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Record W4416008429 · doi:10.1177/23259671251386445

Temporal and Sex-Related Differences in Knee Biomechanics Over the Course of the Varsity Athletic Season: Pre- and Postseason Knee Kinematics in Collegiate Varsity Athletes Using Kinect

2025· article· en· W4416008429 on OpenAlexaff
T. G. Joseph, Athanasios Babouras, Kevin Zhao, Jason Corban, Paul A. Martineau

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsMcGill UniversityConcordia UniversityMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsBiomechanicsAthletesKinematicsSports biomechanicsRange of motion

Abstract

fetched live from OpenAlex

Background: Anterior cruciate ligament (ACL) tears can be a source of significant morbidity, with the potential for career-altering implications for athletes who sustain them. Specific knee biomechanics during a drop vertical jump have been shown to be associated with an increased risk for ACL injury in collegiate varsity athletes. Presently, the evolution of these kinematics from preseason to postseason is not well-understood. Purpose: To compare preseason and postseason knee biomechanics during a drop vertical jump in collegiate varsity athletes and identify changes in ACL injury risk. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 114 collegiate athletes were prospectively enrolled. Of these 114, 67 athletes (male, 21 [31%]; female, 46 [69%]) completed properly captured preseason and postseason drop vertical jumps tracked by an affordable motion capture system. Initial coronal (IC), peak coronal (PC), and peak sagittal (PS) angles of the knee were compared between preseason and postseason using the Wilcoxon signed-rank test and paired-samples t test. Athletes at high risk for ACL injury were identified based on published cutoff angles: IC angle >2.96°, PC angle >6.16°, and PS angle <93.82°, then the distribution of these athletes was compared. Results: In male athletes, all preseason knee angles were in the low-risk range. At postseason, men presented a nonsignificant reduction in mean IC and PC knee angles and a nonsignificant reduction in mean PS angle (90.88 ± 10.69). On average, female athletes were at high risk at preseason according to mean IC and PS angles (4.24 ± 1.09 and 92.90 ± 6.94, respectively). There was a statistically significant reduction in mean IC angle (mean difference [MD], 2.23; P = .03) and mean PC angle (MD, 0.76; P = .04); however, mean IC angle remained in the high-risk range. There was a nonsignificant reduction in mean PS angle, which remained within the high-risk range (MD, 3.96; P = .24). Conclusion: Our study demonstrated that female collegiate varsity athletes demonstrate higher risk knee biomechanics in comparison with their male counterparts. Even with improved biomechanics as their season advances, female athletes have a persistently low PS angle, leaving them at high risk of ACL injury. Using a portable and reliable motion capture system may facilitate monitoring knee kinematics, which could translate into a tool for ACL injury prevention in athletes.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.258
Teacher spread0.250 · 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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