Long-term Effectiveness of Sorbie-QUESTOR Elbow Arthroplasty: Single Surgeon’s Series of 15 Years
Bibliographic record
Abstract
With increasing usage of many types of total elbow replacements, there is a continuing need for clinical series that report survivorship, complications and revisions, and performance of single types of implants over extended time periods. The purpose of this study was to assess the long-term effectiveness of all implants of the Sorbie-QUESTOR (SQ) unlinked surface arthroplasty conducted by a single surgeon (C.S.) over 15 years at a single site, and to determine whether there were diagnostic group differences. Between 1995 and 2002, 51 S-Q prosthetic elbows were implanted into 44 patients. The patient groups were hemophilia, rheumatoid arthritis, and "other," which included osteoarthritis, traumatic arthritis, psoriatic arthritis, and reactive arthritis. Annual evaluations included scores of pain, range of motion, and function. The most recent annual evaluation was included in the data set. Details of complications and revisions were recorded. The hemophiliac group had the best survival outcomes at 87.5%. Eighteen prostheses required revision or removal with all but 3 retained or replaced. Postoperatively, 73% rated their pain as 'slight' or 'none'. The hemophilia and rheumatoid arthritis groups made very large total flexion/extension gains. The rheumatoid arthritis group made significant forearm motion gains. Average functional assessment gains were nearly 2 grades of 5 functional levels and were significant for all groups. The S-Q surface arthroplasty has demonstrated long-term effectiveness in patients with a variety of elbow joint pathologies showing reduction in pain, large gains in joint range and function, and good long-term survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".