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Quadriceps Strength And Drop Vertical Jump Ground Reaction Forces After Anterior Cruciate Ligament Reconstruction

2022· article· en· W4294844853 on OpenAlexaff
Dan Ogborn, Brittany Bruinooge, Sheila McRae, Peter S. Macdonald

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2022
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsPan Am Clinic
Fundersnot available
KeywordsGround reaction forceConcentricAnterior cruciate ligamentAnterior cruciate ligament reconstructionQuadriceps tendonMedicineHamstringVertical jumpJumpingPhysical medicine and rehabilitationKinematicsKnee JointJumpACL injuryOrthodonticsMathematicsTendonAnatomySurgeryPhysicsGeometry

Abstract

fetched live from OpenAlex

Compensatory movements following anterior cruciate ligament (ACL) reconstruction (ACLr) may result in altered ground reaction forces (GRF) as individuals shift loading to the unaffected limb or vary joint contributions within the affected limb. It is unknown whether such movement patterns are the result of underlying impairments including reduced quadriceps strength, persistent kinematic alterations (motor control), or psychological factors (confidence) in isolation or combination. PURPOSE: The purpose of this study was to define the relationship between isokinetic, concentric quadriceps strength, and GRFs during the initial landing, take-off, and subsequent landing phases of a drop vertical jump (DVJ). METHODS: 75 patients (n = 26 bone-patellar-tendon-bone, 27 quadriceps tendon and 22 hamstring grafts; 78.3 ± 17.9 kg, 175.3 ± 9.4 cm) were assessed at 12 months following ACLr. A performance assessment was completed including three repetitions of a DVJ from a 30 cm box to two forces plates at 50% of the patient’s height from the platform. Five repetitions of concentric isokinetic knee extension at 90o/s were completed thereafter. Peak vertical GRF were determined during the initial landing, take-off, and secondary landing phases and averaged over three trials. One and two-way ANOVAs were used to determine the effect of graft type on torque, GRF and LSI values, and linear regression to test the relationship between quadriceps affected limb torque and LSI with DVJ GRF LSI. RESULTS: Quadriceps strength was reduced on the affected limb (p < 0.001) and the quadriceps limb symmetry index (LSI) did not vary by graft (p = 0.173). Similarly, affected limb GRF was reduced (p < 0.001) with no interaction of limb, graft and DVJ phase, and GRF LSI did not vary by graft or phase (p = 0.872). Affected limb torque and concentric quadriceps LSI explained 8.1% (p = 0.008) and 9.7% (p = 0.004) of take-off LSI variance, but not in the initial or subsequent landing phases of the DVJ task. CONCLUSIONS: Concentric quadriceps strength and symmetry hold limited explanatory power in GRF patterns at one-year following ACLr. Future work should consider alternate contraction modes and other outcomes that may explain compensatory movements during the DVJ task, including task-specific measures of confidence or other psychological outcomes.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.271
Teacher spread0.262 · 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
Published2022
Admission routes1
Has abstractyes

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