LATE REFERRAL OF ADOLESCENT IDIOPATHIC SCOLIOSIS: IMPACT OF SOCIOECONOMIC STATUS AND HEALTHCARE UTILIZATION
Bibliographic record
Abstract
Brace treatment minimizes the risk of scoliosis curve progression to surgical range. However, many adolescent idiopathic scoliosis (AIS) patients are referred late for specialist consultation and not considered ideal brace candidates. The purpose of this study was to examine socioeconomic and healthcare utilization trends that may be associated with late AIS referral, that ultimately contribute to a higher than necessary surgical burden. All AIS patients, aged 10-18 years, seen for initial consultation within a single tertiary care spine program between January 1, 2014 to December 31, 2021 were linked to provincial health administrative databases. Linked cohort data included: age, sex, body mass index (BMI), Cob angle, and Risser score. Income and material deprivation quintiles based on geographic area of residence and individual-level data pertaining to immigration were proxies for socioeconomic status. Utilization of health services in the 5 years prior to first spine specialist visit were ascertained by billing codes and represented by rate of physician outpatient visits, stratified by specialty, and number of annual health exams. Late referrals were those with a curve magnitude ≥50° or >40° and Risser 2 or less. A comparative analysis was conducted between youth that were/were not referred late. Impact of independent variables on the probability of being referred late was evaluated with significance set at p < 0 .001. In total 2732 AIS patients (2236 female, 82%) were seen in the study period, average age 14.1y (±1.7, range: 10.0-17.9) and mean Cobb angle 37.6° (±14.4, range: 10-95°). The volume of late referrals was 27% (n=728). Late referral was associated with a younger age at presentation (14.2 vs 13.8), less mature Risser score, and fewer physician outpatient visits (16.1 vs 18.7), but not sex (p=0.39), BMI (p=0.79), or immigration status (p=0.70). The probability of being referred late increased with lower income (Q1=0.32 vs Q5=0.23) and higher level of deprivation (Q5=0.34 vs Q1=0.22) and decreased when the primary care physician had a specialty in paediatrics versus family practice or practice in general (0.13 vs 0.35). Youth that had regular annual health exams were least likely to be referred late (0.11 vs 0.32) with a less than average probability for those having 2 or more exams within 5 years. There are disparities in SES indicators and healthcare utilization between AIS patients that are/are not referred late for specialist consultation. Lower SES and healthcare utilization both increase the probability of late AIS referral, particularly when the primary care physician does not have a specialty in paediatrics, or when annual health exams are infrequent. These findings indicate that education targeted at general practitioners, promotion of annual health exams for adolescents, and screening initiatives in lower socioeconomic regions may facilitate timely AIS referral.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".