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Record W4394838429 · doi:10.1186/s40798-024-00686-9

Attenuating Muscle Damage Biomarkers and Muscle Soreness After an Exercise-Induced Muscle Damage with Branched-Chain Amino Acid (BCAA) Supplementation: A Systematic Review and Meta-analysis with Meta-regression

2024· review· en· W4394838429 on OpenAlexaff
Atef Salem, Khouloud Ben Maaoui, Haithem Jahrami, Mezna A. AlMarzooqi, Omar Boukhris, Balsam Messai, Cain C. T. Clark, Jordan M. Glenn, Hadeel A. Ghazzaoui, Nicola Luigi Bragazzi, Achraf Ammar, Khaled Trabelsi, Hamdi Chtourou

Bibliographic record

VenueSports Medicine - Open · 2024
Typereview
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsYork University
Fundersnot available
KeywordsMeta-analysisMedicineRandomized controlled trialCreatine kinaseDelayed onset muscle sorenessPlaceboMuscle damageInternal medicinePopulationPhysical therapyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Branched-chain amino acid (BCAA) supplementation is one of the most popular strategies used by the general population and athletes to reduce muscle soreness and accelerate the recovery process of muscle damage biomarkers after an intense exercise or training session. OBJECTIVES: This systematic review and meta-analysis investigated the effects of BCAA supplementation on muscle damage biomarkers and muscle soreness after exercise-induced muscle damage (EIMD). METHODS: The systematic literature search for randomized controlled trials was conducted using seven databases, up to September 13th, 2022. The eligibility criteria for selecting studies were as follows: studies performed on healthy active participants, using BCAA at least once, controlled with a placebo or control group, performing resistance or endurance exercises, and followed up at least once post-EIMD. The methodological quality of the studies was assessed using the "SIGN RCT checklist". Random-effects meta-analyses were processed to compute the standardized mean difference (Hedges' g). Meta-regression analyses were completed with daily and total dosage and supplementation as continuous moderator variables. RESULTS: Of the 18 studies included in this meta-analysis, 13 were of high quality and five were of acceptable quality. Our results revealed BCAA supplementation elicits a significant effect on reducing creatine kinase (CK) levels immediately (g = - 0.44; p = 0.006) and 72 h (g = - 0.99; p = 0.002), but not 24 h, 48 h, and 96 h post-EIMD. Additionally, a significant effect on delayed onset of muscle soreness (DOMS) was identified at 24 h (g = - 1.34; p < 0.001), 48 h (g = - 1.75; p < 0.001), 72 h (g = - 1.82; p < 0.001), and 96 h (g = - 0.82; p = 0.008), but not immediately post-EIMD. No significant effect was found on lactate dehydrogenase (LDH) levels at any time point. Meta-regression indicated higher daily and total dosages of BCAA, and longer supplementation periods were related to the largest beneficial effects on CK (total dosage and supplementation period) at 48 h, and on DOMS at 24 h (only daily dosage). CONCLUSION: The overall effects of BCAA supplementation could be considered useful for lowering CK and DOMS after EIMD, but not LDH. The longer supplementation period prior to the EIMD could be more effective for CK and DOMS reduction.

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)0.015
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.030
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0220.053
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.115
GPT teacher head0.401
Teacher spread0.286 · 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 designMeta-analysis
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

Citations36
Published2024
Admission routes1
Has abstractyes

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