title: Clinical evaluation of pacemaker automatic capture management and atrioventricular interval extension algorithm.
abstract: OBJECTIVE
  The present study was to assess the accuracy of automatic atrial and ventricular capture management (ACM and VCM) in determining pacing threshold and the performance of a second-generation automatic atrioventricular (AV) interval extension algorithm for reducing unnecessary ventricular pacing.
  
  
  RESULTS
  A total of 398 patients at 32 centres who received an EnPulse dual-chamber pacing/dual-chamber adaptive rate pacing pacemaker (Medtronic, Minneapolis, MN, USA) were enrolled. The last amplitude thresholds as measured by ACM and VCM prior to the 6-month follow-up were compared with manually measured thresholds. Device diagnostics were used to evaluate ACM and VCM and the percentage of ventricular pacing with and without the AV extension algorithm. Modelling was performed to assess longevity gains relating to the use of automaticity features. Atrial and ventricular capture management performed accurately and reliably provided complete capture management in 97% of studied patients. The AV interval extension algorithm reduced the median per cent of right ventricular pacing in patients with sinus node dysfunction from 99.7 to 1.5% at 6-month follow-up and in patients with intermittent AV block (excluding persistent 3° AV block) from 99.9 to 50.2%. On the basis of validated modelling, estimated device longevity could potentially be extended by 1.9 years through the use of the capture management and AV interval extension features.
  
  
  CONCLUSIONS
  Both ACM and VCM features reliably measured thresholds in nearly all patients; the AV extension algorithm significantly reduced ventricular pacing; and the use of pacemaker automaticity features potentially extends device longevity.
authors.affiliation: Clinical EP Lab and Arrhythmic Center,  Fuwai Hospital, Beijing,  China.
authors.forename: Ke-ping
authors.initials: KP
authors.lastname: Chen
authors.forename: Geng
authors.initials: G
authors.lastname: Xu
authors.forename: Shulin
authors.initials: S
authors.lastname: Wu
authors.forename: Baopeng
authors.initials: B
authors.lastname: Tang
authors.forename: Li
authors.initials: L
authors.lastname: Wang
authors.forename: Shu
authors.initials: S
authors.lastname: Zhang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D001283:Atrioventricular Node / Q000503:physiopathology*; D001331:Automation; D002304:Cardiac Pacing, Artificial; D002681:China; D004562:Electrocardiography; D004867:Equipment Design; D005260:Female; D006352:Heart Ventricles / Q000503:physiopathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D010138:Pacemaker, Artificial; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors