ArticleBMC nephrology2025
Characterization of diabetic kidney disease in 235 patients: clinical and pathological insights with or without concurrent non-diabetic kidney disease.
Article in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Ultrasound radiomics-based machine learning models for differentiating diabetic kidney disease from non-diabetic kidney disease in type 2 diabetes.BMC nephrology · 2026Article
- IgA Nephropathy: Epidemiology, Outcomes, and Insights for Primary Glomerulonephritides.Journal of clinical medicine · 2026Review
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6 authors.
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Abstract
backgroundThis study aimed to explore the clinical and pathological features of patients with diabetic kidney disease (DKD), with and without non-diabetic kidney disease (NDKD), through a retrospective analysis. The objective was to provide clinical insights for accurate identification.
methodsA retrospective analysis of 235 patients admitted to the Department of Nephrology at Hangzhou Hospital of Traditional Chinese Medicine was conducted between July 2014 and December 2022. These patients underwent renal biopsy and received a pathology-based diagnosis of DKD. They were categorized into the DKD alone group (93 cases) and the DKD + NDKD group (142 cases).
resultsIn the DKD alone group, gender distribution was even, with ages mainly between 50 and 59 years, and a disease duration of less than 5 years, primarily presenting nodular diabetic glomerulosclerosis. In contrast, the DKD + NDKD group had a higher male incidence, a wider age range, longer disease duration, and prevalent diffuse diabetic glomerulosclerosis. Acute and chronic tubulointerstitial lesions and IgA nephropathy were the predominant types of combined NDKD, accounting for 40.14% and 35.21%, respectively. Clinical correlation analysis revealed associations between glomerular grading, tubulointerstitial lesions, renal arteriolar vitelliform lesions, renal vascular atherosclerosis, and clinical parameters such as 24-hour urine protein, hemoglobin, and urinary specific gravity. Multifactorial logistic regression analysis identified independent factors affecting DKD + NDKD, including body mass index, blood creatinine level, microscopic erythrocyte grade, urinary immunoglobulin G/creatinine ratio, and serum immunoglobulin A.
conclusionThe research underscores distinctions in age, gender distribution, disease duration, and renal pathology between DKD alone and DKD + NDKD groups. Additionally, significant discriminative factors including BMI, blood creatinine level, microscopic erythrocyte grade, UIgG/urine creatinine ratio, and serum IgA levels help differentiate DKD from NDKD, thereby enabling personalized treatment approaches. Furthermore, the study highlights the role of RASi as the most commonly used drug in the treatment of both DKD and NDKD, with emerging drugs such as SGLT2 inhibitors showing promising renal protective effects.
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