A Novel Risk Score Model for the Differential Diagnosis of Type 2 Diabetic Nephropathy: A Multicenter Study
Open accessAbstract
Introduction. DN is a common complication of diabetes. However, diabetes combined with renal injury may involve DN or NDKD, with different treatment schemes. The purpose of our study was to determine the independent risk factors of DN and establish a risk score model to help differentiate DN and NDKD, providing a reference for clinical treatment. Methods. A total of 678 T2D patients who had undergone renal biopsy in four affiliated hospitals of Peking University were consecutively enrolled. Patients were assigned to the DN group and NDKD group according to histopathological results. Seventy percent of patients from PKUFH were randomly assigned to the training group, and the remaining 30% were assigned to the internal validation group. Patients from the other three centers were assigned to the external validation group. We used univariate and multivariate logistic regression analyses to identify independent risk factors of DN in the training group and conducted multivariate logistic regression analysis with these independent risk factors in the training group to find regression coefficients “β” to establish a risk score model. Finally, we conducted internal and external validation of the model with ROC curves. Results. Diabetic retinopathy, diabetes duration≥5 years, eGFR<30 ml/min/1.73 m2, 24 h UTP≥3 g, and no hematuria were independent risk factors (P<0.05), and each factor scored 2, 1, 1, 1, and 1. We assigned the patients to a low-risk group (0-1 points), a medium-risk group (2-3 points), and a high-risk group (4-6 points), representing unlikely DN, possibly DN, and a high probability of DN, respectively. The AUCs were 0.860, 0.924, and 0.855 for the training, internal validation, and external validation groups, respectively. Conclusion. The risk score model could help differentiate DN and NDKD in a noninvasive manner, reduce the number of renal biopsies, and provide a reference for clinical treatment.
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A multicenter LR-based study identified diabetes duration ≥5 years, severe proteinuria, eGFR <30 ml/min/1.73 m2, and the presence of DR as independent predictors.
“a multicenter LR-based study identified diabetes duration ≥5 years, severe proteinuria, eGFR <30 ml/min/1.73 m2, and the presence of DR as independent predictors”
From Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics (2026) · cites this paper as [68]
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“For instance, a multicenter LR-based study identified diabetes duration ≥ 5 years, severe proteinuria, eGFR 30 ml/min/1.73 m 2 , and the presence of DR as independent predictors [68].”
Influential
- Authors
- Zhao, Y., Liu, L., Zuo, L., Zhou, X., Wang, S., Gao, H., Yu, F., Zhang, X., Wang, M., Chen, L., Zhang, R., Zhang, F., Bi, S., Bai, Q., Ding, J., Yang, Q., Xin, S., Chai, S., Chen, M., & Zhang, J.
- Affiliations
- Peking University First Hospital (CN)
- Peking University People's Hospital (CN)
- Peking University Third Hospital (CN)
- Peking University International Hospital (CN)
- Department of Nephrology, Peking University People’s Hospital, Beijing, China
- Department of Nephrology, Peking University Third Hospital, Beijing, China
- Peking University (CN)
- Corresponding author
- Zhang, Junqing
- ORCID
- Venue
- Journal of Diabetes Research
- Publisher
- Wiley
- Published
- 2023-12-21
- Volume
- 2023
- Pages
- 1-9
- ISSN
- 2314-6745 (ISSN-L)
- 2314-6753
- PMC
- PMC10754636
- OpenAlex
- W4390080698
- Cited by
- 8
- References
- 24
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 1
- FWCI
- 1.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Diabetes Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- PKU-Baidu Fund (2020BD040, D171100002817001, 2016YFC1305405, 2016YFC1305401, 81970701)
- Beijing Science and Technology Plan Project (2020BD040, D171100002817001, 2016YFC1305405, 2016YFC1305401, 81970701)
- National Basic Research Program of China (2020BD040, D171100002817001, 2016YFC1305405, 2016YFC1305401, 81970701)
- National Natural Science Foundation of China (2020BD040, D171100002817001, 2016YFC1305405, 2016YFC1305401, 81970701)
- Topics
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Renal Diseases and Glomerulopathies
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Keywords
- diabetic nephropathy, non-diabetic kidney disease, type 2 diabetes, risk scoring, differential diagnosis, risk factors, diabetic retinopathy, estimated glomerular filtration rate, urinary protein, diabetes duration, renal biopsy, histopathology
- MeSH terms
- Biopsy, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Diagnosis, Differential, Humans, Retrospective Studies, Risk Factors
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