The case for early identification and intervention of chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference
Open accessAbstract
Chronic kidney disease (CKD) causes substantial global morbidity and increases cardiovascular and all-cause mortality. Unlike other chronic diseases with established strategies for screening, there has been no consensus on whether health systems and governments should prioritize early identification and intervention for CKD. Guidelines on evaluating and managing early CKD are available but have not been universally adopted in the absence of incentives or quality measures for prioritizing CKD care. The burden of CKD falls disproportionately upon persons with lower socioeconomic status, who have a higher prevalence of CKD, limited access to treatment, and poorer outcomes. Therefore, identifying and treating CKD at the earliest stages is an equity imperative. In 2019, Kidney Disease: Improving Global Outcomes (KDIGO) held a controversies conference entitled "Early Identification and Intervention in CKD." Participants identified strategies for screening, risk stratification, and treatment for early CKD and the key health system and economic factors for implementing these processes. A consensus emerged that CKD screening coupled with risk stratification and treatment should be implemented immediately for high-risk persons and that this should ideally occur in primary or community care settings with tailoring to the local context.
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Both the ADA and KDIGO recommend annual screening of patients with diabetes for CKD.
“Both the ADA and KDIGO recommend annual screening of patients with diabetes for CKD (17,18) (Fig. 1).”
From Diabetes management in chronic kidney disease: a consensus report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO) (2022) · cites this paper as [18]
Table 1 recommends CKD screening for people with diabetes, supporting that part of the claim. It says screening frequency should be individualized, and the discussion of repeat testing gives risk-dependent intervals rather than annual screening for all patients with diabetes. Our copy cites an ADA guideline but does not state that both the ADA and KDIGO recommend annual screening. (LLM, conf=0.88)
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BackgroundDapagliflozin in Patients with Chronic Kidney Disease
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- Authors
- Shlipak, M. G., Tummalapalli, S. L., Boulware, L. E., Grams, M. E., Ix, J. H., Jha, V., Kengne, A.-P., Madero, M., Mihaylova, B., Tangri, N., Cheung, M., Jadoul, M., Winkelmayer, W. C., Zoungas, S., Abraham, G., Ademi, Z., Alicic, R. Z., de Boer, I., Deo, R., Ding, X., Ebert, N., Fowler, K. J., Fried, L. F., Gansevoort, R. T., Garcia-Garcia, G., Hemmelgarn, B. R., Lee Harding, J., Hudson, J. Q., Iseki, K., Jotwani, V., Karliner, L. S., Levey, A. S., Liew, A., Lin, P. J., Luk, A. O. Y., Martínez, V., Moran, A. E., Nguyen, M., Obrador, G. T., O’Donoghue, D., Pavkov, M. E., Pavlinac, J., Powe, N. R., Seegmiller, J. C., Shen, J. I., Shroff, R., Solá, L., Taal, M. W., Tattersall, J., Vassalotti, J. A., Weir, M. R., & Zomer, E.
- Affiliations
- San Francisco VA Medical Center (US)
- Duke University (US)
- Johns Hopkins University (US)
- University of California San Diego (US)
- Manipal Academy of Higher Education (IN)
- Instituto Nacional de Cardiología (MX)
- Queen Mary University of London (GB)
- University of Manitoba (CA)
- Kidney Disease: Improving Global Outcomes (BE)
- Cliniques Universitaires Saint-Luc (BE)
- Monash Health (AU)
- Corresponding author
- Shlipak, Michael G.
- Zoungas, Sophia
- ORCID
- Shlipak, Michael G.
- Tummalapalli, Sri Lekha
- Boulware, L. Ebony
- Grams, Morgan E.
- Ix, Joachim H.
- Jha, Vivekanand
- Madero, Magdalena
- Mihaylova, Borislava
- Tangri, Navdeep
- Cheung, Michael
- Jadoul, Michel
- Zoungas, Sophia
- Ademi, Zanfina
- Alicic, Radica Z.
- Ding, Xiaoqiang
- Ebert, Natalie
- Fowler, Kevin J.
- Gansevoort, Ron T.
- Hemmelgarn, Brenda R.
- Hudson, Joanna Q.
- Iseki, Kunitoshi
- Jotwani, Vasantha
- Karliner, Leah S.
- Levey, Andrew S.
- Liew, Adrian
- Lin, Peter J.
- Luk, Andrea O.Y.
- Martínez, Verónica
- Moran, Andrew E.
- Obrador, Gregorio T.
- Pavkov, Meda E.
- Powe, Neil R.
- Seegmiller, Jesse C.
- Shen, Jenny I.
- Shroff, Rukshana
- Solá, Laura
- Taal, Maarten W.
- Tattersall, James
- Vassalotti, Joseph A.
- Weir, Matthew R.
- Zomer, Ella
- Venue
- Kidney International
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 99
- Issue
- 1
- Pages
- 34-47
- ISSN
- 0085-2538 (ISSN-L)
- OpenAlex
- W3095099370
- Cited by
- 581
- References
- 9
- Citations by year
- 2026: 77 · 2025: 149 · 2024: 163 · 2023: 106 · 2022: 56 · 2021: 26 · 2020: 3
- FWCI
- 30.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Kidney International (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DIAL (Catholic University of Leuven) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by-nc-nd)
- Funders
- AstraZeneca
- International Society of Nephrology
- Fresenius Medical Care North America
- Kidney Research UK (RP39/2013)
- Bayer HealthCare
- Akebia Therapeutics
- Relypsa
- Topics
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Keywords
- chronic kidney disease, early detection, CKD screening, risk stratification, early intervention, health equity, socioeconomic disparities, primary care, health system implementation, cardiovascular mortality, all-cause mortality
- MeSH terms
- Glomerular Filtration Rate, Humans, Kidney, Risk Factors, Risk Assessment, Renal Insufficiency, Chronic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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