Evidence map›Paper›PMID 23864905›Full record

ArticleComputational and mathematical methods in medicine2013

Multiscale cross-approximate entropy analysis as a measure of complexity among the aged and diabetic.

Hsien-Tsai Wu, Cyuan-Cin Liu, Men-Tzung Lo, Po-Chun Hsu, An-Bang Liu, Kai-Yu Chang, Chieh-Ju Tang

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The perils of being too stable: mood regulation in bipolar disorderJournal of psychiatry & neuroscience : JPN · 2018
    Article
  6. Article
  7. Complexity Change in Cardiovascular Disease.International journal of biological sciences · 2017
    Review
  8. Symmetry Analysis of Gait between Left and Right Limb Using Cross-Fuzzy Entropy.Computational and mathematical methods in medicine · 2016
    Article
  9. Review
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Hsien-Tsai WuDepartment of Electrical Engineering, National Dong Hwa University, No. 1, Section 2, Da Hsueh Road, Shoufeng, Hualien 97401, Taiwan. dsphans@mail.ndhu.edu.tw
Cyuan-Cin Liu
Men-Tzung Lo
Po-Chun Hsu
An-Bang Liu
Kai-Yu Chang
Chieh-Ju Tang
National Dong Hwa University · TWNational Central University · TWTzu Chi University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex fluctuations within physiological signals can be used to evaluate the health of the human body. This study recruited four groups of subjects: young healthy subjects (Group 1, n = 32), healthy upper middle-aged subjects (Group 2, n = 36), subjects with well-controlled type 2 diabetes (Group 3, n = 31), and subjects with poorly controlled type 2 diabetes (Group 4, n = 24). Data acquisition for each participant lasted 30 minutes. We obtained data related to consecutive time series with R-R interval (RRI) and pulse transit time (PTT). Using multiscale cross-approximate entropy (MCE), we quantified the complexity between the two series and thereby differentiated the influence of age and diabetes on the complexity of physiological signals. This study used MCE in the quantification of complexity between RRI and PTT time series. We observed changes in the influences of age and disease on the coupling effects between the heart and blood vessels in the cardiovascular system, which reduced the complexity between RRI and PTT series.

Indexed as

AdolescentAdultAgedAged, 80 and overAgingCardiovascular Physiological PhenomenaComputational BiologyComputer SimulationDiabetes Mellitus, Type 2ElectrocardiographyHeart RateHumansMiddle AgedModels, BiologicalModels, CardiovascularPulse Wave Analysis

Identifiers

PMID23864905
PMCPMC3705813
OpenAlexW2021816116

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.