Evaluating Airflow Sensor Methods: Precision in Indirect Calorimetry

This study assesses the impact of three volumetric gas flow measurement methods-turbine (fT); pneumotachograph (fP), and Venturi (fV)-on predictive accuracy and precision of expired gas analysis indirect calorimetry (EGAIC) across varying exercise intensities. Six males (Age: 38 ± 8 year; Height: 178.8 ± 4.2 cm; $$ : 42 ± 2.8 mL O₂ kg^-1 min^-1) and 14 females (Age = 44.6 ± 9.6 year; Height = 164.6 ± 6.9 cm; $$ = 45 ± 8.6 mL O₂ kg^-1 min^-1) were recruited. Participants completed physical exertion on a stationary cycle ergometer for simultaneous pulmonary minute ventilation ( $$ ) measurements and EGAIC computations. Exercise protocols and subsequent conditions involved a 5-min cycling warm-up at 25 W min^-1, incremental exercise to exhaustion ( $$ ramp test), then a steady-state exercise bout induced by a constant Watt load equivalent to 80% ventilatory threshold (80% VT). A linear mixed model revealed that exercise intensity significantly affected $$ measurements (p < 0.0001), whereas airflow sensor method (p = 0.97) and its interaction with exercise intensity (p = 0.91) did not. Group analysis of precision yielded a $$ CV % = 21%; SEM = 5 mL O₂ kg^-1 min^-1. Intra- and interindividual analysis of precision via Bland-Altman revealed a 95% confidence interval (CI) precision benchmark of 3-5 mL kg^-1 min^-1. Agreement among methods decreased at power outputs eliciting $$ up to 150 L min^-1, indicating a decrease in precision and highlighting potential challenges in interpreting biological variability, training response heterogeneity, and test-retest comparisons. These findings suggest careful consideration of airflow sensor method variance across metabolic cart configurations.