The Journal of sports medicine and physical fitness · 2025
Maximal aerobic power and anaerobic power reserves to prescribe cycling interval training sessions.
СтатьяРандомизированное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
DI Gennaro Simone, Filipas Luca, Panascì Marco, Gallo Gabriele, Meloni Andrea, Codella Roberto, Ruggeri Piero, Faelli Emanuela
Аннотация
BACKGROUND: Prescribing interval training intensity can be challenging due to individual variations in physiological capacity. Traditional methods often rely on maximal aerobic power (MAP), but this may not fully capture the characteristics of different athletes. This study aimed to investigate whether alternative methods, such as anaerobic power reserve (APR) and glycolytic power reserve (GPR), could provide more individualized high-intensity interval training (HIIT) prescriptions.
METHODS: Twelve trained cyclists completed a cardiopulmonary test and Wingate test to determine MAP, APR, and GPR (mean power output during the Wingate test minus MAP). Subsequently, participants performed in a randomized order, three HIIT until-exhaustion sessions with 60-s of work and 60-s of active rest, based on APR (HIIT<inf>APR</inf>: MAP+10% APR), GPR (HIIT<inf>GPR</inf>: MAP+20%GPR) and MAP (HIIT<inf>MAP</inf>: 120%MAP), respectively. Inter-individual variability in time to exhaustion, heart rate, oxygen uptake, and lactate was calculated as the root mean square of residuals and as coefficients of variation (CV).
RESULTS: Although no significant differences in inter-individual variability were observed across the three prescription methods for any of the physiological and perceptual variables (P>0.2), HIIT<inf>MAP</inf> leads to lower inter-individual variability in time to exhaustion (CV=21%) compared to HIIT<inf>APR</inf> (CV=35%) and HIIT<inf>GPR</inf> (CV=45%).
CONCLUSIONS: HIIT based on APR and GPR does not reduce inter-individual variability in physiological responses and tolerance compared with MAP-based prescription. This suggests that both APR and GPR fail to accurately differentiate between the aerobic and anaerobic characteristics of an athlete, hindering the normalization of exercise responses during HIIT.
METHODS: Twelve trained cyclists completed a cardiopulmonary test and Wingate test to determine MAP, APR, and GPR (mean power output during the Wingate test minus MAP). Subsequently, participants performed in a randomized order, three HIIT until-exhaustion sessions with 60-s of work and 60-s of active rest, based on APR (HIIT<inf>APR</inf>: MAP+10% APR), GPR (HIIT<inf>GPR</inf>: MAP+20%GPR) and MAP (HIIT<inf>MAP</inf>: 120%MAP), respectively. Inter-individual variability in time to exhaustion, heart rate, oxygen uptake, and lactate was calculated as the root mean square of residuals and as coefficients of variation (CV).
RESULTS: Although no significant differences in inter-individual variability were observed across the three prescription methods for any of the physiological and perceptual variables (P>0.2), HIIT<inf>MAP</inf> leads to lower inter-individual variability in time to exhaustion (CV=21%) compared to HIIT<inf>APR</inf> (CV=35%) and HIIT<inf>GPR</inf> (CV=45%).
CONCLUSIONS: HIIT based on APR and GPR does not reduce inter-individual variability in physiological responses and tolerance compared with MAP-based prescription. This suggests that both APR and GPR fail to accurately differentiate between the aerobic and anaerobic characteristics of an athlete, hindering the normalization of exercise responses during HIIT.