Document Detail


Automatic sensor algorithms expedite pacemaker follow-ups.
MedLine Citation:
PMID:  12687817     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Demo Klonis; Xiaozheng Zhang; Umesh Patel; Sajad Gulamhusein; Jagdish Patel; Handre Hurwit; Dorothy Banish; Dave Marco
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Publication Detail:
Type:  Clinical Trial; Journal Article; Randomized Controlled Trial; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Pacing and clinical electrophysiology : PACE     Volume:  26     ISSN:  0147-8389     ISO Abbreviation:  Pacing Clin Electrophysiol     Publication Date:  2003 Jan 
Date Detail:
Created Date:  2003-04-11     Completed Date:  2003-07-03     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  7803944     Medline TA:  Pacing Clin Electrophysiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  225-8     Citation Subset:  IM    
Affiliation:
LaBette County Medical Center, Parsons, 1902 S. US Hwy 59, Parsons, KS 67357, USA. dklonis@joplin.com
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MeSH Terms
Descriptor/Qualifier:
Aged
Algorithms*
Cardiac Pacing, Artificial / methods*
Female
Humans
Male
Prospective Studies

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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