An adaptive interval-based algorithm for withholding ICD therapy during sinus tachycardia.

Avoiding inappropriate ICD therapy during supraventricular tachycardia (SVT) while assuring 100% sensitivity for VT/VF remains a challenge. Inappropriate VT/VF therapy during sinus tachycardia (ST) is particularly distressing to the patient because the full sequence of ICD therapies is often deliver...

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Publicado en:Pacing & Clinical Electrophysiology Vol. 26; no. 5; pp. 1189 - 1202
Autores principales: Stadler RW, Gunderson BD, Gillberg JM
Formato: research Journal Article
Publicado: Wiley-Blackwell May2003
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2003
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1046/j.1460-9592.2003.t01-1-00168.x
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        atl: An adaptive interval-based algorithm for withholding ICD therapy during sinus tachycardia.
      aug:
        au:
          Stadler RW
          Gunderson BD
          Gillberg JM
      sug:
        subj:
          Algorithms
          Defibrillators, Implantable
          Tachycardia, Supraventricular Diagnosis
          Tachycardia, Supraventricular Therapy
          Sensitivity and Specificity
          Tachycardia, Supraventricular Physiopathology
          Human
      ab: Avoiding inappropriate ICD therapy during supraventricular tachycardia (SVT) while assuring 100% sensitivity for VT/VF remains a challenge. Inappropriate VT/VF therapy during sinus tachycardia (ST) is particularly distressing to the patient because the full sequence of ICD therapies is often delivered. ST or 1:1 atrial tachycardia (AT) with long PR intervals and ST or AT with atrial oversensing of far-field R waves cause the majority of inappropriate therapy in the Medtronic GEM DR (Model 7271) ICD. The goals of the present effort were to define an adaptive interval-based algorithm for withholding VT/VF therapy in dual chamber ICDs during ST and to compare performance of the adaptive algorithm with that of the original ST withholding algorithm in the GEM DR. The adaptive algorithm uses a combination of 1:1 atrial to ventricular conduction pattern, changes in RR intervals and changes in intrinsic PR intervals to establish evidence for or against the presence of ST. Performances of the adaptive and original ST withholding algorithms were compared on 3 databases collected by implanted GEM DR devices. The first database included 684 spontaneous VT/VF episodes. The second database included 216 spontaneous SVT episodes that received inappropriate VT/VF therapy. These databases included up to 2,000 atrial or ventricular sensed or paced events preceding the spontaneous tachycardias. The third database included 320 spontaneous ST/AT episodes for which therapy was appropriately withheld by the GEM DR. Performance of the adaptive algorithm on the third database was predicted rather than directly computed because of record length limitations. VT/VF therapy was classified as 'withheld' if evidence of ST remained high for one algorithm (i.e., at least 7 more beats to VT/VF detection) at the point of VT/VF detection by the other algorithm. For the 684 true VT/VF episodes, the original algorithm withheld VT/VF therapy in 5 episodes and the adaptive algorithm withheld VT/VF therapy in 3 episodes. The 95% confidence interval for the difference in VT/VF sensitivity between the adaptive and original algorithms was [-0.5 to +1.1%]. Twelve of the 320 ST/AT episodes (3.8%) that were appropriately classified by the original algorithm were predicted to receive inappropriate therapy by the adaptive algorithm. However, relative to the original algorithm, the adaptive algorithm appropriately withheld VT/VF therapy for 76 of 216 true SVT episodes (i.e., incremental specificity of 35.2%). For the specific SVT episodes that were the targets for improvement by the adaptive ST algorithm (ST/AT with long PR intervals and ST/AT with intermittent atrial oversensing of far-field R waves), the adaptive algorithm reduced inappropriate therapy by 63.2%. (PACE 2003; 26:1189-1201).
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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