Biomechanical simulations of costo‐vertebral and anterior vertebral body tethers for the fusionless treatment of pediatric scoliosis
Bibliographic record
Abstract
Compression-based fusionless tethers are an alternative to conventional surgical treatments of pediatric scoliosis. Anterior approaches place an anterior (ANT) tether on the anterolateral convexity of the deformed spine to modify growth. Posterior, or costo-vertebral (CV), approaches have not been assessed for biomechanical and corrective effectiveness. The objective was to biomechanically assess CV and ANT tethers using six patient-specific, finite element models of adolescent scoliotic patients (11.9 ± 0.7 years, Cobb 34° ± 10°). A validated algorithm simulated the growth and Hueter-Volkmann growth modulation over a period of 2 years with the CV and ANT tethers at two initial tensions (100, 200 N). The models without tethering also simulated deformity progression with Cobb angle increasing from 34° to 56°, axial rotation 11° to 13°, and kyphosis 28° to 32° (mean values). With the CV tether, the Cobb angle was reduced to 27° and 20° for tensions of 100 and 200 N, respectively, kyphosis to 21° and 19°, and no change in axial rotation. With the ANT tether, Cobb was reduced to 32° and 9° for 100 and 200 N, respectively, kyphosis unchanged, and axial rotation to 3° and 0°. While the CV tether mildly corrected the coronal curve over a 2-year growth period, it had sagittal lordosing effect, particularly with increasing initial axial rotation (>15°). The ANT tether achieved coronal correction, maintained kyphosis, and reduced the axial rotation, but over-correction was simulated at higher initial tensions. This biomechanical study captured the differences between a CV and ANT tether and indicated the variability arising from the patient-specific characteristics. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:254-264, 2018.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".