Literature DB >> 15519267

Verification of implantable cardioverter defibrillator (ICD) interventions by nonlinear analysis of heart rate variability -- preliminary results.

Andrzej Przybylski1, Rafał Baranowski, Jan Jacek Zebrowski, Hanna Szwed.   

Abstract

AIMS: Conventional ICD algorithms yield approximately 10-30% of spurious interventions. Our aim was to check whether nonlinear dynamics methods might be useful in the verification of ICD interventions. METHODS AND
RESULTS: We extracted 190 consecutive RR files (approximately 2000-9000 RR intervals long) from the ICDs of 70 patients (36 with coronary artery disease, 8 with hypertrophic cardiomyopathy, 19 with dilated cardiomyopathy and 7 with other diseases). The 3D phase space trajectories in delay coordinates, window pattern entropy, and algorithmic complexity of the RR intervals were examined within a 50 beat sliding window. Data were not filtered for arrhythmia and artefacts. Of the 83 recordings with appropriate interventions 79 were correctly recognised in a blind test. Two interventions were not identified in patients with fast atrial fibrillation and two in cases of complex and frequent forms of arrhythmia. There were nine spurious interventions. In all except one case (atrial fibrillation with a fast ventricular response) the analysis by nonlinear methods showed that the intervention was not necessary. All of the 98 control recordings were correctly identified in the blind test.
CONCLUSIONS: The results show that nonlinear dynamics methods may be used to supplement the existing ICD detection algorithms to enhance the detection success rate.

Entities:  

Mesh:

Year:  2004        PMID: 15519267     DOI: 10.1016/j.eupc.2004.08.001

Source DB:  PubMed          Journal:  Europace        ISSN: 1099-5129            Impact factor:   5.214


  2 in total

Review 1.  Movement variability and the use of nonlinear tools: principles to guide physical therapist practice.

Authors:  Regina T Harbourne; Nicholas Stergiou
Journal:  Phys Ther       Date:  2009-01-23

2.  Nonlinear analysis of the movement variability structure can detect aging-related differences among cognitively healthy individuals.

Authors:  Mehran Asghari; Hossein Ehsani; Audrey Cohen; Talia Tax; Jane Mohler; Nima Toosizadeh
Journal:  Hum Mov Sci       Date:  2021-05-20       Impact factor: 2.397

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.