Intercalary allograft augmented with intramedullary cement and plate fixation is a reliable solution after resection of a diaphyseal tumour
Bibliographic record
Abstract
Aims Intercalary allografts following resection of a primary diaphyseal tumour have high rates of complications and failures. At our institution intercalary allografts are augmented with intramedullary cement and fixed using compression plating. Our aim was to evaluate their long-term outcomes. Patients and Methods A total of 46 patients underwent reconstruction with an intercalary allograft between 1989 and 2014. The patients had a mean age of 32.8 years (14 to 77). The most common diagnoses were osteosarcoma (n = 16) and chondrosarcoma (n = 9). The location of the tumours was in the femur in 21, the tibia in 16 and the humerus in nine. Function was assessed using the Musculoskeletal Tumor Society (MSTS) scoring system and the Toronto Extremity Salvage Score (TESS). The survival of the graft and the overall survival were assessed using the Kaplan-Meier method. Results The median follow-up was 92 months (4 to 288). The mean MSTS 87 score was 29.1 (19 to 35), the mean MSTS 93 score was 82.2 (50 to 100) and the mean TESS score was 81.2 (43 to 100). Overall survival of the allograft was 84.8%. A total of 15 patients (33%) had a complication. Five allografts were revised for complications and one for local recurrence. Conclusion Intercalary allografts augmented with intramedullary cement and compression plate fixation provide a reliable and durable method of reconstruction after the excision of a primary diaphyseal bone tumour, with high levels of function and satisfaction. Cite this article: Bone Joint J 2017;99-B:973–8.
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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 | 0.001 | 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".