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Record W4392850610 · doi:10.1136/bjsports-2024-ioc.251

702 MEP032 – Association of COL5A1 gene polymorphisms and knee ligament injuries in professional football (Soccer) players

2024· article· en· W4392850610 on OpenAlex

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Physical Performance
Canadian institutionsnot available
Fundersnot available
KeywordsOdds ratioStatistical significanceMedicineLogistic regressionLigamentConfidence intervalPhysical therapyInternal medicineSurgery

Abstract

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<h3>Background and Objective</h3> While investigating genetic risk factors aids in preventing knee injuries, limited evidence is available. This study aims to explore genetic factors for determining knee ligament injuries in professional soccer players. <h3>Study Design and Participants</h3> This study received approval from the Ethics Committee and included 94 professional soccer players (22.0 years). Genetic testing was conducted upon joining professional teams, examining players’ histories of ACL and MCL injuries, as well as subsequent injuries. Salivary DNA was collected using a DNA Genotek kit (ON, Canada), and TaqMan assays analyzed COL5A1 rs12722 C/T and rs10628678 AGGG/- (deletion) polymorphisms. <h3>Risk Assessment and Main Outcomes</h3> We assessed the impact of genetic variants on the risk of knee ligament injuries. Statistical analysis used SPSS version 26, with statistical significance at P-values &lt;0.05. <h3>Results</h3> Among 94 players, 27 experienced knee ligament injuries. The rs12722 polymorphisms showed CC/CT/TT = 60/32/2 distribution, with CC variants trending toward higher injury risk (35%) but without statistical significance. For rs10628678 polymorphisms, frequencies were AGGG/AGGG = 24, AGGG/- = 53, and -/- = 17. Ligament injuries occurred in 8.3% of AGGG/AGGG, 35.8% of AGGG/-, and 41.2% of -/-, indicating higher injury frequency in AGGG/- or -/- variants compared to AGGG/AGGG (odds ratio [OR] = 6.5, 95% confidence interval [CI] = 1.4–21.9, P &lt; 0.01, Fisher’s exact test). In logistic regression analysis, with knee ligament injury as the dependent variable and AGGG deletion/haploinsufficiency as the explanatory variable, while adjusting for age and the rs12722 variant, the OR was 6.0 (95% CI = 1.3–28.6, P &lt; 0.05). <h3>Conclusions</h3> In the report by Alvarez-Romero and colleagues, only the COL5A1 rs10628678 -/- genotype was associated with ligament injuries in Japanese individuals, while it was not other ethnic groups. Unlike previous questionnaire-based surveys, this study, for the first time, revealed this association in actual clinical settings.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.004
GPT teacher head0.239
Teacher spread0.234 · 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

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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