Impact of Living With Scoliosis: A utility Outcome Score Assessment
Bibliographic record
Abstract
STUDY DESIGN: Survey. OBJECTIVE: The aim of this study was to objectify the burden of adolescent idiopathic scoliosis (AIS) to better advocate for scoliosis care in the future. SUMMARY OF BACKGROUND DATA: AIS is a common spinal deformity that can affect individuals on many levels. Patients with big curves usually seek medical advice for surgical correction of their deformity. METHODS: Participants completed an online questionnaire to help measure the health burden of AIS. Three utility outcome measures were then calculated. These included the visual analog scale, time trade off, and standard gamble. Student t test and linear regression were used for statistical analysis. RESULTS: One hundred and ten participants were included in the analysis. The mean visual analog scale, time trade off, and standard gamble scores for AIS were 0.77 ± 0.16, 0.90 ± 0.11, and 0.91 ± 0.13, respectively. Factors such as age, sex, income, and level of education were dependent predictors of utility scores for AIS. CONCLUSION: Our participants demonstrated a significant perceived burden of AIS. If faced with AIS, participants were willing to sacrifice 3.6 years of their lives and undergo a procedure with 9% mortality rate to gain perfect health. Such findings can guide future allocation of resources for better scoliosis care and management. LEVEL OF EVIDENCE: 4.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".