Biomechanical analysis of fracture risk associated with tibia deformity in children with osteogenesis imperfecta: a finite element analysis.
Bibliographic record
Abstract
OBJECTIVES: Osteogenesis imperfecta (OI) frequently leads to long-bone bowing requiring a surgical intervention in severe cases to avoid subsequent fractures. However, there are no objective criteria to decide when to perform such intervention. The objective is to develop a finite element model to predict the risk of tibial fracture associated with tibia deformity in patients with OI. METHODS: A comprehensive FE model of the tibia was adapted to match bi-planar radiographs of a 7 year-old girl with OI. Ten additional models with different deformed geometries (from 2° to 24°) were created and the elasto-plastic mechanical properties were adapted to reflect OI conditions. Loads were obtained from mechanography of two-legged hopping. Two additional impact cases (lateral and torsion) were also simulated. Principal strain levels were used to define a risk criterion. RESULTS: Fracture risks for the two-legged hopping load case remained low and constant until tibia bowing reached 15° and 16° in sagittal and coronal planes respectively. Fracture risks for lateral and torsion impact were equivalent whatever the level of tibial bowing. CONCLUSIONS: The finite element model of OI tibia provides an objective means of assessing the necessity of surgical intervention for a given level of tibia bowing in OI-affected children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".