Predictive model combining blood pressure, glycemic and renal markers for diabetic nephropathy in elderly hypertensive patients with type 2 diabetes

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Abstract

This retrospective cohort study assessed the predictive value of routine clinical indicators for diabetic nephropathy (DN) in elderly patients (≥60 years) with type 2 diabetes mellitus (T2DM) and hypertension. A total of 102 hospitalized patients (January 2022–December 2023) were divided into DN and non-DN groups. Fasting blood glucose (FBG), 2-h postprandial glucose (2hPG), HbA1c, systolic blood pressure (SBP), urinary microalbumin (UMA), and urinary albumin-to-creatinine ratio (UACR) were analyzed using univariate and multivariate logistic regression to identify independent predictors. A nomogram based on these indicators was developed and evaluated by receiver operating characteristic (ROC) analysis. All six factors independently predicted DN (p < 0.05), with 2hPG showing the strongest association (OR = 8.922). The combined model achieved high predictive accuracy (AUC = 0.906), outperforming any single indicator. This model offers a practical tool for early DN risk stratification in elderly T2DM patients with hypertension, supporting individualized prevention and intervention.

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Guo, F., Qin, L., Chen, B., Xu, H., Wang, J., An, R., & Zhang, Q. (2025). Predictive model combining blood pressure, glycemic and renal markers for diabetic nephropathy in elderly hypertensive patients with type 2 diabetes. Clinical and Experimental Hypertension, 47(1). https://doi.org/10.1080/10641963.2025.2564299

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