Idiopathic Early-onset Scoliosis: Growing Rods Versus Vertically Expandable Prosthetic Titanium Ribs at 5-year Follow-up
Bibliographic record
Abstract
BACKGROUND: Distraction-based techniques allow spinal growth until skeletal maturity while preventing curve progression. METHODS: Two multicenter early-onset scoliosis databases were used to identify patients with idiopathic spine abnormalities treated with traditional growing rods (TGR) or vertically expandable titanium ribs (VEPTR). Patients underwent at least 4 lengthenings and had at least 5-year follow-up. Significance was set at P<0.05. RESULTS: In total, 50 patients treated with TGR and 22 treated with VEPTR were included. Mean (±SD) age at surgery was 5.5 (±2.0) years for the TGR group versus 4.3 (±1.9) years for the VEPTR group (P=0.044); other demographic parameters were similar. VEPTR patients had more procedures (mean 15±4.2) than TGR patients (mean 10±4.0) (P=0.001). Unilateral constructs were present in 18% (4 of 22) of VEPTR and 16% (8 of 50) of TGR patients. Bilateral constructs spanned a mean 2.1 additional surgical levels and exposed patients to 1.6 fewer procedures than unilateral constructs. Curve correction was similar between bilateral and unilateral constructs. TGR patients experienced greater curve correction (50%) than VEPTR patients (27%) (P<0.001) and achieved a greater percentage of thoracic height gain (24%) than VEPTR patients (12%) (P=0.024). At latest follow-up, TGR patients had better maintenance of curve correction, less kyphosis, and 15% greater absolute gain in thoracic height versus VEPTR patients. TGR patients had a lower rate of wound complications (14%) than VEPTR patients (41%) (P=0.011). CONCLUSIONS: In patients with idiopathic early-onset scoliosis, TGRs produced greater initial curve correction, greater thoracic height gains, less kyphosis, and lower incidence of wound complications compared with VEPTR. LEVEL OF EVIDENCE: Level III.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".