The Use of Halo Gravity Traction in Severe, Stiff Scoliosis
Bibliographic record
Abstract
PURPOSE: The correction of severe, stiff scoliosis in children is challenging. One method used to reduce the risk is preoperative halo gravity traction (HGT). In this study, the authors sought to define the efficiency and safety of HGT and characterize the chronology of the correction seen. METHOD: A consecutive group of pediatric patients with severe spinal deformities was treated with HGT before definitive correction. A standard protocol with the daily addition of weight to 50% of body weight at 3 weeks was used. Traction remained in place until signs of impending neurological complication or 6 weeks, whichever was sooner. RESULTS: Twenty-four patients were included with a mean age of 11.8 years. The mean coronal deformity was 123 degrees, with a T1-L5 height of 234 mm. The mean duration of traction was 42 days with a mean improvement in height of 72 mm with 82% occurring over the first 3 weeks. Hundred percent of the angular and 98% of T1-L5 height correction was reached by 6 weeks.One patient showed early signs of a cranial nerve palsy prompting early surgery and 8 patients showed pin loosening, 1 of which required revision of their halo. One patient underwent a slower progression of traction because of transitory urinary disturbance. Following fusion, angular correction of the major curve was 49%. CONCLUSION: HGT is a safe treatment for severe, stiff scoliosis because it can respond to early signs of impending neurological impairment. The first 3 weeks of treatment, reaching 50% of body weight as a traction force accounts for 80% of correction, with the remaining 20% in the following 2 weeks. At least 4 weeks of traction is recommended when following this protocol.
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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 | 0.000 |
| 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".