Application of the Entropy of Approximation for the nonlinear characterization in patients with Chagas Disease

Miguel Angel Vizcardo Cornejo, A. Ravelo, M. Manrique, P. Gomis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Chagas disease American trypanosomiasis is caused by a flagellated parasite: Trypanosoma cruzi, transmitted by an insect of the genus Triatoma and also by blood transfusions. In Latin America, the number of infected people is approximately 6 million, with a population exposed to the risk of infection of 550000. It is our interest to develop a non-invasive and low-cost methodology, capable of detecting any early cardiac alteration that also allows us to see dysautononia or dysfunction within 24 hours and with this it could be used to detect any cardiac alteration caused by T early Cruzi. For this, we analyzed the 24- hour Holter ECG records in 107 patients with ECG abnormalities (CH2), 102 patients without ECG alterations (CH1) who had positive serological results for Chagas disease and 83 volunteers without positive serological results for Chagas disease (CONTROL). Approximate entropy was used to quantify the regularity of electrocardiograms (ECG) in the three groups. We analyzed 288 ECG segments per patient. Significant differences were found between the CONTROL-CH1, CONTROL-CH2 and CH1- CH2 groups.

Original languageEnglish
Title of host publication2019 Computing in Cardiology, CinC 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728169361
DOIs
StatePublished - Sep 2019
Event2019 Computing in Cardiology, CinC 2019 - Singapore, Singapore
Duration: 8 Sep 201911 Sep 2019

Publication series

NameComputing in Cardiology
Volume2019-September
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

Conference2019 Computing in Cardiology, CinC 2019
Country/TerritorySingapore
CitySingapore
Period8/09/1911/09/19

Bibliographical note

Publisher Copyright:
© 2019 Creative Commons.

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