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6 The cognitive and physical effects of pre-competition rapid weight loss and gain in mixed martial arts athletes

2017· article· en· W2778326032 on OpenAlexaff
J Soolaman, Michael Gaetz, Jason P. Brandenburg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsMedicineGrip strengthAthletesMartial artsVertical jumpBody weightHeart rateAnimal sciencePhysical therapyInternal medicineJumpBlood pressurePhysics

Abstract

fetched live from OpenAlex

This study examined the acute physiological and cognitive effects of pre-competition rapid weight loss and gain (weight cutting) on mixed martial arts (MMA) athletes. 60 (8 female; 52 male) licensed amateur and professional MMA athletes participated in the study. Measurements were collected at three time points prior to a competition: 10–14 days (Time-1; n=50), 24 hours (Time-2; n=40) and 1–3 hours (Time-3; n=26). Measurements included body mass (kg), King-Devick Test (KD), Sit-to-Stand Heart Rate Test (SSHR), Vertical Jump Test (VJ), grip strength (kg) and urine specific gravity (USG) (mmol). Also, relative change [((Time-1 – Time-2)/Time-1) × 100] in both body mass and USG were compared to other dependent variables. The following variables [mean(SD)] at Time-2 were different from Time-1 before returning to near baseline at Time-3: body mass [74.44 (13.11) vs 70.77 (12.26) vs 74.07 (13.33) kg; F (1,1.24)=50.72, p=0.00], left grip strength [111 (27) vs 98 (25) vs 108 (27) kg; F (1,2)=23.38, p=0.00], right grip strength [112 (25) vs 100 (23) vs 110 (24) kg; F (1,2)=17.91, p=0.00], USG [1.008 (0.003) vs 1.032 (0.004) vs 1.007 (1.003) mmol; F (1,2)=299, p=0.00] and KD sum time (KDst) adjusted for errors [41.39 (4.78) vs 42.44 (5.92) vs 38.58 (4.58) s; F (1,1.41)=8, p=0.00]. Relative change in USG was significantly correlated with relative change in body mass [rs (30)=−0.405; p=0.03]; and left leg VJ force at Time-2 [rs (18)=−0.71; p=0.00] and Time-3 [rs (11)=−0.64; p=0.04]. Relative change in body mass was significantly correlated with KDst at Time-2 [rs (30)=−0.57; p=0.00] and Time-3 [rs (21)=−0.49; p=0.00]; and SSHR maximum at Time-2 [rs (30)=0.41; p=0.03] and Time-3 [rs (21)=0.49; p=0.03]. Findings indicate that a significant amount of weight loss while weight cutting was due to fluid loss that was sufficient at Time-2 to impair upper body strength, lower body power, SSHR response and cognitive function (higher KDst and errors). In athletes who experienced the most Time-2 fluid loss, the return of body mass and USG to near baseline levels at Time-3 did not fully reverse the effects on SSHR, lower body power and some cognitive functions (KDst). It was concluded that weight cutting causes a substantial disruption to physiology that may impact health and performance.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.269
Teacher spread0.259 · 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
Published2017
Admission routes1
Has abstractyes

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