Progress of nations in the organisation of, and structures for, kidney care delivery between 2019 and 2023: cross sectional survey in 148 countries
Bibliographic record
Abstract
OBJECTIVE: To assess changes in key measures of kidney care using data reported in 2019 and 2023. DESIGN: Cross sectional survey in 148 countries. SETTING: Surveys from International Society of Nephrology Global Kidney Health Atlas between 2019 and 2023 that included participants from countries in Africa (n=36), Eastern and Central Europe (n=16), Latin America (n=18), the Middle East (n=11), Newly Independent States and Russia (n=10), North America and the Caribbean (n=8), North and East Asia (n=6), Oceania and South East Asia (n=15), South Asia (n=7), and Western Europe (n=21). PARTICIPANTS: Countries that participated in both surveys (2019 and 2023). MAIN OUTCOME MEASURES: Comparison of 2019 and 2023 data for availability of kidney replacement treatment services, access, health financing, workforce, registries, and policies for kidney care. Data for countries that participated in both surveys (2019 and 2023) were included in our analysis. Country data were aggregated by International Society of Nephrology regions and World Bank income levels. Proportionate changes in the status of these measures across both periods were reported. RESULTS: Data for 148 countries that participated in both surveys were available for analysis. The proportions of countries that provided public funding (free at point of delivery) increased from 27% in 2019 to 28% in 2023 for haemodialysis, 23% to 28% for peritoneal dialysis, and 31% to 36% for kidney transplantation services. Centres for these treatments increased from 4.4 per million population (pmp) to 4.8 pmp (P<0.001) for haemodialysis, 1.4 pmp to 1.6 pmp for peritoneal dialysis, and 0.43 pmp to 0.46 pmp for kidney transplantation services. Overall, access to haemodialysis and peritoneal dialysis improved, however, access to kidney transplantation decreased from 30 pmp to 29 pmp. The global median prevalence of nephrologists increased from 9.5 pmp to 12.4 pmp (P<0.001). Changes in the availability of kidney registries and in national policies and strategies for kidney care were variable across regions and country income levels. The reporting of specific barriers to optimal kidney care by countries increased from 55% to 59% for geographical factors, 58% to 68% (P=0.043) for availability of nephrologists, and 46% to 52% for political factors. CONCLUSIONS: Important changes in key areas of kidney care delivery were noted across both periods globally. These changes effected the availability of, and access to, kidney transplantation services. Countries and regions need to enact enabling strategies for preserving access to kidney care services, particularly kidney transplantation.
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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) | 0.000 | 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 | 0.001 |
| 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".