The Effect of Correction Amount of Varus Deformity After Unicompartmental Knee Arthroplasty on Functional and Clinical Outcomes
Bibliographic record
Abstract
Objective: This study aimed to investigate the impact of varus deformity correction on functional and clinical outcomes following unicompartmental knee surgery. Materials and Methods: A total of 71 medial unicompartmental knee arthroplasties (UKA) in 51 patients were included in this study. The knees were categorized based on the degree of correction observed in standing orthoroentgenograms post-surgery (Group 1: 0-4.9° correction, Group 2: 5-9.9° correction, and Group 3: 10° or more correction). Functional knee evaluation was assessed using range of motion measurements, posterior tibial slope angles, visual analogue score (VAS), Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Oxford Knee Score (OKS) questionnaires. Results: Following UKA surgery, there was a significant improvement in all patient-reported outcome scores, posterior tibial slope angles, visual analogue scores, and range of motion measurements across all groups. However, no significant differences were observed when comparing postoperative scores between the groups. Conclusion: Patients with varus deformities of up to 15 degrees can safely undergo UKA surgery without compromising clinical and functional outcomes.
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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 | 0.000 | 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) | 0.002 | 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".