Single diagnostic pacing maneuver for supraventricular tachycardia

Veenhuyzen, George D.; Coverett, Kelly; Quinn, F. Russell; Sapp, John L.; Gillis, Anne M.; Sheldon, Robert S.; Exner, Derek V.; Mitchell, L. Brent

doi:10.1016/j.hrthm.2008.04.010

Cited by 38 publications

(47 citation statements)

References 19 publications

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“…Entrainment through basal RV pacing away from the septum may produce prolonged PPI-TCL intervals in the absence of a septal pathway owing to the distance of the RV base from the AV node (activation occurs retrogradely through the distal His-Purkinje system) and has been found to be superior to apical entrainment for diagnostic purposes. 37 Recently, differential entrainment from the apex or the basal area of the RV was investigated. 38 A differential (between base and apex) corrected PPI-TCL Ͼ30 ms or a differential VA interval Ͼ20 ms predicted AVNRT very reliably ( Figure 5).…”

Section: Tachycardia Entrainmentmentioning

confidence: 99%

Atrioventricular Nodal Reentrant Tachycardia

2010

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A trioventricular nodal reentrant tachycardia (AVNRT) represents the most common regular supraventricular arrhythmia in humans. 1 The precise anatomic site and nature of the pathways involved have not yet been established, and several attempts to provide a reasonable hypothesis based on anatomic or anisotropic models have been made. 2 There has been considerable evidence that the right and left inferior extensions of the human atrioventricular (AV) node and the atrionodal inputs they facilitate may provide the anatomic substrate of the slow pathway, and a comprehensive model of the tachycardia circuit for all forms of AVNRT based on the concept of atrionodal inputs has been proposed. 2 Still, however, the circuit of AVNRT remains elusive. Recently, time-honored conventional schemes for the diagnosis and classification of the various forms of the arrhythmia have been refuted in part by evolving evidence. Recognition of the various types of AVNRT is important, however, to expedite diagnosis and allow implementation of appropriate ablation therapy without complications. We present an update on AVNRT with a particular emphasis on electrophysiological criteria used for the differential diagnosis of regular, supraventricular tachycardias. ECG PresentationTypically, AVNRT is a narrow-complex tachycardia, ie, QRS duration Ͻ120 ms, unless aberrant conduction, which is usually of the right bundle-branch type, or a previous conduction defect exists. Tachycardia-related ST depression and RR-interval variation may be seen. RR alternans in AVNRT has been attributed to the proposed model of a figure of 8 reentry with continuous crossing over of antegrade activation through an inferior input to the contralateral superior input via the node. 2 In the typical form of AVNRT (slow-fast), abnormal (retrograde) PЈ waves are constantly related to the QRS and in the majority of cases are indiscernible or very close to the QRS complex (RPЈ/RR Ͻ0.5). Thus, PЈ waves are either masked by the QRS complex or seen as a small terminal PЈ wave that is not present during sinus rhythm (Figure 1). In the atypical form of AVNRT (fast-slow), PЈ waves are clearly visible before the QRS, ie, RPЈ/PЈR Ͼ0.75 (Figure 2), denoting a "long RP tachycardia," and are negative in leads II, III, aVF, and V 6 but positive in V 1 . PЈ waves are shallow in the inferior leads in the rare form of anterior fast-slow AVNRT. 3 Although AV dissociation is usually not seen, it can occur because neither the atria or the ventricles are necessary for the reentry circuit. If the tachycardia is initiated by atrial ectopic beats, the initial (ectopic) PЈ wave usually differs from the subsequent (retrograde) PЈ waves (Figure 1).

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Section: Tachycardia Entrainmentmentioning

confidence: 99%

Atrioventricular Nodal Reentrant Tachycardia

2010

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“…Usually, a combined anatomical and mapping approach is employed with ablation lesions delivered at the inferior or mid part of the triangle of Koch. 60,61 Multicomponent atrial electrograms or low amplitude potentials, although not specific for identification of slow pathway -SA-VA and cPPI-TCL intervals [44][45][46][47] -Differential entrainment or cessation 48 Cumbersome Delta HA during V Pre-excitation index 49 Differential entrainment 58 pacing and tachycardia 36 Entrainment VHA pattern 37 -Anterograde His capture 50 Para-Hisian pacing 38 -Progressive fusion during or after the transition zone 51,52 Induction of retrograde Delta HA during entrainment RBBB 39 and tachycardia 53 SA init -VA and cPPI init --Para-Hisian entrainment [54][55][56] TCL conduction, are successfully used to guide ablation at these areas.…”

Section: Ablationmentioning

confidence: 99%

Classification, Electrophysiological Features and Therapy of Atrioventricular Nodal Reentrant Tachycardia

Katritsis

Josephson

2016

Arrhythmia &Amp; Electrophysiology Review

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Atrioventricular nodal reentrant tachycardia (AVNRT) denotes re-entry in the area of the AV node, and represents the most common regular arrhythmia in the human.1 Although several models have been proposed to explain the mechanism of the arrhythmia in the context of the complex anatomy and the anisotropic properties of the atrioventricular (AV) node and its atrial extensions (see Figure 1), 2 the actual circuit of AVNRT still remains elusive. Recent studies suggest a three-dimensional AV node with greater variability in the space constant of tissue and poor gap junction connectivity due to differential expression of connexin isoforms, that provide an explanation of dual conduction and nodal reentrant arrhythmogenesis. 3,4 AV junctional arrhythmias are presented in Table 1. Classification schemes for AVNRT have been mainly based on the conventional concept of longitudinally dissociated dual AV nodal pathways that conduct around a central obstacle (see Table 2).In typical slow-fast AVNRT the onset of atrial activation appears prior to, at the onset, or just after the QRS complex, thus maintaining an atrial-His/His-atrial ratio, AH/HA >1. The HA interval is usually <70 ms, measured from earliest deflection of the His bundle activation to the earliest rapid deflection of the atrial activation in the His bundle electrogram, and the VA interval, measured from the onset of ventricular activation on surface ECG to the earliest rapid deflection of the atrial activation on the His bundle electrogram, is <60 ms. 1,5,6 In atypical, fast-slow form of atypical AVNRT, the retrograde atrial electrogram begins after ventricular activation with an AH/HA ratio <1. The HA interval is prolonged, ≥70 msec, and the VA interval is ≥60 msec. 5,6 The atypical, slow-slow form, represents, by definition, an arrhythmia utilising two slow pathways. The AH/HA ratio is ≥1 but the HA interval is ≥70 msec, and the AH interval exceeds 200 ms. [7][8][9] There are several inherent limitations of this classification. The distinction between fast-slow and slow-slow atypical AVNRT is often arbitrary in view of the lack of a unanimously accepted definition. In order to establish the diagnosis of a truly fast-slow form, it has been proposed that the AH interval should be less than 185 ms 10 or 200 ms. 6 This criterion, however, has not been adopted by other investigators. 11-13Thus, tachycardias with a relatively prolonged AH interval but an AH/ HA ratio <1 cannot be reliably classified as either fast-slow or slow-slow (see Figure 2). Furthermore, the term 'fast-slow' implies that the fast component of slow-fast AVNRT is the same as the fast in the fast-slow type. There is now evidence that this is not the case in patients who present with both types of tachycardia.14,15 Typical slow-fast and atypical fast-slow AVNRT appear to utilise different anatomical pathways for fast conduction. In addition, electrophysiological behaviour compatible with multiple pathways may also be seen, and in some patients, several forms of AVNRT may be inducible at electrophy...

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“…In some patients, the existence of an accessory pathway (AcP) -an abnormal conductive pathway between the atria and ventricles -creates a substrate for macroreentrant supraventricular arrhythmia. Boyle et al [33] used models with and without AcPs to identify optimal sites for overdrive pacing, a technique used to distinguish AcP-mediated arrhythmia from other tachyardias [125]. As shown in Fig.…”

Section: Pro-arrhythmic Effects Of the Cardiac Conduction Systemmentioning

confidence: 99%

Cardiac Arrhythmias: Mechanistic Knowledge and Innovation from Computer Models

Trayanova

Boyle

2015

MS&A

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Computational simulation is increasingly recognized as an integral aspect of modern cardiovascular research. Realistic and biophysically detailed models of the cardio-circulatory system can help interpret complex experimental observations, dissect underlying mechanisms, and explain emerging organ-scale phenomena resulting from subtle changes at the tissue, cellular, and/or sub-cellular scales. This chapter provides an overview of recent advances in the simulation of cardiac electrical behavior, focusing specifically on detailed models of the initiation, perpetuation, and termination of ventricular arrhythmias, including fibrillation. The development and validation of such models has opened several noteworthy avenues of research, including close scrutiny of arrhythmia dynamics in healthy and diseased hearts, dissection of arrhythmogenic and cardioprotective properties of specialized cardiac tissue regions such as the Purkinje system, and exploration of emerging paradigms for anti-arrhythmia treatment, such as optogenetics. Excitingly, the clinical community is currently taking the first steps towards using patient-specific ventricular models to stratify arrhythmia risk, personalize treatment planning, and optimize device placement for difficult or unusual procedures.

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Single diagnostic pacing maneuver for supraventricular tachycardia

Cited by 38 publications

References 19 publications

Atrioventricular Nodal Reentrant Tachycardia

Atrioventricular Nodal Reentrant Tachycardia

Classification, Electrophysiological Features and Therapy of Atrioventricular Nodal Reentrant Tachycardia

Cardiac Arrhythmias: Mechanistic Knowledge and Innovation from Computer Models

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