Effect of opening-wedge high tibial osteotomy on the three-dimensional kinematics of the knee
Bibliographic record
Abstract
Although it is clear that opening-wedge high tibial osteotomy (HTO) changes alignment in the coronal plane, which is its objective, it is not clear how this procedure affects knee kinematics throughout the range of joint movement and in other planes. Our research question was: how does opening-wedge HTO change three-dimensional tibiofemoral and patellofemoral kinematics in loaded flexion in patients with varus deformity?Three-dimensional kinematics were assessed over 0° to 60° of loaded flexion using an MRI method before and after opening-wedge HTO in a cohort of 13 men (14 knees). Results obtained from an iterative statistical model found that at six and 12 months after operation, opening-wedge HTO caused increased anterior translation of the tibia (mean 2.6 mm, p < 0.001), decreased proximal translation of the patella (mean -2.2 mm, p < 0.001), decreased patellar spin (mean -1.4°, p < 0.05), increased patellar tilt (mean 2.2°, p < 0.05) and changed three other parameters. The mean Western Ontario and McMaster Universities Arthritis Index improved significantly (p < 0.001) from 49.6 (standard deviation (sd) 16.4) pre-operatively to a mean of 28.2 (sd 16.6) at six months and a mean of 22.5 (sd 14.4) at 12 months. The three-dimensional kinematic changes found may be important in explaining inconsistency in clinical outcomes, and suggest that measures in addition to coronal plane alignment should be considered.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".