Does a predictive model combining blood pressure, glycemic and renal markers predict diabetic nephropathy in elderly hypertensive patients with type 2 diabetes?
A nomogram combining routine glycemic, blood pressure, and renal markers provides high predictive accuracy (AUC 0.906) for diabetic nephropathy in elderly patients with T2DM and hypertension.
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.
Guo et al. (Fri,) studied this question.