Lorenzo Capellá, IrmaRamos Álvarez, Juan JoséJiménez Herranz, María ElenaMaffulli, NicolaIuliano, EnzoPadulo, JohnnyCalderón Montero, Francisco Javier2025-11-052025-11-052025-02-17Lorenzo-Capellá I, Ramos-Álvarez JJ, Jiménez-Herranz E, Maffulli N, Iuliano E, Padulo J, Calderón-Montero FJ. Prediction of maximum voluntary ventilation based on forced expiratory volume in athletes. Arch Physiol Biochem. 2025 Aug;131(4):569-577. doi: 10.1080/13813455.2025.246533310.1080/13813455.2025.2465333https://hdl.handle.net/20.500.14352/125760Objective: 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.engjournal articlehttps://doi.org/10.1080/13813455.2025.2465333https://pubmed.ncbi.nlm.nih.gov/39957505/restricted access612Exercise physiologyCardio-pulmonary exercise testingMaximum ventilationMaximum voluntary ventilationValidityMedicinaFisiología32 Ciencias Médicas2411 Fisiología Humana