Growth Modulation for Childhood Scoliosis: From Where Have We Come, and Where are We Going?
Bibliographic record
Abstract
Study Design: Literature Review Background: This white paper reviews the early reported outcomes of anterior vertebral body tethering (AVBT) and provides a brief update on the recent changes in regulatory status. Growth modulation by AVBT has the potential to transform scoliosis treatment in children and adolescents by reducing spinal curvature without definitive fusion. To date, nearly all patients with anterior vertebral body tethering (AVBT) have been treated in off-label use, sometimes with controversial indications. Methods: A literature review was conducted of published papers and abstracts from national conferences. We searched PubMed for “vertebral body stapling” and “vertebral body tethering,” including only primary research. We also reviewed the last 10 programs of ICEOS, SRS, and POSNA. Regulatory officials within the spinal device industry and the FDA were also consulted. Results: Early published experience (5 papers) in 67 patients and unpublished data (8 presentations) in over 200 patients suggests that AVBT can effectively prevent curve progression in the majority of skeletally immature patients. Rates of complications and secondary surgery for curve progression or overcorrection are variable and necessitate further investigation. Conclusions: With the recent FDA regulatory approval of the vertebral tether under and Humanitarian Device Exemption (HDE) mechanism, we are poised to better understand the long term outcomes of this novel and potentially disruptive approach to the treatment of pediatric spine deformity. Level V
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".