Economic trend in kidney transplantation costs in the world; insights from the ISN global kidney health atlas 2019-2023
Bibliographic record
Abstract
Introduction: Kidney transplantation is a critical treatment for end-stage kidney disease, but its costs vary widely across countries and over time. Objectives: This study investigates changes in kidney transplantation costs between 2019 and 2023 using data from the International Society of Nephrology Global Kidney Health Atlas (ISN-GKHA). Methods: This ecological study analyzed kidney transplantation costs reported globally for 2019 and 2023 using data from the ISN-GKHA. The study included countries with complete cost data for both years, excluding those with missing or inconsistent records. Data collection focused on extracting first-year and subsequent annual transplantation costs from the publicly available ISN database. The primary outcome was the change in transplantation costs over time, evaluated to identify trends and regional variations in expenses across the included countries. Results: The trend from 2019 to 2023 in kidney transplantation costs varies by continent and globally. In Latin America, Brazil showed the highest increase, while Bolivia had the smallest. Oceania and Southeast Asia saw Australia with the largest increase and Indonesia with a decrease. Western Europe had the Netherlands with the greatest rise and Germany with a decrease. Saudi Arabia had the highest increase in the Middle East, while the West Bank and Gaza had the least. South Asia’s Bangladesh showed a modest increase. In North America, the United States experienced the largest increase, whereas Canada had a decrease. North and East Asia saw Japan with the most notable increase and China with a decrease. Africa had Morocco with the highest increase and Egypt with the smallest. Eastern and Central Europe recorded the largest rise in Slovenia and the smallest in Serbia. Overall, the United States had the most significant increase, while Germany showed the greatest decrease. Conclusion: The findings highlight significant regional disparities in kidney transplantation costs globally, emphasizing the necessity for targeted healthcare policies and ongoing monitoring to ensure cost-effective and equitable access to transplantation services worldwide.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| 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) | 0.002 | 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".