A Prospective Comparison of the Coronal Deformity Correction in Thoracic Scoliosis Using Four Different Instrumentations and the Fulcrum-Bending Radiograph
Bibliographic record
Abstract
STUDY DESIGN: A prospective study on comparing coronal deformity correction in thoracic scoliosis using four different instrumentations. OBJECTIVES: To compare the ability of four different instrumentation systems in correcting thoracic scoliosis based on the curve flexibility as reviewed by the fulcrum-bending radiograph. SUMMARY OF BACKGROUND DATA: The fulcrum-bending radiograph has been shown to be able to accurately reflect the flexibility of thoracic curves, and the fulcrum bending correction index (FBCI) predicts the amount of correction achieved by current surgical techniques. By recruiting curves of known flexibility, the efficacy of the different instrumentations in correcting coronal deformity can be truly compared. METHODS: A consecutive series of 127 patients with idiopathic scoliosis were treated by one of four implants: CD-Horizon (CD-H), Moss Miami (MM), TSRH, and ISOLA. All surgeries were performed by the same group of surgeons using the respective recommended techniques. FBCI was used to compare the correction achieved by these implants. RESULTS: The mean FBCI/correction rate was 101.0%/57.9% in the TSRH group, 103.5%/58.5% in ISOLA, 109.1%/67.6% in CD-H, and 100.2%/62.7% in the MM group. The correction rate was significantly (P < 0.05) higher in the CD-H group than those in the TSRH and ISOLA groups, while the differences in the FBCI between the four implants were not statistically significant. CONCLUSIONS: When curve flexibility is taken into account, despite differences in material and design of four commonly used instrumentations, their ability to correct thoracic scoliosis is the same. Future studies describing surgical correction results should be based on the FBCI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".