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Serum cystatin C in early prediction of risk of chronic kidney disease progression in type 2 diabetes (LB727)
Author(s) -
Wijayatunga Nadeeja,
Perera Pradeep,
Wanigasuriya Kameni,
Wijeysiri Ananda,
MoustaidMoussa Naima,
Peiris Hemantha
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.lb727
Subject(s) - medicine , kidney disease , cystatin c , creatinine , renal function , diabetic nephropathy , diabetes mellitus , nephropathy , type 2 diabetes mellitus , urology , gastroenterology , endocrinology
Serum cystatin C (CysC) is superior to serum creatinine (SCr) in diagnosing mild diabetic nephropathy. We hypothesized that, CysC can predict the risk of CKD progression at an early stage in T2DM. Our objective was to compare levels of CysC, SCr and eGFR in T2DM patients in no/low risk with moderate risk of CKD progression according to Kidney Disease Initiative Global Outcomes (KDIGO) guideline’s CKD risk stratification. Sixty one non‐obese, T2DM patients aged 30‐60 years, suspected of mild to moderate CKD were recruited. Creatinine was measured using Jaffe method in serum and urine. Serum CysC and urine albumin were measured using immunoturbidimetry. eGFRs were calculated using Modification of Diet in Renal Disease equation (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) equations. Moreover, Albumin to Creatinine Ratio (ACR) was calculated. Patients were categorized, to CKD risks categories using eGFR CKD‐EPI based on SCr and ACR. Our results demonstrate that patients in the moderately increased risk group had significantly higher CysC than those in the no/low risk group. However, SCr, eGFR based on CKD EPI and MDRD equations were not significantly different between the two groups. Thus, CysC is valuable in detecting moderately increased risk in CKD progression in T2DM patients than SCr and SCr based eGFR. These observations may be useful for early prediction of CKD progression and clinical management of patients with early diabetic nephropathy. Grant Funding Source : Research award from the University of Sri Jayewardenepura (Grant number : ASP/06/R/MED/2011/21), and Texas Tech University