Consistency of Racial Variation in Medical Outcomes Among Publicly and Privately Insured Living Kidney Donors
Bibliographic record
Abstract
BACKGROUND: Racial disparities in health outcomes after living donation have been reported, but generalizability is not known. METHODS: We linked Organ Procurement and Transplantation Network (OPTN) registry data for 4,007 living kidney donors in 1987 to 2008 with Medicare billing claims (2000-2008). Cox regression with left and right censoring was used to estimate the frequencies and relative risks of postdonation medical diagnoses according to race. Patterns were compared with findings from a previous linkage of OPTN donor records and private insurance claims. RESULTS: Among the Medicare-insured donors, 8% were African American and 5.7% were Hispanic. Diagnosis frequencies at 5 years after donation in the Medicare- versus privately insured donors included the following: malignant hypertension, 5.0% versus 0.9%; diabetes, 18.5% versus 4.1%; and chronic kidney disease, 21.8% versus 4.9%. After age and sex adjustment in the Medicare sample, African Americans, as compared with white donors, experienced higher risks of any hypertension diagnosis, including 2.4 times the likelihood of malignant hypertension (adjusted hazard ratio [aHR], 2.35; 95% confidence interval [CI], 1.40-3.93), and more common diabetes (aHR, 1.50; 95% CI, 1.12-2.04), chronic kidney disease (aHR, 1.84; 95% CI, 1.37-2.47), and proteinuria (aHR, 2.44; 95% CI, 1.45-4.11) diagnoses. Relative patterns for privately insured African American versus white donors were similar, including approximately three times the risk of malignant hypertension (aHR, 3.27; 95% CI, 1.82-5.88) and twice the relative risks of chronic kidney disease and proteinuria. CONCLUSIONS: Consistent demonstration of racial variation in postdonation medical conditions regardless of sample/payer source supports the need for continued study of mediators and consequences of outcomes in non-white donors.
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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) | 0.000 | 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) | 0.001 | 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".