Use of vascular access for haemodialysis in Europe: a report from the ERA-EDTA Registry
Bibliographic record
Abstract
BACKGROUND: Although arteriovenous fistulas (AVFs) are actively promoted, their use at the start of haemodialysis (HD) seems to be decreasing worldwide. In this paper, we describe recent trends in incidence and prevalence of vascular access types in Europe from 2005 to 2009 and their relationship with patient characteristics and survival. METHODS: Ten European renal registries participating in the ERA-EDTA Registry provided data on incidence (n = 13,044) and/or prevalence (n = 75,715) of vascular access types. We used logistic regression to assess which factors influence the likelihood to be treated with an AVF rather than another type. RESULTS: The use of AVFs at the start of HD showed a significant decreasing trend from 42% in 2005 to 32% in 2009 (P < 0.0001), while the use of central venous catheters (CVCs) increased from 58 to 68% (P < 0.0001). A similar evolution pattern was observed for the prevalence; use of AVFs decreased from 66 to 62% and use of CVCs increased from 28 to 32%. There was a large international variation in the use of the different vascular access types. Female patients [adjusted odds ratio: 0.84, 95% confidence interval (CI): 0.78-0.90] and those ≥80 years (0.77, 95% CI: 0.67-0.90) were least likely to start HD with an AVF. CONCLUSION: In Europe, there is a decreasing trend in the use of AVFs and an increasing trend in the use of CVCs at the start and after the start of HD. We cannot explain all between-country variations we found, and more research is needed to clarify how healthcare around vascular access is organized in Europe.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".