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Automatic Sensor Algorithms Expedite Pacemaker Follow-ups

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  • This study was supported by St. Jude Medical

Address for reprints: Demo Klonis, M.D., Labette County Medical Center, 1902 S. US Hwy 59, Parsons, KS 67357. Fax: (620) 421-5309; e-mail: dklonis@joplin.com

Abstract

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 ± 10.7years 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  minvs13.5 ± 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 ± 0.9vs0.9 ± 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)

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