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Earlier shift in race pacing can predict future performance during a single-effort ultramarathon under sleep deprivation

OBJECTIVE: We constructed research camps at single-effort ultramarathons (50 and 100 miles) in order to study human endurance capabilities under extreme sleep loss and stress. It takes > 24h, on average, to run 100 miles on minimal sleep, allowing us to construct 24h human performance profiles (H...

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Detalles Bibliográficos
Autores principales: Brager, Allison J, Demiral, Sukru, Choynowski, John, Kim, Jess, Campbell, Bill, Capaldi, Vincent F, Simonelli, Guido, Hammer, Steve
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Brazilian Association of Sleep and Latin American Federation of Sleep 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347363/
https://www.ncbi.nlm.nih.gov/pubmed/32670489
http://dx.doi.org/10.5935/1984-0063.20190132
Descripción
Sumario:OBJECTIVE: We constructed research camps at single-effort ultramarathons (50 and 100 miles) in order to study human endurance capabilities under extreme sleep loss and stress. It takes > 24h, on average, to run 100 miles on minimal sleep, allowing us to construct 24h human performance profiles (HPP). METHODS: We collected performance data plotted across time (race splits) and distance (dropout rates; n=257), self-reported sleep and training patterns (n=83), and endpoint data on cardiovascular fitness/adaptation to total sleep deprivation and extreme exercise/stress (n=127). RESULTS: In general, we found that self-reported napping was higher for 100-miler versus 50-miler runners and that ultra-endurance racing may possibly pre-select for early morning risers. We also compared HPPs between the first 50 miles completed by all runners in order to examine amplitude and acrophase differences in performance using a cosinor model. We showed that even though all runners slowed down over time, runners who completed a 100-miler ultramarathon had an earlier acrophase shift in race pace compared to non-finishers. DISCUSSION: We were able to identify time-dependent predictions on overall performance under minimal sleep, warranting the ultramarathon athlete as a unique demographic for future study of sleep and chronobiological relationships in the real world.