Literature DB >> 10084384

Detection of abnormal high-frequency components in the QRS complex by the wavelet transform in patients with idiopathic dilated cardiomyopathy.

K Maehara1, T Kokubun, N Awano, K Taira, M Ono, T Furukawa, Y Shimizu, Y Maruyama.   

Abstract

In order to investigate whether increased fine, fractionated signals within the QRS complex can detect arrhythmogenic substrates and how these fine signals link with ventricular mechanical dysfunction, wavelet analysis was performed on averaged QRS complexes obtained from the left precordial lead in 26 patients with idiopatic dilated cardiomyopathy (IDCM) and in 12 normal subjects. The number of local maxima and the duration of the wavelet transform were significantly greater in patients with IDCM than in normal subjects; the number at 100 Hz was 8.8+/-3.1 vs 6.0+/-1.1 (p<0.01), and the duration at 100Hz was 93+/-15 vs 75+/-7ms (p<0.01). Both of these indices were greater in the patients with than in those without late potentials, repetitive ventricular premature beats or cardiac death. In addition, significant inverse curvilinear relationships were observed between the left ventricular ejection fraction and both the number of local maxima and the duration of the wavelet transform. In conclusion, fine fragmented signals in the QRS complex detected by wavelet analysis would be an important marker for potentially arrhythmogenic substrates and seemed to progress in parallel with left ventricular mechanical dysfunction in IDCM.

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Year:  1999        PMID: 10084384     DOI: 10.1253/jcj.63.25

Source DB:  PubMed          Journal:  Jpn Circ J        ISSN: 0047-1828


  3 in total

1.  A new approach for the comparison of conduction abnormality between arrhythmogenic right ventricular cardiomyopathy/dysplasia and Brugada syndrome.

Authors:  Kenji Yodogawa; Norishige Morita; Yoshinori Kobayashi; Hideo Takayama; Toshihiko Ohara; Yoshihiko Seino; Takao Katoh; Kyoichi Mizuno
Journal:  Ann Noninvasive Electrocardiol       Date:  2011-07       Impact factor: 1.468

2.  An automated algorithm for online detection of fragmented QRS and identification of its various morphologies.

Authors:  Sidharth Maheshwari; Amit Acharyya; Paolo Emilio Puddu; Evangelos B Mazomenos; Gourav Leekha; Koushik Maharatna; Michele Schiariti
Journal:  J R Soc Interface       Date:  2013-10-16       Impact factor: 4.118

Review 3.  Fragmented ECG as a risk marker in cardiovascular diseases.

Authors:  Rahul Jain; Robin Singh; Sundermurthy Yamini; Mithilesh K Das
Journal:  Curr Cardiol Rev       Date:  2014-08
  3 in total

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