Puberty changes the natural history of idiopathic scoliosis: three prediction models for future radiographic curve severity from 1563 consecutive patients
Bibliographic record
Abstract
Abstract Purpose Understanding idiopathic scoliosis (IS) natural history during growth is essential for shared decision-making between patients and physicians. We developed a retrospective model with the largest available sample in the literature and we aimed to investigate if using three peri-pubertal growth periods provides better prediction than a unique model. Methods Secondary analysis of a previous study on IS natural history data from radiographs before and at the first consult. Three groups: BEFORE (age 6–10), AT (age 11-Risser 2) and AFTER (from Risser 3) the pubertal growth spurt. Available predictors: Cobb angle, curve type, sex, observation time, and Risser score. We used linear mixed-effects models to predict future Cobb angles in each group. We internally validated prediction accuracy with over 100 patients per group (3 to 5-fold cross-validation). Results We included 1563 participants (275 BEFORE, 316 AFTER, 782 females and 190 males AT). Curves increased over time mostly in AT, importantly in BEFORE, but also in AFTER. All models performed better than the general one. In BEFORE, 74.2% of the predictions were within ± 5 o , 71.8% in AFTER, 68.2% in AT females, and 60.4% in males. The predictors (baseline curve, observation time also squared and cubic, and Risser score) were similar in all the models, with sex influencing only AFTER. Conclusion IS curve severities increase differently during growth with puberty stages. Model accuracy increases when tailored by growth spurt periods. Our models may help patients and clinicians share decisions, identify the risk of progression and inform treatment planning.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".