Evidence map›Paper›PMID 33435378›Full record

ArticleEntropy (Basel, Switzerland)2021

Entropy Analysis of COVID-19 Cardiovascular Signals.

Dragana Bajić, Vlado Đajić, Branislav Milovanović

Open access · goldAbstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

13 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
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  6. Review
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  8. Article
  9. Complexity of COVID-19 Dynamics.Entropy (Basel, Switzerland) · 2021
    Article
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  12. Review
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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

3 authors at 3 institutions in 2 countries.

Dragana BajićFaculty of Technical Sciences, University of Novi Sad, Novi Sad 21000, Serbia.ORCID 0000-0002-4662-7939
Vlado ĐajićNeurology Clinic, University Clinical Centre of the Republic of Srpska, 78000 Banja Luka, Bosnia and Herzegovina.
Branislav MilovanovićFaculty of Medicine, University of Belgrade, Belgrade 11000, Serbia.
University clinical center of Republika Srpska · BAUniversity of Belgrade · RSUniversity of Novi Sad · RS

Funding

Ministry of education, science and technology development, Serbia 451-03-68/2020-14/200156 (TR32040)Science Fund of Republic of Serbia COVANSA
6 · The paper itself

Abstract

The world has faced a coronavirus outbreak, which, in addition to lung complications, has caused other serious problems, including cardiovascular. There is still no explanation for the mechanisms of coronavirus that trigger dysfunction of the cardiac autonomic nervous system (ANS). We believe that the complex mechanisms that change the status of ANS could only be solved by advanced multidimensional analysis of many variables, obtained both from the original cardiovascular signals and from laboratory analysis and detailed patient history. The aim of this paper is to analyze different measures of entropy as potential dimensions of the multidimensional space of cardiovascular data. The measures were applied to heart rate and systolic blood pressure signals collected from 116 patients with COVID-19 and 77 healthy controls. Methods that indicate a statistically significant difference between patients with different levels of infection and healthy controls will be used for further multivariate research. As a result, it was shown that a statistically significant difference between healthy controls and patients with COVID-19 was shown by sample entropy applied to integrated transformed probability signals, common symbolic dynamics entropy, and copula parameters. Statistical significance between serious and mild patients with COVID-19 can only be achieved by cross-entropies of heart rate signals and systolic pressure. This result contributes to the hypothesis that the severity of COVID-19 disease is associated with ANS disorder and encourages further research.

Indexed as

composite multiscale entropycopulaCOVID-19dependency structuressample entropy

Identifiers

PMID33435378
PMCPMC7826611
OpenAlexW3121088591

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.