Global Policy and Advocacy Initiatives for Improving Kidney Care
Bibliographic record
Abstract
Key Points Inclusion and prioritization of CKD and kidney failure within national health strategies are generally lacking. Countries with CKD-specific strategies tend to include and fund a broader spectrum of kidney disease populations and kidney care. Greater global and national prioritization of kidney health are required to reduce global inequities in access to kidney care. Background National strategies to address CKD are crucial to support kidney health. Lack of political support in the form of policy decisions and funding leads to fragmentation of kidney care and catastrophic health expenditure. This study used data from the third iteration of the International Society of Nephrology Global Kidney Health Atlas to obtain a global overview of the existence and reach of national strategies for kidney care. Methods We leveraged data from an international survey of stakeholders (clinicians, policymakers, and patient advocates) conducted by the International Society of Nephrology between July and September 2022. Data were extracted on existence and scope of national noncommunicable disease (NCD) and/or CKD-specific strategies and policies, as well as recognition of kidney disease as a national health priority through participant perception and existence of CKD advocacy groups. Results Overall, stakeholders from 167 countries responded to the survey, representing 97.4% of the global population. National strategies for NCDs were reported by 56% of countries. In 29% of countries, CKD was addressed within an NCD strategy, whereas 25% of countries reported CKD-specific strategies. Countries with CKD-specific strategies were more likely to address all CKD populations (non–dialysis-dependent CKD, chronic dialysis, and kidney transplantation) compared with those with NCD strategies only (51.2% versus 19%). Of the 54% of countries with any CKD strategy, 89% reported public funding of the full spectrum of CKD care compared with 64% of those with no CKD strategy. Kidney failure, CKD, and AKI were reported to be recognized as national health priorities by 63%, 48%, and 19% of countries, respectively. Conclusions The inclusion of CKD and kidney failure within national health strategies is frequently lacking. Countries with CKD-specific policies tend to include a broader spectrum of kidney disease populations and to fund kidney care more than those with CKD policies integrated within NCD strategies. Greater global and national prioritization of kidney health are required to reduce global inequities in access to kidney care.
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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 | 0.032 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.034 | 0.003 |
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".