Trial Tibial Inserts May Result in Different Knee Kinematics from Final Poly Inserts in Total Knee Arthroplasty
Bibliographic record
Abstract
INTRODUCTION: Trialling is a key step in total knee arthroplasty (TKA) and helps the surgeon assess for adequate balancing, range of motion, and stability. Despite this, there are no studies investigating knee kinematics when using trial versus final polyethylene tibial inserts. MATERIALS AND METHODS: Fourteen fresh frozen cadaveric specimens were cycled in a VIVO joint motion simulator. Using both simple compression and simulated muscle loads, joints were tested after TKA with a trial insert or a final tibial poly insert. Anterior/posterior (AP), internal/external (IE), and varus/valgus (VV) kinematics and laxities were analyzed. RESULTS: Knees with trial poly inserts had significantly greater AP hysteresis (difference between flexion and extension motion) than those with final poly inserts (p=0.001). There was no significant difference in IE (p=0.563) or VV (p=0.580) hysteresis. There was no difference in AP, IE, or VV motion or laxities when considering the flexion path alone. Prosthetic joints followed different paths in flexion versus extension. CONCLUSION: While trial tibial inserts impart valuable information, they may not accurately reproduce the same joint kinematics as final inserts. Balancing of the knee at specific degrees of flexion may depend on the path taken to get there.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".