Key result
Novel equation using exercise duration, BMI, and activity accurately predicts VO2max with ~0.1 mL/kg/min bias.
Why the study?
Measuring VO2max during a graded exercise test poses challenges in population-based studies.
Can graded exercise test duration (GXTd) accurately predict VO2max and what is the agreement among secondary VO2max criteria in middle-aged adults?
Cross-Sectional (n=580)
Yes
Can graded exercise test duration (GXTd) accurately predict VO2max and what is the agreement among secondary VO2max criteria in middle-aged adults?
Graded exercise test duration is a reliable surrogate for directly measured VO2max in population-based studies, and maximal heart rate is a more concordant secondary validation criterion than perceived exertion.
Answers are grounded in this paper and cite their sources.
Supports GXT duration-based VO2max estimation in cohorts; extends prior models to middle-aged adults but leaves open external validation.
Introduction Measuring maximal oxygen consumption (V˙O 2max ) during a graded exercise test (GXT) poses challenges in population-based studies. We examined the relationship between GXT duration (GXTd) and V˙O 2max to create a prediction equation for estimating V˙O 2max from GXTd. We also assessed the agreement among secondary V˙O 2max criteria: respiratory exchange ratio (RER; ≥1.10), maximal heart rate (mHR; ≥85% age-predicted), and ratings of perceived exertion (RPE; >17). Methods Data include 580 Coronary Artery Risk Development in Young Adults (CARDIA) participants (55.9% female, 38.6% Black) who attended the year 35 exam (age 54–66 yr) and completed a GXT with gas analysis. Pearson correlation coefficients were computed between GXTd (seconds) and V˙O 2max (mL·kg −1 ·min −1 ). A regression equation was developed to predict V˙O 2max from GXTd. Secondary criteria agreement was assessed using percent agreement, kappa, sensitivity/specificity, and receiver operating characteristics (ROC) analysis, excluding 38 participants on beta-blockers. Results Mean (standard deviation) GXTd and V˙O 2max were 341.6 (137.0) s and 26.6 (7.1) mL·kg −1 ·min −1 , respectively, exhibiting a strong correlation ( r = 0.83) similar for male and female participants ( r = 0.81 and 0.80, respectively). The final prediction model included GXTd, body mass index, and physical activity status as significant V˙O 2max predictors ( R 2 = 0.72; bias = 0.14 mL·kg −1 ·min −1 ; 95% confidence interval (CI), −1.24 to 1.52). RER, mHR, and RPE thresholds were met by 90.8%, 85.2%, and 42.8%, respectively. Agreement between mHR and RER was 82.9% (kappa = 0.178 (95% CI, 0.07–0.29); 34.0% sensitivity, 87.9% specificity). The agreement between RPE and RER was 45.3% (kappa = 0.018 (95% CI, −0.02 to 0.06); 62.5% sensitivity, 43.6% specificity). ROC analyses showed a larger area under the curve for mHR and RER (0.762 (95% CI, 0.705–0.820)) compared to RPE and RER (0.598 (95% CI, 0.522–0.674)). Conclusions GXTd serves as a reliable measure of cardiorespiratory fitness in the absence of gas analysis, and a corresponding V˙O 2max prediction equation can be effectively utilized. Discrepancies in secondary criteria highlight challenges in determining maximal effort, especially based on participant reports.
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Hornikel et al. (2025) conducted a cross-sectional in Healthy adults (n=580). Graded exercise test duration (GXTd) prediction equation vs. Direct measurement of VO2max via gas analysis was evaluated on Mean bias of predicted versus measured VO2max (MD 0.14, 95% CI -1.24 to 1.52). A prediction equation incorporating graded exercise test duration, BMI, and physical activity status accurately estimated VO2max with a minimal bias of 0.14 mL/kg/min compared to direct gas analysis.
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