Approaches to Treating NF1 Tibial Pseudarthrosis
Bibliographic record
Abstract
BACKGROUND: Neurofibromatosis 1 (NF1) is an autosomal dominant disorder with various skeletal abnormalities occurring as part of a complex phenotype. Tibial dysplasia, which typically presents as anterolateral bowing of the leg with subsequent fracture and nonunion (pseudarthrosis), is a serious but infrequent osseous manifestation of NF1. Over the past several years, results from clinical and experimental studies have advanced our knowledge of the role of NF1 in bone. On the basis of current knowledge, we propose a number of concepts to consider as a theoretical approach to the optimal management of tibial pseudarthrosis. METHODS: A literature review for both clinical treatment and preclinical models for tibial dysplasia in NF1 was performed. Concepts were discussed and developed by experts who participated in the Children's Tumor Foundation sponsored International Bone Abnormalities Consortium meeting in 2011. RESULTS: Concepts for a theoretical approach to treating tibial pseudarthrosis include: bone fixation appropriate to achieve stability in any given case; debridement of the "fibrous pseudarthrosis tissue" between the bone segments associated with the pseudarthrosis; creating a healthy vascular bed for bone repair; promoting osteogenesis; controlling overactive bone resorption (catabolism); prevention of recurrence of the "fibrous pseudarthrosis tissue"; and achievement of long-term bone health to prevent recurrence. CONCLUSIONS: Clinical trials are needed to assess effectiveness of the wide variation of surgical and pharmacologic approaches currently in practice for the treatment of tibial pseudarthrosis in NF1. LEVEL OF EVIDENCE: Level V, expert opinion.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".