Comparison of the Kinematics and Laxity of Total Knee Arthroplasty Bearing Designs Stabilized With Specimen-Specific Virtual Ligaments on a Joint Motion Simulator
Bibliographic record
Abstract
A variety of total knee arthroplasty (TKA) designs offer increased congruency bearing options, primarily to compensate for a loss of posterior cruciate ligament (PCL) function. However, their efficacy in providing sufficient stability under different circumstances requires further investigation. The preclinical testing of prosthesis components on joint motion simulators is useful for quantifying how design changes affect joint stability. However, this type of testing may not be clinically relevant because surrounding ligaments are either ignored or greatly simplified. This study aimed to assess the kinematics and stability of TKA joints during various motions using condylar-stabilized (CS) bearings without a PCL versus cruciate-retaining (CR) bearings with an intact PCL. TKA prosthetic components were tested on a joint motion simulator while being stabilized with five different sets of specimen-specific virtual ligament envelopes. In comparison to CR knees, CS knees without a PCL exhibited a greater amount of posterior tibial displacement laxity, with a mean increase of 2.7±2.1 mm (p = 0.03). Additionally, significant differences were observed in the anterior-posterior kinematics of the knee joint during activities of daily living (ADL) between the two designs. These results were consistent with previous cadaveric investigations, which indicated that CS knees without a PCL are less resistant to posterior tibial displacement than CR knees with one. This study employing virtual ligaments confirms previous findings that the raised anterior lip of some CS bearings may not completely compensate for the absence of the PCL; however, as both studies used reduced joint contact forces, the contributions of this design feature may be attenuated.
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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 | 0.001 | 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".