Global Variability and Patterns of Use in Vascular and Peritoneal Access for Dialysis: Analysis of the ISN-Global Kidney Health Atlas Data
Bibliographic record
Abstract
Background: A well-functioning access (vascular or peritoneal) is key to adequate performance of dialysis. The International Society of Nephrology Global Kidney Health Atlas (ISN-GKHA) survey identified gaps in availability, patterns of use, funding models, and workforce for the provision of vascular and peritoneal accesses across countries. Methods: Using the second iteration of the ISN-GKHA, countries were categorized by affiliations in the ISN regional boards and by World Bank income classification. Questions focused on availability of surgical aspects of care, access to education and availability of providers for the access creation. Results: Data was available from 159 countries out of 160 that participated in the survey. Overall, public funding was available for hemodialysis (HD) central venous catheters in 92 countries (57%), for HD fistula or graft creation in 86 countries (54%), and for PD catheter surgery in 85 countries (54%). Public funding for the access types was highest in high-income countries than other country income categories. Overall, and in countries where HD was available, >75% of patients initiated HD with a temporary catheter in 21% of countries compared to patients commencing with a tunneled catheter (5%) or a fistula (5%) (Figures 1). Shortages of surgeons and radiologists were highest in low-income and lower-middle income countries. Conclusions: There is significant variation in the availability, accessibility and patterns of use of vascular access and peritoneal catheters across countries with significant limitations in the needed workforce. In order to improve the outcomes and survival of patients on dialysis, strategies to increase the uptake of viable access are required.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| 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".