Safety and efficacy of anterior vertebral body tethering in the treatment of idiopathic scoliosis
Bibliographic record
Abstract
Aims Spinal fusion remains the gold standard in the treatment of idiopathic scoliosis. However, anterior vertebral body tethering (AVBT) is gaining widespread interest, despite the limited data on its efficacy. The aim of our study was to determine the clinical efficacy of AVBT in skeletally immature patients with idiopathic scoliosis. Methods All consecutive skeletally immature patients with idiopathic scoliosis treated with AVBT enrolled in a longitudinal, multicentre, prospective database between 2013 and 2016 were analyzed. All patients were treated by one of two surgeons working at two independent centres. Data were collected prospectively in a multicentre database and supplemented retrospectively where necessary. Patients with a minimum follow-up of two years were included in the analysis. Clinical success was set a priori as a major coronal Cobb angle of < 35° at the most recent follow-up. Results A total of 57 patients were included in the study. Their mean age was 12.7 years (SD 1.5; 8.2 to 16.7), with 95% being female. The mean preoperative Sanders score and Risser grade was 3.3 (SD 1.2), and 0.05 (0 to 3), respectively. The majority were thoracic tethers (96.5%) and the mean follow-up was 40.4 months (SD 9.3). The mean preoperative major curve of 51° (SD 10.9°; 31° to 81°) was significantly improved to a mean of 24.6° (SD 11.8°; 0° to 57°) at the first postoperative visit (45.6% (SD 17.6%; 7% to 107%); p < 0.001)) with further significant correction to a mean of 16.3° (SD 12.8°; -12 to 55; p < 0.001) at one year and a significant correction to a mean of 23° (SD 15.4°; -18° to 57°) at the final follow-up (42.9% (-16% to 147%); p < 0.001). Clinical success was achieved in 44 patients (77%). Most patients reached skeletal maturity, with a mean Risser score of 4.3 (SD 1.02), at final follow-up. The complication rate was 28.1% with a 15.8% rate of unplanned revision procedures. Conclusion AVBT is associated with satisfactory correction of deformity and an acceptable complication rate when used in skeletally immature patients with idiopathic scoliosis. Improved patient selection and better implant technology may improve the 15.8% rate of revision surgery in these patients. Further scrutiny of the true effectiveness and long-term risks of this technique remains critical. Cite this article: Bone Joint J 2020;102-B(12):1703–1708.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".