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Cited by 161

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Evaluating the physiological significance of respiratory sinus arrhythmia: looking beyond ventilation–perfusion efficiency

Open access
Ben‐Tal, A., Shamailov, S. S., Paton, J. F. R.·2012·The Journal of Physiology

Abstract

Key points Respiratory sinus arrhythmia (RSA) is the variation of heart rate with breathing: heart rate increases during inspiration and decreases during expiration. RSA is seen in many species including humans where it is strongest in the young and fit. The loss of RSA has been linked with cardiac mortality; however, the function of RSA is presently unknown. One hypothesis proposed previously is that RSA allows for more efficient gas exchange between the lungs and the blood. Our theoretical study does not support this hypothesis. Instead, a new hypothesis is proposed and tested using computational tools – that RSA helps the heart do less work while maintaining healthy levels of blood gases. Of course, this new hypothesis needs to be further tested both experimentally and by using more sophisticated mathematical models, but if correct, it could explain why inducing RSA artificially in patients with cardiovascular disease improves their health.

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Registry

Crossref · 10.1113/jphysiol.2011.222422

Cites

7 of 7 references verified0 citation errors · 0 not checkable

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Metadata

Authors
Ben‐Tal, A., Shamailov, S. S., & Paton, J. F. R.
Venue
The Journal of Physiology
Publisher
Wiley
Published
2012-04-13
Volume
590
Issue
8
Pages
1989-2008
ISSN
  • 0022-3751 (ISSN-L)
  • 1469-7793
OpenAlex
W1580490094
Cited by
161
References
7
FWCI
6.33
Type
journal article
Language
en
Open access
green

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.