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Meta-Analysis of the Effect of Exercise-Induced Dehydration on Endurance Performance

2008· article· en· W2066606001 on OpenAlexaff
Eric Goulet, Michel O. Mélançon, Kfir Madjar

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2008
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversité de SherbrookeMcGill University
Fundersnot available
KeywordsDehydrationEndurance trainingAnimal scienceChemistryIntensity (physics)Physical therapyMedicineBiochemistryBiology

Abstract

fetched live from OpenAlex

It is generally accepted that exercise-induced dehydration impairs endurance performance. The effect of dehydration on endurance performance has not been yet systematically quantified. PURPOSE: Use the meta-analytic approach to determine the magnitude and importance of the effect of dehydration on endurance performance. METHODS: Studies were located via database searches, cross-referencing, and e-mails sent to researchers. Inclusion criteria were: dehydration induced during exercise; fluid replacement given orally; data to calculate percent change in power output, effect size and dehydration level; hydration level in the less-dehydrated control group between + 0.5 to −1% body mass; dehydration level in the more-dehydrated experimental group >1% body mass and>0.5% more than control; equal quantity of carbohydrate administered in control and experimental groups; and performance assessed in compensable exerciseheat stress. A random-effect model was used to determine the standardized effect. RESULTS: Fourteen studies met the inclusion criteria, providing 27 estimates. Exercise duration, exercise intensity and ambient temperature were respectively 94 ± 34 min (mean ± SD, range 60-171 min), 70 ± 12% (51-85%), and 26 ± 6°C (20-35°C). The decreases in body mass in control and experimental groups were 0.6 ± 0.3% and 2.4 ± 0.9%, respectively. Overall, mean power output fell by 2.0% (95% CI: 0.4 to 3.7%) in dehydrated group relative to control (standardized effect size of 0.20, 95% CI: −0.01 to 0.40). Percent dehydration of control group, exercise duration, exercise intensity and ambient temperature were entered in a hierarchical, weighted least-squares regression model to determine the predictors of the percent change in power output. Only percent dehydration was retained in the model, with a prediction equation consistent with a decline in power output of 3.0% for each percent loss in body mass above a threshold loss of 1.7%. CONCLUSION: Exercise-induced dehydration equal or greater than 2% body mass can significantly impair endurance performance in elite athletes as well as in amateur athletes racing for personal best times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.057
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0150.055
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.319
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
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

Citations2
Published2008
Admission routes1
Has abstractyes

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