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Record W3134091429 · doi:10.3390/su13052970

Resting Heart Rate Measurement in Elite Athletes during COVID-19 Lockdown: The Impact of Decreased Physical Activity

2021· article· en· W3134091429 on OpenAlexaff
Robin Pla, Laurent Bosquet, Anaël Aubry, Jean‐François Toussaint, Adrien Sedeaud

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSupine positionHeart rateElite athletesAthletesMedicinePhysical therapyPopulationCoronavirus disease 2019 (COVID-19)Physical activityPhysical medicine and rehabilitationPsychologyCardiologyInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

The purpose was to observe the effects of a four-week lockdown on the resting heart rate (RHR) and well-being perception of elite swimmers. Twenty elite swimmers performed RHR measurements upon waking in supine and standing positions. Baseline values and those measured after four weeks of lockdown were compared. Swimmers completed a questionnaire on their training volume and state of well-being. During the lockdown, swimmers reported a weekly mean physical activity of 10.4 ± 3.6 h (an estimated reduction of 254% compared to their usual training volume). After four weeks of lockdown, RHR in the supine position increased by more than two beats per minute (58.8 ± 8.2 vs. 56.5 ± 7.4 bpm, p < 0.05). In the standing position, RHR increased by almost 15 beats per minute (103.3 ± 13.2 vs. 88.4 ± 9.4 bpm, p < 0.0001). Fifty percent of these athletes expressed a decrease in well-being. These results underline that the lockdown circumstances induced a large reduction in parasympathetic activity in elite athletes, which was associated with a decrease in training volume. This increase in RHR may reflect that a highatly strenuous environment and maintaining a high level of physical activity in this population could be favorable to preserve physical and psychological health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.339
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

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