4.6 Article

Dividing CKD stage 3 into G3a and G3b could better predict the prognosis of IgA nephropathy

Journal

PLOS ONE
Volume 12, Issue 4, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0175828

Keywords

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Funding

  1. National Natural Science Foundation of China [81570645/H0509]
  2. Major Project of Program for Medical Science and Technology Development of Henan Province [201501018]
  3. Youth Innovation Fund of the First Affiliated Hospital of Zhengzhou University

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Chronic kidney disease (CKD) stage 3 was divided into stage G3a and stage G3b in the 2013 Kidney Disease Improving Global Outcomes guidelines. Whether it is appropriate to regard 45 mL/min/per 1.73 m(2) as the threshold value of G3a/G3b staging and whether dividing CKD stage 3 into G3a/G3b plays a useful role in assessing the prognosis of patients with IgA nephropathy (IgAN) remain unknown. Three hundred and ninety patients from the First Affiliated Hospital of Zhengzhou University and Peking University First Hospital diagnosed with IgAN in CKD stage 3 were enrolled and successfully followed up. Cox proportional hazards model was used to analyze hazard ratios of reaching the composite endpoints (doubling of serum creatinine, end-stage renal disease: estimated glomerular filtration rate (eGFR) < 15 ml/min/per 1.73 m(2) or renal replacement therapy, or death) for patients with different eGFR and risk factors affecting composite endpoints. The Kaplan-Meier method was used to calculate the cumulative renal survival rate of patients. When eGFR was lower than 45 ml/min/per 1.73 m(2), the hazard ratio increased sharply for patients in CKD stage 3 who reached the composite endpoints. Renal injury and prognosis were significantly different between patients in the G3a and G3b groups. Stage G3b was a major risk factor affecting prognosis. A threshold value of 45 ml/min/per 1.73 m(2) appears appropriate to assess the prognosis of IgAN patients with CKD stage 3. Dividing IgAN patients with CKD stage 3 into G3a and G3b is very useful to help understand disease conditions and for predicting the risk for disease progression.

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