Expanded Prospective Payment System and Use of and Outcomes with Home Dialysis by Race and Ethnicity in the United States
Bibliographic record
Abstract
Background and objectives We investigated whether the recent growth in home dialysis use was proportional among all racial/ethnic groups and also whether there were changes in racial/ethnic differences in home dialysis outcomes. Design, setting, participants, & measurements This observational cohort study of US Renal Data System patients initiating dialysis from 2005 to 2013 used logistic regression to estimate racial/ethnic differences in home dialysis initiation over time, and used competing risk models to assess temporal changes in racial/ethnic differences in home dialysis outcomes, specifically: ( 1 ) transfer to in-center hemodialysis (HD), ( 2 ) mortality, and ( 3 ) transplantation. Results Of the 523,526 patients initiating dialysis from 2005 to 2013, 55% were white, 28% black, 13% Hispanic, and 4% Asian. In the earliest era (2005–2007), 8.0% of white patients initiated dialysis with home modalities, as did a similar proportion of Asians (9.2%; adjusted odds ratio [aOR], 0.95; 95% confidence interval [95% CI], 0.86 to 1.05), whereas lower proportions of black [5.2%; aOR, 0.71; 95% CI, 0.66 to 0.76] and Hispanic (5.7%; aOR, 0.83; 95% CI, 0.86 to 0.93) patients did so. Over time, home dialysis use increased in all groups and racial/ethnic differences decreased (2011–2013: 10.6% of whites, 8.3% of blacks [aOR, 0.81; 95% CI, 0.77 to 0.85], 9.6% of Hispanics [aOR, 0.94; 95% CI, 0.86 to 1.00], 14.2% of Asians [aOR, 1.04; 95% CI, 0.86 to 1.12]). Compared with white patients, the risk of transferring to in-center HD was higher in blacks, similar in Hispanics, and lower in Asians; these differences remained stable over time. The mortality rate was lower for minority patients than for white patients; this difference increased over time. Transplantation rates were lower for blacks and similar for Hispanics and Asians; over time, the difference in transplantation rates between blacks and Hispanics versus whites increased. Conclusions From 2005 to 2013, as home dialysis use increased, racial/ethnic differences in initiating home dialysis narrowed, without worsening rates of death or transfer to in-center HD in minority patients, as compared with white patients.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".