Combined Tibial Tubercle Osteotomy With Medial Opening Wedge High Tibial Osteotomy Minimizes Changes in Patellar Height
Bibliographic record
Abstract
BACKGROUND: Medial opening wedge high tibial osteotomy (HTO) for the treatment of varus gonarthrosis can be associated with inadvertent decreases in patellar height. HYPOTHESIS: Decreases in patellar height observed after medial opening wedge HTO can be minimized with the addition of a tibial tubercle osteotomy (TTO). STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Twenty-nine patients undergoing medial opening wedge HTO with a concurrent TTO were matched with 29 controls who previously underwent medial opening wedge HTO without a TTO. Both groups had substantial varus malalignment (mean mechanical axis angle, -10° ± 3°) requiring large corrections. Measurements of patellar height and posterior tibial slope were calculated from standing lateral radiographs and compared preoperatively and 6 months postoperatively. Patellar height measures included the Blackburne-Peel index, Caton-Deschamps index, Miura-Kawamura index, Insall-Salvati ratio, and modified Insall-Salvati ratio. RESULTS: The changes in the Blackburne-Peel, Caton-Deschamps, and Miura-Kawamura indices were significantly less in the HTO/TTO group versus the HTO group. There were 3 of 29 (10%) new cases that met the radiographic criteria for patella infera in the HTO/TTO group versus 11 of 29 (38%) new cases of patella infera found postoperatively in the HTO group, suggesting an absolute risk reduction of 28% with TTO. The changes in the Blackburne-Peel and Caton-Deschamps indices were correlated to a larger preoperative varus deformity in the coronal plane (r = 0.52 and r = 0.41, respectively). CONCLUSION: The addition of a TTO when performing a medial opening wedge HTO minimizes the decreases in patellar height associated with the procedure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".