Evidence map›Paper›PMID 33419293›Full record

ArticleEntropy (Basel, Switzerland)2020

Bivariate Entropy Analysis of Electrocardiographic RR-QT Time Series.

Bo Shi, Mohammod Abdul Motin, Xinpei Wang, Chandan Karmakar, Peng Li

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. 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

5 authors.

Bo ShiSchool of Medical Imaging, Bengbu Medical College, Bengbu 233030, China.ORCID 0000-0003-0445-0095
Mohammod Abdul MotinDepartment of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC 3110, Australia.ORCID 0000-0003-1618-3772
Xinpei WangSchool of Control Science and Engineering, Shandong University, Jinan 250061, China.
Chandan KarmakarSchool of Information Technology, Deakin University, Geelong, VIC 3225, Australia.ORCID 0000-0003-1814-0856
Peng LiDivision of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0002-4684-4909

Funding

National Natural Science Foundation of China 31600862National Natural Science Foundation of China 61601263the ''512'' Outstanding Talents Fostering Project of Bengbu Medical College 2020-42-3-12the Scientific Research Innovation Project of Bengbu Medical College BYKC201905
6 · The paper itself

Abstract

QT interval variability (QTV) and heart rate variability (HRV) are both accepted biomarkers for cardiovascular events. QTV characterizes the variations in ventricular depolarization and repolarization. It is a predominant element of HRV. However, QTV is also believed to accept direct inputs from upstream control system. How QTV varies along with HRV is yet to be elucidated. We studied the dynamic relationship of QTV and HRV during different physiological conditions from resting, to cycling, and to recovering. We applied several entropy-based measures to examine their bivariate relationships, including cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), cross conditional entropy (XCE), and joint distribution entropy (JDistEn). Results showed no statistically significant differences in XSampEn, XFuzzyEn, and XCE across different physiological states. Interestingly, JDistEn demonstrated significant decreases during cycling as compared with that during the resting state. Besides, JDistEn also showed a progressively recovering trend from cycling to the first 3 min during recovering, and further to the second 3 min during recovering. It appeared to be fully recovered to its level in the resting state during the second 3 min during the recovering phase. The results suggest that there is certain nonlinear temporal relationship between QTV and HRV, and that the JDistEn could help unravel this nuanced property.

Indexed as

ambulatory monitoringcross entropyjoint distribution entropyRR–QT relationship

Identifiers

PMID33419293
PMCPMC7766536

What OpenQuestion holds

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Registered trials

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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.