The publication detail shows the title, authors (with indicators showing other profiled authors), information on the publishing organization, abstract and a link to the article in PubMed. This abstract is what is used to create the fingerprint of the publication. If any grants are referenced by the publication, they will be listed here as well.
Validation of creatinine-based estimates of GFR when evaluating risk factors in longitudinal studies of kidney disease.
Xuelei Wang; Julia Lewis; Lawrence Appel; DeAnna Cheek; Gabriel Contreras; Marquetta Faulkner; Harold Feldman; Jennifer Gassman; Janice Lea; Joel Kopple; et al. (Profiled Author: Lawrence Appel)
Cleveland Clinic Foundation, Department of Quantitative Health Sciences, Wb-4, 9500 Euclid Avenue, Cleveland, OH 44195, USA. firstname.lastname@example.org
Journal of the American Society of Nephrology : JASN 2006;17(10):2900-9.
Whereas much research has investigated equations for obtaining estimated GFR (eGFR) from serum creatinine in cross-sectional settings, little attention has been given to validating these equations as outcomes in longitudinal studies of chronic kidney disease. A common objective of chronic kidney disease studies is to identify risk factors for progression, characterized by slope (rate of change over time) or time to event (time until a designated decline in kidney function or ESRD). The relationships of 35 baseline factors with eGFR-based outcomes were compared with the relationships of the same factors with iothalamate GFR (iGFR)-based outcomes in the African American Study of Kidney Disease and Hypertension (AASK; n = 1094). With the use of the AASK equation to calculate eGFR, results were compared between time to halving of eGFR or ESRD and time to halving of iGFR or ESRD (with effect sizes expressed per 1 SD) and between eGFR and iGFR slopes starting 3 mo after randomization. The effects of the baseline factors were similar between the eGFR- and iGFR-based time-to-event outcomes (Pearson R = 0.99, concordance R = 0.98). Small but statistically significant differences (P < 0.05, without adjustment for multiple analyses) were observed for seven of the 35 factors. Agreement between eGFR and iGFR was somewhat weaker, although still relatively high for slope-based outcomes (Pearson R = 0.93, concordance R = 0.92). Effects of covariate adjustment for age, gender, baseline GFR, and urine proteinuria also were similar between the eGFR and iGFR outcomes. Sensitivity analyses including death in the composite time-to-event outcomes or using the Modification of Diet in Renal Disease equation instead of the AASK equation provided similar results. In conclusion, the data from the AASK provide tentative support for use of outcomes that are based on an established eGFR formula using serum creatinine as a surrogate for measured iGFR-based outcomes in analyses of risk factors for the progression of kidney disease.
This section shows information related to the publication - computed using the fingerprint of the publication - including related publications, related experts and related grants with fingerprints representing significant amounts of overlap between their fingerprint and this publication. The red dots indicate whether those experts or terms appear within the publication, thereby showing potential and actual connections.
Julia Lewis; Tom Greene; Lawrence Appel; Gabriel Contreras; Janice Douglas; Jim Lash; Robert Toto; Fredrick Van Lente; Xuelei Wang; Jackson T Wright; et al.Journal of the American Society of Nephrology : JASN 2004;15(12):3175-83.
Julia J Scialla; Brad C Astor; Tamara Isakova; Huiliang Xie; Lawrence J Appel; Myles WolfJournal of the American Society of Nephrology : JASN 2013;24(1):125-35.
Julia J Scialla; Lawrence J Appel; Brad C Astor; Edgar R Miller; Srinivasan Beddhu; Mark Woodward; Rulan S Parekh; Cheryl A M Anderson;Kidney international 2012;82(1):106-12.
Appears in this Publication
Author of this Publication