Cumulative Risk for Developing End-Stage Renal Disease in the US Population
Bibliographic record
Abstract
The individual risk of developing end-stage renal disease (ESRD) and its overall impact on life expectancy is not known. This study's objectives were to determine the effect of ESRD on life expectancy for a cohort of 20-yr-olds and to compare this impact to that of several cancers for which population-based screening programs exist. A computer simulation, stratified by race (white, black) and by gender was used to calculate cumulative lifetime risk of ESRD, life-years lost to ESRD, and cumulative Medicare payments for ESRD. Similar calculations were made for breast, prostate, and colorectal cancer. The cumulative lifetime risk of ESRD for a 20-yr-old black woman is 7.8%. Equivalent risks for black men are 7.3%, white men 2.5%, and white women 1.8%. Lost years of life attributable to ESRD are 1.09, 1.10, 0.40, and 0.32 yr for black women, black men, white men, and white women, respectively. In blacks, ESRD is responsible for nearly as much loss of life-years as breast cancer in women and more loss of life-years than colorectal or prostate cancer in men. In addition, treatment costs for ESRD in this population are many-fold more expensive than cumulative treatment costs of these cancers. Exploring new screening and treatment strategies may be warranted to prevent ESRD, particularly in the US black population.
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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 | 0.001 |
| 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 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".