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Record W4412420609 · doi:10.1186/s13102-025-01245-9

Eccentric external and internal rotation peak torque ratios predict shoulder injuries with national judokas; a prospective cohort study

2025· article· en· W4412420609 on OpenAlexaff
Shirzad Mian Darbandi, Masoud Sebyani, Shiva Behpour, David G. Behm, Mahdi Hosseinzadeh

Bibliographic record

VenueBMC Sports Science Medicine and Rehabilitation · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEccentricInternal rotationExternal rotationProspective cohort studyMedicineTorquePhysical medicine and rehabilitationPhysical therapyPhysicsSurgeryStructural engineeringEngineering

Abstract

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This study aimed to identify isokinetic strength variables of the shoulder rotator muscles that are associated with the risk of upper limb injuries in elite judokas, and to establish predictive cut-off values for injury risk using a prospective cohort design. Prospective cohort study. Fifty-three male national team judokas Fifty-three male judokas of the national teams (Mean ± SD, age 18.68 ± 3.08 years, weight 75.34 ± 11.62 kg, height 175.28 ± 7.24 cm) participated in this study. We assessed concentric (CON) and eccentric (ECC) peak torque (PT) values at 60º/s and 300º/s, and the strength status of ER/IR muscles, such as the traditional ipsilateral strength deficit (ER/IR), ER/ER, IR/IR, and the non-dominant (ND) ER/IR: dominant (DOM) ER/IR (ERIR: ERIR), known as the bilateral strength asymmetry. Additionally, we recorded the ratio of Eccentric External (ECC ER) / Concentric Internal rotation (CON IR) before judo activity. The isokinetic Biodex system measured all of the variables. The injury occurrences were recorded during the 10-month follow-up period in the judo national team camps from 2020 to 2021. We followed fourteen upper limb sport injuries among the 53 judokas. Assessing shoulder rotator muscle strength, particularly in the eccentric mode, played a significant role in shoulder risk factor identification. Significant accuracy of ipsilateral PT deficit ECC ER/IR at (ND) 60º/s (OR 0.973, 95% CI 0.951 to 0.996, p = 0.024), as well as the bilateral PT deficit ECC ERIR: ERIR ratios 60º/s (OR 0.043, 95% CI 0.002 to 0.728, p = 0.029) discriminated between injured and uninjured judokas. The optimal cut-off point of the ND ER/IR ratio associated with the uninjured judokas group was 72.7 (sensitivity, 0.667; specificity, 0.643). The findings of the present study suggest that incorporating pre-participation testing of ipsilateral and bilateral shoulder ER/IR rotator assessment of isokinetic PT, particularly in ECC, can be valuable in an injury prevention program for judokas. Pre-participation testing involving isokinetic peak torque assessment of ipsilateral and bilateral shoulder external/internal rotators, particularly on eccentric strength, can significantly contribute to an effective injury prevention program for judokas. These tests can help identify potential weaknesses or imbalances in the shoulder rotator muscles, allowing for targeted interventions and training strategies to mitigate injury risks. The findings of this study provide suggestive evidence for the development of a preventive training program that incorporates controlled eccentric exercises specifically tailored for elite judokas. Integrating eccentric training into their regular training regimen may significantly enhance shoulder strength and stability in judokas. This enhancement is expected to decrease the risk of shoulder injuries while simultaneously improving overall judokas performance. Therefore, the implementation of such a program could be a critical component in promoting both injury prevention and performance optimization in this population.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.321
Teacher spread0.311 · 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
Published2025
Admission routes1
Has abstractyes

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