Physeal Distraction for Joint Preservation in Malignant Metaphyseal Bone Tumors in Children
Bibliographic record
Abstract
BACKGROUND: Physeal distraction facilitates metaphyseal bone tumor resection in children and preserves the adjacent joint. The technique was first described by Cañadell. Tumor resection procedures allowing limb-sparing reconstruction have been used increasingly in recent years without compromising oncologic principles. QUESTIONS/PURPOSES: We report our results with Cañadell's technique by assessing tumor control, functional outcome, and complications. METHODS: Six consecutive children with primary malignant metaphyseal bone tumors underwent physeal distraction as a part of tumor resection. Tumor location was the distal femur in four patients, the proximal humerus in one patient, and the proximal tibia in one patient. The functional outcome was evaluated after a minimum of 18 months (median, 62 months; range, 18-136 months) using the Musculoskeletal Tumor Society (MSTS) score and the Toronto Extremity Salvage Score (TESS). RESULTS: At latest followup, five patients were alive and disease-free and one had died from metastatic disease. All tumor resections resulted in local control; there were no local recurrencies. The mean MSTS score was 79% (range, 53%-97%) and corresponding mean TESS was 83% (range, 71%-92%). In one case, postoperative infection required amputation of the proximal lower leg. All physeal distractions were successful except for one patient in whom distraction resulted in rupturing into the tumor. This situation was salvaged by transepiphyseal resection. CONCLUSIONS: We consider Cañadell's technique a useful tool in the armamentarium to treat children with malignant tumors that are in close proximity to an open physis. LEVEL OF EVIDENCE: Level IV, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.001 |
| 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".