KLONIS, D., et al.: 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.(PACE 2003; 26[Pt. II]:225–228)