Does Sacral Slanting Affect Postoperative Shoulder Balance in Patients With Lenke Type 2A Adolescent Idiopathic Scoliosis?
Bibliographic record
Abstract
OBJECTIVE: Even minor sacral slanting can influence T1 tilt and shoulder balance. Yet, the relationship between sacral slanting and postoperative shoulder imbalance (PSI) has not been previously explored. To determine risk factors for PSI in Lenke 2A adolescent idiopathic scoliosis (AIS) patients, with an emphasis on sacral slanting. METHODS: The study encompassed 96 consecutive patients who had undergone posterior correction and fusion surgery for Lenke type 2A AIS. Patients were grouped into PSI(+) and PSI(-) based on postoperative outcomes. Additionally, they were classified into left-sided slanting, no slanting, and right-sided slanting groups according to the degree of sacral slanting. Various radiological measures were compared. RESULTS: Patients in the PSI(+) group exhibited a smaller preoperative proximal thoracic curve and a higher main thoracic curve correction rate than those in the PSI(-) group. The presence or absence of sacral slanting did not exhibit a significant variation in PSI occurrence. However, the right-sided sacral slanting group showed a larger delta radiologic shoulder height compared to the other 2 groups (7.1 mm vs. 1.5 & 3.3 mm). CONCLUSION: Sacral slanting was not directly linked to the development of PSI. Despite the common postoperative elevation of the left shoulder, the shoulder height differences decreased over the follow-up period. Especially in cases with a right-sided tilted sacrum, the PSI demonstrated progressive improvement, with an associated increase in the rightward distal wedging angle, leading to distal adding-on.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".