Gap healing after medial open-wedge high tibial osteotomy using injectable beta-tricalcium phosphate
Bibliographic record
Abstract
PURPOSE: The study aim was to evaluate gap healing after medial open-wedge high tibial osteotomy (MOWHTO) using novel injectable beta-tricalcium phosphate (β-TCP) as gap filler. We also aimed to evaluate radiographic and clinical outcome of MOWHTO using injectable β-TCP. METHODS: Consecutive 28 patients underwent MOWHTO using anatomical locking plate fixation, and β-TCP was injected as gap filler. Serial radiographs and computed tomography were taken at postoperative 3 and 12 months, and gap healing was assessed. Lower extremity alignment was measured on radiographs, and clinical outcome was evaluated by determining International Knee Documentation Committee, Western Ontario and McMaster Universities Arthritis Index, and visual analogue scales for pain scores. RESULTS: Progress of bone union was found on plain radiographs, and the mean ratio (β-TCP/host bone) of computed tomography attenuation values significantly changed from postoperative 3 months to 12 months, which indicates maturation of β-TCP. The average mechanical femoro-tibial angle changed from 4.1° varus (preoperative) to 4.8° valgus (3 months) and maintained until 12 months (4.3° valgus). All clinical outcome scores were significantly improved and no significant complication occurred. CONCLUSION: Using injectable β-TCP as gap filler for MOWHTO resulted in satisfactory gap healing without complication. Radiographic and clinical results were satisfactory. The injectable β-TCP can be a safe and effective option for gap filling after MOWHTO.
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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) | 0.000 | 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".