Holistic Impact of CKD: A Clinical, Economic, and Environmental Analysis by IMPACT CKD
Bibliographic record
Abstract
Introduction: Chronic kidney disease (CKD) is a growing global health problem driven by aging and the rise of comorbidities, including diabetes and hypertension. Although clinical and economic burdens have been reported, there is a lack of information on the multidimensional impact of CKD across countries with varying demographics and health system archetypes. Methods: The validated IMPACT CKD model was used to project the clinical, health care resource use (HCRU), economic, patient, societal, and environmental burden of CKD in 8 countries (Australia, Brazil, China, Germany, Netherlands, Spain, United Kingdom, and United States) over 10 years (baseline: 2022; simulated years: 2023-2032). Results: By 2032, 11.7% to 16.5% of the countries' populations were projected to have CKD, with prevalence rising in 7 countries over 10 years, and a shift toward later stages. These increases were accompanied by projected increases of 3.6% to 170.8% and 41.9% to 80.1% in the number of patients living on dialysis and with a functioning kidney transplant, respectively. Driven by this growing clinical burden, increases of over 19% in CKD costs and 20% in kidney replacement therapy (KRT) costs were projected across all countries. Impaired work productivity led to significant projected losses in gross domestic product, full-time equivalents, and tax revenue. Freshwater consumption, fossil fuel depletion, and carbon production in patients on KRT were projected to increase by over 11% in all the countries. Conclusion: This study demonstrates the multifaceted burden of CKD globally and supports the adoption of policies such as CKD screening programs and public health awareness to promote early diagnosis and treatment to mitigate the growing disease burden.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".