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Record W4384157272 · doi:10.1016/j.ptsp.2023.06.006

Is quadriceps strength associated with patellofemoral joint loading after anterior cruciate ligament reconstruction?

2023· article· en· W4384157272 on OpenAlexfundno aff
Anthony G. Schache, Prasanna Sritharan, Kay M. Crossley, Luke Perraton, Adam L. Bryant, Hayden G. Morris, Timothy S. Whitehead, Adam G Culvenor

Bibliographic record

VenuePhysical Therapy in Sport · 2023
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilUniversity of British ColumbiaUniversity of MelbourneLa Trobe UniversityArthritis Australia
KeywordsIsometric exerciseMedicineAnterior cruciate ligament reconstructionKnee JointAnterior cruciate ligamentGround reaction forceBiomechanicsKnee flexionPhysical medicine and rehabilitationOrthodonticsQuadriceps tendonJoint (building)Physical therapyContact forcePatellaSurgeryAnatomyStructural engineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To test whether quadriceps strength is associated with measures of patellofemoral (PF) joint loading during running and hopping in people after an anterior cruciate ligament reconstruction (ACLR). DESIGN: Cross-sectional study. SETTING: Biomechanics laboratory. PARTICIPANTS: Sixty-five participants (24 women; 41 men) 1-2 years post-ACLR. MAIN OUTCOME MEASURES: Peak isometric quadriceps strength for the surgical limb was measured using a dynamometer. Motion analysis and ground reaction force data were combined with musculoskeletal modelling to measure PF joint loading variables for the reconstructed knee (peak knee flexion angle; peak/impulse of the PF joint contact force; time to peak PF joint contact force) during the stance phase of running and during the landing phase of a standardised forward hop. Linear regression analysis (adjusting for age and sex) assessed the association between quadriceps strength and PF joint loading variables. RESULTS: = 0.159). CONCLUSIONS: A strong link between quadriceps strength and PF joint loading was not evident in people 1-2 years post-ACLR.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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.

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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