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HRV analysis: undependability of approximate entropy at locating optimum complexity in malnourished children

Published online by Cambridge University Press:  17 June 2021

David M. Garner
Affiliation:
Cardiorespiratory Research Group, Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Headington Campus, Gipsy Lane, Oxford, OX3 0BP, UK
Gláucia S. Barreto
Affiliation:
Faculdade de Tecnologia Intensiva. FATECI – Fortaleza, Ceará, Sao Paulo, Brazil
Vitor E. Valenti*
Affiliation:
Autonomic Nervous System Center, Sao Paulo State University, UNESP, Marília, Sao Paulo, Brazil
Franciele M. Vanderlei
Affiliation:
Department of Physiotherapy, Sao Paulo State University, UNESP, Presidente Prudente, Sao Paulo, Brazil
Andrey A. Porto
Affiliation:
Autonomic Nervous System Center, Sao Paulo State University, UNESP, Marília, Sao Paulo, Brazil
Luiz Carlos M. Vanderlei
Affiliation:
Department of Physiotherapy, Sao Paulo State University, UNESP, Presidente Prudente, Sao Paulo, Brazil
*
Author for correspondence: Vitor E. Valenti, Autonomic Nervous System Center, Sao Paulo State University, UNESP, Av. Hygino Muzzi Filho, 737. Mirante, 17.525-900 – Marilia, Sao Paulo, Brazil. Tel: +55 14 3402–1300. E-mail: vitor.valenti@unesp.br

Abstract

Introduction:

Approximate Entropy is an extensively enforced metric to evaluate chaotic responses and irregularities of RR intervals sourced from an eletrocardiogram. However, to estimate their responses, it has one major problem – the accurate determination of tolerances and embedding dimensions. So, we aimed to overt this potential hazard by calculating numerous alternatives to detect their optimality in malnourished children.

Materials and methods:

We evaluated 70 subjects split equally: malnourished children and controls. To estimate autonomic modulation, the heart rate was measured lacking any physical, sensory or pharmacologic stimuli. In the time series attained, Approximate Entropy was computed for tolerance (0.1→0.5 in intervals of 0.1) and embedding dimension (1→5 in intervals of 1) and the statistical significances between the groups by their Cohen’s ds and Hedges’s gs were totalled.

Results:

The uppermost value of statistical significance accomplished for the effect sizes for any of the combinations was −0.2897 (Cohen’s ds) and −0.2865 (Hedges’s gs). This was achieved with embedding dimension = 5 and tolerance = 0.3.

Conclusions:

Approximate Entropy was able to identify a reduction in chaotic response via malnourished children. The best values of embedding dimension and tolerance of the Approximate Entropy to identify malnourished children were, respectively, embedding dimension = 5 and embedding tolerance = 0.3. Nevertheless, Approximate Entropy is still an unreliable mathematical marker to regulate this.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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