| Autor: |
Henrik Loe, Bjarne M Nes, Ulrik Wisløff |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
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| Zdroj: |
PLoS ONE, Vol 11, Iss 1, p e0144873 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0144873 |
| Popis: |
PURPOSE:Peak oxygen uptake (VO2peak) 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 VO2peak prediction models for men and women based on directly measured VO2peak from a large healthy population. METHODS:VO2peak 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 VO2peak accurately classified 91% of the participants within the correct or nearest quintile of measured VO2peak. CONCLUSION:Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO2peak, which may be beneficial for risk stratification in health care settings. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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