Osteocartilaginous Transfer of the Proximal Part of the Fibula for Osseous Overgrowth in Children with Congenital or Acquired Tibial Amputation
Bibliographic record
Abstract
BACKGROUND: Osseous overgrowth is a common problem in children after tibial transcortical amputation. We present the results of forty-seven children (fifty tibiae) treated for tibial osseous overgrowth with an autologous osteocartilaginous cap from the proximal part of the ipsilateral fibula. METHODS: We reviewed the records of all patients who underwent amputation at a single pediatric hospital from 1990 to 2011. All patients who had been followed for a minimum of two years after undergoing osteocartilaginous capping with the proximal part of the ipsilateral fibula to treat established tibial overgrowth were included. Patients with acquired and congenital amputations were compared. RESULTS: Fifty tibiae in forty-seven patients met our inclusion criteria. There were thirty-one acquired and nineteen congenital amputations. The mean age at surgery was 7.6 years (range, 2.1 to 15.6 years), and the mean duration of follow-up was 7.2 years (range, 2.2 to 15.4 years). Five tibiae (10%) in four patients had recurrence of the overgrowth at a mean of 5.4 years (range, 2.8 to 7.6 years) after the osteocartilaginous transfer. There was no significant difference in the results between children with an acquired amputation and those with a congenital amputation. CONCLUSIONS: At a mean of 7.2 years after autologous osteocartilaginous capping with the proximal part of the fibula, 90% of the limbs had not had recurrent overgrowth. This is a safe and effective treatment of long-bone overgrowth following either congenital or acquired amputation in children.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".