A systematic review of methods to predict maximal oxygen uptake from submaximal, open circuit spirometry in healthy adults.
OBJECTIVE
This systematic review aimed to (i) report the accuracy of submaximal exercise-based predictive equations that incorporate oxygen uptake (measured via open circuit spirometry) to predict maximal oxygen uptake (VO₂max) and (ii) provide a critical reflection of the data to inform health professionals and researchers when selecting a prediction equation.


METHODS
Systematic review.


METHODS
A systematic search of MEDLINE, EMBASE (via OvidSP), CINAHL, SPORTDiscus (via EBSCO Host) and Scopus databases was undertaken in February 2013. Studies were required to report data on healthy participants aged 18-65y. Following tabulation of extracted data, a narrative synthesis was conducted.


RESULTS
From a total of 7597 articles screened, 19 studies were included, from which a total of 43 prediction equations were extracted. No significant difference was reported between the measured and predicted VO₂max in 28 equations. Pearson's correlation coefficient between the predicted and measured VO₂max ranged from r=0.92 to r=0.57. The variables most commonly used in predictive equations were heart rate (n=19) and rating of perceived exertion (n=24).


CONCLUSIONS
Overall, submaximal exercise-based equations using open circuit spirometry to predict VO₂max are moderately to highly accurate. The heart rate and rating of perceived exertion methods of predicting VO₂max were of similar accuracy. Important factors to consider when selecting a predictive equation include: the level of exertion required; participant medical conditions or medications; the validation population; mode of ergometry; time and resources available for familiarisation trials; and the level of bias of the study from which equations are derived.
Exercise for Health and Human Performance Group, Sansom Institute for Health Research, School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, Australia. Electronic address: Harrison.Evans@mymail.unisa.edu.au.
Harrison J L
HJ
Evans
Exercise for Health and Human Performance Group, Sansom Institute for Health Research, School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, Australia.
Katia E
KE
Ferrar
Exercise for Health and Human Performance Group, Sansom Institute for Health Research, School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, Australia.
Ashleigh E
AE
Smith
Exercise for Health and Human Performance Group, Sansom Institute for Health Research, School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, Australia.
Gaynor
G
Parfitt
Exercise for Health and Human Performance Group, Sansom Institute for Health Research, School of Health Sciences, University of South Australia, GPO Box 2471, Adelaide, Australia; Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, Exeter, UK.
Roger G
RG
Eston
D000328:Adult; D000465:Algorithms; D005080:Exercise Test / Q000379:methods*; D006801:Humans; D010101:Oxygen Consumption; D013147:Spirometry
Exercise test; Exercise tolerance; Oxygen consumption; Predictive value of tests; Regression analysis