title: Advanced rhythm discrimination for implantable cardioverter defibrillators using electrogram vector timing and correlation.
abstract: BACKGROUND
  Discrimination of ventricular and supraventricular arrhythmias remains one of the major challenges for appropriate implantable defibrillator (ICD) therapy delivery. The electrogram vector timing and correlation (VTC) algorithm was developed for such rhythm discrimination. The VTC algorithm differentiates normally conducted supraventricular beats from abnormally conducted ventricular beats by comparing the timing and correlation of rate and shock channel electrograms.
  
  
  RESULTS
  Rate and shock channel electrograms of sinus rhythm and induced arrhythmias were collected from 93 patients during ICD placement. The algorithm was developed using data from 50 patients and prospectively tested in a software model with the remaining 43 patients. A sinus rhythm reference was formed by averaging complexes of the shock channel signal aligned by the peak amplitude of the rate channel. Eight features measuring the amplitude and timing of shock channel signal characteristics were extracted from the reference for comparison. When a high-rate rhythm was detected, the VTC algorithm computed the correlation of the arrhythmia complex features with the reference. Rhythms with a sufficient number of uncorrelated beats were classified as ventricular tachycardia (VT). In a dual-chamber implementation, the VTC algorithm is integrated with ventricular and atrial rate comparison (V>A) and stability above an atrial fibrillation rate threshold. The test set consisted of 117 arrhythmias. Dual-chamber sensitivity was 100% (81/81 VT) and specificity was 97% (35/36 supraventricular tachycardia). Single-chamber analysis demonstrated 99% sensitivity and 97% specificity.
  
  
  CONCLUSIONS
  The VTC algorithm demonstrated high sensitivity and specificity in discriminating between ventricular and supraventricular arrhythmias.
authors.affiliation: Division of Cardiology, Medical University of South Carolina, Charleston, South Carolina 29425, USA. goldmr@musc.edu
authors.forename: Michael R
authors.initials: MR
authors.lastname: Gold
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Shorofsky
authors.forename: Julie A
authors.initials: JA
authors.lastname: Thompson
authors.forename: Jaeho
authors.initials: J
authors.lastname: Kim
authors.forename: Mark
authors.initials: M
authors.lastname: Schwartz
authors.forename: Joe
authors.initials: J
authors.lastname: Bocek
authors.forename: Eric G
authors.initials: EG
authors.lastname: Lovett
authors.forename: William
authors.initials: W
authors.lastname: Hsu
authors.forename: Milton M
authors.initials: MM
authors.lastname: Morris
authors.forename: Douglas J
authors.initials: DJ
authors.lastname: Lang
mesh_terms: D000368:Aged; D000465:Algorithms; D000818:Animals; D001145:Arrhythmias, Cardiac / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology / Q000628:therapy*; D017147:Defibrillators, Implantable; D003937:Diagnosis, Differential; D004594:Electrophysiology; D006339:Heart Rate; D006801:Humans; D051379:Mice; D008875:Middle Aged; D011446:Prospective Studies; D012680:Sensitivity and Specificity