Objective: Maximum-voluntary-ventilation (MVV) is the maximal volume of which an individual can move by voluntary effort in one minute. It is possible that the first second forced-expiratory-volume (FEV1) could be more to reliable assess respiratory muscle endurance to estimate MVV. Methods: For this aim, 422 athletes (Age 22.9 ± 8.5 years; 98/324 - females/males) were performed a MVV, and FEV1 measurements. Results: The coefficient of determination was R2 = 0.594 between MVV and FEV1, with a predictive equation for overall participants: MVV = (FEV1 × 33.5)+12.7. The robust regression showed a good multiple correlation coefficient (R = 0.815) with the coefficient of determination R2 = 0.661 for the model including FEV1, age and gender as predictors. These equations MVV = (FEV1 X 27.3)+(Age(y) × 1.1)+20.5 and MVV = (FEV1 × 27.3)+(Age(y) × 1.1) were derived for male and female, respectively. Conclusion: FEV1 can predict MVV in different athletes with greater accuracy when stratified per gender. Therefore, this new approach can be used in a short all-out test without stress of the respiratory muscle to predict MVV in athletes.

Prediction of maximum voluntary ventilation based on forced expiratory volume in athletes

Iuliano, Enzo;Padulo, Johnny;
2025-01-01

Abstract

Objective: Maximum-voluntary-ventilation (MVV) is the maximal volume of which an individual can move by voluntary effort in one minute. It is possible that the first second forced-expiratory-volume (FEV1) could be more to reliable assess respiratory muscle endurance to estimate MVV. Methods: For this aim, 422 athletes (Age 22.9 ± 8.5 years; 98/324 - females/males) were performed a MVV, and FEV1 measurements. Results: The coefficient of determination was R2 = 0.594 between MVV and FEV1, with a predictive equation for overall participants: MVV = (FEV1 × 33.5)+12.7. The robust regression showed a good multiple correlation coefficient (R = 0.815) with the coefficient of determination R2 = 0.661 for the model including FEV1, age and gender as predictors. These equations MVV = (FEV1 X 27.3)+(Age(y) × 1.1)+20.5 and MVV = (FEV1 × 27.3)+(Age(y) × 1.1) were derived for male and female, respectively. Conclusion: FEV1 can predict MVV in different athletes with greater accuracy when stratified per gender. Therefore, this new approach can be used in a short all-out test without stress of the respiratory muscle to predict MVV in athletes.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11389/74770
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