Total Knee Arthroplasty Using a Medial Pivot or Posterior Cruciate-Stabilizing Prosthesis in Chinese Patients
Bibliographic record
Abstract
There is an unmet need for a prosthesis designed according to the anatomical parameters of the Chinese population. This study aims to compare the use of a medial pivot (MP) implant or posterior cruciate ligament (PCL) substitution (posterior-stabilized [PS]) prosthesis for unilateral total knee arthroplasty (TKA) in a Chinese population. The medical records of patients undergoing unilateral TKA with an MP implant (Group A) or a PS prosthesis (Group B) at our institution between January 2010 and December 2011 were retrospectively reviewed. Patients were followed up for 5 years. Preoperatively and at the December 2016 postoperative follow-up, the Hospital for Special Surgery scoring system (HSS knee score) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score were measured to evaluate TKA outcomes. This study included 49 patients in Group A and 51 in Group B. As of December 2016, there were no significant differences in the preoperative/postoperative changes in any category of the HSS knee score or WOMAC score between the groups. There were no postoperative complications in either group during the 5-year follow-up. There were no periprosthetic infections or need for revision surgery. One patient in Group A experienced aching and a small amount of effusion in the articular cavity that was attributed to overexertion. In conclusion, there were no significant differences in midterm outcomes in Chinese patients receiving an MP implant or a PS prosthesis for unilateral TKA. These data suggest that the MP and PCL substitution design are safe and effective for unilateral TKA in China.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".