Prevalence of Renal Insufficiency in Patients With Type 2 Diabetes : A Retrospective Study.

Overview

the prevalence of renal insufficiency in patients with type 2 diabetes (T2D) visiting a large diabetes care center in Southern India. The prevalence estimates reported previously have shown variability to a large extent due to differences in selection criteria, cut-off values for diagnosis of renal insufficiency and the type of population selected.

This was a retrospective cross-sectional analysis of data collected during 2022 and 2023 in patients with T2D and persistent renal insufficiency for at least a period of 3 months. The data was extracted from the electronic medical records of Dr.A. Ramachandran's Diabetes Hospitals, Chennai. We excluded patients with other forms of diabetes, renal complications (end stage renal disease, pylonephritis) and with missing data. Patient records with the following data were included in the analysis. Anthropometry (height, weight and body mass index), systolic and diastolic blood pressure (measured thrice in a time-gap of 5 minutes each), laboratory parameters (fasting blood glucose, postprandial blood glucose, HbA1c, lipid profile (total cholesterol, triglycerides, HDL, LDL and VLDL) and renal function tests (serum creatinine, spot urine albumin to creatinine ratio)). Renal insufficiency was defined as an eGFR of \<60ml/min/1.73m2. calculated using the CKD EPI equation3. Presence of albuminuria was classified as microalbuminuria (UACR 30-300 mg/g) or macroalbuminuria (UACR \> 300 mg/g). The cut-off values for assessing renal insufficiency were based on the Kidney Disease Outcomes Quality Initiative (KDOQI) recommendations 3. Data was presented as mean ± SD for continuous variables and as n (%) for categorical variables. Intergroup differences between sub-categories of renal insufficiency were done using chi-square tests or Fisher's exact tests for categorical variables and student t-test or ANOVA for continuous variables. To study the factors associated with renal insufficiency a logistic regression analysis was performed. The dependent variable was presence of renal insufficiency defined as an eGFR of \<60ml/min/1.73m2 and or albuminuria ≥30 mg/g of creatinine. Independent variables included in the equation were age, duration of diabetes, gender, BMI, HbA1c, presence of hypertension, triglycerides, total cholesterol and HDLc. A p value of \<0.05 was considered statistically significant.

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Outcomes