Automatic sensor algorithms expedite pacemaker follow-ups

Individual optimization of pacing sensors improves exercise capacity without influencing quality of life

INTRODUCTION

Programmable pacemaker sensor features are frequently used in default setting. Limited data are available about the effect of sensor optimization on exercise capacity and quality of life (QOL). Influence of individual optimization of sensors on QOL and exercise tolerance was investigated in a randomized, single blind study in patients with VVIR, DDDR, or AAIR pacemakers.

METHODS

Patients with > or =75% pacing were randomized to optimized sensor settings (OSS) or default sensor setting (DSS). Standardized optimization was performed using three different exercise tests. QOL questionnaires (QOL-q: Hacettepe, Karolinska, and RAND-36) were used for evaluation of the sensor optimization. One month before and after optimization, exercise capacity using chronotropic assessment exercise protocol and the three QOL-q were assessed.

RESULTS

Fifty-four patients (26 male, 28 female) with a mean age of 65 +/- 16 years were enrolled in the study. In each group (OSS and DSS) 27 patients were included. One month after sensor optimization, the achieved maximal heart rate (HR) and metabolic workload (METS) were significantly higher in OSS when compared with DSS (124 +/- 28 bpm vs 108 +/- 20 bpm, P = 0.036; 7.3 +/- 4 METS vs 4.9 +/- 4 METS, P = 0.045). Highest HR and METS were achieved in patients with pacemakers with accessible sensor algorithms. In patients with automatic slope settings (33%), exercise capacity did not improve after sensor optimization. QOL did not improve in OSS compared with DSS.

CONCLUSION

After 1 month of individual optimization of rate response pacemakers, exercise capacity was improved and maximum HR increased, although QOL remained unchanged. Accessible pacemaker sensor algorithms are mandatory for individual optimization.