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Cited by 223

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Chapter 2: Definition, identification, and prediction of CKD progression

Open access
·2013·Kidney International Supplements

Abstract

RATIONALE The statement is worded this way to remind the practitioner to use both GFR and albuminuria in order to assess progression and is consistent with the definition offered in Chapter 1 regarding definitions of CKD which include both parameters. There is increasing evidence which supports that both parameters are valuable. Lower GFR and greater albuminuria are both associated with an increased rate of progression and are synergistic. More frequent measures of eGFR and albuminuria should be considered in patients with a lower GFR and greater albuminuria as these people are more likely to progress. Frequency of measurement should also be individualized based on the patient history and underlying cause of kidney disease. In specific conditions (e.g., GN or increased levels of albuminuria), frequent (every 1–3 months) assessment may guide therapeutic decisions. Regular monitoring of stable patients may include more frequent monitoring than annually, but will be dictated by underlying cause, history, and estimates of GFR and ACR values obtained previously.

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Crossref · 10.1038/kisup.2012.65

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Metadata

Venue
Kidney International Supplements
Publisher
Elsevier BV
Published
2013-01
Volume
3
Issue
1
Pages
63-72
ISSN
2157-1716 (ISSN-L)
OpenAlex
W4235787011
Cited by
223
References
1
FWCI
3.16
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Chapter 2: Definition, identification, and prediction of CKD progression. https://app.cochat.ai/papers/10.1038/kisup.2012.65
The paper
Chapter 2: Definition, identification, and prediction of CKD progression. (2013). Kidney International Supplements. https://doi.org/10.1038/kisup.2012.65

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.