Early Clinical Outcomes of a New Posteriorly Stabilized Total Knee Arthroplasty Prosthesis: Comparisons with Two Established Prostheses
Bibliographic record
Abstract
Purpose: We sought to determine whether early clinical performance of new posterior stabilized (PS) knee system, the Vega-PS (Aesculap), is better than that of two established total knee arthroplasty (TKA) prostheses, the E.motion-PS (Aesculap) and the Genesis II (Smith & Nephew) in terms of functional outcomes, patient satisfaction, and incidence of adverse events. Materials and Methods: We compared the clinical outcomes of 206 consecutive TKAs using Vega-PS with those of 205 TKAs using E.motion-PS and 216 TKAs using Genesis II at 2 years of follow-up. Results: Overall, the knees with the Vega-PS had better functional outcome scores than the knees with the E.motion-PS, but had similar outcome scores to the knees with the Genesis II, as evident from the American Knee Society knee score (94.2 vs. 92.5 vs. 93.2), Western Ontario McMaster Universities Osteoarthritis (WOMAC) stiffness index (1.8 vs. 2.3 vs. 2.0), WOMAC function index (11.8 vs. 16.8 vs. 18.5), Short Form 36 (SF-36) physical component summary score (41.9 vs. 39.3 vs. 41.6), and SF-36 mental component summary score (50.0 vs. 45.8 vs. 46.9). Patient satisfaction was higher in the Vega-PS and Genesis II groups than the E.motion-PS group. No notable group differences were found in terms of the incidence of adverse events. Conclusions: The Vega-PS, a newly developed PS fixed bearing prosthesis, had comparable or superior clinical performance in comparison with the two established fixed or mobile bearing PS prostheses.
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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) | 0.001 | 0.001 |
| 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".