Successful mid‐ to long‐term outcome after reconstruction of the extensor apparatus using proximal tibia‐patellar tendon composite allograft
Bibliographic record
Abstract
PURPOSE: The purpose of the study was to assess the outcomes of extensor mechanism reconstruction with proximal tibia-patellar tendon composite allograft. METHODS: 24 consecutive patients treated with allograft-prosthetic composite for proximal tibia tumour resection and a conventional total knee arthroplasty were included. Extensor mechanism reconstruction was performed with a proximal tibia-patellar tendon composite allograft and the suture of the donor tendon to the remnant native patellar tendon. Function was evaluated by the Musculoskeletal Tumor Society score (MSTS) and range of motion. Western Ontario and MacMaster University (WOMAC) and visual analogue scale for pain also were used. RESULTS: After a mean follow-up of 11.7 (range 3-15) years, mean MSTS score was 22.4 (range 20-30), mean flexion was 94.0° (range 84°-110°), and mean extension lag was 7.2° (range 0°-18°). The mean VAS-pain was 4.3 (range 2-6), and WOMAC score was 72.4 (range 58-100). There was no failure of the reconstructed extensor mechanism. CONCLUSION: Patellar tendon reconstruction with allogeneic tissue from the proximal tibia allograft sutured to the recipient's remnant patellar tendon provides the mechanical support needed for healing of the reconstructed extensor mechanism with a substantial functional benefit to stabilize active knee extension and successful reconstruction survival at long-term. LEVEL OF EVIDENCE: III.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".