Changes in knee kinematics following total knee arthroplasty
Bibliographic record
Abstract
Total knee arthroplasty (TKA) changes the knee joint in both intentional and unintentional, known and unknown, ways. Patellofemoral and tibiofemoral kinematics play an important role in postoperative pain, function, satisfaction and revision, yet are largely unknown. Preoperative kinematics, postoperative kinematics or changes in kinematics may help identify causes of poor clinical outcome. Patellofemoral kinematics are challenging to record since the patella is obscured by the metal femoral component in X-ray and moves under the skin. The purpose of this study was to determine the kinematic degrees of freedom having significant changes and to evaluate the variability in individual changes to allow future study of patients with poor clinical outcomes. We prospectively studied the 6 degrees of freedom patellofemoral and tibiofemoral weightbearing kinematics, tibiofemoral contact points and helical axes of rotation of nine subjects before and at least 1 year after total knee arthroplasty using clinically available computed tomography and radiographic imaging systems. Normal kinematics for healthy individuals were identified from the literature. Significant differences existed between pre-TKA and post-TKA kinematics, with the post-TKA kinematics being closer to normal. While on average the pre-total knee arthroplasty knees in this group displayed no pivoting (only translation), individually only five knees displayed this behaviour (of these, two showed lateral pivoting, one showed medial pivoting and one showed central pivoting). There was considerable variability postoperatively as well (five central, two lateral and two medial pivoting). Both preop and postop, flexion behaviour was more hinge-like medially and more rolling laterally. Helical axes were more consistent postop for this group. An inclusive understanding of the pre-TKA and post-TKA kinematics and changes in kinematics due to total knee arthroplasty could improve implant design, patient diagnosis and surgical technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".