Int J Med Sci 2008; 5(1):9-17. doi:10.7150/ijms.5.9
Does eGFR improve the diagnostic capability of S-Creatinine concentration results? A retrospective population based study
1. Department of Clinical Chemistry, Karolinska University Hospital, SE 17176, Stockholm, Sweden
2. Department of Biochemistry, Queen's Hospital, Romford, Essex, RM70AG UK
Kallner A, Ayling PA, Khatami Z. Does eGFR improve the diagnostic capability of S-Creatinine concentration results? A retrospective population based study. Int J Med Sci 2008; 5(1):9-17. doi:10.7150/ijms.5.9. Available from http://www.medsci.org/v05p0009.htm
The use of MDRD-eGFR to diagnose Chronic Kidney Disease (CKD) is based on the assumption that the algorithm will minimize the influence of age, gender and ethnicity that is observed in S-Creatinine concentration and thus allow a single cut-off at which further diagnostic and therapeutic actions should be considered. This hypothesis is tested in a retrospective analysis of outpatients (N=93,404) and hospitalised (N=35,572) patients in UK and Sweden, respectively. An algorithm based on the same model as the MDRD-eGFR algorithm was derived from simultaneously measured S-Creatinine concentrations and Iohexol GFR in a subset of 565 patients. The combined uncertainty of using this algorithm was estimated to about 15 % which is about three times that of the S-Creatinine concentration results. The diagnostic performance of S-Creatinine concentration was evaluated using the Iohexol clearance as the reference procedure. It was shown that the diagnostic capacity of MDRD-eGFR, as it stands, has no added value compared to S-Creatinine. The gender and age differences of the S-Creatinine concentrations in the dataset persist after applying the MDRD-eGFR algorithm. Thus, a general use of the MDRD-eGFR does not seem justified. Furthermore the claim that the eGFR is adjusted for body area is misleading; the algorithm does not include any body size marker. It is thus a dangerous marker for guiding drug administration.
Keywords: CKD, Diagnosis, algorithm, outpatients, inpatients