Comparison of clinical and radiographic results between total knee arthroplasties using medial pivot and posterior-stabilized prosthesis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the clinical and radiographic outcomes of total knee arthroplasties (TKA) between using medial-pivot (MP) and posterior-stabilized (PS) prosthesis. Does MP prosthesis and PS prosthesis influence the clinical results of a TKA? METHODS: An electronic literature search of PubMed Medline and the Cochrane Library was performed from inception to October 1, 2019. A meta-analysis to compare postoperative outcomes of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, Knee Society Score (KSS), range of motion (ROM), complications, and radiographic results between MP and PS prosthesis were conducted. RESULTS: Seven eligible studies involving 934 adult patients (MP group, n = 461; PS group, n = 473) were identified for analysis. This study showed no significant difference between the 2 groups in the WOMAC scores, KSS, ROM, and complications (P > .05). The differences of the femorotibial angle, position of implant, and patellar tilt were also not significant between the 2 groups (P > .05). CONCLUSION: The present meta-analysis has shown that patients with the MP prosthesis have similar clinical results as patients with PS prosthesis. Furthermore, the radiographic results, especially patella tilt angle, were also similar between the 2 groups. Therefore, surgeons should be aware that the types of prostheses are not a decisive factor to ensure successful operation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".