Pain Trajectories Following Adolescent Idiopathic Scoliosis Correction
Bibliographic record
Abstract
BACKGROUND: A better understanding of early pain trajectories (patterns) following scoliosis surgery and how they relate to baseline patient characteristics and functional outcomes may allow for the development of mitigating strategies to improve patient outcomes. METHODS: This was a prospective cohort study. Adolescents with idiopathic scoliosis were recruited across multiple centers. Latent growth mixture modeling techniques were used to determine pain trajectories over the first postoperative year. RESULTS: The median numerical rating scale for pain in the hospital following surgery for adolescent idiopathic scoliosis was 5.0. It improved to 1.0 by 6 weeks, and was maintained at <1 by 3 to 12 months postoperatively. Three trajectories were identified, 2 of which involved moderate acute postoperative pain: 1 with good resolution and 1 with incomplete resolution by 1 year. The third trajectory involved mild acute postoperative pain with good resolution by 1 year. Membership in the "moderate pain with incomplete resolution" trajectory was predicted by higher baseline pain and anxiety, and patients in this trajectory reported worse quality of life than those in the trajectories with good resolution. CONCLUSIONS: Pain recovery following surgery for idiopathic scoliosis was found to be substantial during the first 6 weeks and continued up to 1 year. We identified 3 main trajectories, 2 with favorable outcomes and 1 with persistent pain and worse quality of life at 1 year postoperatively. The risk factors most associated with the latter trajectory included increased baseline pain and anxiety. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".