Relationship Between Varus-Valgus Alignment and Patellar Kinematics in Individuals with Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Abnormal varus-valgus alignment is a risk factor for patellofemoral osteoarthritis, but tibiofemoral alignment alone does not explain compartmental patellofemoral osteoarthritis progression. Other mechanical factors, such as patellar kinematics, probably play a role in the initiation and progression of the disease. The objective of this study was to determine which three-dimensional patellar kinematic parameters (patellar flexion, spin, and tilt and patellar proximal, lateral, and anterior translation) are associated with varus and valgus alignment in subjects with osteoarthritis. METHODS: Ten individuals with knee osteoarthritis and varus (five subjects) or valgus (five subjects) knee alignment underwent assessment of three-dimensional patellar kinematics. We used a validated magnetic resonance imaging-based method to measure three-dimensional patellar kinematics in knee flexion while the subjects pushed against a pedal with constant load (80 N). A linear random-effects model was used to test the null hypothesis that there was no difference in the relationship between tibiofemoral flexion and patellar kinematics between the varus and valgus groups. RESULTS: Patellar spin was significantly different between groups (p = 0.0096), with the varus group having 2 degrees of constant internal spin and the valgus group having 4.5 degrees of constant external spin. In the varus group, the patellae tracked with a constant medial tilt of 9.6 degrees with flexion, which was significantly different (p = 0.0056) from the increasing medial tilt (at a rate of 1.8 degrees per 10 degrees of increasing knee flexion) in the valgus group. The patellae of the valgus group were 7.5 degrees more extended (p = 0.0093) and positioned 8.8 mm more proximally (p = 0.0155) than the varus group through the range of flexion that was studied. The pattern of anterior translation differed between the groups (p = 0.0011). CONCLUSIONS: Our results suggest that authors of future large-scale studies of the relationships between knee mechanics and patellofemoral osteoarthritis should not rely solely on measurements of tibiofemoral alignment and should assess three-dimensional patellar kinematics directly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".