The potential of kidney transplantation to reduce mortality from chronic kidney disease: a global, cross-sectional, modelling study
Bibliographic record
Abstract
BACKGROUND: Globally, the burden of chronic kidney disease and ensuing need for kidney replacement therapy (KRT)-dialysis or kidney transplantation-are increasing. Despite the mortality benefit of transplantation over dialysis, dialysis services are expanding more rapidly than access to transplantation. We aimed to cross-sectionally assess the association between country-level KRT rates and chronic kidney disease mortality to facilitate evidence-based prioritisation of KRT modalities. METHODS: For all countries with publicly available data, we collected income level and gross domestic product per capita (GDP-PC) from the World Bank (data from 2022), age-standardised chronic kidney disease prevalence and mortality from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD; data from 2021), and dialysis prevalence and kidney transplantation incidence from the International Society of Nephrology-Global Kidney Health Atlas (ISN-GKHA) and Global Observatory on Donation and Transplantation (data from 2022). To account for varying chronic kidney disease prevalence among countries, we divided each of the latter three variables by the chronic kidney disease prevalence to obtain national dialysis rates, kidney transplantation rates, and the mortality-prevalence ratio, respectively. We modelled mortality-prevalence ratio as a multivariable function of GDP-PC and KRT rates. We used this model to estimate how increased kidney transplantation rates might affect chronic kidney disease mortality. FINDINGS: Among 203 countries and territories with epidemiological data available from both the GBD and ISN-GKHA, median age-standardised chronic kidney disease prevalence was 7·78% (IQR 6·54-9·48%). Data availability was associated with income level (p<0·0001). Higher GDP-PC was associated with higher KRT rates (p<0·0001 for both dialysis and kidney transplantation) and lower mortality-prevalence ratio (p<0·0001). On multivariable analysis, decreases in mortality-prevalence ratio were independently associated with GDP-PC (coefficient -0·258; 95% CI -0·413 to -0·103; p=0·0031) and kidney transplantation rates (-574; -1090 to -43·5; p=0·039), but not dialysis rates (10·8; -29·5 to -6·27; p=0·22). Conservative increases in kidney transplantation rates could avert 290 000 chronic kidney disease deaths annually. INTERPRETATION: We provide, to our knowledge, the first compilation of evidence that countries with higher kidney transplantation rates have lower mortality-prevalence ratio, regardless of GDP-PC; dialysis does not have a similar association. GDP-PC-based disparities in data availability, kidney transplantation rates, and mortality-prevalence ratio are expected to worsen with anticipated increases in prevalence of chronic kidney disease. To mitigate this risk, policy makers should leverage international guidelines and partnerships to increase access to safe and ethical transplantation. FUNDING: None.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".