Impact of data averaging strategies on V̇O2max assessment: Mathematical modeling and reliability
Peer reviewed, Journal article
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Original versionScandinavian Journal of Medicine & Science in Sports. 2019, 29(10), 1473-1488. 10.1111/sms.13495
Background: No consensus exists on how to average data to optimize VO2max assessment. Although the VO2max value is reduced with larger averaging blocks, no mathematical procedure is available to account for the effect of the length of the averaging block on VO2max. Aims: To determine the effect that the number of breaths or seconds included in the averaging block has on the VO2max value and its reproducibility and to develop correction equations to standardize VO2max values obtained with different averaging strategies. Methods: Eighty‐four subjects performed duplicate incremental tests to exhaustion (IE) in the cycle ergometer and/or treadmill using two metabolic carts (Vyntus and Vmax N29). Rolling breath averages and fixed time averages were calculated from breath‐by‐breath data from 6 to 60 breaths or seconds. Results: VO2max decayed from 6 to 60 breath averages by 10% in low fit (VO2max < 40 mL kg−1 min−1) and 6.7% in trained subjects. The VO2max averaged from a similar number of breaths or seconds was highly concordant (CCC > 0.97). There was a linear‐log relationship between the number of breaths or seconds in the averaging block and VO2max (R2 > 0.99, P < 0.001), and specific equations were developed to standardize VO2max values to a fixed number of breaths or seconds. Reproducibility was higher in trained than low‐fit subjects and not influenced by the averaging strategy, exercise mode, maximal respiratory rate, or IE protocol. Conclusions: The VO2max decreases following a linear‐log function with the number of breaths or seconds included in the averaging block and can be corrected with specific equations as those developed here.
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