Tibiofemoral Kinematics of the Anterior Cruciate Ligament (ACL)-Deficient Weightbearing, Living Knee Employing Vertical Access Open “Interventional” Multiple Resonance Imaging
Bibliographic record
Abstract
BACKGROUND: Our current understanding of tibiofemoral kinematics in the anterior cruciate ligament (ACL)-deficient knee is very limited. Using vertical open-access MRI, it is possible to accurately analyze tibiofemoral motion in patients with isolated rupture of the ACL. STUDY: Prospective cohort study. PURPOSE: To assess if ACL rupture alters normal knee weightbearing kinematics. METHODS: Tibiofemoral motion was assessed through the arc of flexion from 0 degrees to 90 degrees in 10 patients with isolated rupture of the ACL in one knee and a normal contralateral knee. Midmedial and midlateral sagittal images were analyzed in all positions of flexion in both knees to assess the tibiofemoral relationship. RESULTS: In the lateral compartment of the knee, the tibial plateau is persistently subluxed anteriorly throughout the arc of flexion from 0 degrees to 90 degrees (flexion facet center to posterior tibial cortex distance of 15.8 mm +/- 2.9 in ACL-deficient knees compared to 21.4 mm +/- 1.4 in normal knees at 0 degrees extension, P <.0001) when compared to normal knees. The medial tibiofemoral relationship is unchanged compared to normal knees. CONCLUSION: Rupture of the ACL changes tibiofemoral kinematics producing anterior subluxation of the lateral tibial plateau. CLINICAL SIGNIFICANCE: Altered kinematics may explain, at least in part, the increased incidence of secondary osteoarthritis in patients with ACL rupture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".