Automatic sensor algorithms expedite pacemaker follow-ups.
OBJECTIVE: Automatic algorithms can be used to optimize settings and reduce the duration of pacemaker (PM) clinical follow-up. METHODS: This study prospectively evaluated 87 patients (74.2 +/- 10.7 years old, 52% men) who received PM with the Autoslope algorithm. Patients randomized to the manual group (group M, n = 43) performed a walk test and used sensor-indicated rate histograms to adjust the sensor, while in the automatic group (group A, n = 44) the sensor was automatically adjusted by the Autoslope. The patients were followed for 6 months. Follow-up time required for device interrogation and optimal sensor set-up, and the number of sensor parameters reprogramming were recorded. Changes in the patients' activity level were also evaluated. RESULTS: Group A required significantly less follow-up time than group M (9.4 +/- 5.7 min vs 13.5 +/- 8.5 min, P = 0.0002). The average number of sensor parameters reprogrammed during visits was significantly lower in group A than M (0.6 +/- 0.9 vs 0.9 +/- 1.3, P = 0.048). Threshold was adjusted 34.4% of the time in the sensor evaluations in group M versus 12.9% in group A (P = 0.0004). Although more patients in group A reported being more active, the changes in patients' activity level did not lead to increasing sensor setup time or number of parameter reprogramming in either group. CONCLUSIONS: Auto sensor adjustment required less time during routine PM clinical follow-up by reducing steps needed for manual sensor threshold adjustment.