Supplemented ERA-EDTA Registry data evaluated the frequency of dialysis, kidney transplantation, and comprehensive conservative management for patients with kidney failure in Europe
Bibliographic record
Abstract
The aims of this study were to determine the frequency of dialysis and kidney transplantation and to estimate the regularity of comprehensive conservative management (CCM) for patients with kidney failure in Europe. This study uses data from the ERA-EDTA Registry. Additionally, our study included supplemental data from Armenia, Germany, Hungary, Ireland, Kosovo, Luxembourg, Malta, Moldova, Montenegro, Slovenia and additional data from Israel, Italy, Slovakia using other information sources. Through an online survey, responding nephrologists estimated the frequency of CCM (i.e. planned holistic care instead of kidney replacement therapy) in 33 countries. In 2016, the overall incidence of replacement therapy for kidney failure was 132 per million population (pmp), varying from 29 (Ukraine) to 251 pmp (Greece). On 31 December 2016, the overall prevalence of kidney replacement therapy was 985 pmp, ranging from 188 (Ukraine) to 1906 pmp (Portugal). The prevalence of peritoneal dialysis (114 pmp) and home hemodialysis (28 pmp) was highest in Cyprus and Denmark respectively. The kidney transplantation rate was nearly zero in some countries and highest in Spain (64 pmp). In 28 countries with five or more responding nephrologists, the median percentage of candidates for kidney replacement therapy who were offered CCM in 2018 varied between none (Slovakia and Slovenia) and 20% (Finland) whereas the median prevalence of CCM varied between none (Slovenia) and 15% (Hungary). Thus, the substantial differences across Europe in the frequency of kidney replacement therapy and CCM indicate the need for improvement in access to various treatment options for patients with kidney failure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| 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 | 0.000 | 0.000 |
| 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".