A stability-based model of a growing spine with adolescent idiopathic scoliosis: A combination of musculoskeletal and finite element approaches
Bibliographic record
Abstract
Using a combined musculoskeletal and finite element (FE) approach, this study aimed to evaluate stability-based muscle forces in a spine with adolescent idiopathic scoliosis (AIS) as compared to a normal spine; and subsequently, determine the effects of stress distribution on the growth plates (GPs) of the growing spine. For this purpose a nonlinear 3D FE model of one normal and one scoliotic thoracolumbar spine, consisting of GPs attached to rigid L1 to L4 vertebrae, were developed using computed tomography images coupled with a growth modulation using the Stokes' model. Corresponding well with recent in-vivo and in-vitro studies, results of the models predicted intradiscal pressures at the L3-L4 and L4-L5 levels of 0.32 and 0.38 MPa in the normal spine and 0.30 and 0.36 MPa in the scoliotic spine, respectively; and hydrostatic and octahedral shear stresses on the apical GP of 0.11 and 0.06 MPa, respectively. The reaction moments in the scoliotic model resulted in higher compression on the posteroconcave side of the GPs, which led to deformity progression as predicted by the Hueter-Volkmann theory. Moreover, the augmented baseline growth in the Stokes' model magnified both the scoliotic spine height and Cobb angle growth rates. The presented stability-based approach can be used to predict the performance of rehabilitation strategies in the clinical management of AIS.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".