Does knee malalignment predict the efficacy of realignment therapy for patients with knee osteoarthritis?
Bibliographic record
Abstract
BACKGROUND: Realignment therapies, including knee braces, foot orthoses and shoes are prescribed to patients with medial knee osteoarthritis (OA) with the goal of unloading the medial tibiofemoral (TF) compartment. It is uncertain whether realignment therapies have different effects in those with knee malalignment. We studied whether the efficacy of realignment therapy for pain and function in persons with medial TF OA is predicted by the severity of the baseline knee malalignment. METHODS: The baseline characteristics of 48 participants with moderate to severe medial knee OA were collected. Participants' pain and function were measured using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scale before and after 12 weeks of realignment therapy using a valgus unloader knee brace plus bilateral neutral foot orthoses and motion control shoes. Anatomical axis (AA) was measured on weight-bearing knee radiographs by a blinded reader and knee malalignment was categorized as either varus malaligned (moderate or severe) or neutral according to the AA angle. We assessed for differences in response to treatment according to alignment category. General linear statistical models were generated to determine which of the measured alignment variables and covariates predicted change in the pain outcome. RESULTS: Anatomical axis knee alignment was not a significant predictor of pain or function change with active treatment. Baseline WOMAC scores were the best predictor of change in WOMAC (P < 0.01 and P = 0.06 for pain and function, respectively). CONCLUSIONS: Baseline knee alignment did not predict the efficacy of 12 weeks realignment therapy in participants with medial tibiofemoral OA. [Correction added on 27 August 2015, after first online publication: 'did predict' has been corrected to 'did not predict' in the conclusions of the abstract section.].
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 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".