St Georg Sled medial unicompartmental arthroplasty: survivorship analysis and function at 20 years follow up
Bibliographic record
Abstract
PURPOSE: The peri-operative and short-term benefits of unicompartmental knee arthroplasty (UKA) are well supported in the literature. However, there remains concern regarding the higher revision rate when compared with total knee replacement. This manuscript reports the functional outcome and survivorship of a large series of fixed bearing, medial unicompartmental replacements (St Georg Sled), with a minimum of 20 years follow-up. METHODS: Between 1974 and 1994, 399 patients (496 knees) underwent a medial fixed-bearing UKA. Prospective data were collected pre-operatively and at regular intervals post-operatively using the Bristol Knee Score (BKS), Oxford Knee (OKS) and Western Ontario MacMaster (WOMAC) scores. Kaplan-Meier survival analysis was used to determine survivorship, with revision or need for revision as end point, and differences assessed using Mantel-Cox log rank test. RESULTS: Functional knee scores improved post-operatively, but demonstrated a slight decline from 10 years of follow-up onwards. Survivorship is estimated as 86% at 10 years, 80% at 15 years, and 78% at 20 years. Sixty knees were revised, with progression of disease in another compartment the commonest reason. Eighty eight percent were revised using a primary prosthesis. For patients over the age of 65 years at the time of index procedure, 93% died with a functioning prosthesis in situ. CONCLUSION: Medial UKA demonstrates good long-term function and survivorship, and represents an excellent surgical option for patients aged over 65 years of age, where few patients will require a revision procedure. LEVEL OF EVIDENCE: IV.
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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 | 0.000 | 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) | 0.001 | 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".