Outcomes of Megaprosthesis Reconstruction for the Salvage of Failed Osteoarticular Allograft Around the Knee implanted before Skeletal Maturity in Primary Bone Sarcoma: A Case-Series.
Bibliographic record
Abstract
Objectives: Functional expectations following the salvage of a failed osteoarticular allograft are poorly described. In this study, we aim to evaluate functional outcomes, implant survival, and complications of the megaprosthesis in salvaging a failed osteoarticular allograft around the knee. Methods: We retrospectively reviewed the medical profiles of 21 skeletally mature patients who underwent megaprosthesis reconstruction to salvage a failed osteoarticular allograft around the knee implanted before skeletal maturity. The location of reconstruction was the proximal tibia in 13 patients and the distal femur in eight patients. Knee function was evaluated by the Musculoskeletal Tumor Society (MSTS) score and the Toronto Extremity Salvage Score (TESS). Results: The mean age of patients was 16±1.7 years. The mean interval between the primary (allograft) and secondary (megaprosthesis) reconstructions was 59.4±23.6 months. At an average follow-up of 51.2 months, the mean knee range of motion was 101.2±15.6°. The mean MSTS score and TESS were 83.6±7 and 86.6±7.9, respectively. The mean limb length discrepancy was 2.5±1 cm before and 0.36±0.74 cm after the operation (P<0.001). Six postoperative complications (28.6%) occurred in this series, including one wound dehiscence, one periprosthetic fracture, two acute infections, one aseptic loosening, and one delayed periprosthetic infection. Only the last two complications required revision. Accordingly, the two- and five-year implant survivals were 95.7% and 90%, respectively. Conclusion: Megaprosthesis is a viable option for salvaging failed osteoarticular allografts around the knee. It also provides the opportunity to correct the limb length discrepancy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".