Literature DB >> 23365823

Identifying increased risk of post-infarct people with diabetes using multi-lag Tone-Entropy analysis.

Chandan Karmakar1, Herbert Jelinek, Ahsan Khandoker, Mikko Tulppo, Timo Makikallio, Antti Kiviniemi, Heikki Huikuri, Marimuthu Palaniswami.   

Abstract

Diabetes mellitus is associated with multi-organ system dysfunction. One of the key causative factors is the increased blood sugar level that leads to an increase in free radical activity and organ damage including the cardiovascular and nervous system. Heart rhythm is extrinsically modulated by the autonomic nervous system and cardiac autonomic neuropathy or dysautonomia has been shown to lead to sudden cardiac death in people with diabetes due to the decrease in heart rate variability (HRV). Current algorithms for determining HRV describe only beat-to-beat variation and therefore do not consider the ability of a heart beat to influence a train of succeeding beats. Therefore mortality risk analysis based on HRV has often not been able to discern the presence of an increased risk. This study used a novel innovation of the tone-entropy algorithm by incorporating increased lag intervals and found that both the sympatho-vagal balance and total activity changed at larger lag intervals. Tone-Entropy was found to be better risk identifier of cardiac mortality in people with diabetes at lags higher than one and best at lag seven.

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Year:  2012        PMID: 23365823     DOI: 10.1109/EMBC.2012.6345862

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Multi-lag tone-entropy in neonatal stress.

Authors:  Matej Šapina; Chandan Kumar Karmakar; Karolina Kramarić; Matthieu Garcin; P David Adelson; Krešimir Milas; Marko Pirić; Dario Brdarić; John Yearwood
Journal:  J R Soc Interface       Date:  2018-09-19       Impact factor: 4.118

Review 2.  Complexity Change in Cardiovascular Disease.

Authors:  Chang Chen; Yu Jin; Iek Long Lo; Hansen Zhao; Baoqing Sun; Qi Zhao; Jun Zheng; Xiaohua Douglas Zhang
Journal:  Int J Biol Sci       Date:  2017-10-17       Impact factor: 6.580

  2 in total

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