Post-operative bracing following adult spine deformity surgery: Results from the AO Spine surveillance of post-operative management of patients with adult spine deformity
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional international survey with a literature review. OBJECTIVES: While some surgeons favor spine bracing after surgery for adult spine deformity (ASD) to help prevent mechanical failures, there is a lack of evidence. The objective of the present study was to better understand the current trend in the use of bracing following ASD surgery based on an international survey. METHODS: An e-mail-based online survey was conducted among over 6000 international AO Spine members regarding the post-operative management of patients with ASD. The details of brace prescription, indications and influencing factors were solicited. Descriptive data were summarized based on different demographic groups and fusion levels for the responding surgeons who annually perform at least 10 long-segment fusions of >5 levels extending to the pelvis. RESULTS: A total of 116 responses were received, including 71 surgeons (61%) who used post-operative bracing for >5 levels of long fusion. The most common reason for bracing was pain management (55%) and bone quality was the strongest influencing factor (69%). Asia-Pacific surgeons had the highest rate of bracing (88%), while North American surgeons had the lowest (45%). The most common type of brace used were TLSO for cases with an uppermost instrumented vertebra (UIV) in the low- or mid-thoracic spine and a cervical brace for UIV at T1-3. The majority (56%) used bracing for 6-12 weeks after surgery. CONCLUSIONS: The present survey demonstrated significant interest in bracing following ASD surgery, however, there is substantial variability in post-operative bracing practice. A formal study on the role of bracing in ASD surgery is needed.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| 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".