The aim of this study is to assess the risk of dynamical diseases in malnourished children. This is achieved by the application of novel chaotic global techniques to the RR-intervals of the electrocardiogram (ECG) in the cohort. Heart Rate Variability (HRV) is an inexpensive and non-invasive tool to measure the autonomic impulses. Here there has been a decrease in chaotic response of HRV. Seventy children were divided into equal groups and the HRV monitored for 20-25 minutes. The Chaos Forward Parameter (CFP) which applies all three chaotic global parameters is suggested to be the most robust algorithm. These three parameters are high spectral entropy (hsEntropy), high spectral detrended fluctuation analysis (hsDFA) and spectral multi-taper method (sMTM). hsEntropy is a function of the irregularity of amplitude and frequency of the power spectrums peaks. It is derived by applying Shannon entropy to the multi-taper method power spectrum. To derive hsDFA we calculate the spectral adaptation in exactly the same way as for hsEntropy using an adaptive multi-taper method power spectrum with the same settings; but DFA rather than Shannon entropy is the algorithm applied. sMTM is the area between the multi-taper method power spectrum and the baseline. After Anderson-Darling and Lilliefors tests of normality; Kruskal-Wallis was used for the statistical analysis, with the level of significance set at (p < 0.01). Principal Component Analysis (PCA) identified two components representing 100% of total variance. Autonomic imbalance measured as HRV and an increased cardiovascular risk are described for overweight children as well as for malnourished and those with anorexia nervosa. The relationship between malnourishment and complexity measures is useful in the risk assessment of dynamical diseases associated with the condition. This is supportive in treatments, assisting the determination of the level of dietary or pharmacological intervention especially in related dynamical diseases.
Malnourished children present changes in cardiac autonomic modulation, characterized by reductions in both sympathetic and parasympathetic activity, as well as increased heart rate and decreased blood pressure.
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.
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