Femoral and tibial insert downsizing increases the laxity envelope in TKA
Bibliographic record
Abstract
PURPOSE: This study examines the effect of component downsizing in a modern total knee arthroplasty (TKA) system on the laxity envelope of the knee throughout flexion. METHODS: A robotic testing system was utilized to measure laxity envelopes in the implanted knee by in the anterior-posterior (AP), medial-lateral (ML), internal-external (IE) and varus-valgus (VV) directions. Five fresh-frozen cadavers were tested with a modern cruciate retaining TKA implantation, a 1-mm thinner polyethylene insert and a femoral component 2 mm smaller in the AP dimension. RESULTS: The downsized tibial insert was more lax throughout the flexion arc with up to 2.0 mm more laxity in the AP direction at full extension, a 43.8% increase over the original implantation. A thinner insert consistently increased laxity throughout the arc of flexion in all degrees of freedom. Downsizing the femoral component resulted in 8.5 mm increase in AP laxity at 90°, a 73.9% increase. In mid-flexion, downsizing the femur produced similar laxity values to the downsized insert in AP, ML, IE and VV directions. CONCLUSION: Downsizing the TKA components had significant effects on laxity throughout flexion. Downsizing a femoral component 2 mm had an equivalent increase in laxity in mid-flexion as downsizing the tibial insert 1 mm. This study quantifies the importance of choosing the appropriate implant component size, having the appropriate size available and the effect of downsizing. The laxity of the implanted knee contributes to how the implant feels to the patient and ultimately the patient's satisfaction with their new knee.
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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".