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Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway
PURPOSE: Peak oxygen uptake (VO(2peak)) is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO(2peak) prediction models for men and women based on directly measured VO(2peak) from a large heal...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721596/ https://www.ncbi.nlm.nih.gov/pubmed/26794677 http://dx.doi.org/10.1371/journal.pone.0144873 |
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author | Loe, Henrik Nes, Bjarne M. Wisløff, Ulrik |
author_facet | Loe, Henrik Nes, Bjarne M. Wisløff, Ulrik |
author_sort | Loe, Henrik |
collection | PubMed |
description | PURPOSE: Peak oxygen uptake (VO(2peak)) is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO(2peak) prediction models for men and women based on directly measured VO(2peak) from a large healthy population METHODS: VO(2peak) prediction models based on submaximal- and peak performance treadmill work were derived from multiple regression analysis. 4637 healthy men and women aged 20–90 years were included. Data splitting was used to generate validation and cross-validation samples. RESULTS: The accuracy for the peak performance models were 10.5% (SEE = 4.63 mL⋅kg(-1)⋅min(-1)) and 11.5% (SEE = 4.11 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 75% and 72% of the variance explained. For the submaximal performance models accuracy were 14.1% (SEE = 6.24 mL⋅kg(-1)⋅min(-1)) and 14.4% (SEE = 5.17 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 55% and 56% of the variance explained. The validation and cross-validation samples displayed SEE and variance explained in agreement with the total sample. Cross-classification between measured and predicted VO(2peak) accurately classified 91% of the participants within the correct or nearest quintile of measured VO(2peak). CONCLUSION: Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO(2peak), which may be beneficial for risk stratification in health care settings. |
format | Online Article Text |
id | pubmed-4721596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-47215962016-01-30 Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway Loe, Henrik Nes, Bjarne M. Wisløff, Ulrik PLoS One Research Article PURPOSE: Peak oxygen uptake (VO(2peak)) is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO(2peak) prediction models for men and women based on directly measured VO(2peak) from a large healthy population METHODS: VO(2peak) prediction models based on submaximal- and peak performance treadmill work were derived from multiple regression analysis. 4637 healthy men and women aged 20–90 years were included. Data splitting was used to generate validation and cross-validation samples. RESULTS: The accuracy for the peak performance models were 10.5% (SEE = 4.63 mL⋅kg(-1)⋅min(-1)) and 11.5% (SEE = 4.11 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 75% and 72% of the variance explained. For the submaximal performance models accuracy were 14.1% (SEE = 6.24 mL⋅kg(-1)⋅min(-1)) and 14.4% (SEE = 5.17 mL⋅kg(-1)⋅min(-1)) for men and women, respectively, with 55% and 56% of the variance explained. The validation and cross-validation samples displayed SEE and variance explained in agreement with the total sample. Cross-classification between measured and predicted VO(2peak) accurately classified 91% of the participants within the correct or nearest quintile of measured VO(2peak). CONCLUSION: Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO(2peak), which may be beneficial for risk stratification in health care settings. Public Library of Science 2016-01-21 /pmc/articles/PMC4721596/ /pubmed/26794677 http://dx.doi.org/10.1371/journal.pone.0144873 Text en © 2016 Loe et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Loe, Henrik Nes, Bjarne M. Wisløff, Ulrik Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title | Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title_full | Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title_fullStr | Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title_full_unstemmed | Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title_short | Predicting VO(2peak) from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway |
title_sort | predicting vo(2peak) from submaximal- and peak exercise models: the hunt 3 fitness study, norway |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721596/ https://www.ncbi.nlm.nih.gov/pubmed/26794677 http://dx.doi.org/10.1371/journal.pone.0144873 |
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