<b><i>In vivo</i></b>patellar kinematics during total knee arthroplasty
Bibliographic record
Abstract
Patellar maltracking after total knee arthroplasty often results in complications, including anterior knee pain, instability and impingement, and is therefore better resolved intraoperatively. Many factors can affect patellar kinematics during knee replacement, including component position, implant design, joint alignment, and soft tissue tensions. However, to our knowledge, the impact of arthroplasty on patellar kinematics has not been previously reported in vivo. A computer-assisted surgery (CAS) system was developed to measure the pre-arthroplasty patellar kinematics, display the distance between this path and the surface of the planned femoral component, and compare the post-arthroplasty path to the pre-arthroplasty path. Three surgeons from three centers used this CAS system to measure the in vivo pre- and post-arthroplasty kinematics of 18 patients. There was a small, but consistent, proximal shift in the tibial joint lines (mean: 4.2 mm), resulting in pseudo patella-baja, i.e., relatively more distal contact of the patella on the femoral component. This led to significant changes in proximodistal and anteroposterior patellar positioning as well as patellar flexion following arthroplasty (p < 0.008). Mediolateral shift, tilt and internal/external spin had the greatest magnitudes of change (mean: 4.1 mm, 4.6 degrees and 4.6 degrees, respectively) relative to their mean pre-arthroplasty ranges (averaging 2.1 mm, 5.8 degrees and 5.8 degrees, respectively); however, these changes were distributed almost equally medially and laterally, indicating no surgical bias in any one direction. Female patients had more lateral tilt on average than male patients throughout flexion (p < 0.004 post-arthroplasty, p < 0.03 pre-arthroplasty, in later flexion), as well as other kinematic differences; there may therefore be potential for improving overall kinematic results by focusing on gender differences during research, design and surgery. This study demonstrated the feasibility of using a CAS system to measure patellofemoral kinematics. Intraoperative awareness of patellar tracking, including knowledge of the tibiofemoral joint line, could have an impact on the surgical plan and thereby improve the postoperative outcome.
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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 | 0.002 |
| 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 | 0.001 | 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".