The clinical outcome of total knee arthroplasty is compromised by a previously implanted medial unicondylar knee arthroplasty
Bibliographic record
Abstract
OBJECTIVE: To investigate the clinical outcome of patients that underwent conversion of a medial unicondylar knee arthroplasty (UKA) to a total knee arthroplasty (TKA) and to compare that outcome to patients that underwent primary TKA. It was hypothesized that those groups would significantly differ in terms of knee score outcome and implant survival. METHODS: A retrospective-comparative study was conducted utilizing data from the Federal state's arthroplasty registry. Included were patients from our department that undergone a conversion of a medial UKA to a TKA (UKA-TKA group). The Western Ontario and MacMaster Universities Osteoarthritis Index (WOMAC) from preoperative and 1-year postoperative was used. Moreover, the implant survival was analyzed. RESULTS: In the UKA-TKA group, there were 51 cases (age 67 ± 10, 74% women), and in the TKA group, there were 2247 cases (age 69 ± 9, 66% women). The one-year postoperative WOMAC total score was 33 in the UKA-TKA group und 21 in the TKA group (p < 0.001). Similarly, the WOMAC pain, WOMAC stiffness, and WOMAC function scores were significantly worse in the UKA-TKA. After 5 years, the survival rates were 82% and 95% (p = 0.001). The 10-years prosthesis survival was 74% and 91% in the UKA-TKA and TKA groups, respectively (p < 0.001). CONCLUSIONS: Based on our findings it is concluded that patients who received a TKA after UKA have inferior results than those that directly receive a TKA. This is true for both patient-reported knee outcome and prosthesis survival. Converting UKA to TKA should not be seen as an easy operation, but should rather be done by surgeons with considerable experience in both primary and revision knee arthroplasty.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".