Current trends and future directions in the management of neuromuscular scoliosis
Bibliographic record
Abstract
This review article highlights the importance of early diagnosis, individualized treatment planning, and the integration of new surgical techniques and technologies for enhancing patient outcomes in neuromuscular scoliosis (NMS) management. Neuromuscular scoliosis (NMS) is a severe form of spinal deformity arising from neuromuscular disorders and is characterized by progressive, often debilitating, spinal curvature that complicates basic functions and significantly affects quality of life. Understanding the prevalence, etiology, diagnosis, and management options for NMS is crucial in providing effective treatment for individuals with this condition. Advancements in managing neuromuscular scoliosis include improved surgical techniques, genetic therapies, and robotics. A multidisciplinary approach involving orthopedics, neurology, genetics, and rehabilitation optimizes patient outcomes. More research is needed on fusionless surgeries, genetic therapies, and improving imaging and robotic tools for better surgical precision and outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".