The Effect of Joint Line Elevation on In Vivo Knee Kinematics in Bicruciate Retaining Total Knee Arthroplasty
Bibliographic record
Abstract
Abstract Prior studies have reported a negative effect on both clinical outcomes and patient-reported outcome measures (PROMS) following joint line elevation (JLE) in cruciate-retaining (CR) total knee arthroplasty (TKA) and posterior stabilized (PS) TKA designs. This experimental study was aimed to quantify the effect of JLE on in vivo knee kinematics in patients with bicruciate retaining (BCR) TKA during strenuous activities. Thirty unilateral BCR TKA patients were evaluated during single-leg deep lunge and sit-to-stand using a validated combined computer tomography and dual fluoroscopic imaging system. Correlation analysis was performed to quantify any correlations between JLE and in vivo kinematics, as well as PROMS. There was a significant negative correlation between JLE and maximum flexion angle during single-leg deep lunge (ρ = −0.34, p = 0.02), maximum varus joint angles during single-leg deep lunge (ρ = −0.37, p = 0.04), and sit-to-stand (ρ = −0.29, p = 0.05). There was a significant negative correlation between JLE and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score (ρ = −0.39, p = 0.01) and knee disability and osteoarthritis outcome score physical function (KOOS-PS; ρ = −0.33, p = 0.03). The JLE that yields a significant loss in PROMS and maximum flexion angles were 2.6 and 2.3 mm, respectively. There was a linear negative correlation of JLE with both in vivo knee kinematics and PROMS, with changes in JLE of greater than 2.6 and 2.3 mm, leading to a clinically significant loss in PROMS and maximum flexion angles, respectively, suggesting an increased need to improve surgical precision to optimize patient outcomes following BCR TKA.
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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 | 0.002 |
| 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 | 0.000 | 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".