Dual V̇O2plateau Method for Confirming V̇O2max Validity in Trained Female Runners Original Research
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Keywords
Graded exercise test, metabolic data processing, aerobic capacity
Abstract
Introduction: Breath-by-breath (BxB) data in modern metabolic carts exhibit high variability and are rarely filtered. With sampling intervals (SI) ≤30-s commonly incorporated, not accounting for outlier breaths can greatly inflate maximal oxygen consumption (V̇O2max) and reduce robustness. Purpose: this study attempted to address these issues by demonstrating that positive BxB outliers from unfiltered 30-s SI (V̇O2max30) wouldn’t differ in a meaningful (d≤0.15) way from 60-s SI (V̇O2max60), and 15-s SI (V̇O2max15) would increase in a significant enough fashion (d≥0.20) to be deemed a non-preferred SI. A novel, dual V̇O2plateau model was then created using ΔV̇O2max60-V̇O2max30 and ΔV̇O2max60-V̇O2non-max60 to form simple and objective sex-specific criterion guidelines for validation of V̇O2max60 assessment.
Methods: Unfiltered BxB averages from the last 2-min of a graded exercise test to exhaustion were collected from female NCAA Division I cross-country runners (n=14).
Results: V̇O2max60 and V̇O2max30 differed statistically but trivially from each other (2.91±0.28 vs 2.94±0.29 L/min; d=0.11). The differences between V̇O2max15 (3.01±0.33 L/min) and V̇O2max30 (d=0.23) and V̇O2max60 (d=0.33) were meaningful, confirming our hypotheses. Furthermore, four V̇O2max15 occurred before the final 2 min. V̇O2max60-V̇O2max30 (±0.05 L/min; <1%) and V̇O2max60-V̇O2non-max60 (±0.08 L/min; 1.60%) exhibited tight Bland-Altman 95% levels of agreement and coefficient of variation. V̇O2max60 validity can be confirmed using criteria of a dual V̇O2plateau model of Δ ≤0.08 L/min for ΔV̇O2max60-V̇O2max30 and Δ ≤0.15 L/min for ΔV̇O2max60-V̇O2non-max60.
Conclusions: These simple guidelines can replace more subjective secondary confirmation markers to increase confidence in V̇O2max outcomes and determine need for verification testing without having to filter BxB data.
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