Functional and radiographic outcome after tumor limb salvage surgery using STANMORE megaprostheses.
Bibliographic record
Abstract
PURPOSE: To report the clinical and radiological outcome of limb salvage surgery with the STANMORE megaprostheses. METHODS: We retrospectively studied 33 patients with musculoskeletal tumor limb salvage surgery using STANMORE megaprostheses. Clinical evaluation was done using the Enneking and the Toronto Extremity Salvage Score (TESS). Radiographic evaluation was done using the International Society of Limb Salvage (ISOLS) score. RESULTS: At a mean follow-up of 18 months, 21 patients were alive with no evidence of disease and two patients were alive with metastatic disease; 9 patients died of metastatic disease and one patient of causes unrelated to the primary tumor. Local recurrence was not observed in any of the patients. The mean Enneking and TESS scores were 76 and 88.4%, respectively. The ISOLS score was excellent or good in 30 cases for bone remodelling, 30 cases for the interface, in 30 cases for anchorage, in 32 cases for the implant body, and in 33 cases for the articulation. Extracortical bone bridging greater than 25% was observed in 8 prostheses. Mechanical survival of the megaprostheses was 97% (32 megaprostheses). Complications included seroma and hematoma formation (12%), skin necrosis and dehiscence at the knee wound (9%), aseptic loosening and infection (6%), quadriceps tendon rupture and peroneal nerve palsy (3%). CONCLUSION: The local recurrence-free survival in this series supports limb salvage surgery. The 97% survival rate of the megaprostheses suggests that the STANMORE modular megaprostheses are valuable for reconstruction of bone defects after tumor resection.
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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) | 0.002 | 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".