Evidence map›Paper›PMID 34836328›Full record

ArticleNutrients2021

Hydration Status and Fluid Replacement Strategies of High-Performance Adolescent Athletes: An Application of Machine Learning to Distinguish Hydration Characteristics.

Haresh T Suppiah, Ee Ling Ng, Jericho Wee, Bernadette Cherianne Taim, Minh Huynh, Paul B Gastin, Michael Chia, Chee Yong Low, Jason K W Lee

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 18 citations in OpenAlex.

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  10. Nutritional Recommendations for the Young Athlete.Journal of the Pediatric Orthopaedic Society of North America · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Haresh T SuppiahSport and Exercise Science, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0001-9828-2349
Ee Ling NgNational Youth Sports Institute, Singapore 397778, Singapore.
Jericho WeeNational Youth Sports Institute, Singapore 397778, Singapore.
Bernadette Cherianne TaimNational Youth Sports Institute, Singapore 397778, Singapore.
Minh HuynhSport and Exercise Science, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, VIC 3086, Australia.
Paul B GastinSport and Exercise Science, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, VIC 3086, Australia.
Michael ChiaPhysical Education and Sports Science Group, National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore.ORCID 0000-0002-1289-0552
Chee Yong LowNational Youth Sports Institute, Singapore 397778, Singapore.
Jason K W LeeHuman Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.ORCID 0000-0003-4042-795X
La Trobe University · AUAgency for Science, Technology and Research · SGNanyang Technological University · SGNational University of Singapore · SGTechnological University of the Shannon: Midlands Midwest

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are limited data on the fluid balance characteristics and fluid replenishment behaviors of high-performance adolescent athletes. The heterogeneity of hydration status and practices of adolescent athletes warrant efficient approaches to individualizing hydration strategies. This study aimed to evaluate and characterize the hydration status and fluid balance characteristics of high-performance adolescent athletes and examine the differences in fluid consumption behaviors during training. In total, 105 high-performance adolescent athletes (male: 66, female: 39; age 14.1 ± 1.0 y) across 11 sports had their hydration status assessed on three separate occasions-upon rising and before a low and a high-intensity training session (pre-training). The results showed that 20-44% of athletes were identified as hypohydrated, with 21-44% and 15-34% of athletes commencing low- and high-intensity training in a hypohydrated state, respectively. Linear mixed model (LMM) analyses revealed that athletes who were hypohydrated consumed more fluid (F (1.183.85)) = 5.91, (

Indexed as

Drinking BehaviorMachine LearningOrganism Hydration StatusAdolescentAthletesAthletic PerformanceCluster AnalysisDehydrationDrinkingFemaleHumansMaleSingaporeSportsWater-Electrolyte Balancedehydrationhypohydrationsporttraining intensityyoung sportsmen/women

Identifiers

PMID34836328
PMCPMC8625246
OpenAlexW3213732001

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.