Does the amount of spontaneous thoracic curve correction after selective lumbar fusion for Lenke type 5C adolescent idiopathic scoliosis affect outcomes of posterior deformity correction?
Bibliographic record
Abstract
OBJECTIVE: Selective lumbar fusion (SLF) is commonly performed for Lenke type 5C adolescent idiopathic scoliosis (AIS). However, whether a greater amount of spontaneous thoracic curve correction (STCC) could lead to better surgical outcome remains unclear. This retrospective cohort study was conducted to identify whether the amount of STCC after SLF for Lenke 5C AIS is associated with outcomes of posterior deformity correction and to clarify factors that could predict greater STCC. METHODS: A total of 62 patients who underwent posterior-only SLF and were followed up for > 2 years were reviewed. Radiographic measurements and Scoliosis Research Society (SRS)-22 scores were analyzed. Patients with an STCC rate of > 50% at postoperative 2 years were classified as the middle thoracic (MT)-corrected group, while those with an STCC rate of ≤ 50% were included in the MT-uncorrected group. RESULTS: In total, 62.9% (39/62) of patients reached an STCC rate of > 50%, while the remaining 37.1% (23/62) failed to achieve an STCC rate of > 50%. The Cobb angle of MT significantly increased during the postoperative 2-year follow-up in the MT-uncorrected group (mean difference [MD] 2.279, 95% CI 0.681-3.877, p = 0.002), while it did not increase in the MT-corrected group (p = 0.820). Patients with an STCC rate of > 50% demonstrated significantly higher self-image (MD 1.513, 95% CI 0.943-2.854, p = 0.001), satisfaction (MD 1.322, 95% CI 0.529-2.231, p = 0.001), and overall (MD 0.611, 95% CI 0.321-1.219, p = 0.004) SRS-22 scores at the postoperative 2-year follow-up. Furthermore, greater MT curve flexibility (p = 0.042, cutoff value 55%) and less apical vertebral translation (AVT) of MT (p = 0.003, cutoff value 7 mm) demonstrated significant results for predicting an STCC rate of > 50% at the 2-year postoperative follow-up. CONCLUSIONS: Patients with an STCC rate of ≤ 50% demonstrated worse outcomes compared to those with an STCC rate of > 50%. Patients with greater preoperative MT curve flexibility and less AVT of MT were more likely to achieve an STCC rate of > 50% with SLF. Inclusion of thoracic curve within the fusion construct could be considered for those who do not meet these criteria.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".