High Tibial Osteotomy versus Unicompartmental Knee Arthroplasty for Medial Compartment Arthrosis with Kissing Lesions in Relatively Young Patients
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to compare the clinical and radiographic outcomes of high tibial osteotomy (HTO) and unicompartmental arthroplasty (UKA) in advanced medial compartment arthritis accompanied by kissing lesions in relatively young patients. MATERIALS AND METHODS: Forty-five patients were divided into the HTO (n=23) and UKA (n=22) groups. Clinically, we evaluated the Lysholm knee scoring scale, visual analogue scale, Hospital for Special Surgery, and Western Ontario and McMaster Universities Osteoarthritis index scores preoperatively, 6 and 12 months postoperatively, and at the final follow-up. Radiographically, we measured the femoral-tibial angle and mechanical axis deviation preoperatively and at the final follow-up. RESULTS: All clinical outcomes gradually improved in both groups from the postoperative period to the final follow-up. At the final follow-up, all clinical outcomes were slightly better in the UKA group than in the HTO group; however, differences were not statistically significant. CONCLUSIONS: HTO is comparable to UKA in terms of clinical outcomes. Thus, the results of this study suggest that HTO might be a good alternative treatment to UKA for medial unicompartmental arthritis accompanied by kissing lesions in relatively young patients.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".