Disparities in Total Hip Arthroplasty Outcomes: Census Tract Data Show Interactions Between Race and Community Deprivation
Bibliographic record
Abstract
INTRODUCTION: Socioeconomic factors such as poverty may mediate racial disparities in health outcomes after total hip arthroplasty (THA) and confound analyses of differences between blacks and whites. METHODS: Using a large institutional THA registry, we built models incorporating individual and census tract data and analyzed interactions between race and percent of population with Medicaid coverage and its association with 2-year patient-reported outcomes. RESULTS: Black patients undergoing THA had worse baseline and 2-year pain and function scores compared with whites. We observed strong positive correlations between census tract Medicaid coverage and percent living below poverty (rho = 0.69; P < 0.001). Disparities in 2-year Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function were magnified in communities with high census tract Medicaid coverage. For blacks in these communities, 2-year WOMAC function scores were predicted to be -5.54 points lower (80.42 versus 85.96) compared with blacks in less deprived communities, a difference not observed among whites. CONCLUSION: WOMAC pain and function 2 years after THA are similar among blacks and whites in communities with little deprivation (low percent census tract Medicaid coverage). WOMAC function at 2 years is worse among blacks in areas of higher deprivation but is not seen among whites. LEVEL OF EVIDENCE: Level II - Cohort Study.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".