Literature DB >> 9474682

Prevalence of supraventricular arrhythmias from the automated analysis of data stored in the DDD pacemakers of 617 patients: the AIDA study. The AIDA Multicenter Study Group. Automatic Interpretation for Diagnosis Assistance.

P Defaye1, F Dournaux, E Mouton.   

Abstract

The confirmation of the occurrence of supraventricular arrhythmias (SVAs) is possible only if a surface electrocardiogram (ECG) is recorded during an episode, or if SVAs occur during 24 h ambulatory monitoring (Holter). The automatic interpretation of memory functions in DDD pacemakers may be useful in this diagnostic task over longer periods of follow up. This hypothesis was tested in 384 men and 233 women (mean age = 70 +/- 11 years) who had received Chorus 6034/6035, 6234 or 7034 pacemakers (ELA Medical, Montrouge, France) with fall-back function in case of sustained SVAs. The Automatic Interpretation for Diagnostic Assistance (AIDA) algorithm included in these pacemakers was compared with 24 h Holters recorded simultaneously (D1) and with the clinical history of symptoms consistent with SVAs up to 28 days of follow up (D28). Indications for pacing were atrioventricular block (AVB) in 269 patients, sinus node dysfunction (SND) in 248, and AVB + SND in 100. SVAs were documented before implant in 199 patients (32%). Among the 617 patients included at D1, 76 (12.4%) developed at least one SVA episode, lasting between 1 min and 24 hours, simultaneously recorded on Holter and by AIDA with a 93.8% sensitivity and 94.2% specificity. Data from 354 patients were available for analysis at D28. AIDA diagnosed SVAs in 179 patients (50.6%), 104 of whom (65%) had remained asymptomatic and 117 of whom (65%) had had no SVA documented before implant. Among the 354 patients, AIDA diagnosed SVAs in 76 (21%) asymptomatic patients who had no known SVA before implant. The prevalence of SVA in our AVB population was higher than reported in previous studies: 89 patients (56.3%) with AVB had SVAs versus 90 patients (45.9%) with other diagnoses (p = 0.55). Furthermore atrial pacing was associated with fewer SVAs. These first clinical results of the AIDA study demonstrate that the memory functions of Chorus pacemakers and the AIDA software are reliable to analyze the prevalence of SVA at 1 month of follow-up. From a clinical point of view, AIDA is a valuable tool to evaluate the efficacy of antiarrhythmic therapy, particularly as it pertains to the prevention of stroke due to atrial fibrillation.

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Year:  1998        PMID: 9474682     DOI: 10.1111/j.1540-8159.1998.tb01098.x

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


  35 in total

1.  Quality of life in patients with silent atrial fibrillation.

Authors:  I Savelieva; M Paquette; P Dorian; B Lüderitz; A J Camm
Journal:  Heart       Date:  2001-02       Impact factor: 5.994

2.  No incremental benefit of multisite atrial pacing compared with right atrial pacing in patients with drug refractory paroxysmal atrial fibrillation.

Authors:  T Levy; S Walker; S Rex; J Rochelle; V Paul
Journal:  Heart       Date:  2001-01       Impact factor: 5.994

3.  Automatic atrial anti-tachy pacing for the termination of spontaneous atrial tachyarrhythmias: clinical experience with a novel dual-chamber pacemaker.

Authors:  D Vollmann; J Stevens; A B Buchwald; C Unterberg
Journal:  J Interv Card Electrophysiol       Date:  2001-12       Impact factor: 1.900

Review 4.  Clinical relevance of silent atrial fibrillation: prevalence, prognosis, quality of life, and management.

Authors:  I Savelieva; A J Camm
Journal:  J Interv Card Electrophysiol       Date:  2000-06       Impact factor: 1.900

5.  Prevalence and clinical implications of atrial fibrillation episodes detected by pacemaker in patients with sick sinus syndrome.

Authors:  H F Tse; C P Lau
Journal:  Heart       Date:  2005-03       Impact factor: 5.994

Review 6.  Management of atrial fibrillation--what are the possibilities of early detection with home monitoring?

Authors:  R P Ricci; M Russo; M Santini
Journal:  Clin Res Cardiol       Date:  2006       Impact factor: 5.460

Review 7.  Identification, diagnosis and assessment of atrial fibrillation.

Authors:  R I Dewar; G Y H Lip
Journal:  Heart       Date:  2006-09-04       Impact factor: 5.994

8.  [Not Available].

Authors:  R C Funck; B Kriebel; E Himmrich; W Hartung; W Dänschel; F Saborowski; H Kühnert; B Maisch
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2000-01

9.  A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation.

Authors:  David D McManus; Jinseok Lee; Oscar Maitas; Nada Esa; Rahul Pidikiti; Alex Carlucci; Josephine Harrington; Eric Mick; Ki H Chon
Journal:  Heart Rhythm       Date:  2012-12-06       Impact factor: 6.343

10.  The usefulness of minimal ventricular pacing and preventive AF algorithms in the treatment of PAF: the 'MinVPace' study.

Authors:  Rick A Veasey; Anita Arya; Nick Freemantle; John Silberbauer; Nikhil R Patel; Guy W Lloyd; A Neil Sulke
Journal:  J Interv Card Electrophysiol       Date:  2010-01-16       Impact factor: 1.900

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