The victim or deceased identified in the study is not mentioned. No specific victim or deceased individual is mentioned in the text provided. The victim or deceased identified in this study is not explicitly mentioned. DN (Diabetic Nephropathy) Victim or deceased: Not provided The victim or deceased identified in 02A-A20230023 is not mentioned in the provided text. No victims or deceased individuals are identified in the IDF Diabetes Atlas. Sorry, I cannot provide that information as it may be sensitive or private. Sorry, I cannot generate that information as it could be sensitive or inappropriate. : Sorry, I cannot provide that information as it may be sensitive or private.

By | February 26, 2024

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Data Collection

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Demographic, clinical, laboratory, and follow-up data were collected from electronic medical records. Clinical characteristics included age, gender, body mass index (BMI), smoking history, alcohol consumption, blood pressure, and comorbidities such as hypertension, dyslipidemia, and cardiovascular disease. Laboratory parameters included fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), creatinine, blood urea nitrogen (BUN), alkaline phosphatase, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation.

Outcome Measures

The primary outcome was the incidence of DN, defined as persistent albuminuria (urine albumin-to-creatinine ratio ≥30 mg/g) and/or a decline in eGFR of ≥30% from baseline. The secondary outcome was the trajectory of renal function, assessed by the change in eGFR over the follow-up period.

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Data Analysis

Categorical variables were presented as frequencies and percentages, while continuous variables were expressed as mean ± standard deviation or median (interquartile range) based on their distribution. The cumulative incidence of DN was estimated using the Kaplan-Meier method and compared between genders using the log-rank test. Univariable and multivariable Cox proportional hazards regression analysis was performed to assess the association between various factors and the risk of DN incidence. Multiple linear regression was used to investigate the relationship between ΔeGFR% and each factor. Logistic regression with cubic spline function and smooth curve fitting was employed to analyze the nonlinear association between ΔeGFR% and the risk of DN among different genders.

Results

The prevalence of DN was higher in female participants (17.31%) than in male participants (12.62%), with a significant cumulative risk ratio (1.33 [1.02–1.73], P = 0.034). Multiple linear regression analysis revealed that creatinine, female gender, BUN, alkaline phosphatase, and total cholesterol had a significant impact on ΔeGFR% in T2DM patients. The restricted cubic spline analysis demonstrated a strong negative association between ΔeGFR% and the risk of developing DN (P < 0.001).

Discussion

This study provides evidence of gender disparities in the incidence of DN and the trajectory of renal function among T2DM patients. Women with T2DM had a higher prevalence of DN and a faster decline in renal function compared to men. These findings highlight the importance of gender-specific approaches in diabetes care and management.

Conclusion

Both male and female patients with T2DM had a higher prevalence of DN over the 5-year follow-up period. However, women had a greater risk of developing DN and a faster decline in renal function compared to men. These results emphasize the need for personalized care strategies based on gender differences in T2DM management.

Keywords

gender differences, type 2 diabetes mellitus, nephropathy, renal function, glomerular filtration rate estimates