Renal replacement therapy for autosomal dominant polycystic kidney disease (ADPKD) in Europe: prevalence and survival--an analysis of data from the ERA-EDTA Registry
Bibliographic record
Abstract
BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the fourth most common renal disease requiring renal replacement therapy (RRT). Still, there are few epidemiological data on the prevalence of, and survival on RRT for ADPKD. METHODS: This study used data from the ERA-EDTA Registry on RRT prevalence and survival on RRT in 12 European countries with 208 million inhabitants. We studied four 5-year periods (1991-2010). Survival analysis was performed by the Kaplan-Meier method and by Cox proportional hazards regression. RESULTS: From the first to the last study period, the prevalence of RRT for ADPKD increased from 56.8 to 91.1 per million population (pmp). The percentage of prevalent RRT patients with ADPKD remained fairly stable at 9.8%. Two-year survival of ADPKD patients on RRT (adjusted for age, sex and country) increased significantly from 89.0 to 92.8%, and was higher than for non-ADPKD subjects. Improved survival was noted for all RRT modalities: haemodialysis [adjusted hazard ratio for mortality during the last versus first time period 0.75 (95% confidence interval 0.61-0.91), peritoneal dialysis 0.55 (0.38-0.80) and transplantation 0.52 (0.32-0.74)]. Cardiovascular mortality as a proportion of total mortality on RRT decreased more in ADPKD patients (from 53 to 29%), than in non-ADPKD patients (from 44 to 35%). Of note, the incidence rate of RRT for ADPKD remained relatively stable at 7.6 versus 8.3 pmp from the first to the last study period, which will be discussed in detail in a separate study. CONCLUSIONS: In ADPKD patients on RRT, survival has improved markedly, especially due to a decrease in cardiovascular mortality. This has led to a considerable increase in the number of ADPKD patients being treated with RRT.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".