A NEW CLASSIFICATION ALGORITHM FOR DISCRIMINATION OF VENTRICULAR FROMSUPRAVENTRICULAR TACHYCARDIA IN A DUAL-CHAMBER IMPLANTABLE CARDIOVERTER-DEFIBRILLATOR

New Atrioventricular Classification Algorithm. Introduction: The high incidence of inappropriate therapies due to supraventricular tachycard ia remains a major unsolved problem of implantable cardioverter defibr illators. We report a new detection formula for discrimination of vent ricular tachycardia from supraventricular tachycardia in a patient wit h a dual chamber implantable cardioverter defibrillator and a new atri oventricular classification algorithm. Methods and Results: The enhanc ed detection algorithm performs a stepwise arrhythmia analysis, The rh ythm is first classified on the basis of cycle length, Each episode is then classified as supraventricular or ventricular on the basis of at rioventricular association, stability of circle length, and origin of acceleration, Sophisticated diagnostic information is provided by atri oventricular markers and electrogram recordings. Successful discrimina tion of two spontaneous episodes of ventricular tachycardia and suprav entricular tachycardia is demonstrated. Conclusion: This new dual cham ber detection algorithm may significantly improve the specificity of t achyarrhythmia detection without sacrificing sensitivity, thereby redu cing the number of spurious shocks in patients with recurrent supraven tricular tachycardias. Further studies are needed to assess the sensit ivity and specificity of this detection algorithm.