A systematic review of methods to predict maximal oxygen uptake from submaximal, open circuit spirometry in healthy adults. Issue 2 (March 2015) - Evans, Harrison J.L.; Ferrar, Katia E.; Smith, Ashleigh E.; Parfitt, Gaynor; Eston, Roger G.
Abstract: 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 ˙ O 2   max ) 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™ (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 ˙ O 2   max in 28 equations. Pearson's correlation coefficient between the predicted and measured V ˙ O 2   max 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 ˙ O 2   max are moderately to highly accurate. The heart rate and rating of perceived exertion methods of predicting V ˙ O 2   max 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.