Success Rate of Brace Treatment for Juvenile-Onset Idiopathic Scoliosis up to Skeletal Maturity
Bibliographic record
Abstract
BACKGROUND: Natural history studies have reported that the progression rate of juvenile idiopathic scoliosis (JIS) curves larger than 20° is high and tends to progress. The aim of this study was to investigate the outcome of bracing on JIS and to determine the prognostic factors on the success rate of brace treatment. METHODS: From March 1985 to February 2015, the clinical data of all JIS patients with referral age from 4 to 10 years who received brace treatment were reviewed. Those patients with a prebrace Cobb angle >20° and a Risser sign of 0 to 2 were included and followed up a minimum of 2 years after discontinuation of the brace or time of spinal fusion. The Cobb angle was recorded at the time of diagnosis, before initiation of bracing, weaning time, brace discontinuation, and final follow-up. RESULTS: From 297 patients with JIS, a total of 75 cases (18 boys, 57 girls) with an average curve magnitude of 31.9° at the time of diagnosis met the inclusion criteria of the study. For successfully treated patients, the average best in-brace correction was 55% for Lenke I curves, 59% for Lenke II curves, 41% for Lenke III curves, and 62% for Lenke V curves. For a total of 27 patients (36%), the brace treatment failed. Of these, 21 patients (78%) reached spinal fusion, and curves of 6 patients (22%) increased to ≥50°. The progression rate was highest in patients with Lenke type III curves (67%), and also in those with a curve magnitude of ≥46° (94%). CONCLUSIONS: Brace treatment is an effective strategy for controlling the curve progression and avoiding spinal fusion in JIS. LEVEL OF EVIDENCE: 4.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".