Premium
Optimization of Pacing Algorithms to Prevent and Treat Supraventricular Tachyarrhythmias
Author(s) -
RICCI RENATO P.,
BORIANI GIUSEPPE,
GRAMMATICO ANDREA,
SANTINI MASSIMO
Publication year - 2006
Publication title -
pacing and clinical electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.686
H-Index - 101
eISSN - 1540-8159
pISSN - 0147-8389
DOI - 10.1111/j.1540-8159.2006.00484.x
Subject(s) - medicine , supraventricular arrhythmia , cardiac pacing , supraventricular tachycardia , algorithm , cardiology , tachycardia , atrial fibrillation , computer science
Preventive atrial pacing and antitachycardia pacing have been proposed for the treatment of atrial fibrillation and associated arrhythmias in patients with indications for device implantation. Preventive algorithms provide overdrive atrial pacing, reduction of atrial premature beats, and prevent short‐long atrial cycles with good patient tolerance. However, clinical trials testing preventive algorithms have shown contradictory results, possibly because of different trial designs, end points and patient populations. Factors probably responsible for neutral results include an already high atrial pacing percentage with the conventional DDDR mode, suboptimal atrial pacing site, and the deleterious effects of high percentages of right ventricular apical pacing. Atrial antitachycardia pacing therapies are effective in treating organized atrial tachyarrhythmias (that precede atrial fibrillation), mainly when delivered early after the onset particularly if the tachycardia is relatively slow. Antitachycardia pacing therapies might influence atrial fibrillation burden, but clinical studies have shown conflicting results about this issue. Consistent monitoring of atrial and ventricular rhythm including progression to persistent forms of atrial arrhythmias, variability of atrial arrhythmia recurrence patterns and onset mechanisms as well as antitachycardia pacing efficacy should be recorded in the stored device memory and used for optimal individual programming of these new functions.