MyMedR

Displaying all 4 publications

Abstract:

Sort:

Fulltext Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing events

Knechtle B, Weiss K, Valero D, Villiger E, Nikolaidis PT, Andrade MS, et al.

PLoS One, 2024;19(8):e0303960.
PMID: 39172797 DOI: 10.1371/journal.pone.0303960

The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the running speed from the athlete's age (Age group), gender (Gender), country of origin (Athlete country) and where the race occurred (Event country). Model explainability tools were then used to investigate how each independent variable influenced the predicted running speed. A total of 172,110 race records from 65,392 unique runners from 68 different countries participating in races held in 44 different countries were used for analyses. The model rates Event country (0.53) as the most important predictor (based on data entropy reduction), followed by Athlete country (0.21), Age group (0.14), and Gender (0.13). In terms of participation, the United States leads by far, followed by Great Britain, Canada, South Africa, and Japan, in both athlete and event counts. The fastest 100-mile races are held in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. The fastest athletes come mostly from Eastern European countries (Lithuania, Latvia, Ukraine, Finland, Russia, Hungary, Slovakia) and also Israel. In contrast, the slowest athletes come from Asian countries like China, Thailand, Vietnam, Indonesia, Malaysia, and Brunei. The difference among male and female predictions is relatively small at about 0.25 km/h. The fastest age group is 25-29 years, but the average speeds of groups 20-24 and 30-34 years are close. Participation, however, peaks for the age group 40-44 years. The model predicts the event location (country of event) as the most important predictor for a fast 100-mile race time. The fastest race courses were occurred in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. Athletes and coaches can use these findings for their race preparation to find the most appropriate racecourse for a fast 100-mile race time.
Fulltext Psychophysiological Adaptations to Exercise Training in COVID-19 Patients: A Systematic Review

Al-Mhanna SB, Batrakoulis A, Hofmeister M, Drenowatz C, Ghazali WSW, Badicu G, et al.

Biomed Res Int, 2024;2024:3325321.
PMID: 38726292 DOI: 10.1155/2024/3325321

INTRODUCTION: Many COVID-19 patients display adverse symptoms, such as reduced physical ability, poor quality of life, and impaired pulmonary function. Therefore, this systematic review is aimed at evaluating the effectiveness of physical exercise on various psychophysiological indicators among COVID-19 patients who may be at any stage of their illness (i.e., critically ill, hospitalized, postdischarge, and recovering).
METHODS: A systematic search was conducted in PubMed, Scopus, ScienceDirect, Web of Science, and Google Scholar from 2019 to 2021. Twenty-seven studies, which assessed a total of 1525 patients, were included and analysed.
RESULTS: Overall, data revealed significant improvements in the following parameters: physical function, dyspnoea, pulmonary function, quality of life (QOL), lower limb endurance and strength, anxiety, depression, physical activity level, muscle strength, oxygen saturation, fatigue, C-reactive protein (CRP), interleukin 6 (IL-6), tumour necrosis factor-alpha (TNF-α), lymphocyte, leukocytes, and a fibrin degradation product (D-dimer).
CONCLUSIONS: Physical training turns out to be an effective therapy that minimises the severity of COVID-19 in the intervention group compared to the standard treatment. Therefore, physical training could be incorporated into conventional treatment of COVID-19 patients. More randomized controlled studies with follow-up evaluations are required to evaluate the long-term advantages of physical training. Future research is essential to establish the optimal exercise intensity level and assess the musculoskeletal fitness of recovered COVID-19 patients. This trial is registered with CRD42021283087.
Fulltext Training During the COVID-19 Lockdown: Knowledge, Beliefs, and Practices of 12,526 Athletes from 142 Countries and Six Continents

Washif JA, Farooq A, Krug I, Pyne DB, Verhagen E, Taylor L, et al.

Sports Med, 2022 04;52(4):933-948.
PMID: 34687439 DOI: 10.1007/s40279-021-01573-z

OBJECTIVE: Our objective was to explore the training-related knowledge, beliefs, and practices of athletes and the influence of lockdowns in response to the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
METHODS: Athletes (n = 12,526, comprising 13% world class, 21% international, 36% national, 24% state, and 6% recreational) completed an online survey that was available from 17 May to 5 July 2020 and explored their training behaviors (training knowledge, beliefs/attitudes, and practices), including specific questions on their training intensity, frequency, and session duration before and during lockdown (March-June 2020).
RESULTS: Overall, 85% of athletes wanted to "maintain training," and 79% disagreed with the statement that it is "okay to not train during lockdown," with a greater prevalence for both in higher-level athletes. In total, 60% of athletes considered "coaching by correspondence (remote coaching)" to be sufficient (highest amongst world-class athletes). During lockdown,
Fulltext Correction to: Training During the COVID-19 Lockdown: Knowledge, Beliefs, and Practices of 12,526 Athletes from 142 Countries and Six Continents

Washif JA, Farooq A, Krug I, Pyne DB, Verhagen E, Taylor L, et al.

Sports Med, 2022 Oct 22.
PMID: 36272061 DOI: 10.1007/s40279-022-01776-y