Exploring the Influence of Acid-Base Status on Athletic Performance during Simulated Three-Day 400 m Race.

This study aimed to investigate the ability of highly trained athletes to consistently perform at their highest level during a simulated three-day 400 m race and to examine the impact of an alkaline diet associated with chronic consumption of bicarbonate-rich water or placebo on their blood metabolic responses before and after the three races. Twenty-two highly trained athletes, divided into two groups-one with an alkalizing diet and placebo water (PLA) and the other with an alkalizing diet and bicarbonate-rich water (BIC)-performed a 400 m race for three consecutive days. Performance metrics, urine and blood samples assessing acid-base balance, and indirect markers of neuro-muscular fatigue were measured before and after each 400 m race. The evolution of the Potential Renal Acid Load (PRAL) index and urinary pH highlights the combination of an alkalizing diet and bicarbonate-rich hydration, modifying the acid-base state (p < 0.05). Athletes in the PLA group replicated the same level of performance during three consecutive daily races without an increase in fatigue-associated markers. Athletes experienced similar levels of metabolic perturbations during the three 400 m races, with improved lactate clearance 20 min after the third race compared to the first two (p < 0.05). This optimization of the buffering capacity through ecological alkaline nutrition and hydration allowed athletes in the BIC group to improve their performance during the third 400 m race (p < 0.01). This study highlights athletes' ability to replicate high-level performances over three consecutive days with the same extreme level of metabolic disturbances, and an alkaline diet combined with bicarbonate-rich water consumption appears to enhance performance in a 400 m race.

Exploring the effect of the menstrual cycle or oral contraception on elite athletes' training responses when workload is not objectively quantifiable: the MILS approach and findings from female Olympians.

Objectives: Develop the Markov Index Load State (MILS) model, based on hidden Markov chains, to assess athletes' workload responses and investigate the effects of menstrual cycle (MC)/oral contraception (OC), sex steroids hormones and wellness on elite athletes' training. Methods: On a 7-month longitudinal follow-up, daily training (volume and perceived effort, n=2200) and wellness (reported sleep quality and quantity, fitness, mood, menstrual symptoms, n=2509) data were collected from 24 female rowers and skiers preparing for the Olympics. 51 MC and 54 OC full cycles relying on 214 salivary hormone samples were analysed. MC/OC cycles were normalised, converted in % from 0% (first bleeding/pill withdrawal day) to 100% (end). Results: MILS identified three chronic workload response states: 'easy', 'moderate' and 'hard'. A cyclic training response linked to MC or OC (95% CI) was observed, primarily related to progesterone level (p=8.23e-03 and 5.72e-03 for the easy and hard state, respectively). MC athletes predominantly exhibited the 'easy' state during the cycle's first half (8%-53%), transitioning to the 'hard' state post-estimated ovulation (63%-96%). OC users had an increased 'hard' state (4%-32%) during pill withdrawal, transitioning to 'easy' (50%-60%) when on the pill. Wellness metrics influenced the training load response: better sleep quality (p=5.20e-04), mood (p=8.94e-06) and fitness (p=6.29e-03) increased the likelihood of the 'easy' state. Menstrual symptoms increased the 'hard' state probability (p=5.92e-02). Conclusion: The MILS model, leveraging hidden Markov chains, effectively analyses cumulative training load responses. The model identified cyclic training responses linked to MC/OC in elite female athletes.

The COVID-19 pandemic impact on the best performers in athletics and swimming among paralympic and non-disabled athletes.

BACKGROUND: The COVID 19 pandemic has greatly disrupted high performance sport and international competition. The aim of this study was to quantify the impact of the COVID-19 pandemic on the world's top 10 performances in Athletics and Swimming among non-disabled and Paralympic athletes. METHODS: The results of the 10-best world performers in 66 Olympic events since 1891 and 255 Paralympic events since 2010 were collected. To quantify the performance trend, the slopes of the 4 years moving average were calculated and analyzed by time period. The distribution of performances (in % of the world record) by year was analyzed to compare the 2020 values to the ten previous years. The stability rate (athletes joining and leaving each year) since 2010 and the number of annual competitions events were also measured. RESULTS: Over the study period, such declines in performance have only been observed during the two World Wars. In 2020, the level of performances has decreased significantly, corresponding to a 6 to 10 years setback. In 2020, the number of new athletes in the 10-best was significantly higher with a lower number of organized competitions. CONCLUSIONS: The impact on the performances of the best international non-disabled and Para athletes has been considerable.

Potential estimation model in French alpine skiing - Individual evolution curve and progression typology.

Estimating the potential of alpine skiers is an unresolved question, especially because of the complexity of sports performance. We developed a potential estimation model based solely on the evolution of performance as a function of age. A bayesian mixed model allowed to estimate the potential curve and the age at peak performance for the population (24.81 ± 0.2) and for each individual as the uncertainty around this curve. With Gaussian mixtures, we identified among all the estimates four types of curves, clustered according to the performance level and the progression per age. Relying on the uncertainty calculated on the progression curve the model created also allow to estimate a score and an uncertainty associated with each cluster for all individuals. The results allows to: i) describe and explain the relationship between age and performance in alpine skiing from a species point of view (at 0.87%) and ii) to provide to sport staffs the estimation of the potential of each individual and her/his typology of progression to better detect sports potential. The entire methodology is based on age and performance data, but the progression identified may depend on parameters specific to alpine skiing.