The analysis of risk factors for diabetic kidney disease progression: a single-centre and cross-sectional experiment in Shanghai

Abstract

ObjectiveTo identify the risk factors for diabetic kidney disease (DKD) development, especially the difference between patients with different courses.Patients and methods791 patients were considered to be eligible and were enrolled in the cross-sectional study from Shanghai Tongren Hospital Inpatient Department. 36 variables were initially screened by univariate analysis. The risk factors affecting progression of DKD were determined by logistics regression analysis. Subgroups were grouped according to the course of diabetes disease, and multivariate logistics regression analysis was performed to find out the different risk factors in two subgroups. Finally, the receiver operating characteristics curve is used to verify the result.ResultsThe logistic regression model indicated age (OR=1.020, p=0.017, 95% CI 1.004 to 1.040), systolic blood pressure (OR=1.013, p=0.006, 95% CI 1.004 to 1.022), waist circumference (OR=1.021, p=0.015, 95% CI 1.004 to 1.038), white blood cells (WBC, OR=1.185, p=0.001, 95% CI 1.085 to 1.295) and triglycerides (TG, OR=1.110, p=0.047, 95% CI 1.001 to 1.230) were risk factors for DKD, while free triiodothyronine (fT3, OR=0.711, p=0.011, 95% CI 0.547 to 0.926) was a protective factor for DKD in patients with type 2 diabetes mellitus (T2DM). Subgroup analysis revealed that in patients with a short duration of diabetes (<8 years), WBC (OR=1.306, p<0.001, 95% CI 1.157 to 1.475) and TG (OR=1.188, p=0.033, 95% CI 1.014 to 1.393) were risk factors for DKD,fT3 (OR=0.544, p=0.002, 95% CI 0.367 to 0.804) was a protective factor for DKD; whereas for patients with disease course more than 8 years, age (OR=1.026, Pp=0.012, 95%CI=95% CI[ 1.006– to 1.048]) was identified as the only risk factor for DKD and fT3 (OR=0.036, Pp=0.017, 95%CI=95% CI[ 0.439– to 0.922]) was a protective factor for DKD.ConclusionThe focus of attention should especially be on patients with a prolonged course of T2DM, and those with comorbid hypertension and hypertriglyceridaemia waist phenotype. More potential clinical indexes such as thyroid function and inflammatory indicators might be considered as early warning factors for DKD in T2DM. Women should pay attention to controlling inflammation and TGs, and men should strictly control blood pressure. Avoiding abdominal obesity in both men and women will bring great benefits.

Analysis of independent risk factors for progression of different degrees of diabetic retinopathy as well as non-diabetic retinopathy among type 2 diabetic patients

“…retinal barrier (Liu et al, 2022). Therefore, diabetic patients with high UACR levels should be screened for DR by fundus examination as early as possible.…”

“…Our results showed that UACR levels could not only assess the risk of concurrent DR in patients with type 2 diabetes but also were positively correlated with the prevalence of DR. Both glomerular and retinal vessels of the microcirculation system that share similar physiological features, with hyperglycemia driving the production of glycosylation end products, resulting in functional impairment of the vascular endothelium, enhanced oxidative stress and release of inflammatory mediators, causing disruption of the glomerular filtration membrane barrier and blood retinal barrier ( Liu et al, 2022 ). Therefore, diabetic patients with high UACR levels should be screened for DR by fundus examination as early as possible.…”

Interleukin-6 gene polymorphism (rs1800796) in patient with diabetic nephropathy among Balinese

“…19 The progression of diabetic nephropathy is also influenced by factors such as gender, blood pressure, and HbA1c concentration. 20 This study identified a significant difference between male and female subjects. The proportion of male subject with DN are higher than the female proportion.…”

A Random Forest Algorithm for Assessing Risk Factors Associated With Chronic Kidney Disease: Observational Study

“…Feng et al [ 24 ] used an adjusted LR model to investigate CKD prevalence and related risk factors in 38 megacities across China. Liu et al [ 25 ] and Yang et al [ 26 ] performed cross-sectional studies to analyze risk factors for diabetic nephropathy in Shanghai, whereas a community-based, 7-year-long cohort study from Tianjin used LR to examine the association between the high triglyceride waist phenotype and risk of CKD development [ 27 ]. Yan et al [ 28 ] performed LR analysis to assess the correlation between residual cholesterol levels and CKD, and identify other significant risk factors affecting middle-aged and older individuals residing within a city.…”