Clinicopathological features and risk factors analysis of IgA nephropathy associated with acute kidney injury
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Updated: Mar 23, 2026

A Large Animal Model for Acute Kidney Injury by Temporary Bilateral Renal Artery Occlusion
Published on: February 2, 2021
Ling Zhang1, Jianbo Li1, Shicong Yang2
1a Department of Nephrology , The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health , Guangzhou , PR China ;
Objective:
The aim of this work is to investigate the distinctive clinicopathological characteristics of AKI in Chinese IgAN population and possible risk factors for AKI.
Methods:
We performed a retrospective analysis of 1512 patients with biopsy-proven primary IgAN in the period 2006 through 2011 in The First Affiliated Hospital of Sun Yat-sen University. AKI was defined as 2012 KDIGO (Kidney Diseases: Improving Global Outcomes) criteria, and the patients were divided into AKI group (n = 145) and non-AKI group (n = 1367).
Results:
The prevalence of AKI of the IgAN patients in our center was 9.59% (145/1512). Most AKI patients were older age, male, with higher percentage of smoke, hypertension, hyperlipidemia and preexisting impaired kidney function (Scr > 133 μmol/L), and higher serum creatinine, proteinuria, uric acid, whilst less onset of macroscopic hematuria as well as lower serum albumin and hemoglobin (p < 0.05). The pathological features were much more severe in AKI group as well. Acute tubulointerstitial nephritis was found as the most predominant pathological change of intrinsic AKI in our IgAN population instead of macroscopic hematuria associated acute tubular injury/necrosis. In multivariate logistic regression analysis, we found that older age, male gender, malignant hypertension, proteinuria, cellular crescent, fibrocellular crescent, glomerular sclerosis ≥ 50% were possible risk factors for AKI.
Conclusions:
AKI is commonly seen among IgAN population. The clinicopathological features are much more severe in IgAN patients with AKI. Useful clinicopathological predictors are recognized to improve the identification of IgAN patients who are at high risk for AKI.
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