventricular late potential in post-myocardial infarction patients.

Takeshi Tsutsumi1, Nami Takano, Narihisa Matsuyama, Yukei Higashi, Kuniaki Iwasawa, Toshiaki Nakajima.   

Abstract

BACKGROUND: Ventricular late potentials (VLPs) have been known to be a predictor of lethal ventricular arrhythmias (L-VAs); however, detection of other arrhythmogenic signals within the QRS complex remains obscure.
OBJECTIVE: The aim of this study was to evaluate whether abnormal intra-QRS high-frequency powers (IQHFP) within the QRS complex become a new predictor of L-VAs in addition to VLPs.
METHODS: Both 12-lead electrocardiograms (ECG) and VLPs were recorded from 142 subjects, including 37 patients without heart diseases, 97 patients post-myocardial infarction (MI), and 45 post-MI patients with L-VAs. Time-frequency analysis of ECG (leads V(1) or II) using wavelet transform with the Morlet function was performed. After the time-frequency powers were calculated, the ratios of the peak of signal power during the QRS complex in high-frequency bands against the peak power at 80 Hz (b/a ratio; P100, P150, P200, P250, or P300Hz/P80Hz) were measured. Abnormal IQHFP was defined when the b/a ratio exceeded the optimal cut-off values estimated by receiver-operator characteristic curves.
RESULTS: The combination of abnormal IQHFP appearing at 200, 250, and 300 Hz with positive VLPs increased the sensitivity for prediction of L-VAs from 53.3% by VLPs to 89.5%, and the negative predictive value from 74.7% by VLPs to 87.7%.
CONCLUSION: The combined use of VLPs and IQHFP hidden within the QRS complex improved the prediction of L-VAs in post-MI patients.
Copyright © 2011 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21723240     DOI: 10.1016/j.hrthm.2011.06.027

Source DB:  PubMed          Journal:  Heart Rhythm        ISSN: 1547-5271            Impact factor:   6.343


  4 in total

1.  Novel frequency analysis of signal-averaged electrocardiograms is predictive of adverse outcomes in implantable cardioverter defibrillator patients.

Authors:  Ryan Chow; Javad Hashemi; Sami Torbey; Johnny Siu; Benedict Glover; Adrian M Baranchuk; Hoshiar Abdollah; Christopher Simpson; Selim Akl; Damian P Redfearn
Journal:  Ann Noninvasive Electrocardiol       Date:  2019-01-28       Impact factor: 1.468

2.  Analysis of the High-Frequency Content in Human QRS Complexes by the Continuous Wavelet Transform: An Automatized Analysis for the Prediction of Sudden Cardiac Death.

Authors:  Daniel García Iglesias; Nieves Roqueñi Gutiérrez; Francisco Javier De Cos; David Calvo
Journal:  Sensors (Basel)       Date:  2018-02-12       Impact factor: 3.576

3.  Analysis of Abnormal Intra-QRS Potentials in Signal-Averaged Electrocardiograms Using a Radial Basis Function Neural Network.

Authors:  Chun-Cheng Lin
Journal:  Sensors (Basel)       Date:  2016-09-27       Impact factor: 3.576

Review 4.  ECG Parameters for Malignant Ventricular Arrhythmias: A Comprehensive Review.

Authors:  Satria Mandala; Tham Cai Di
Journal:  J Med Biol Eng       Date:  2017-06-28       Impact factor: 1.553

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.