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Cardiac surgery does not lead to loss of oscillatory components in circulatory signals
The circulatory system is oscillatory in its nature. Oscillatory components linked to physiological processes and underlying regulatory mechanisms are identifiable in circulatory signals. Autonomic regulation is essential for the system's ability to deal with external exposure, and the integrit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202984/ https://www.ncbi.nlm.nih.gov/pubmed/32378333 http://dx.doi.org/10.14814/phy2.14423 |
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author | Knai, Kathrine Aadahl, Petter Skjaervold, Nils K. |
author_facet | Knai, Kathrine Aadahl, Petter Skjaervold, Nils K. |
author_sort | Knai, Kathrine |
collection | PubMed |
description | The circulatory system is oscillatory in its nature. Oscillatory components linked to physiological processes and underlying regulatory mechanisms are identifiable in circulatory signals. Autonomic regulation is essential for the system's ability to deal with external exposure, and the integrity of oscillations may be considered a hallmark of a healthy system. Loss of complexity is seen as a consequence of several diseases and aging. Heart rate variability is known to decrease after cardiac surgery and remain reduced for up to 6 months. Oscillatory components of circulatory signals are linked to the system's overall complexity. We therefore hypothesize that the frequency distributions of circulatory signals show loss of oscillatory components after cardiac surgery and that the observed changes persist. We investigated the development of the circulatory frequency distributions of eight patients undergoing cardiac surgery by extracting three time series from conventional blood pressure and electrocardiography recordings: systolic blood pressure, heart rate, and amplitude of the electrocardiogram's R‐wave. Four 30‐min selections, representing key events of the perioperative course, were analyzed with the continuous wavelet transform, and average wavelet power spectra illustrated the circulatory frequency distributions. We identified oscillatory components in all patients and variables. Contrary to our hypothesis, they were randomly distributed through frequencies, patients, and situations, thus, not representing any reduction in the overall complexity. One patient showed loss of a 25‐s oscillation after surgery. We present a case where noise is misclassified as an oscillation, raising questions about the robustness of such analyses. |
format | Online Article Text |
id | pubmed-7202984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72029842020-05-07 Cardiac surgery does not lead to loss of oscillatory components in circulatory signals Knai, Kathrine Aadahl, Petter Skjaervold, Nils K. Physiol Rep Original Research The circulatory system is oscillatory in its nature. Oscillatory components linked to physiological processes and underlying regulatory mechanisms are identifiable in circulatory signals. Autonomic regulation is essential for the system's ability to deal with external exposure, and the integrity of oscillations may be considered a hallmark of a healthy system. Loss of complexity is seen as a consequence of several diseases and aging. Heart rate variability is known to decrease after cardiac surgery and remain reduced for up to 6 months. Oscillatory components of circulatory signals are linked to the system's overall complexity. We therefore hypothesize that the frequency distributions of circulatory signals show loss of oscillatory components after cardiac surgery and that the observed changes persist. We investigated the development of the circulatory frequency distributions of eight patients undergoing cardiac surgery by extracting three time series from conventional blood pressure and electrocardiography recordings: systolic blood pressure, heart rate, and amplitude of the electrocardiogram's R‐wave. Four 30‐min selections, representing key events of the perioperative course, were analyzed with the continuous wavelet transform, and average wavelet power spectra illustrated the circulatory frequency distributions. We identified oscillatory components in all patients and variables. Contrary to our hypothesis, they were randomly distributed through frequencies, patients, and situations, thus, not representing any reduction in the overall complexity. One patient showed loss of a 25‐s oscillation after surgery. We present a case where noise is misclassified as an oscillation, raising questions about the robustness of such analyses. John Wiley and Sons Inc. 2020-05-06 /pmc/articles/PMC7202984/ /pubmed/32378333 http://dx.doi.org/10.14814/phy2.14423 Text en © 2020 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Knai, Kathrine Aadahl, Petter Skjaervold, Nils K. Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title | Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title_full | Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title_fullStr | Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title_full_unstemmed | Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title_short | Cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
title_sort | cardiac surgery does not lead to loss of oscillatory components in circulatory signals |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202984/ https://www.ncbi.nlm.nih.gov/pubmed/32378333 http://dx.doi.org/10.14814/phy2.14423 |
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