Mid-Term Outcomes of Metal-Backed Unicompartmental Knee Arthroplasty Show Superiority to All-Polyethylene Unicompartmental and Total Knee Arthroplasty
Bibliographic record
Abstract
Background Two commonly used tibial designs for unicompartmental knee arthroplasty (UKA) are all-polyethylene “inlay” and metal-backed “onlay” components. Biomechanical studies showed that the metal baseplate in onlay designs better distributes forces over the tibia but studies failed to show differences in functional outcomes between both designs at mid-term follow-up. Furthermore, no studies have compared both designs with total knee arthroplasty (TKA). Questions/Purposes The goal of this study was to compare outcomes of inlay UKA and onlay UKA at mid-term follow-up and compare these with TKA outcomes. Methods In this retrospective study, 52 patients undergoing inlay medial UKA, 59 patients undergoing onlay medial UKA, and 59 patients undergoing TKA were included. Western Ontario and McMaster Universities Arthritis Index scores were collected preoperatively and at mean 5.1-year follow-up (range 4.0–7.0 years). Results Preoperatively, no differences were observed in patient characteristics or outcome scores. At mid-term follow-up, patients undergoing onlay medial UKA reported significant better functional outcomes than those of inlay medial UKA (92.0 ± 10.4 vs. 82.4 ± 18.7, p = 0.010) and when compared to TKA (92.0 ± 10.4 vs. 79.6 ± 18.5, p < 0.001) while no significant differences between inlay medial UKA and TKA were noted. No significant differences in revision rates were found. Conclusion Functional outcomes following onlay metal-backed medial UKA were significantly better compared to inlay all-polyethylene medial UKA and to TKA. Based on the results of this study and on biomechanical and survivorship studies in the literature, we recommended using metal-backed onlay tibial components for unicompartmental knee arthroplasty.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".