Brace Compliance, Sex, and Initial Cobb Angle as Predictors of Immediate In-Brace Curve Correction in Adolescents With Scheuermann’s Kyphosis
Bibliographic record
Abstract
ABSTRACT INTRODUCTION Bracing is the most effective nonoperative treatment for adolescents with Scheuermann’s kyphosis; however, its outcome is not equal for all patients. The effects of potential predictive parameters for the outcome of bracing have not been well evaluated in the literature. The aim of the study was to investigate the potential prognostic factors that affect in-brace curve correction in adolescents with Scheuermann's kyphosis. MATERIALS AND METHODS In this prospective cohort study, patients with thoracic Scheuermann’s kyphosis treated with the Milwaukee brace with a curve of 55° to 86° were included. The primary prognostic factors for in-brace curve correction, including brace compliance and daily exercise by log book, pad pressure by a modified sphygmomanometer, joint hypermobility by Beighton's scale, patients’ sex, and initial Cobb angle were measured. Analyses considered multiple linear regression and independent sample t-test. RESULTS Nineteen boys (13.74 ± 1.55 years) and 33 girls (13.67 ± 1.61 years) were included in the study. The results of the multiple linear regression analysis showed that the degrees of in-brace curve correction were significantly associated with brace compliance and initial Cobb angle (R 2 = 0.48). The results of the independent t-test showed a significant difference in average curve correction, brace compliance, and in-brace pressure between girls and boys. CONCLUSIONS Results of the current study indicated that the amount of in-brace curve correction is primarily affected by brace compliance and initial Cobb angle. Brace compliance, curve correction, and pad pressure in boys were significantly higher than in girls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".