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Effects of Combined Creatine and Glycerol Supplementation on Physiological Responses During Exercise in the Heat

2006· article· en· W2055159882 on OpenAlexaboutno aff
Chris Easton, Stephen Turner, Yannis Pitsiladis

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsPlaceboRegimenThermoregulationCreatineMedicineTime trialInternal medicinePhysical exerciseEndocrinologyExercise physiologyPhysical therapyAnimal scienceHeart rateBlood pressureBiology

Abstract

fetched live from OpenAlex

It is well documented that exercising in high ambient temperature environments can have a profound effect on thermoregulation and exercise performance. Both glycerol (Gly) and creatine (Cr) have been shown to act as hyperhydrating agents when consumed with fluid and to reduce thermal strain during prolonged exercise in the heat (e.g. Lyons et al. Med Sci Sports Exerc 22: 77–83, 1990; Kilduff et al. Int J Sport Nutr Exerc Metab 14: 443–60, 2004). PURPOSE: To examine the effects of combined Cr and Gly supplementation, intended to increase initial total body water (TBW) levels, on the physiological responses to prolonged exercise in the heat. METHODS: Twenty-three well-trained male cyclists were matched for body mass (BM) and were randomised in a double blind fashion to either a Cr or a placebo (Pl) group. Cr supplementation consisted of 22.8 g·d−1 of Cr·H2O (equivalent to 10 g Cr × 2 daily) and 75 g of glucose polymer made up in 1 litre (L) of warm water (x 2 daily). The Pl supplement consisted of 170 g·d−1 of glucose polymer (85 g × 2 daily). Subjects participated in two supplementation regimens each lasting seven days and comprising an exercise trial both pre- and post-supplementation. During the first supplementation regimen, subjects in both groups received either 1 g Gly·kg−1 BM or an equivalent amount of Pl before crossing over during the second supplementation regimen. The exercise trials consisted of 40 min constant-load exercise at 63% WRmax followed by a 16.1 km (10 mile) time trial at 30° C ambient temperature and 70% relative humidity. RESULTS: In the Pl group, TBW increased (mean ± s.d.) by 0.57 ± 0.27 L (p<0.01) during Gly supplementation and did not change significantly during supplementation with Pl (P=0.52). In the Cr group, TBW increased by 0.63 ± 0.33 L (p<0.01) during Pl and by 0.87 ± 0.21 L (p<0.01) during Gly supplementation. The rise in heart rate (HR), rectal temperature (Tre) and rating of perceived exertion (RPE) during exercise was significantly attenuated after both supplementation regimens in the Cr group. However, there was no difference in pre and post supplementation time trial performance in either group. The addition of Gly to Cr significantly increased TBW further than Cr alone (P=0.02) but did not further enhance the attenuation in HR, Tre and RPE during exercise. CONCLUSIONS: The combination of Cr and Gly is more effective at hyperhydrating than either Cr or Gly alone but does not further enhance the reduction in thermal strain compared to Cr alone. The possibility that this novel “water-loading” protocol may improve performance during exercise of greater duration in the heat remains to be determined. Supported by Iovate Health Sciences Research Inc, Canada.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.263
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2006
Admission routes1
Has abstractyes

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