Effect of Sociodemographic Factors on Surgical Consultations and Hip or Knee Replacements Among Patients with Osteoarthritis in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To quantify the effect of demographic variables and socioeconomic status (SES) on surgical consultation and total joint arthroplasty (TJA) rates among patients with osteoarthritis (OA), using population-based administrative data. METHODS: A cohort study was conducted in British Columbia using population data from 1991 to 2004. From April 1996 to March 1998, we documented 34,420 new patients with OA and these patients were followed to March 2004 for their first surgical consultation and TJA. Effects of age, sex, and SES were evaluated by Cox proportional hazards models after adjusting for comorbidities and pain medication used. RESULTS: During a mean 5.5-year followup period, 7475 patients with OA had their first surgical consultations and 2814 patients received TJA within a 6-year mean followup period. Crude hazards ratio (HR) for men compared to women was 1.25 (95% CI 1.20-1.31) for surgical consultation and was 1.14 (95% CI 1.06-1.23) for TJA. The interaction between sex and SES was significant. Stratified analysis showed among men an HR of 1.42 (95% CI 1.27-1.58) and 1.52 (95% CI 1.26-1.83) for surgical consultations and TJA, respectively, for the highest SES compared with the lowest SES quintiles. Similarly significant results were observed among women. CONCLUSION: Differential access to the healthcare system exists among patients with OA. Women with OA were less likely than men to see an orthopedic surgeon as well as to obtain TJA. Patients with higher SES consulted orthopedic surgeons more frequently and received more TJA than those with the lowest SES.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".