کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
3885732 | 1249522 | 2009 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: The Oxford classification of IgA nephropathy: pathology definitions, correlations, and reproducibility The Oxford classification of IgA nephropathy: pathology definitions, correlations, and reproducibility](/preview/png/3885732.png)
Pathological classifications in current use for the assessment of glomerular disease have been typically opinion-based and built on the expert assumptions of renal pathologists about lesions historically thought to be relevant to prognosis. Here we develop a unique approach for the pathological classification of a glomerular disease, IgA nephropathy, in which renal pathologists first undertook extensive iterative work to define pathologic variables with acceptable inter-observer reproducibility. Where groups of such features closely correlated, variables were further selected on the basis of least susceptibility to sampling error and ease of scoring in routine practice. This process identified six pathologic variables that could then be used to interrogate prognostic significance independent of the clinical data in IgA nephropathy (described in the accompanying article). These variables were (1) mesangial cellularity score; percentage of glomeruli showing (2) segmental sclerosis, (3) endocapillary hypercellularity, or (4) cellular/fibrocellular crescents; (5) percentage of interstitial fibrosis/tubular atrophy; and finally (6) arteriosclerosis score. Results for interobserver reproducibility of individual pathological features are likely applicable to other glomerulonephritides, but it is not known if the correlations between variables depend on the specific type of glomerular pathobiology. Variables identified in this study withstood rigorous pathology review and statistical testing and we recommend that they become a necessary part of pathology reports for IgA nephropathy. Our methodology, translating a strong evidence-based dataset into a working format, is a model for developing classifications of other types of renal disease.
Journal: Kidney International - Volume 76, Issue 5, 1 September 2009, Pages 546–556