Responders to Medial Opening Wedge High Tibial Osteotomy for Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Medial opening wedge high tibial osteotomy (HTO) aims to improve symptoms for patients with knee osteoarthritis (OA) and varus alignment, yet the likelihood of achieving a minimum clinical threshold of response and the factors predictive of response are unclear. We evaluated the proportion of patients meeting responder criteria based on the Outcome Measures in Rheumatology-Osteoarthritis Research Society International consensus 2 years after medial opening wedge HTO and investigated predictors of response. METHODS: Patients in a prospective cohort with symptomatic knee OA and varus alignment completed the Knee Injury and Osteoarthritis Outcome Score questionnaire < 3 months before and 2 years after HTO. For our primary analysis, we calculated the proportion of responders with ≥ 20% relative improvement and an absolute change of ≥ 10 points in pain and function from baseline. We performed logistic regression to evaluate the association of predictors with response and completed sex-disaggregated analyses. RESULTS: At a mean of 20.3 (SD 6.2) months post-HTO, 406 patients (78%) met the responder criteria. Older age, higher BMI, and larger postoperative mechanical axis angles (ie, slight valgus) were associated with increased odds of achieving responder criteria, although odds ratios were small. When stratified by sex, 316/405 male patients (78%) and 90/118 female patients (76%) met the responder criteria. CONCLUSION: Based on responder criteria for knee OA, 78% of patients undergoing medial opening wedge HTO were responders at 2 years postsurgery. Although patients who are younger, male, and nonobese are viewed as appropriate candidates for HTO, patients who are female, are older, and have a high BMI also achieve sizable improvements in pain and function.
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".