Kidney-Failure Risk Projection for the Living Kidney-Donor Candidate
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Evaluation of candidates to serve as living kidney donors relies on screening for individual risk factors for end-stage renal disease (ESRD). To support an empirical approach to donor selection, we developed a tool that simultaneously incorporates multiple health characteristics to estimate a person's probable long-term risk of ESRD if that person does not donate a kidney. METHODS: We used risk associations from a meta-analysis of seven general population cohorts, calibrated to the population-level incidence of ESRD and mortality in the United States, to project the estimated long-term incidence of ESRD among persons who do not donate a kidney, according to 10 demographic and health characteristics. We then compared 15-year projections with the observed risk among 52,998 living kidney donors in the United States. RESULTS: A total of 4,933,314 participants from seven cohorts were followed for a median of 4 to 16 years. For a 40-year-old person with health characteristics that were similar to those of age-matched kidney donors, the 15-year projections of the risk of ESRD in the absence of donation varied according to race and sex; the risk was 0.24% among black men, 0.15% among black women, 0.06% among white men, and 0.04% among white women. Risk projections were higher in the presence of a lower estimated glomerular filtration rate, higher albuminuria, hypertension, current or former smoking, diabetes, and obesity. In the model-based lifetime projections, the risk of ESRD was highest among persons in the youngest age group, particularly among young blacks. The 15-year observed risks after donation among kidney donors in the United States were 3.5 to 5.3 times as high as the projected risks in the absence of donation. CONCLUSIONS: Multiple demographic and health characteristics may be used together to estimate the projected long-term risk of ESRD among living kidney-donor candidates and to inform acceptance criteria for kidney donors. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others.).
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| 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 it