Evidence map›Paper›PMID 33285890›Full record

ArticleEntropy (Basel, Switzerland)2020

Association between Mean Heart Rate and Recurrence Quantification Analysis of Heart Rate Variability in End-Stage Renal Disease.

Martín Calderón-Juárez, Gertrudis Hortensia González-Gómez, Juan C Echeverría, Héctor Pérez-Grovas, Claudia Lerma

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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

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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

5 authors.

Martín Calderón-JuárezFaculty of Medicine, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
Gertrudis Hortensia González-GómezDepartment of Physics, Faculty of Sciences, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.ORCID 0000-0002-8187-8573
Juan C EcheverríaDepartment of Electrical Engineering, Universidad Autónoma Metropolitana, Unidad Iztapalapa, Mexico City 09340, Mexico.
Héctor Pérez-GrovasDepartment of Nephrology, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City 14080, Mexico.
Claudia LermaDepartment of Electromechanical Instrumentation, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City 14080, Mexico.ORCID 0000-0002-4679-7751

Funding

Universidad Nacional Autónoma de México PAPIIT-RN2163188
6 · The paper itself

Abstract

Linear heart rate variability (HRV) indices are dependent on the mean heart rate, which has been demonstrated in different models (from sinoatrial cells to humans). The association between nonlinear HRV indices, including those provided by recurrence plot quantitative analysis (RQA), and the mean heart rate (or the mean cardiac period, also called meanNN) has been scarcely studied. For this purpose, we analyzed RQA indices of five minute-long HRV time series obtained in the supine position and during active standing from 30 healthy subjects and 29 end-stage renal disease (ESRD) patients (before and after hemodialysis). In the supine position, ESRD patients showed shorter meanNN (i.e., faster heart rate) and decreased variability compared to healthy subjects. The healthy subjects responded to active standing by shortening the meanNN and decreasing HRV indices to reach similar values of ESRD patients. Bivariate correlations between all RQA indices and meanNN were significant in healthy subjects and ESRD after hemodialysis and for most RQA indices in ESRD patients before hemodialysis. Multiple linear regression analyses showed that RQA indices were also dependent on the position and the ESRD condition. Then, future studies should consider the association among RQA indices, meanNN, and these other factors for a correct interpretation of HRV.

Indexed as

active standingheart rate variabilityhemodialysisrecurrence plot analysis

Identifiers

PMID33285890
PMCPMC7516420

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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.