A Predictive Model of Progression for Adolescent Idiopathic Scoliosis Based on 3D Spine Parameters at First Visit
Bibliographic record
Abstract
MINI: The aim of this prospective cohort study was to improve the prediction of curve progression in AIS. By adding the 3D morphology parameters at first visit, the predictive model explains 65% of the variability. It is one of the greatest advances in the understanding of scoliosis progression in the last 30 years. STUDY DESIGN: Prospective cohort study. OBJECTIVE: The objective of the present study was to design a model of AIS progression to predict Cobb angle at full skeletal maturity, based on curve type, skeletal maturation, and 3D spine parameters available at first visit. SUMMARY OF BACKGROUND DATA: Adolescent idiopathic scoliosis (AIS) is a three-dimensional (3D) spinal deformity that affects 1% of adolescents. Curve severity is assessed using the Cobb angle. Prediction of scoliosis progression remains challenging for the treating physician and is currently based on curve type, severity, and maturity. The objective of this study was to develop a predictive model of final Cobb angle, based on 3D spine parameters at first visit, to optimize treatment. METHODS: A prospective cohort of AIS patients at first orthopedic visit was enrolled between 2006 and 2010, all with 3D reconstructions. Measurements of five types of descriptors were obtained: angle of plane of maximum curvature, Cobb angles, 3D wedging, rotation, and torsion. A general linear model analysis with backward selection was done with final Cobb angle (either just before surgery or at skeletal maturity) as outcome and 3D spine parameters and clinical parameters as predictors. RESULTS: Of 195 participants, 172 (88%) were analyzed; average age at presentation was 12.5 ± 1.3 years and mean follow-up to outcome, 3.2 years. The final model includes significant predictors: initial skeletal maturation, curve type, frontal Cobb angle, angle of plane of maximal curvature, and 3D disk wedging (T3-T4, T8-T9) and achieved a determination coefficient (R) = 0.643. Positive and negative predictive values to identify a curve of 35 degrees are 79% and 94%. CONCLUSION: This study developed a predictive model of spinal curve progression in scoliosis based on first-visit information. The model will help the treating physician to initiate appropriate treatment at first visit. LEVEL OF EVIDENCE: 3.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".