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Cited by 316

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Mayo Clinic/Renal Pathology Society Consensus Report on Pathologic Classification, Diagnosis, and Reporting of GN

Open access
Sethi, Sanjeev, Haas, Mark, Markowitz, Glen S., D’Agati, Vivette D., Rennke, Helmut G., Jennette, J. Charles, Bajema, Ingeborg M., Alpers, Charles E., Chang, Anthony, Cornell, Lynn D., Cosio, Fernando G., Fogo, Agnes B., Glassock, Richard J., Hariharan, Sundaram, Kambham, Neeraja, Lager, Donna J., Leung, Nelson, Mengel, Michael, Nath, Karl A., Roberts, Ian S., Rovin, Brad H., Seshan, Surya V., Smith, Richard J.H., Walker, Patrick D., Winearls, Christopher G., Appel, Gerald B., Alexander, Mariam P., Cattran, Daniel C., Casado, Carmen Avila, Cook, H. Terence, De Vriese, An S., Radhakrishnan, Jai, Racusen, Lorraine C., Ronco, Pierre, Fervenza, Fernando C.·2016·Journal of the American Society of Nephrology

Abstract

Renal pathologists and nephrologists met on February 20, 2015 to establish an etiology/pathogenesis-based system for classification and diagnosis of GN, with a major aim of standardizing the kidney biopsy report of GN. On the basis of etiology/pathogenesis, GN is classified into the following five pathogenic types, each with specific disease entities: immune-complex GN, pauci-immune GN, antiglomerular basement membrane GN, monoclonal Ig GN, and C3 glomerulopathy. The pathogenesis-based classification forms the basis of the kidney biopsy report. To standardize the report, the diagnosis consists of a primary diagnosis and a secondary diagnosis. The primary diagnosis should include the disease entity/pathogenic type (if disease entity is not known) followed in order by pattern of injury (mixed patterns may be present); score/grade/class for disease entities, such as IgA nephropathy, lupus nephritis, and ANCA GN; and additional features as detailed herein. A pattern diagnosis as the sole primary diagnosis is not recommended. Secondary diagnoses should be reported separately and include coexisting lesions that do not form the primary diagnosis. Guidelines for the report format, light microscopy, immunofluorescence microscopy, electron microscopy, and ancillary studies are also provided. In summary, this consensus report emphasizes a pathogenesis-based classification of GN and provides guidelines for the standardized reporting of GN.

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Metadata

Authors
Sethi, S., Haas, M., Markowitz, G. S., D’Agati, V. D., Rennke, H. G., Jennette, J. C., Bajema, I. M., Alpers, C. E., Chang, A., Cornell, L. D., Cosio, F. G., Fogo, A. B., Glassock, R. J., Hariharan, S., Kambham, N., Lager, D. J., Leung, N., Mengel, M., Nath, K. A., Roberts, I. S., Rovin, B. H., Seshan, S. V., Smith, R. J. H., Walker, P. D., Winearls, C. G., Appel, G. B., Alexander, M. P., Cattran, D. C., Casado, C. A., Cook, H. T., De Vriese, A. S., Radhakrishnan, J., Racusen, L. C., Ronco, P., & Fervenza, F. C.
Venue
Journal of the American Society of Nephrology
Published
2015-11-13
Volume
27
Issue
5
Pages
1278-1287
ISSN
  • 1046-6673 (ISSN-L)
  • 1533-3450
OpenAlex
W2198068262
Cited by
316
References
34
FWCI
15.71
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Mayo Clinic/Renal Pathology Society Consensus Report on Pathologic Classification, Diagnosis, and Reporting of GN. https://app.cochat.ai/papers/10.1681/asn.2015060612
The paper
Sethi, S., Haas, M., Markowitz, G. S., D’Agati, V. D., Rennke, H. G., Jennette, J. C., Bajema, I. M., Alpers, C. E., Chang, A., Cornell, L. D., Cosio, F. G., Fogo, A. B., Glassock, R. J., Hariharan, S., Kambham, N., Lager, D. J., Leung, N., Mengel, M., Nath, K. A., . . . Fervenza, F. C. (2016). Mayo Clinic/Renal Pathology Society Consensus Report on Pathologic Classification, Diagnosis, and Reporting of GN. Journal of the American Society of Nephrology. https://doi.org/10.1681/asn.2015060612

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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.