An In Vitro Biomechanical Analysis of the Contributions of Medial Ligaments to the Stability of the PCL-Deficient Knee
Bibliographic record
Abstract
Objectives: Approximately 95% of PCL injuries are multi-ligament injuries, yet it remains unclear if simultaneous injuries sustained to medial-side knee stabilizers such as the posterior oblique ligament (POL) and deep medial collateral ligament (dMCL) also need to be addressed. Pathomechanical kinematics that still exists after PCL reconstructions may be the result of residual instability due to deficiency of these secondary stabilizers. The objective of this study is to characterize the relative contributions of the POL, dMCL and superficial medial collateral ligament (sMCL) in PCL-deficient knees. We hypothesize that the POL would contribute to stability in extension only, whereas the dMCL would provide stability throughout the entire flexion range of motion. Methods: Eight specimens (aged 40-63, 5 female, 1 male, 2 pairs) were potted and the PCL was dissected arthroscopically. Each specimen was mounted onto a VIVO joint motion simulator (AMTI) and flexed from 0 to 90 degrees with a 10 N compressive load applied along the long axis of the tibia. During this motion, a 5 Nm internal or external moment was applied to the tibia, and the resulting kinematics were recorded. Recorded kinematics were applied back on the specimen, while the joint’s reaction torque to this rotation was measured. The decrease in reaction torque was measured following randomized dissection of the POL and dMCL (4 POL first and 4 dMCL first); the sMCL was always dissected last. The contribution of each ligament to this reaction torque was measured by calculating the change in the reaction torque caused by the ligament’s dissection at 0, 30, 60 and 90 degrees. Each ligament’s relative contribution was compared to the net reaction torque of the joint to calculate the percentage contribution of the ligament. The contribution of each ligament was analyzed using a one-way repeated measure ANOVA with a significance value of 0.05. Results: With an internal torque applied, the dMCL’s contribution to the reaction torque was greatest at 30 degrees, accounting for up to 23% +/- 19% of the overall reaction torque; its contribution was not significantly affected by flexion angle (p>0.05). The POL’s contribution was significantly affected by flexion angle (p=0.007), accounting for 40% +/- 15% of the reaction torque at 0 degrees but only 6% +/- 4% at 90 degrees. The sMCL’s contribution was also sensitive to flexion angle (p=0.006), accounting for 14% ± 16% of the reaction torque at 0 degrees and increasing to 28% +/- 12% at 90 degrees. With an external torque applied, the dMCL’s contribution accounted for 12% +/- 4% of the reaction torque at 0°, but this decreased to 4% +/- 2% at 90 degrees; its contribution was significantly affected by flexion angle (p=0.038). The POL’s contribution accounted for 12% +/- 3% of the reaction torque at 0 degrees and 3% +/- 3% at 90 degrees and the flexion angle changed this contribution significantly (p=0.003). A large portion of the reaction torque was provided by the sMCL, accounting for 52% +/- 7% at 90 degrees. Conclusions: Our results show that, with internal torques applied to the tibia, the POL plays an important role in resisting motion when the joint is near full extension. Conversely, the dMCL’s (and sMCL’s) contribution is largest in flexion. Neither the POL nor dMCL have a large contribution towards resisting external tibial torques; the sMCL seems to be the primary ligament resisting external rotation among medial ligaments. Thus, there is the potential for increased posteromedial instability if POL and dMCL injuries are not addressed, increasing the risk of a failed PCL reconstruction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".