Time to surgery for adolescent idiopathic scoliosis: How long does it take? A multicenter study
Bibliographic record
Abstract
Retrospective review of multicentric data. To estimate the time from initial visit to surgery in adolescent idiopathic scoliosis (AIS) patients and the main reasons for the time to surgery in a multicenter study. This retrospective study evaluated 509 patients with AIS from 16 hospitals across six Latin American countries. From each hospital's deformity registry, the following patient data were extracted: demographics, main curve Cobb angle, Lenke Classification at the initial visit and time of surgery, time from indication-for-surgery to surgery, curve progression, Risser skeletal-maturity score and causes for surgical cancelation or delay. Surgeons were asked if they needed to change the original surgical plan due to curve progression. Data also were collected on each hospital's waiting list numbers and mean delay to AIS surgery. 66.8% of the patients waited over six months and 33.9% over a year. Waiting time was not impacted by the patient's age when surgery first became indicated (p = 0.22) but waiting time did differ between countries (p < 0.001) and hospitals (p < 0.001). Longer time to surgery was significantly associated with increasing magnitude of the Cobb angle through the second year of waiting (p < 0.001). Reported causes for delay were hospital-related (48.4%), economic (47.3%), and logistic (4.2%). Oddly, waiting time for surgery did not correlate with the hospital's reported waiting-list lengths (p = 0.57) Prolonged waits for AIS surgery are common in Latin America, with rare exceptions. At most centers, patients wait over six months, most commonly for economic and hospital-related reasons. Whether this directly impacts surgical outcomes in Latin America still must be studied.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| 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".