A systematic review of methods to predict maximal oxygen uptake from submaximal, open circuit spirometry in healthy adults

Objectives: 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 ((V) over dotO(2max)) and (ii) provide a critical reflection of the data to inform health professionals and researchers when selecting a prediction equation. Design: Systematic review. Methods: A systematic search of MEDLINE, EMBASE (via OvidSP), CINAHL, SPORTDiscus (TM) (via EBSCO Host) and Scopus databases was undertaken in February 2013. Studies were required to report data on healthy participants aged 18-65 y. 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 (V) over dotO(2max) in 28 equations. Pearson's correlation coefficient between the predicted and measured (V) over dotO(2max) 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 (V) over dotO(2max) are moderately to highly accurate. The heart rate and rating of perceived exertion methods of predicting (V) over dotO(2max) 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. (C) 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.