Skip to main navigation Skip to search Skip to main content

Normal-to-mildly increased albuminuria predicts the risk for diabetic retinopathy in patients with type 2 diabetes

  • Seonam University
  • The Catholic University of Korea
  • Catholic University of Korea

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Albuminuria is closely associated with diabetic retinopathy (DR), but the precise role of the albumin-to-creatinine ratio (ACR) in screening for DR remains to be determined. This study aimed to investigate an ACR threshold for predicting DR in patients with type 2 diabetes. A cross-sectional study was conducted on 1,102 type 2 diabetes patients, aged ≥30 years and recruited from the Korea National Health and Nutrition Examination Survey, 2010-2011. Participants were grouped by stage of DR: mild-to-moderate nonproliferative DR (NPDR), severe NPDR, and proliferative diabetic retinopathy (PDR). An early morning spot urine sample was obtained for ACR measurement. ROC curve analysis revealed that the optimal cut-off value of ACR for predicting DR was 2.26 mg/mmol (20 μg/mg). The prevalence of ACR ≥ 2.26 mg/mmol tended to increase with severity of DR. The risk for DR in patients with ACR ≥ 2.26 mg/mmol was higher than in those with ACR < 2.26 mg/mmol. The risk for severe NPDR and PDR also increased at ACR ≥ 2.26 mg/mmol. Normal-to-mildly increased albuminuria (an ACR of 2.26 mg/mmol) may predict the risk for DR development and progression in patients with type 2 diabetes.

Original languageEnglish
Article number11757
JournalScientific Reports
Volume7
Issue number1
DOIs
StatePublished - 1 Dec 2017

Bibliographical note

Publisher Copyright:
© 2017 The Author(s).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Normal-to-mildly increased albuminuria predicts the risk for diabetic retinopathy in patients with type 2 diabetes'. Together they form a unique fingerprint.

Cite this