End‐stage renal disease from hemolytic uremic syndrome in the <scp>U</scp>nited <scp>S</scp>tates, 1995–2010
Bibliographic record
Abstract
Management of hemolytic uremic syndrome (HUS) has evolved rapidly, and optimal treatment strategies are controversial. However, it is unknown whether the burden of end-stage renal disease (ESRD) from HUS has changed, and outcomes on dialysis in the United States are not well described. We retrospectively examined data for patients initiating maintenance renal replacement therapy (RRT) (n = 1,557,117), 1995-2010, to define standardized incidence ratios (SIRs) and outcomes of ESRD from HUS) (n = 2241). Overall ESRD rates from HUS in 2001-2002 were 0.5 cases/million per year and were higher for patients characterized by age 40-64 years (0.6), ≥65 years (0.7), female sex (0.6), and non-Hispanic African American race (0.7). Standardized incidence ratios remained unchanged (P ≥ 0.05) between 2001-2002 and 2009-2010 in the overall population. Compared with patients with ESRD from other causes, patients with HUS were more likely to be younger, female, white, and non-Hispanic. Over 5.4 years of follow-up, HUS patients differed from matched controls with ESRD from other causes by lower rates of death (8.3 per 100 person-years in cases vs. 10.4 in controls, P < 0.001), listing for renal transplant (7.6 vs. 8.6 per 100 person-years, P = 0.04), and undergoing transplant (6.9 vs. 9 per 100 person-years, P < 0.001). The incidence of ESRD from HUS appears not to have risen substantially in the last decade. However, given that HUS subtypes could not be determined in this study, these findings should be interpreted with caution.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".