Equity and Quality of Global Chronic Kidney Disease Care: What Are We Waiting for?
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) is an important but insufficiently recognized public health problem. Unprecedented advances in delaying progression of CKD and reducing kidney failure and death have been made in recent years, with the addition of the sodium-glucose cotransporter 2 inhibitors and other newer medication to the established standard of care with inhibitors of the renin-angiotensin system. Despite knowledge of these effective therapies, their prescription and use remain suboptimal globally, and more specially in low resource settings. Many challenges contribute to this gap between knowledge and translation into clinical care, which is even wider in lower resource settings across the globe. Implementation of guideline-directed care is hampered by lack of disease awareness, late or missed diagnosis, clinical inertia, poor quality care, cost of therapy, systemic biases, and lack of patient empowerment. All of these are exacerbated by the social determinants of health and global inequities. SUMMARY: CKD is a highly manageable condition but requires equitable and sustainable access to quality care supported by health policies, health financing, patient and health care worker education, and affordability of medications and diagnostics. KEY MESSAGES: The gap between the knowledge and tools to treat CKD and the implementation of optimal quality kidney care should no longer be tolerated. Advocacy, research and action are required to improve equitable access to sustainable quality care for CKD everywhere.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".