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A Network approach to find poor orthostatic tolerance by simple tilt maneuvers

The approach introduced by Network Physiology intends to find and quantify connectedness between close- and far related aspects of a person’s Physiome. In this study I applied a Network-inspired analysis to a set of measurement data that had been assembled to detect prospective orthostatic intoleran...

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Autor principal: Karemaker, John M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012999/
https://www.ncbi.nlm.nih.gov/pubmed/36926547
http://dx.doi.org/10.3389/fnetp.2023.1125023
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author Karemaker, John M.
author_facet Karemaker, John M.
author_sort Karemaker, John M.
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description The approach introduced by Network Physiology intends to find and quantify connectedness between close- and far related aspects of a person’s Physiome. In this study I applied a Network-inspired analysis to a set of measurement data that had been assembled to detect prospective orthostatic intolerant subjects among people who were destined to go into Space for a two weeks mission. The advantage of this approach being that it is essentially model-free: no complex physiological model is required to interpret the data. This type of analysis is essentially applicable to many datasets where individuals must be found that “stand out from the crowd”. The dataset consists of physiological variables measured in 22 participants (4f/18 m; 12 prospective astronauts/cosmonauts, 10 healthy controls), in supine, + 30° and + 70° upright tilted positions. Steady state values of finger blood pressure and derived thereof: mean arterial pressure, heart rate, stroke volume, cardiac output, systemic vascular resistance; middle cerebral artery blood flow velocity and end-tidal pCO2 in tilted position were (%)-normalized for each participant to the supine position. This yielded averaged responses for each variable, with statistical spread. All variables i.e., the “average person’s response” and a set of %-values defining each participant are presented as radar plots to make each ensemble transparent. Multivariate analysis for all values resulted in obvious dependencies and some unexpected ones. Most interesting is how individual participants maintained their blood pressure and brain blood flow. In fact, 13/22 participants had all normalized Δ-values (i.e., the deviation from the group average, normalized for the standard deviation), both for +30° and +70°, within the 95% range. The remaining group demonstrated miscellaneous response patterns, with one or more larger Δ-values, however of no consequence for orthostasis. The values from one prospective cosmonaut stood out as suspect. However, early morning standing blood pressure within 12 h after return to Earth (without volume repletion) demonstrated no syncope. This study demonstrates an integrative way to model-free assess a large dataset, applying multivariate analysis and common sense derived from textbook physiology.
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spelling pubmed-100129992023-03-15 A Network approach to find poor orthostatic tolerance by simple tilt maneuvers Karemaker, John M. Front Netw Physiol Network Physiology The approach introduced by Network Physiology intends to find and quantify connectedness between close- and far related aspects of a person’s Physiome. In this study I applied a Network-inspired analysis to a set of measurement data that had been assembled to detect prospective orthostatic intolerant subjects among people who were destined to go into Space for a two weeks mission. The advantage of this approach being that it is essentially model-free: no complex physiological model is required to interpret the data. This type of analysis is essentially applicable to many datasets where individuals must be found that “stand out from the crowd”. The dataset consists of physiological variables measured in 22 participants (4f/18 m; 12 prospective astronauts/cosmonauts, 10 healthy controls), in supine, + 30° and + 70° upright tilted positions. Steady state values of finger blood pressure and derived thereof: mean arterial pressure, heart rate, stroke volume, cardiac output, systemic vascular resistance; middle cerebral artery blood flow velocity and end-tidal pCO2 in tilted position were (%)-normalized for each participant to the supine position. This yielded averaged responses for each variable, with statistical spread. All variables i.e., the “average person’s response” and a set of %-values defining each participant are presented as radar plots to make each ensemble transparent. Multivariate analysis for all values resulted in obvious dependencies and some unexpected ones. Most interesting is how individual participants maintained their blood pressure and brain blood flow. In fact, 13/22 participants had all normalized Δ-values (i.e., the deviation from the group average, normalized for the standard deviation), both for +30° and +70°, within the 95% range. The remaining group demonstrated miscellaneous response patterns, with one or more larger Δ-values, however of no consequence for orthostasis. The values from one prospective cosmonaut stood out as suspect. However, early morning standing blood pressure within 12 h after return to Earth (without volume repletion) demonstrated no syncope. This study demonstrates an integrative way to model-free assess a large dataset, applying multivariate analysis and common sense derived from textbook physiology. Frontiers Media S.A. 2023-02-06 /pmc/articles/PMC10012999/ /pubmed/36926547 http://dx.doi.org/10.3389/fnetp.2023.1125023 Text en Copyright © 2023 Karemaker. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Network Physiology
Karemaker, John M.
A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title_full A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title_fullStr A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title_full_unstemmed A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title_short A Network approach to find poor orthostatic tolerance by simple tilt maneuvers
title_sort network approach to find poor orthostatic tolerance by simple tilt maneuvers
topic Network Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012999/
https://www.ncbi.nlm.nih.gov/pubmed/36926547
http://dx.doi.org/10.3389/fnetp.2023.1125023
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