Results of Selective Thoracic Versus Nonselective Fusion in Lenke Type 3 Curves
Bibliographic record
Abstract
STUDY DESIGN: A retrospective analysis of a prospectively collected multicenter database. OBJECTIVE: To identify the radiographical and clinical outcomes in Lenke 3 curves fused selectively (S) versus nonselectively (NS). SUMMARY OF BACKGROUND DATA: Surgical treatment options for Lenke 3 curves include fusion of both curves (NS) or selective thoracic curve fusion (S). Selective fusion of the thoracic curve spares lumbar motion segments; however, it may result in marked residual deformity. METHODS: A prospectively collected multicenter database was retrospectively reviewed for adolescent idiopathic scoliosis Lenke 3 curves treated with posterior spinal fusion with a minimum of 2 years of follow-up. Patients were divided into 2 groups: NS (nonselective fusion) and S (selective thoracic fusion). Radiographical and clinical data were compared between the groups using the unpaired Student t test and analysis of variance. RESULTS: A total of 74 patients met our inclusion criteria, with 49 (66.2%) in the NS group and 25 (33.8%) in the S group. Overall, both groups were similar preoperatively except for lumbar Cobb (NS = 56.3°, S = 47.2°, P < 0.001), lumbar lordosis (NS = 56.9°, S = 67.2°, P = 0.001), lumbar rotational prominence (NS = 11.2°, S = 8.2°, P < 0.05), and lumbar apical translation (NS = 3.2 cm, S = 1.9 cm, P < 0.05). Postoperatively, NS fusion demonstrated significantly less coronal imbalance of 2 cm or less (NS = 10.2%, S = 56.0%, P < 0.001), better lumbar curve correction (NS = 68.2%, S = 51.9%, P < 0.001), better lumbar apical translation correction (NS = 1.2 cm, S = 2.1 cm, P < 0.01), and better percent correction of the lumbar prominence (NS = 66.5%, S = 40.4%, P < 0.05). Scoliosis Research Society Questionnaire 22 scores at 2 years were similar between the groups. CONCLUSION: Despite preoperatively smaller lumbar curves with less apical translation and lumbar prominence, most patients with selective fusions were out of balance postoperatively and had inferior radiographical outcomes as compared with their nonselective comparison cohort with similar patient-reported outcomes. Long-term follow-up is required to determine whether the trade-off of sparing motion segments at the expense of somewhat lessened radiographical outcomes is worthwhile.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".