Treatment of Severe Pediatric Spinal Deformities
Bibliographic record
Abstract
The management of severe pediatric spinal deformities continues to evolve as advances in spinal instrumentation, surgical techniques, and neuromonitoring occur. The techniques of spinal osteotomies have been refined to allow surgeons to perform better corrections with less operative time, more safely, and through a posterior approach alone, making multiple patient positioning changes during surgery a less common occurrence. With these techniques comes a learning curve for the entire surgical team, wherein communication and planning can help minimize major complications and morbidity. This overview will review various techniques used in the correction of severe spinal deformities. Topics reviewed include the role of anterior release, traction, posterior releases, and osteotomies. Indications, techniques, and pitfalls will be reviewed. A clear understanding of the patient's deformity, normal sagittal parameters, spinal anatomy, and the principles of neuromonitoring will help improve surgical planning and patient outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".