Data collection, handling, and fitting strategies to optimize accuracy and precision of oxygen uptake kinetics estimation from breath-by-breath measurements

This study identified an unbiased method for data collection, handling, and fitting to optimize Vo2P kinetics estimation. A validated computational model of Vo2P kinetics and a Monte Carlo approach simulated 2 x 105 moderate-intensity transitions using a distribution of metabolic and circulatory parameters spanning normal health. Effects of averaging (interpolation, binning, stacking, or separate fitting of up to 10 transitions) and fitting procedures (biexponential fitting, or 2 isolation by time removal, statistical, or derivative methods followed by monoexponential fitting) on accuracy and precision of Vo2P kinetics estimation were assessed. The optimal strategy to maximize accuracy and precision of Vo2P estimation was 1-s interpolation of 4 bouts, ensemble averaged, with the first 20 s of exercise data removed. Contradictory to previous advice, we found optimal fitting procedures removed no more than 20 s of 1 data. Averaging method was less critical: interpolation, binning, and stacking gave similar results, each with greater accuracy compared with analyzing repeated bouts separately. The optimal procedure resulted in 2 Vo2P estimates for transitions from an unloaded or loaded baseline that averaged 1.97 ± 2.08 and 1.04 ± 2.30 s from true, but were within 2 s of true in only 47–62% of simulations. Optimized 95% confidence intervals for Vo2P ranged from 4.08 to 4.51 s, suggesting a minimally important difference of ~5 s to determine significant changes...
Source: Journal of Applied Physiology - Category: Physiology Authors: Tags: RESEARCH ARTICLE Source Type: research