Increasing access to integrated ESKD care as part of universal health coverage
Bibliographic record
Abstract
The global nephrology community recognizes the need for a cohesive strategy to address the growing problem of end-stage kidney disease (ESKD). In March 2018, the International Society of Nephrology hosted a summit on integrated ESKD care, including 92 individuals from around the globe with diverse expertise and professional backgrounds. The attendees were from 41 countries, including 16 participants from 11 low- and lower-middle-income countries. The purpose was to develop a strategic plan to improve worldwide access to integrated ESKD care, by identifying and prioritizing key activities across 8 themes: (i) estimates of ESKD burden and treatment coverage, (ii) advocacy, (iii) education and training/workforce, (iv) financing/funding models, (v) ethics, (vi) dialysis, (vii) transplantation, and (viii) conservative care. Action plans with prioritized lists of goals, activities, and key deliverables, and an overarching performance framework were developed for each theme. Examples of these key deliverables include improved data availability, integration of core registry measures and analysis to inform development of health care policy; a framework for advocacy; improved and continued stakeholder engagement; improved workforce training; equitable, efficient, and cost-effective funding models; greater understanding and greater application of ethical principles in practice and policy; definition and application of standards for safe and sustainable dialysis treatment and a set of measurable quality parameters; and integration of dialysis, transplantation, and comprehensive conservative care as ESKD treatment options within the context of overall health priorities. Intended users of the action plans include clinicians, patients and their families, scientists, industry partners, government decision makers, and advocacy organizations. Implementation of this integrated and comprehensive plan is intended to improve quality and access to care and thereby reduce serious health-related suffering of adults and children affected by ESKD worldwide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 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".