The Effect of Lower Limb Alignment on Tibiofemoral Joint Contact Biomechanics after Medial Meniscus Posterior Root Repair: A Finite-Element Analysis
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study was to determine how variations in lower limb alignment affect tibiofemoral joint contact biomechanics in the setting of medial meniscus posterior root tear (MMPRT) and associated root repair. METHODS: A finite-element model of an intact knee joint was developed. Limb alignments ranging from 4° valgus to 8° varus were simulated under a 1,000 N compression load applied to the femoral head. For the intact, MMPRT, and root repair conditions, the peak contact pressure (PCP), total contact area, mean and maximum local contact pressure (LCP) elevation, and total area of LCP elevation of the medial tibiofemoral compartment were quantified. RESULTS: The PCP and total contact area of the medial compartment in the intact knee increased from 2.43 MPa and 361 mm 2 at 4° valgus to 9.09 MPa and 508 mm 2 at 8° of varus. Compared with the intact state, in the MMPRT condition, medial compartment PCP was greater and the total contact area smaller for all alignment conditions. Root repair roughly restored PCPs in the medial compartment; however, this ability was compromised in knees with increasing varus alignment. Specifically, elevations in PCP relative to the intact state increased with increasing varus, as did the total contact area with LCP elevation. After root repair, medial compartment PCP remained elevated above the intact state at all degrees tested, ranging from 0.05 MPa at 4° valgus to 0.27 MPa at 8° of varus, with overall PCP values increasing from 2.48 to 9.09 MPa. For varus alignment greater than 4°, root repair failed to reduce the total contact area with LCP elevation relative to the MMPRT state. DISCUSSION: Greater PCPs and areas of LCP elevation in varus knees may reduce the clinical effectiveness of root repair in delaying or preventing the development of tibiofemoral osteoarthritis.
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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 | 0.001 |
| 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) | 0.002 | 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".