Early functional outcome after lateral UKA is sensitive to postoperative lower limb alignment
Bibliographic record
Abstract
PURPOSE: The predictive role of patient-specific characteristics and radiographic parameters on medial unicompartmental knee arthroplasty (UKA) outcomes is well known, but knowledge of these predictors is lacking in lateral UKA. Therefore, purpose of this study was to assess the predictive role of these parameters on short-term functional outcomes of lateral UKA. METHODS: In this retrospective cohort study, Western Ontario and McMaster Universities Arthritis Index scores were collected at 2-year follow-up (median 2.2 years, range 2.0-4.0 years) in 39 patients who underwent lateral UKA. Patient-specific characteristics included age, BMI and gender, while radiographic parameters included osteoarthritis severity of all three compartments and both preoperative and postoperative hip-knee-ankle alignment. RESULTS: BMI, gender, age and preoperative valgus alignment were not correlated with functional outcomes, while postoperative valgus alignment was correlated with functional outcomes (0.561; p = 0.001). Postoperative valgus of 3°-7° was correlated with better outcomes than more neutral (-2° to 3° valgus) alignment (96.7 vs. 85.6; p = 0.011). Postoperative alignment was a predictor when corrected for patient-specific characteristics (regression coefficient 4.1; p < 0.001) and radiological parameters (regression coefficient 3.8; p = 0.002). CONCLUSIONS: Postoperative valgus alignment of 3°-7° was correlated with the best short-term functional outcomes in lateral UKA surgery, while patient-specific parameters and preoperative alignment were not correlated with functional outcomes. Based on these findings, a surgeon should aim for valgus alignment of 3°-7° when performing lateral UKA surgery for optimal functional outcomes. LEVEL OF EVIDENCE: Prognostic study, Level II.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".