Identifying the end of ventricular activation: body surface late potentials versus electrogram measurements in a canine infarction model.

Introduction: Identification of the end of the QRS is perhaps the single most important feature obtained from the high resolution signal- averaged electrocardiogram (SAECG). This point relies on computer algorithms to select a point above the noise levels. Prior studies to substantiate this approach...

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Publicado en:Journal of Cardiovascular Electrophysiology Vol. 5; no. 1; pp. 28 - 41
Autores principales: Berbari EJ, Lander P, Geselowitz DB, Scherlag BJ, Lazzara R
Formato: Journal Article
Publicado: Wiley-Blackwell Jan1994
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Identifying the end of ventricular activation: body surface late potentials versus electrogram measurements in a canine infarction model.
      aug:
        au:
          Berbari EJ
          Lander P
          Geselowitz DB
          Scherlag BJ
          Lazzara R
      sug:
        subj:
          Action Potentials Physiology
          Cardiovascular System Physiology
          Models, Biological
          Myocardial Infarction Physiopathology
          Animals
          Dogs
          Electrocardiography
      ab: Introduction: Identification of the end of the QRS is perhaps the single most important feature obtained from the high resolution signal- averaged electrocardiogram (SAECG). This point relies on computer algorithms to select a point above the noise levels. Prior studies to substantiate this approach using electrograms for comparison have demonstrated many examples of the body surface recordings failing to detect the full extent of the late potentials. Methods and Results: An animal model that generates late potentials was used in conjunction with epicardial cardiac mapping system to systematically examine the reasons for these failures. In 11 of 13 dogs we found a concordance between the signal-averaged recordings and the epicardial recordings within 5 msec. The two discordant studies were attributed to a failure of epicardial mapping to record all late potential sources. Also, a means of accurately comparing measurements from the two recording technologies was required in this study as well as a new definition for identifying the end of activation currents in epicardial electrograms. Conclusion: To achieve these results required approaches different from those used in the clinical setting to record the SAECG. These include: (1) the analysis of individual XYZ leads as opposed to the vector magnitude derived from these leads; (2) visual identification of very low level signals, as automatic algorithms often fail to detect low level signals: and (3) the use of finite impulse response digital filters instead of the bidirectional Butterworth filter.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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