Risk Factor For Diabetic Kidney Disease Research Articles

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model's performance. The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model's performance was greatly improved.

Association between the triglyceride glucose index, triglyceride-glucose body mass index and diabetic kidney disease in adults with newly diagnosed type 2 diabetes.

The triglyceride glucose (TyG) index has been proved to be a reliable marker of diabetic kidney disease (DKD). We further investigated the association between TyG index, and its derivative, triglyceride-glucose body mass index (TyG-BMI), and the risk of DKD among adults with newly diagnosed type 2 diabetes (T2D). This cross-sectional study was conducted among patients with newly diagnosed T2D. We assessed the correlation between TyG index, TyG-BMI, and the risk of DKD using logistic regression analysis, restricted cubic spline analysis, trend tests, receiver operating characteristic curve, and subgroup analyses. Among the 924 included patients, 199 (21.5%) had DKD. Logistic regression revealed that TyG index (odds ratio [OR] 1.232, 95% confidence interval [CI] 1.064-1.428, p = 0.005) and TyG-BMI (OR 1.003, 95% CI 1.000-1.006, p = 0.021) were risk factors for DKD. The trend test demonstrated a dose-response association between TyG index (p for trend = 0.004), TyG-BMI (p for trend = 0.035), and the risk of DKD. Restricted cubic spline analysis indicated a nonlinear correlation between TyG index and the risk of DKD, with an increase in the risk of DKD when the TyG index was greater than 9.68 (p for nonlinearity = 0.014). In contrast, TyG-BMI and the risk of DKD exhibited a linear dose-response relationship, with an increase in the risk of DKD when the TyG-BMI was greater than 243 (p for nonlinearity = 0.034). According to the receiver operating characteristic curve, the optimal cutoff values for TyG index and TyG-BMI were 10.08 and 221.5, respectively. Among newly diagnosed T2D patients, the risk of DKD increases with the increase of TyG index and TyG-BMI, with their respective cut-off values being 9.68 and 243. Both TyG index and TyG-BMI have poor diagnostic value for the risk of DKD.

Low Levels of Metrnl are Linked to the Deterioration of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Metrnl is a secreted protein that plays an important role in kidney disease. The aim of this study was to investigate DKD-related factors and the correlation between serum Metrnl levels and the severity of DKD. Ninety-six type 2 diabetes mellitus (T2DM) patients and 45 DKD patients were included in the study. A range of parameters were measured simultaneously, including waist-to-hip ratio (WHR), body mass index (BMI), urinary albumin/creatinine ratio (UACR), monocyte-lymphocyte ratio (MLR), albumin/globulin (A/G), liver and kidney function, blood lipid profile, islet function, and others. Subsequently, the related factors and predictive significance of DKD were identified. The correlation between the relevant factors of DKD and serum Metrnl levels with DKD was evaluated. The duration of the disease (OR: 1.12, 95% CI: 1.01-1.24, P=0.031), hypertension (OR: 4.86, 95% CI: 1.16-20.49, P=0.031), fasting blood glucose (OR: 1.23, 95% CI: 1.03-1.48, P=0.025), WHR (OR: 2.53, 95% CI: 1.03-6.22, P=0.044), and MLR (OR: 1.91, 95% CI: 1.18-3.08, P=0.008) are independent risk factors for DKD (P < 0.05). Conversely, A/G (OR: 0.13, 95% CI: 0.02-0.76, P=0.024) and Metrnl (OR: 0.99, 95% CI: 0.98-1.00, P=0.001) have been identified as protective factors against DKD. Furthermore, the level of Metrnl was negatively correlated with the severity of DKD (rs=-0.447, P<0.001). The area under receiver operating characteristic (ROC) curves for the diagnostic accuracy of Metrnl for DKD is 0.765 (95% CI: 0.686-0.844). The duration of the disease, hypertension, fasting blood glucose, WHR, and MLR are major risk factors for DKD. Metrnl and A/G are protective factors for DKD. Serum Metrnl concentrations are inversely correlated with DKD severity.

Association of Systemic Immune-Inflammation Index and Systemic Inflammation Response Index with Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus.

To evaluate the association of the systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI) with the clinical and pathological features and progression of diabetic kidney disease (DKD). We analyzed 303 patients with type 2 diabetes mellitus (T2DM), classifying them into distinct groups: T2DM, early DKD (EDKD), and clinical DKD (Cli-DKD). Variations in SII and SIRI levels across these groups and their association with renal function were assessed. Logistic regression analysis was used to identify independent risk factors for DKD. Additionally, in 43 patients with biopsy-confirmed DKD, we analyzed the relationship between SII, SIRI, and pathological changes. Kaplan-Meier survival analysis and the Cox proportional hazards model were used to assess the influence of SII and SIRI levels on outcomes in patients with DKD. SII and SIRI were significantly higher in the Cli-DKD group than in the T2DM and EDKD groups, and were positively correlated with the urinary albumin-creatinine ratio and negatively correlated with estimated glomerular filtration rate. Notably, SIRI was identified as an independent risk factor for DKD development. Additionally, a lower SII score was associated with a higher cumulative survival rate. This study demonstrates an association between SII, SIRI, and renal function in patients with T2DM. A high SIRI was an independent risk factor for DKD, while an elevated SII was associated with an increased risk of kidney disease progression in biopsy-confirmed DKD cases. Our findings underscore the potential implications of utilizing SII and SIRI as cost-effective and readily available inflammatory indicators for monitoring DKD in primary care settings.

Plasma thrombin-activatable fibrinolysis inhibitor and the 1040C/T polymorphism are risk factors for diabetic kidney disease in Chinese patients with type 2 diabetes.

Inflammatory and hemostatic disorders in diabetic microangiopathy (DMA) can be linked to thrombin-activatable fibrinolysis inhibitor (TAFI) and its own gene polymorphisms. Thus, the study aimed to investigate the associations of plasma TAFI and gene polymorphisms with DMA in Chinese patients with type 2 diabetes (T2D). Plasma TAFI of 223 patients with T2D was measured, and the genotypes and alleles of the 1040C/T, 438G/A, and 505G/A polymorphisms of the TAFI gene were analyzed. A ROC curve was constructed to evaluate the identifying power of TAFI between patients with T2D and DMA, and logistic regression analysis was used to observe the correlation of plasma TAFI and gene polymorphisms with the risk for DMA. Plasma TAFI was higher in patients with DMA than in patients with only T2D (p < 0.05). TAFI exhibited the largest area under ROC in identifying diabetic kidney disease (DKD) from only T2D (0.763, 95% CI [0.674-0.853], p < 0.01), and adjusted multivariate analysis showed a high odds ratio (OR: 15.72, 95% CI [4.573-53.987], p < 0.001) for DKD. Higher frequencies of the CT genotype and T allele of the 1040C/T polymorphism were found in DKD compared with only T2D (respectively p < 0.05), and the CT genotype exhibited a high OR (1.623, 95% CI [1.173-2.710], p < 0.05) for DKD. DKD patients with the CT genotype had higher plasma TAFI levels, while T2D and DKD patients with CC/TT genotypes had lower plasma TAFI levels. Plasma TAFI and the CT genotype and T allele of the 1040C/T polymorphism are independent risk factors for DKD in Chinese T2D patients.

Blood Lipid Indicators and Different Clinical Classifications of Dyslipidemia and Diabetic Kidney Disease: Correlation and Predictive Value

To explore the relationship between blood lipid indicators and different clinical classifications of dyslipidemia and diabetic kidney disease (DKD) and to compare the value of different clinical classifications of dyslipidemia for predicting DKD. Continuously enrollment of subjects was conducted at the First Affiliated Hospital of Chongqing Medical University and the Yongchuan Hospital of Chongqing Medical University between October 2020 and October 2021. A total of 356 type 2 diabetes mellitus (T2DM) patients admitted to the two hospitals were enrolled. They were divided into DKD group ( n=126) and simple T2DM group ( n=230) according to whether their T2DM was combined with DKD. In addition, 250 healthy individuals undergoing physical examination during the same period were enrolled for the control group. The blood pressure, blood lipid, blood glucose, and the kidney function indicators of the three groups were measured. The effects of different classifications of dyslipidemia on DKD were analyzed with unconditional logistic regression models, the receiver operating characteristic (ROC) curve was constructed, the area under the curve ( AUC) of ROC was calculated, and the value of different classifications of dyslipidemia for predicting DKD was analyzed. The diastolic blood pressure (DBP), systolic blood pressure (SBP), total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), uric acid (UA), and glycosylated hemoglobin A1c (HbA1c) of the DKD group and the simple T2DM group were significantly higher than those of the control group, while the high-density lipoprotein cholesterol (HDL-C) levels of the DKD group and the simple T2DM group were lower than that of the control group (all P<0.05). The disease course of T2DM, DBP, SBP, TC, TG, Scr, UA and HbA1c of the DKD group were significantly higher than those of the T2DM group (all P<0.05). After adjusting for the effects of T2DM disease course, DBP, SBP, Scr, UA and HbA1c, the results showed that TC ( OR=1.426, 95% CI: 1.088-1.868) and TG ( OR=1.404, 95% CI: 1.075-1.833) were independent risk factors for DKD, and that hypercholesterolemia ( OR=1.817, 95% CI: 1.040-3.177) and mixed hyperlipidemia ( OR=2.148, 95% CI: 1.110-4.159) were independent risk factors for DKD (all P<0.05). The AUC (95% CI) of hypercholesterolemia was 0.789 (0.729-0.871). The AUC (95% CI) of mixed hyperlipidemia was 0.671 (0.579-0.760). Hypercholesterolemia showed better predictive value for the diagnosis and prediction of DKD. Among the blood lipid indicators, TC and TG are independent risk factors of DKD. In the clinical classifications of dyslipidemia, hypercholesterolemia and mixed hyperlipidemia are independent risk factors of DKD. Hypercholesterolemia can be used as a predictor to screen for DKD among T2DM patients and is well suited for extensive application in outpatient screening.

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan.

To investigate the association of five obesity indices and the variability of these indices with diabetic kidney disease (DKD) in patients with type 2 diabetes and compare the predictive validity of these markers for the risk of DKD in this large longitudinal cohort study. A total of 2659 patients with type 2 diabetes who did not have DKD were enrolled between 2006 and 2019 at Lee's United Clinic in Taiwan. Data were collected for each subject, including demographic data, personal medical history, clinical parameters and calculated Body mass index (BMI), visceral adiposity index (VAI), lipid accumulation product (LAP), body roundness index (BRI) and variability of five obesity indices. Cox regression analysis was performed to determine the relationship between different obesity indicators and DKD risk. Cox's proportional hazards model was evaluated the predictive effect of obesity indices on DKD. The risk of developing DKD increased with an increase in the BRI, LAP, VAI, WC and BMI (all P trend<0.05), and the variability of VAI was significantly associated with DKD [HR=1.132, 95% CI (1.001, 1.281)] after adjusting for corresponding variables. BRI had the strongest predictive effect on DKD. BRI had the best predictive performance, with AUC of 0.807, 0.663 and 0.673 at 1, 3 and 5 years, respectively. Cox regression analysis of risk factors for DKD in patients stratified by BRI quartiles showed that patients in the Q4 group had the highest risk of developing DKD [HR=1.356, 95% CI (1.131, 1.626)]. BMI, WC, VAI, LAP, BRI and VAI variability were associated with a significant increase in the risk of DKD events, and BRI was superior and alternative obesity index for predicting DKD.

Predictive Effects of FT3/FT4 on Diabetic Kidney Disease: An Exploratory Study on Hospitalized Euthyroid Patients with T2DM in China.

This study aims to explore the correlation between the free-triiodothyronine (FT3)-to-free-thyroxine (FT4) ratio (FT3/FT4) and diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). This study retrospectively analyzed 1729 patients with T2DM hospitalized in the Department of Endocrinology, Peking University International Hospital, from January 2017 to August 2021, including 1075 males and 654 females. In accordance with the FT3/FT4, the patients were divided into three groups. (1) The levels of glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG) and postprandial blood glucose (PBG) among the three groups were significantly different, with the low FT3/FT4 group having the highest HbA1c, FBG and PBG among the three groups (F = 39.39, p < 0.01; F = 27.04, p < 0.01; F = 5.76, p = 0.03; respectively). (2) The proportion of DKD is the highest in the low FT3/FT4 group and the lowest in the high FT3/FT4 group (χ2 = 25.83, p < 0.01). (3) Logistic regression showed that low FT3/FT4 were independent risk factors for DKD (OR = 2.36, 95 CI% 1.63, 3.43; p = 0.01). A decrease in the FT3/FT4 is an independent predictor of DKD occurrence in patients with T2DM.

Changes in urinary exosomal protein CALM1 may serve as an early noninvasive biomarker for diagnosing diabetic kidney disease

BackgroundThe risk of the development and progression of diabetic kidney disease (DKD) was increased by abnormal calcium release. However, it is still unknown whether calcium signal pathway-related proteins are changed in urinary exosomes. This study aims to explore the changes in urinary exosomal proteins, which may provide novel biomarkers for diagnosing DKD. MethodsUrinary exosomes were isolated from 132 participants by size exclusion chromatography method and 72 participants were tested by LC-MS/MS (Discovery phase). Correlation and multivariate logistics analysis were applied to evaluate selected urinary proteins. Western blot and ELISA were used to validate the selected protein (Validation phase: n = 60). The diagnostic performance of the selected biomarker was evaluated by receiver operating characteristic curve analyses between the discovery and validation phases. ResultsSixteen calcium signal pathway-related proteins were identified, however, only Calmodulin-1(CALM1) was continuously increased. Different expression of CALM1 was found in patients with different level of estimated glomerular filtration rate (eGFR) in two cohorts. The level of CALM1 was correlated with eGFR and serum creatinine levels in two cohorts. Multivariate analysis revealed that serum albumin (ALB) levels and CALM1 were independent risk factors for DKD. A diagnostic model based on CALM1 and serum ALB levels that could significantly distinguish DKD was established and validated. ConclusionsSignificant changes in calcium signal pathway-related urinary exosomal proteins were observed. The CALM1 may serve as an early noninvasive biomarker for diagnosing DKD.

427-P: Comparison of Diabetic Kidney Disease Risk Factors between Normoalbuminuric Reduced and Albuminuric Preserved Kidney Function Groups

The prevalence of normoalbuminuric diabetic kidney disease (NA-DKD) in the U.S. has increased over the past 20 years, and it is higher among patients with good glycemic control. However, the factors associated with NA-DKD remained to be elucidated. Studies have compared NA-DKD with albuminuric DKD (ALB-DKD: ACR ≥ 30 mg/g and eGFR &amp;lt; 60 mL/min/1.73m2); however, ALB-DKD may include cases who have progressed from NA-DKD. Therefore, we aimed to compare DKD risk factors between patients with NA-DKD and those with only albuminuria (only-ALB) status. Among NHANES (1999-2016) adult participants with diagnosed diabetes, we compared DKD risk factors (including demographics) between patients with NA-DKD (ACR &amp;lt; 30 mg/g and eGFR &amp;lt; 60 mL/min/1.73m2) and only-ALB (ACR ≥ 30 mg/g and eGFR ≥ 60 mL/min/1.73m2) using univariate and multivariable analyses. In our diabetes cohort, there were 827 (17.9%) NA-DKD and 923 (16.6%) only-ALB cases. In the multivariable model, diabetes diagnosis age, total cholesterol, HOMA-IR, CRP, and serum uric acid were not significantly associated with albuminuric status, while blood pressure control was the strongest predictor followed by gender [Table]. Future studies should characterize pathways separate from hyperglycemia and elevated BP which contribute to NA-DKD. Disclosure M.Mosslemi: None. T.Costacou: None.

The Triglyceride Glucose (TyG) Index as a Sensible Marker for Identifying Insulin Resistance and Predicting Diabetic Kidney Disease.

BACKGROUND Patients with insulin-resistant diabetes have the highest risk of kidney disease. The triglyceride glucose (TyG) index is considered a reliable and simple marker of insulin resistance. We studied the relationship between the TyG index, diabetic kidney disease (DKD), and related metabolic disorders in patients with type 2 diabetes. MATERIAL AND METHODS This retrospective study included a consecutive case series from January 2021 to October 2022 in the Department of Endocrinology at Hebei Yiling Hospital. In total, 673 patients with type 2 diabetes met the inclusion criteria. The TyG index was calculated by napierian logarithmic (ln) (fasting triglyceride×fasting glucose /2). Patient demographic and clinical indicators were obtained from medical records, and statistical analysis was conducted using SPSS version 23. RESULTS The TyG index was significantly related to metabolic indicators (low-density lipoprotein, high-density lipoprotein, alanine aminotransferase, plasma albumin, serum uric acid, triglyceride, and fasting glucose) and urine albumin (P<0.01) but not with serum creatinine and estimated glomerular filtration rate. In multiple regression analysis, an increase in the TyG index was revealed to be an independent risk factor for DKD (OR: 1.699, P<0.001). CONCLUSIONS The TyG index was independently related to DKD and related metabolic disorders; therefore, the TyG index can be used as an early sensitive target for clinical guidance in the treatment of DKD with insulin resistance.

Genetic and epigenetic background of diabetic kidney disease.

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

Diagnostic value of serum cathepsin S in type 2 diabetic kidney disease.

Identification of risk factors that have causal effects on the occurrence of diabetic kidney disease (DKD), is of great significance in early screening and intervening for DKD, and in delaying the progression of DKD to end-stage renal disease. Cathepsin S (Cat-S), a novel non-invasive diagnostic marker, mediates vascular endothelial dysfunction. The diagnostic value of Cat-S for DKD has rarely been reported in clinical studies. To analyze whether Cat-S is a risk factor for DKD and evaluate the diagnostic value of serum Cat-S for DKD. Forty-three healthy subjects and 200 type 2 diabetes mellitus (T2DM) patients were enrolled. T2DM patients were divided into subgroups according to various criteria. Enzyme-linked immunosorbent assay was used to detect serum Cat-S levels among different subgroups. Spearman correlation analysis was used to analyze correlations between serum Cat-S and clinical indicators. Multivariate logistic regression analysis was performed to analyze risk factors for the occurrence of DKD and decreased renal function in T2DM patients. Spearman analysis showed that serum Cat-S level was positively correlated with urine albumin creatinine ratio (r=0.76, P<0.05) and negatively correlated with estimated glomerular filtration rate (r=-0.54, P<0.01). Logistic regression analysis showed that increased serum Cat-S and cystatin C(CysC) were independent risk factors for DKD and decreased renal function in T2DM patients (P<0.05). The area under the receiver operating characteristic (ROC) curve was 0.900 of serum Cat-S for diagnosing DKD, and when the best cut-off value was 827.42 pg/mL the sensitivity and specificity were 71.6% and 98.8%, respectively. Thus, serum Cat-S was better than CysC for diagnosing DKD (for CysC, the area under the ROC curve was 0.791, and when the cut-off value was 1.16 mg/L the sensitivity and specificity of CysC were 47.4% and 98.8%, respectively). Increased serum Cat-S were associated with the progression of albuminuria and decreased renal function in T2DM patients. The diagnostic value of serum Cat-S was better than that of CysC for DKD. Monitoring of serum Cat-S levels could be helpful for early screening DKD and assessing the severity of DKD and could provide a new strategy for diagnosing DKD.

Association of Obesity Indices with Diabetic Kidney Disease and Diabetic Retinopathy in Type 2 Diabetes: A Real-World Study.

Diabetic microvascular complications mainly include diabetic kidney disease (DKD) and diabetic retinopathy (DR). Obesity was recognized as a risk factor for DKD, while the reported relationship between obesity and DR was inconsistent. Moreover, whether the associations can be attributed to C-peptide levels is unknown. Data from 1142 sequential inpatients with T2DM at Xiangyang Central Hospital between June 2019 and March 2022 were extracted retrospectively from the electronic medical record system. The associations between four obesity indices (body mass index (BMI), waist-hip circumference ratio (WHR), visceral fat tissue area (VFA), and subcutaneous fat tissue area (SFA)) and DKD and DR were evaluated. Whether the associations can be attributed to C-peptide levels was also explored. Obesity was a risk factor for DKD after adjusting for sex, HbA1c, TG, TC, HDL, LDL, smoking history, education, duration of diabetes, and insulin use (obesity indices: BMI (OR 1.050: 95% CI: 1.008-1.094; P = 0.020); WHR (OR 10.97; 95% CI: 1.250-92.267; P = 0.031); VFA (OR 1.005; 95% CI: 1.001-1.008; P = 0.008)), but it became insignificant after further adjusting for fasting C-peptide. The associations between BMI, WHR, VFA, and DKD might be U-shaped. Obesity and FCP tended to protect against DR; however, they became insignificant after adjusting for multiple potential confounders. C2/C0 (the ratio of the postprandial serum C-peptide to fasting C-peptide) was a protective factor for both DKD (OR 0.894, 95% CI: 0.833-0.959, P < 0.05) and DR (OR 0.851, 95% CI: 0.787-0.919; P < 0.05). Obesity was a risk factor for DKD, and the effect may be attributable to C-peptide, which represents insulin resistance. The protective effect of obesity or C-peptide on DR was not independent and could be confounded by multiple factors. Higher C2/C0 was associated with both decreased DKD and DR.

Diagnostic Value of the Combined Measurement of Serum HCY and NRG4 in Type 2 Diabetes Mellitus with Early Complicating Diabetic Nephropathy

This study aimed to investigate the value of combined detection of HCY and NRG4 in the diagnosis of early diabetic kidney disease (DKD) and to explore the association between the ratio of HCY/NRG4 and DKD. A total of 140 diabetic patients and 43 healthy people were prospectively enrolled. The plasma HCY level, NRG4 level and HCY/NRG4 of them were measured to compare their differences and analyze the correlation with DKD. The independent influencing factors of patients with DKD were screened, and the nomograph of DKD occurrence was constructed. The levels of HCY and HCY/NRG4 in diabetic patients were significantly increased, while the level of NRG4 was significantly decreased (p < 0.01). The AUCs of HCY/NRG4 predicted for DKD were 0.961. HCY/NRG4 and the course of DM were independent risk factors for DKD. A predictive nomograph of DKD was constructed, and decision curve analysis (DCA) showed good clinical application value. HCY/NRG4 was positively correlated with Scr, UACR, TG, UA, BUN, TCHOL and LDL and negatively correlated with eGFR and HDL (p < 0.05). The level of HCY and NRG4 is closely related to the severity of DM, and combined detection of HCY/NRG4 can identify patients with DKD at an early stage.

Association between hemoglobin glycation index and diabetic kidney disease in type 2 diabetes mellitus in China: A cross- sectional inpatient study.

To investigate the association between Hemoglobin Glycation Index (HGI) and Diabetic Kidney Disease (DKD) in Chinese type 2 diabetic individuals and to construct a risk score based on HGI to predict a person's risk of DKD. We retrospectively analyzed 1622 patients with type 2 diabetes mellitus (T2DM). HGI was obtained by calculating the fasting plasma glucose (FPG) level into the formula, and they were grouped into low HGI group (L-HGI), medium HGI group (H-HGI) and high HGI group (H-HGI) according to tri-sectional quantile of HGI. The occurrence of DKD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of DKD in patients with T2DM. A total of 1622 patients with T2DM were enrolled in the study. Among them, 390 cases were DKD. The prevalence of DKD among the three groups was 16.6%, 24.2% and 31.3%. The difference was statistically significant (P = 0.000). There were significant differences in age (P=0.033), T2DM duration (P=0.005), systolic blood pressure (SBP) (P=0.003), glycosylated hemoglobin (HbA1c) (P=0.000), FPG (P=0.032), 2-hour postprandial plasma glucose (2h-PPG) (P=0.000), fasting C-peptide FCP (P=0.000), 2-hour postprandial C-peptide (2h-CP) (P=0.000), total cholesterol (TC) (P=0.003), low density lipoprotein cholesterol (LDL-C) (P=0.000), serum creatinine (sCr) (P=0.001), estimated glomerular filtration rate (eGFR) (P=0.000) among the three groups. Mantel-Haenszel chi-square test showed that there was a linear relationship between HGI and DKD (x2=177.469, p < 0.001). Pearson correlation analysis showed that with the increase of HGI level the prevalence of DKD was increasing (R= 0.445, P=0.000). It was indicated by univariate logistic regression analysis that individuals in H-HGI was more likely to develop DKD (OR: 2.283, 95% CI: 1.708~ 3.052) when compared with L-HGI. Adjusted to multiple factors, this trend still remained significant (OR: 2.660, 95% CI: 1.935~ 3.657). The combined DKD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.702. High HGI is associated with an increased risk of DKD. DKD risk score may be used as one of the risk predictors of DKD in type 2 diabetic population.

Sex-Specific Computed Tomography Abdominal Fat and Skeletal Muscle Characteristics in Type 2 Diabetic Retinopathy Patients With/Without Comorbid Diabetic Kidney Disease

To investigate differences in sex-specific computed tomography abdominal fat and skeletal muscle (SM) characteristics between type 2 diabetic retinopathy (DR) patients with and without diabetic kidney disease (DKD). This retrospective study included type 2 diabetes mellitus DR patients with/without DKD between January 2019 and July 2021. Visceral adipose tissue (VAT), subcutaneous adipose tissue, perirenal adipose tissue (PAT), intramuscular adipose tissue, and SM areas were measured. Univariate and multivariate logistic regression analyses were used to analyze risk factors for DKD. Correlation and multiple linear regression analyses were used to clarify the association between computed tomography abdominal fat, SM characteristics, and cystatin C. Two hundred and forty-one patients were enrolled and divided into DR with DKD group (n=142) and DR without DKD group (n=99). In men, hypertension (OR: 5.21; 95%CI: 1.93-14.05; p=0.001), diastolic pressure (OR: 1.07; 95%CI: 1.01-1.12; p=0.011), hemoglobin (OR: 0.94; 95%CI: 0.92-0.97; p < 0.001) and PAT attenuation value (OR: 1.09; 95%CI: 1.01-1.17; p=0.026) were independent risk factors for DKD progression in DR patients, while the VAT index (VATI) (OR: 1.03; 95%CI: 1.01-1.05; p=0.014) was an independent risk factor for female patients. Multiple linear regression analysis revealed significant correlations between hypertension (β=0.22, p=0.002) and hemoglobin (β=-0.53, p < 0.001) with cystatin C in men, and a significant correlation between VATI and cystatin C (β=0.35, p=0.037) in women after adjustment for confounders. Female DR patients with elevated VAT level may suffer from a higher risk of DKD than that in male patients.

Lactic acidosis associated with metformin in patients with diabetic kidney disease; a mini-review

Background: Diabetes mellitus is a metabolite disorder with parameters of high blood sugar levels. In the management of diabetes can be used the drug metformin is the gold of choice to achieve a therapeutic effect and rarely causes side effects of the drug, but it still has debate view. However, if used in excessive doses for patients with kidney disease, it will be contraindicated with side effects such as lactic acidosis. Objective: This study aims to evaluate the side effect of metformin for diabetic kidney disease (DKD) patients. Methods: This study used the Narrative Review Method that was obtained from 2011 to 2021, in the English language from PubMed, Google Scholar, and Cochrane Library. Results: Metformin is at the forefront of the treatment of type 2 diabetes mellitus (DM2). Metformin is likely to have lactic acidosis-related adverse effects in chronic kidney disease (CKD) patients, such as increased arterial lactate. Lactic acidosis is defined as an increase in arterial lactate with an indicator of more than five mmol/L and an arterial blood pH of less than 7.35. Metformin-induced lactate levels are below the parameters. DKD risk factors can be conceptually classified as several susceptibility factors, initiation factors, and developmental factors. The two most prominent risk factors are hyperglycemia and hypertension. Conclusion: Metformin can increase lactate levels in CKD patients but is still below the parameters of lactic acidosis. This study may have some weaknesses and requires further prospective research to validate the results.

Association of Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio with Diabetic Kidney Disease in Chinese Patients with Type 2 Diabetes: A Cross-Sectional Study.

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been extensively studied in a variety of diseases. However, research on their relationship with diabetic kidney disease (DKD) is limited. The aim of our study was to investigate the association between these two indicators and renal function in Chinese patients with type 2 diabetes and assess whether they can serve as predictors of DKD. This cross-sectional study enrolled 655 Chinese patients with type 2 diabetes. Subjects were divided into three groups according to the urinary albumin-to-creatinine ratio (UACR). The differences in the NLR and PLR among the groups and their correlation with renal function were analyzed. Logistic regression analysis was used to analyze independent risk factors for DKD, and receiver operating characteristic (ROC) curves were used to assess the predictive values of the NLR and PLR for the disease. The NLR and PLR were significantly different among the three groups, and they increased with increasing levels of albuminuria. Pearson's correlation analysis showed that the NLR and PLR were positively correlated with the UACR but negatively correlated with the estimated glomerular filtration rate (eGFR) (p<0.001). Logistic regression analysis showed that these two indicators were independent risk factors for DKD (p<0.001). The results of ROC curve analysis suggested that the NLR (AUC=0.794; 95% CI, 0.760-0.827; p<0.001) and PLR (AUC=0.665; 95% CI, 0.623-0.706, p<0.001) had important diagnostic value for DKD. The NLR and PLR were closely associated with renal function among Chinese patients with type 2 diabetes, and high NLR and PLR values may serve as predictors of DKD.

Prognostic nutritional index as a risk factor for diabetic kidney disease and mortality in patients with type 2 diabetes mellitus.

Microinflammation and malnutrition are common in individuals with type 2 diabetes mellitus (T2DM). We aimed to validate whether prognostic nutritional index (PNI) may increase the risk of diabetic kidney disease (DKD) and all-cause mortality in T2DM patients. This retrospective cohort study was based on the National Health and Nutrition Examination Survey (NHANES) and National Death Index (NDI) 2013-2018 database. A total of 14,349 eligible subjects were included, and 2720 of them were with T2DM. PNI was assessed by the 5 × lymphocyte count (109/L) + serum albumin (g/L). The Logistic and Cox regression analyses were conducted to investigate the risk factors of DKD and mortality in T2DM patients. For 14,349 participants represented 224.7 million noninstitutionalized residents of the United State, the average PNI was 53.72 ± 0.12, and the prevalence of T2DM was 14.89%. T2DM patients had a lower level of PNI and dietary protein intake, a higher risk of mortality, kidney injury, anemia, arterial hypertension and hyperuricemia, compared with non-T2DM subjects. DKD occurred in 35.06% of diabetic participants and a higher PNI was independently related with a lower risk of DKD (OR 0.64, 95% CI 0.459-0.892, p = 0.01) in T2DM after multivariate adjustment. During a median follow-up of 46 person-months (29-66months), a total of 233 T2DM individuals died from all causes (mortality rate = 8.17%). Subjects with T2DM who had a higher PNI showed a lower risk of all-cause mortality (HR 0.60, 95% CI 0.37-0.97, p = 0.036). PNI, as a marker of immunonutrition, correlated with the incidence of DKD, and was an independent predictor for all-cause mortality in participants with T2DM. Thus, PNI may conduce to the risk stratification and timely intervention of T2DM patients.