Fixed-Bearing versus Mobile-Bearing Unicondylar Knee Arthroplasty: Comparison of Patients with Similar Component and Mechanical Axis Alignment
Bibliographic record
Abstract
Aim: Unicondylar knee arthroplasty (UKA) is among the treatment options for patients with arthritis limited to one compartment of the knee. Fixed-bearing (FB) and mobile-bearing (MB) inserts are present. This study aimed to compare functional and clinical outcomes and revision rates of patients operated with FB-UKA and MB-UKA. Material and Methods: A total of 131 knees of 118 patients underwent cemented UKA, with a mean follow-up period of 80.58±31.31 months for FB-UKA and 97.66±29.24 months for MB-UKA. Clinical and functional evaluation was performed by the Knee Society Score (KSS) and Western Ontario and McMaster Universities Arthritis Index (WOMAC) score, at the last follow-up visit. The factors affecting the radiological and functional results, complication, and revision rates were examined under three main titles; i) surgeon-related, ii) patient-related, and iii) component alignment-related factors. Results: There was no significant difference between the groups in terms of age, gender, body mass index, and side. Regarding the KSS scores, 9 (6.87%) knees were within acceptable limits, 62 (47.32%) knees were found to be good, and 60 (45.80%) knees were found to be excellent. No statistically significant difference was found between groups (p=0.497). Regarding the WOMAC scores, the MB-UKA group had significantly lower pain (p=0.049) and stiffness (p=0.014), but similar functional (p=0.591) scores. There was no statistically significant difference regarding revision rates (p=0.931). Conclusion: Similar clinical, functional, and radiological results and low revision rates were found. In terms of pain and joint stiffness, a significant difference was found between groups, in favor of MB-UKA.
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 | 0.000 | 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) | 0.002 | 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".