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Record W3108336448 · doi:10.1136/bmjsem-2020-000868

Concentric and eccentric isokinetic hamstring injury risk among 582 professional elite soccer players: a 10-years retrospective cohort study

2020· article· en· W3108336448 on OpenAlexaff
Ricardo Lima Burigo, Robson Dias Scoz, Bruno Mazziotti de Oliveira Alves, Rubens Alexandre da Silva, César Augusto Melo‐Silva, Edgar Ramos Vieira, Rogério Pessoto Hirata, César Ferreira Amorim

Bibliographic record

VenueBMJ Open Sport & Exercise Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsConcentricHamstringEccentricLogistic regressionPhysical therapyMultivariate statisticsMedicineStepwise regressionStatisticsPhysical medicine and rehabilitationMathematicsEngineeringStructural engineeringGeometry

Abstract

fetched live from OpenAlex

BACKGROUND/AIM: Different authors have tried to correlate the peak isokinetic torque values with the incidence of soccer match injuries. However, due to the wide variety of assessment testing protocols, such an inference becomes difficult. This study aimed to verify the capacity of an isokinetic test to establish injury risk reference values for hamstring strain injuries. METHODS: A retrospective cohort study based on isokinetic data and clinical records from the last 10 years was conducted in 582 Brazilian elite-professional soccer players, who were subjected to the same isokinetic test protocol, machine, and tester. A Multivariate Logistic Regression Analysis for Complex Data Sampling was used to generate injury risk statistical indexes. RESULTS: Multivariate regression analysis of both legs provided important data to identify the cut-off values of Concentric Peak Torque (181.82 Newton/*metres), Concentric Work (236.23 watts) and Concentric Power (130.11 joules). CONCLUSIONS: The injury risk indexes indicate that an increase of just one Newton unit in CPT (Concentric Peak Torque) and CJ (Concentric Power) above those cut-off values, can reduce the risk of future injuries by 2% and 2.7%, respectively.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.341
Teacher spread0.322 · 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 teacher head, not a consensus.

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".

Quick stats

Citations13
Published2020
Admission routes1
Has abstractyes

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