Active Versus Passive Recovery in High-Intensity Intermittent Exercises in Children: An Exploratory Study.

International audienceThis study aimed to compare the effect of active recovery (AR) versus passive recovery (PR) on time to exhaustion and time spent at high percentages of peak oxygen uptake ( ) during short, high-intensity intermittent exercises in children. Twelve children (9.5 [0.7] y) underwent a graded test and 2 short, high-intensity intermittent exercises (15 s at 120% of maximal aerobic speed) interspersed with either 15 seconds of AR (50% of maximal aerobic speed) or 15-second PR until exhaustion. A very large effect (effect size = 2.42; 95% confidence interval, 1.32 to 3.52) was observed for time to exhaustion in favor of longer time to exhaustion with PR compared with AR. Trivial or small effect sizes were found for , peakHR, and peak ventilation between PR and AR, while a moderate effect in favor of higher average values (effect size = -0.87; 95% confidence interval, -1.76 to -0.01) was found using AR. The difference between PR and AR for the time spent above 80% (t80%) and 90% (t90%) of was trivial. Despite the shorter running duration in AR, similar t80% and t90% were spent with AR and PR. Time spent at a high percentage of may be attained by running 3-fold shorter using AR compared with using PR

Prediction of One-Hour Running Performance Using Constant Duration Tests

International audienceCritical velocity (CV) represents, theoretically, the highest velocity that can be sustained without fatigue. The aim of this study was to compare CV computed from 5 mathematical models in order to determine which CV estimate is better correlated with 1-hour performance and which model provides the most accurate prediction of performance. Twelve trained middle- and long-distance male runners (29 +/- 5 years) performed 3 randomly ordered constant duration tests (6, 9, and 12 minutes), a maximal running velocity test for the estimation of CV, and a 1-hour track test (actual performance). Two linear, 2 nonlinear, and 1 exponential mathematical models were used to estimate CV and to predict the highest velocity that could be sustained during 1 hour (predicted performance). Although all CV estimates were correlated with performance (0.80 < r < 0.93, p < 0.01), it appeared that CV estimated from the exponential model was more closely associated with performance than all other models (r = 0.93; p < 0.01). Analysis of the bias +/- 95% interval of confidence between actual and predicted performance revealed that none of the models provided an accurate prediction of the 1-hour performance velocity. In conclusion, the estimation of CV allows us to rank middle- and long-distance runners with regard to their ability to perform well in long-distance running. However, no models provide an accurate prediction of performance that could be used as a reference for coaches or athletes

Glycaemic Effects of a 156-km Ultra-trail Race in Athletes: An Observational Field Study

International audienceBackground: Ultra-trail running races pose appreciable physiological challenges, particularly for glucose metabolism. Previous studies that yielded divergent results only measured glycaemia at isolated times.Objectives: We aimed to explore the impact of an ultra-endurance race on continuously measured glycaemia and to understand potential physiological mechanisms, as well as the consequences for performance and behavioural alertness.Methods: Fifty-five athletes (78% men, 43.7 ± 9.6 years) ran a 156-km ultra-trail race (six 26-km laps, total elevation 6000 m). Participants wore a masked continuous glucose monitoring sensor from the day before the race until 10 days post-race. Blood was taken at rest, during refuelling stops after each lap, and after 24-h recovery. Running intensity (% heart rate reserve), performance (lap times), psychological stress, and behavioural alertness were explored. Linear mixed models and logistic regressions were carried out.Results: No higher risk of hypo- or hyperglycaemia was observed during the exercise phases of the race (i.e. excluding stops for scientific measurements and refuelling) compared with resting values. Laps comprising a greater proportion of time spent at maximal aerobic intensity were nevertheless associated with more time > 180 mg/dL (P = 0.021). A major risk of hyperglycaemia appeared during the 48-h post-race period compared with pre-race (P 180 mg/dL during recovery versus 5.5% during resting. Changes in circulating insulin, cortisol, and free fatty acids followed profiles comparable with those usually observed during traditional aerobic exercise. However, creatine phosphokinase, and to a lesser extent lactate dehydrogenase, increased exponentially during the race (P < 0.001) and remained high at 24-h post-race (P < 0.001; respectively 43.6 and 1.8 times higher vs. resting). Glycaemic metrics did not influence physical performance or behavioural alertness.Conclusion: Ultra-endurance athletes were exposed to hyperglycaemia during the 48-h post-race period, possibly linked to muscle damage and inflammation. Strategies to mitigate muscle damage or subsequent inflammation before or after ultra-trail races could limit recovery hyperglycaemia and hence its related adverse health consequences.Trial registration number: NCT05538442 2022-09-21 retrospectively registered