High incidence of pacemaker syndrome in patients with sinus node dysfunction treated with ventricular-based pacing in the Mode Selection Trial (MOST).

OBJECTIVES: We evaluated the incidence, predictors, and treatment of pacemaker syndrome in patients with sinus node dysfunction treated with ventricular-based (VVIR) pacing in the Mode Selection Trial (MOST). BACKGROUND: Pacemaker syndrome, or intolerance to VVIR pacing, consists of cardiovascular signs and symptoms induced by VVIR pacing. METHODS: The definition of pacemaker syndrome required that a patient with single-chamber VVIR pacing develop either congestive signs and symptoms associated with retrograde conduction during VVIR pacing or a >or=20 mm Hg reduction of systolic blood pressure during VVIR pacing, associated with reproducible symptoms of weakness, lightheadedness, or syncope. RESULTS: Of 996 patients randomized to VVIR pacing, 182 (18.3%) met criteria for pacemaker syndrome in follow-up. Pacemaker syndrome occurred early in most patients (13.8% at 6 months, 16.0% at 1 year, increasing to 19.7% at 4 years). Baseline univariate predictors of pacemaker syndrome included a lower sinus rate and higher programmed pacemaker rate. Previous heart failure, ejection fraction, and drop in systolic blood pressure with VVIR pacing at implantation did not predict the development of pacemaker syndrome. Post-implantation predictors of pacemaker syndrome were a higher percentage of paced beats, higher programmed low rate, and slower underlying spontaneous sinus rate. Quality of life decreased at the time of diagnosis of pacemaker syndrome and improved with reprogramming to atrial-based pacing. CONCLUSIONS: Severe pacemaker syndrome developed in nearly 20% of VVIR-paced patients and improved with reprogramming to the dual-chamber pacing mode. Because prediction of pacemaker syndrome is difficult, the only way to prevent pacemaker syndrome is to implant atrial-based pacemakers in all patients.

Duke Scholars

Author Manesh Raman Patel Medicine, Cardiology

Author Kerry L. Lee Biostatistics & Bioinformatics, Division of Biostatistics