BACKGROUND: Mathematical procedures involved in the calculation of fatigue index (FI) and power drop (PD) are the main reasons why these traditional fatigue-related indices of Wingate All-out Test (WAT) are the least reliable indices. Mathematical procedures involved in the calculation of fatigue index (FI) and power drop (PD) are the main reasons why these traditional fatigue-related indices of Wingate All-out Test (WAT) are the least reliable indices. OBJECTIVE: To suggest a highly reliable fatigue-related output calculated by drop in mechanical work production (DMW). To suggest a highly reliable fatigue-related output calculated by drop in mechanical work production (DMW). METHODS: Twenty-one well-trained male athletes (age: 21.8 ± 1.9 years, peak power [PP]: 14.7 ± 1.3 W · kg - 1 ) participated in a series of WAT sessions, using 10% of their body mass as the workload, separated by 2-4 days. These WAT sessions were continued until the difference in PP between successive trials was less than 5%. Traditional FI and PD values were calculated using mean power data obtained from 5, 3, 2 and 1-second time intervals and using instantaneous power data, while DMW was calculated by predetermined areas in power-time curve. Twenty-one well-trained male athletes (age: 21.8 ± 1.9 years, peak power [PP]: 14.7 ± 1.3 W · kg - 1 ) participated in a series of WAT sessions, using 10% of their body mass as the workload, separated by 2-4 days. These WAT sessions were continued until the difference in PP between successive trials was less than 5%. Traditional FI and PD values were calculated using mean power data obtained from 5, 3, 2 and 1-second time intervals and using instantaneous power data, while DMW was calculated by predetermined areas in power-time curve. RESULTS: Intraclass correlation coefficients (ICC) and coefficient of variations (CV) revealed that DMW had higher reliability level (ICC = 0.92, CV = 4.53%) than that of traditional fatigue-related indices (ICC = 0.91, CV = 5.71%). In addition, DMW had the lowest limit of ``real change'' with 10.2% as the minimum detectable change score at 90% confidence. Intraclass correlation coefficients (ICC) and coefficient of variations (CV) revealed that DMW had higher reliability level (ICC = 0.92, CV = 4.53%) than that of traditional fatigue-related indices (ICC = 0.91, CV = 5.71%). In addition, DMW had the lowest limit of "real change" with 10.2% as the minimum detectable change score at 90% confidence. CONCLUSIONS: DMW might be used as a reliable output to evaluate fatigue-related power data of the anaerobic capability. Besides, Monark Inc. may easily modify its Peak Bike 894E software to make 30-second all-out test more reliable for the assessment of fatigability levels. DMW might be used as a reliable output to evaluate fatigue-related power data of the anaerobic capability. Besides, Monark Inc. may easily modify its Peak Bike 894E software to make 30-second all-out test more reliable for the assessment of fatigability levels.
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