ArticleJournal of diabetes investigation2015
Cardiovascular autonomic function analysis using approximate entropy from 24-h heart rate variability and its frequency components in patients with type 2 diabetes.
Article in Journal of diabetes investigation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Heart rate variability in type 2 diabetes mellitus: A systematic review and meta-analysis.PloS one · 2018Pooled it
- Associations between body composition and autonomic cardiorespiratory modulation in young adults.Physiological reports · 2026Article
- Doppler signal analysis of the tricuspid valve in healthy fetuses during the first trimester: a cohort study.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2026Article
- On Quantization Errors in Approximate and Sample Entropy.Entropy (Basel, Switzerland) · 2021Article
- Age induced interactions between heart rate variability and systolic blood pressure variability using approximate entropy and recurrence quantification analysis: a multiscale cross correlation analysis.Physical and engineering sciences in medicine · 2021Article
- Article
- On Entropy of Probability Integral Transformed Time Series.Entropy (Basel, Switzerland) · 2020Article
- Entropy Measures as Descriptors to Identify Apneas in Rheoencephalographic Signals.Entropy (Basel, Switzerland) · 2019Article
- A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.Medical & biological engineering & computing · 2019Article
- Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects.Entropy (Basel, Switzerland) · 2018Article
- Complexity Change in Cardiovascular Disease.International journal of biological sciences · 2017Review
- Heart rate variability based on risk stratification for type 2 diabetes mellitus.Einstein (Sao Paulo, Brazil)Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AIMS/
introductionThe principal aim of the present study was to investigate the cardiovascular autonomic system status of diabetes patients using approximate entropy (ApEn) extracted from 24-h heart rate variability (HRV) and its frequency components. MATERIALS AND
methodsA total of 29 healthy controls and 63 type 2 diabetes patients were included. Participants' 24-h HRV signals were recorded, and decomposed and reconstructed into four frequency components: high, low, very low and ultra low. The total 24-h HRV and its four components were divided into 24 1-h segments. ApEn values were extracted and statistically analyzed. Four traditional HRV indices, namely standard deviation of the RR intervals, root mean square of successive differences, coefficient of variance of RR intervals and ratio of low to high power of HRV, were also calculated.
resultsThe low-frequency component contained the most abundant non-linear information, so was potentially most suitable for studying the cardiovascular system status with non-linear methods. ApEn values extracted from low- and high-frequency components of healthy controls were higher than those of diabetes patients. Except for root mean square of successive differences, standard deviation of the RR intervals, low to high power of HRV and coefficient of variance of RR intervals of healthy controls were all higher than those of diabetes patients.
conclusionsThe results showed that ApEn contained information on disorders of autonomic system function of diabetes patients as traditional HRV indices in time and frequency domains. ApEn and three traditional indices showed accordance to some degree. Non-linear information in subcomponents of HRV was shown, which is potentially more effective for distinguishing healthy individuals and diabetes patients than that extracted from the total HRV. Compared with diabetes patients, the cardiovascular system of healthy controls showed information of higher complexity, and better regulation function in response to changes of environment.
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