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Record W4412098936 · doi:10.3389/fnut.2025.1572961

Tailored nutrition strategies for Paralympic athletes: addressing unique energy, nutrients, and hydration needs to enhance performance and health

2025· review· en· W4412098936 on OpenAlexaff
Hadeel Ghazzawi, Raghad Al Aqaili, Batool Khataybeh, Fajer Al-Aittan, Saja Hamaideh, Tamara Alhalaiqah, Adam Tawfiq Amawi, Khaled Trabelsi, Haitham Jahrami, M. Zahid Hasan

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsBayer (Canada)
Fundersnot available
KeywordsAthletesMicronutrientScopusMedicineEnvironmental healthPsychologyPhysical therapyMEDLINEPolitical science

Abstract

fetched live from OpenAlex

The achievements of Olympic athletes are often highlighted, whereas the successes of Paralympians are frequently overlooked. Paralympic athletes with disabilities face unique nutritional challenges due to variations in energy expenditure and nutrient requirements associated with their specific disabilities and sports. Hydration is critical, particularly for athletes with spinal cord injuries, who may struggle with body temperature regulation. Despite the importance of nutrition in enhancing athletic performance, there is a lack of research focused on the nutritional requirements of Paralympic athletes. This scholarly review provides a comprehensive overview of the energy, macronutrient, and micronutrient requirements, including those for minerals and vitamins, supplements, and fluid intake, of Paralympic athletes aged 18 and older. This literature search was conducted via the Scopus and Google Scholar databases and focused on English-language original articles published between 1990 and 2024. This review included 56 studies. These findings highlight the necessity for tailored nutritional planning to support the performance and health of Paralympic athletes. Close monitoring of individual intake is essential to adjust for fluctuations in macronutrients, micronutrient supplements, and fluid intake. Ongoing research is vital for developing effective nutritional strategies that accommodate the diverse needs of these athletes.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.324
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2025
Admission routes1
Has abstractyes

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