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Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters

Overview of attention for article published in Frontiers in Physiology, January 2017
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Title
Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters
Published in
Frontiers in Physiology, January 2017
DOI 10.3389/fphys.2017.00010
Pubmed ID
Authors

Renata Miyabara, Karsten Berg, Jan F. Kraemer, Ovidiu C. Baltatu, Niels Wessel, Luciana A. Campos

Abstract

Objective: The aim of this study was to identify the most sensitive heart rate and blood pressure variability (HRV and BPV) parameters from a given set of well-known methods for the quantification of cardiovascular autonomic function after several autonomic blockades. Methods: Cardiovascular sympathetic and parasympathetic functions were studied in freely moving rats following peripheral muscarinic (methylatropine), β1-adrenergic (metoprolol), muscarinic + β1-adrenergic, α1-adrenergic (prazosin), and ganglionic (hexamethonium) blockades. Time domain, frequency domain and symbolic dynamics measures for each of HRV and BPV were classified through paired Wilcoxon test for all autonomic drugs separately. In order to select those variables that have a high relevance to, and stable influence on our target measurements (HRV, BPV) we used Fisher's Method to combine the p-value of multiple tests. Results: This analysis led to the following best set of cardiovascular variability parameters: The mean normal beat-to-beat-interval/value (HRV/BPV: meanNN), the coefficient of variation (cvNN = standard deviation over meanNN) and the root mean square differences of successive (RMSSD) of the time domain analysis. In frequency domain analysis the very-low-frequency (VLF) component was selected. From symbolic dynamics Shannon entropy of the word distribution (FWSHANNON) as well as POLVAR3, the non-linear parameter to detect intermittently decreased variability, showed the best ability to discriminate between the different autonomic blockades. Conclusion: Throughout a complex comparative analysis of HRV and BPV measures altered by a set of autonomic drugs, we identified the most sensitive set of informative cardiovascular variability indexes able to pick up the modifications imposed by the autonomic challenges. These indexes may help to increase our understanding of cardiovascular sympathetic and parasympathetic functions in translational studies of experimental diseases.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 22%
Student > Bachelor 3 17%
Researcher 3 17%
Student > Doctoral Student 2 11%
Student > Postgraduate 2 11%
Other 2 11%
Unknown 2 11%
Readers by discipline Count As %
Medicine and Dentistry 6 33%
Neuroscience 2 11%
Social Sciences 2 11%
Economics, Econometrics and Finance 1 6%
Psychology 1 6%
Other 4 22%
Unknown 2 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2017.
All research outputs
#17,870,599
of 22,947,506 outputs
Outputs from Frontiers in Physiology
#7,195
of 13,711 outputs
Outputs of similar age
#292,605
of 419,040 outputs
Outputs of similar age from Frontiers in Physiology
#134
of 230 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,711 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 419,040 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 230 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.