Incidence Of Diabetic Kidney Disease Research Articles

Associations between cardiometabolic indices and the risk of diabetic kidney disease in patients with type 2 diabetes

BackgroundThis study was designed to assess the associations between emerging cardiometabolic indices—the atherogenic index of plasma (AIP), the stress hyperglycemia ratio (SHR), the triglyceride-glucose (TyG) index, and the homeostasis model assessment of insulin resistance (HOMA-IR)—and the incidence of diabetic kidney disease (DKD) in type 2 diabetes (T2D) patients.MethodsWe consecutively enrolled 4351 T2D patients. The AIP, SHR, TyG index, and HOMA-IR were calculated from baseline parameters. DKD was defined as a urine albumin/creatinine ratio > 30 mg/g or an eGFR < 60 mL/min per 1.73 m. All participants were categorized into tertiles based on the cardiometabolic indices. Multivariate logistic regression models, restricted cubic splines, and receiver operating characteristic (ROC) curves were used for analysis.ResultsA total of 1371 (31.5%) patients were diagnosed with DKD. A restricted cubic spline showed a J-shaped association of the AIP and TyG index with DKD, a log-shaped association between HOMA-IR and DKD, and a U-shaped association between the SHR and DKD incidence. Multivariate logistic regression revealed that individuals in the highest tertile of the four cardiometabolic indices had a significantly greater risk of DKD than did those in the lowest tertile (AIP: OR = 1.08, 95% CI = 1.02–1.14, P = 0.005; SHR: OR = 1.42, 95% CI = 1.12–1.81, P = 0.004; TyG index: OR = 1.86, 95% CI = 1.42–2.45, P < 0.001; HOMA-IR: OR = 2.24, 95% CI = 1.52–3.30, P < 0.001). The receiver operating characteristic curves showed that the HOMA-IR score was better than other indices at predicting the risk of DKD, with an optimal cutoff of 3.532.ConclusionsElevated AIP, SHR, TyG index and HOMA-IR are associated with a greater risk of DKD in patients with T2D. Among these indices, the HOMA-IR score demonstrated the strongest association with and predictive value for DKD incidence.

Endothelial CXCR2 deficiency attenuates renal inflammation and glycocalyx shedding through NF-κB signaling in diabetic kidney disease

BackgroundThe incidence of diabetic kidney disease (DKD) continues to rapidly increase, with limited available treatment options. One of the hallmarks of DKD is persistent inflammation, but the underlying molecular mechanisms of early diabetic kidney injury remain poorly understood. C-X-C chemokine receptor 2 (CXCR2), plays an important role in the progression of inflammation-related vascular diseases and may bridge between glomerular endothelium and persistent inflammation in DKD.MethodsMultiple methods were employed to assess the expression levels of CXCR2 and its ligands, as well as renal inflammatory response and endothelial glycocalyx shedding in patients with DKD. The effects of CXCR2 on glycocalyx shedding, and persistent renal inflammation was examined in a type 2 diabetic mouse model with Cxcr2 knockout specifically in endothelial cells (DKD-Cxcr2eCKO mice), as well as in glomerular endothelial cells (GECs), cultured in high glucose conditions.ResultsCXCR2 was associated with early renal decline in DKD patients, and endothelial-specific knockout of CXCR2 significantly improved renal function in DKD mice, reduced inflammatory cell infiltration, and simultaneously decreased the expression of proinflammatory factors and chemokines in renal tissue. In DKD conditions, glycocalyx shedding was suppressed in endothelial Cxcr2 knockout mice compared to Cxcr2L/L mice. Modulating CXCR2 expression also affected high glucose-induced inflammation and glycocalyx shedding in GECs. Mechanistically, CXCR2 deficiency inhibited the activation of NF-κB signaling, thereby regulating inflammation, restoring the endothelial glycocalyx, and alleviating DKD.ConclusionsTaken together, under DKD conditions, activation of CXCR2 exacerbates inflammation through regulation of the NF-κB pathway, leading to endothelial glycocalyx shedding and deteriorating renal function. Endothelial CXCR2 deficiency has a protective role in inflammation and glycocalyx dysfunction, suggesting its potential as a promising therapeutic target for DKD treatment.

Correlation between weight variability and the risk of diabetic nephropathy in patients with type 2 diabetes mellitus

Objective: To evaluate the relationship between different indexes of weight variability and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). Methods: A retrospective cohort study. The clinical data of 2 180 T2DM patients without DKD who underwent case management at Lee's United Clinic in Taiwan, China from 2002 to 2018 were retrospectively analyzed, including 1 103 females and 1 077 males, with an average age of (64.8±12.4) years. Regular follow-up was conducted for patients for at least 2 years, and their metabolic indexes were monitored annually. BMI variability independent of the mean (BMI-VIM), average yearly mean square successive difference (BMI-ASV), coefficient of variation (BMI-CV) and standard deviation (BMI-SD) were calculated,based on the body mass index (BMI) recorded annually by the patients. Patients were divided into four groups (Q1-Q4) based on the quartiles of the four weight variability indexes. DKD group and non-DKN group(NDKD group) were defined based on the occurrence of DKD at the end of the follow-up. Cox proportional hazards regression models were used to analyze the relationship between the four weight variability indicators and the incidence of DKD. Subgroup analysis was performed by categorizing patients into non-obesity (BMI<28 kg/m2) and obesity groups (BMI≥28 kg/m2) to investigate the impact of the four weight variability indicators on the risk of DKD. Results: After a follow-up of (4.55±2.13) years, 904 patients developed DKD. Compared with the NDKD group, patients in the DKD group had a higher proportion of females, older age, longer duration of diabetes, more insulin users, higher waist-to-hip ratio, higher levels of BMI-VIM, BMI-ASV, BMI-CV, BMI-SD, systolic blood pressure, diastolic blood pressure, and urine albumin-creatinine ratio, a lower proportion of hypoglycemic drugs, estimated glomerular filtration rate, and high-density lipoprotein cholesterol level, with statistically significant differences between the two groups(all P<0.05). Cox proportional hazards regression analysis results revealed that the risk of DKD in T2DM patients increased with the increase in BMI-SD, BMI-CV, BMI-VIM, and BMI-ASV after correcting a series of influencing factors. In the BMI-VIM subgroup, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.4% [HR=1.224 (95%CI:1.008-1.487), P=0.041]. In the BMI-ASV group, compared with the Q1 group, the risk of DKD in the Q4 group increased by 51.1% [HR=1.511 (95%CI:1.240-1.841), P<0.01]. In the BMI-CV group, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.2% [HR=1.222 (95%CI:1.006-1.485), P=0.044]. In the BMI-SD subgroup, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.2% [HR=1.222 (95%CI:1.002-1.490), P=0.048]. Sub-group analysis showed that when the non-obesity group was grouped by BMI-ASV, after correcting a series of influencing factors, compared with the Q1 group, the highest risk of DKD occurred in the Q4 group [HR=1.551 (95%CI:1.228-1.958), P<0.001];when the obesity group was grouped by BMI-ASV, after correcting a series of influencing factors, compared with the Q1 group, the highest risk of DKD occurred in the Q4 group [HR=1.703 (95%CI:1.168-2.485), P=0.006]. Conclusion: Increases in BMI-VIM, BMI-ASV, BMI-CV, and BMI-SD are associated with an increased risk of DKD in T2DM patients.

Impact of baseline and trajectory of the atherogenic index of plasma on incident diabetic kidney disease and retinopathy in participants with type 2 diabetes: a longitudinal cohort study

BackgroundSome studies have assessed the predictive role of the atherogenic index of plasma (AIP) for macrovascular diseases. This prospective investigation aimed to elucidate whether AIP is associated with diabetic kidney disease (DKD) and diabetic retinopathy (DR) incidence.MethodsThe data were extracted from 4831 participants, of whom 2943 and 3360 participants with type 2 diabetes (T2D) were included in the DKD and DR follow-up analyses, respectively. Cox regression models were performed to test the relationships of AIP value at baseline with the risk of incident DKD and DR. Group-based trajectory modelling was utilized to discern AIP trajectories during the follow-up period. Subsequently, logistic regressions were applied to ascertain the influence of AIP trajectories on the incidence of DKD and DR.ResultsDuring the follow-up period, 709 (24.1%) and 193 (5.7%) participants developed DKD and DR, respectively. The median (interquartile range) follow-up time was 24.2 (26.3) months for DKD and 25.7 (27.0) months for DR. According to the multivariate Cox regression models, baseline AIP was positively and linearly related to the occurrence of DKD, with a hazard ratio of 1.75 (95% confidence interval [CI] 1.36–2.26). Three distinct trajectories of AIP were identified throughout the follow-up time: Low (31.4%), Median (50.2%), and High (18.3%). Compared to participants with the Low AIP trajectory, those with High and Median AIP trajectories presented 117% (95% CI: 1.62–2.91) and 84% (95% CI 1.46–2.32) greater odds of developing DKD, respectively. However, neither baseline levels nor trajectories of AIP were shown to be related to DR after adjusting for confounding factors.ConclusionsBaseline levels and trajectories of AIP were independently related to elevated DKD risk, indicating that AIP could be used as a predictor for identifying T2D participants at higher risk of DKD. No association between AIP and DR was detected.

Prediction of diabetic kidney disease risk using machine learning models: A population-based cohort study of Asian adults.

Machine learning (ML) techniques improve disease prediction by identifying the most relevant features in multidimensional data. We compared the accuracy of ML algorithms for predicting incident diabetic kidney disease (DKD). We utilized longitudinal data from 1365 Chinese, Malay, and Indian participants aged 40-80 y with diabetes but free of DKD who participated in the baseline and 6-year follow-up visit of the Singapore Epidemiology of Eye Diseases Study (2004-2017). Incident DKD (11.9%) was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 with at least 25% decrease in eGFR at follow-up from baseline. A total of 339 features, including participant characteristics, retinal imaging, and genetic and blood metabolites, were used as predictors. Performances of several ML models were compared to each other and to logistic regression (LR) model based on established features of DKD (age, sex, ethnicity, duration of diabetes, systolic blood pressure, HbA1c, and body mass index) using area under the receiver operating characteristic curve (AUC). ML model Elastic Net (EN) had the best AUC (95% CI) of 0.851 (0.847-0.856), which was 7.0% relatively higher than by LR 0.795 (0.790-0.801). Sensitivity and specificity of EN were 88.2 and 65.9% vs. 73.0 and 72.8% by LR. The top 15 predictors included age, ethnicity, antidiabetic medication, hypertension, diabetic retinopathy, systolic blood pressure, HbA1c, eGFR, and metabolites related to lipids, lipoproteins, fatty acids, and ketone bodies. Our results showed that ML, together with feature selection, improves prediction accuracy of DKD risk in an asymptomatic stable population and identifies novel risk factors, including metabolites. This study was supported by the National Medical Research Council, NMRC/OFLCG/001/2017 and NMRC/HCSAINV/MOH-001019-00. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

1288-P: Predictive Modeling of Type 2 Diabetes and Complications Using Machine Learning

Background: Given the prevalence of T2D worldwide, early detection and prevention of both T2D and its complications are of utmost importance. We propose comprehensive person-centered machine learning (ML) risk prediction models for T2D and complications. Methods: From the UK biobank (UKBB), we identified a prevalent T2D group at baseline (9,136 cases and 108,615 controls), an incident T2D group over 10 years of follow-up (29,845 cases and 354,818 controls), and an incident diabetic kidney disease (DKD) group (4435 cases and 33083 controls). We included 3 types of risk factors: clinical (biomarkers and diseases with known diabetes risk like CVD), genetic in the form of polygenic risk scores (PRS) for the pathogenesis of T2D and other clinical risks, and lifestyle. For each group, we trained a model using decision-tree-based ensemble ML algorithm. We then used SHAP values to determine feature importance and chose the top 10 predictors to build a final model. Results: The T2D prevalence model included 74 features and had an AUC of 0.97, and area under the precision-recall curve (PR AUC) of 0.83. The final model with the top features (HbA1c, T2D PRS, primary HTN, LDL, major dietary changes in the last 5 years, age, plasma glucose, waist circumference, and total cholesterol) had an AUC of 0.98, and PR AUC of 0.88. The T2D incidence model included the same 74 features and had an AUC of 0.92, and PR AUC of 0.57. The final model with the top features had an AUC of 0.93, and PR AUC of 0.65. The DKD risk prediction model comprised 85 features, and it had an AUC of 0.81, and PR AUC of 0.37. The final model with the top features (Cystatin C, primary HTN, eGFR, age, HbA1c, T2D PRS, urea, BMI, BMI PRS, NAFLD PRS) had an AUC of 0.80, and PR AUC of 0.39. Conclusions: This study is an ongoing work; our interim results show the capability of ML to identify relevant risk factors and that comprehensive ML models could help clinicians decide on more precise and individualized T2D screening and treatment approaches to prevent T2D and complications. Disclosure A.Khattab: None. S.Chen: None. H.J.Sadaei: None. A.Torkamani: None.

1003-P: Cost of Care for Patients with Diabetic Kidney Disease in Veterans Health Administration

Introduction: Diabetic kidney disease (DKD) represents a substantial burden on the Veterans Health Administration (VHA). We calculated the cost of DKD care for US Veterans from the healthcare system perspective. Methods: Veterans with type 2 diabetes (T2D) in 2015-2021 were identified using diagnosis codes, prescription records, and problem lists. We identified prevalent and incident DKD stages based on urine albumin, urine protein, and eGFR, and following the Kidney Disease Improving Global Outcome definitions. Aggregate all-cause monthly healthcare costs per patient for managing each DKD stage (ie, stages 1 through 5) were estimated by summing patient-level VHA costs in incident DKD stages from January 2018 until December 2021. Summary statistics include descriptive median and interquartile ranges of per-patient per-month [PPPM] cost. All costs were inflated to 2022 US dollars (USD) based on the Consumer Price Index of all items for urban consumers. Results and Conclusion: Out of two million US Veterans with T2D, we identified 401,214 DKD patients with 1+ incident stage progression in the follow-up period. Median PPPM all-cause healthcare cost increased exponentially from $748 at Stage 1 to $2,661 at Stage 5 (Figure). Interventions targeting patients with rapid DKD progression could markedly decrease the burden of DKD in US Veterans. Disclosure K.Kim: Research Support; Renalytix, GRAIL (acquired by Illumina in 2021), AstraZeneca. J.L.Crook: None. C.S.Lu: None. R.E.Nelson: None. H.Nyman: None. J.Lafleur: Research Support; Renalytix, Genentech, Inc., Novartis Pharmaceuticals Corporation.

#4326 STATIN INITIATION AND RISK OF INCIDENT KIDNEY DISEASE IN PATIENTS WITH DIABETES

Abstract Background and Aims The role of statin therapy in the development of kidney disease in patients with type 2 diabetes mellitus (T2DM) remains uncertain. We aim to determine the relationships between statin initiation and kidney outcomes in patients with T2DM. Method Using deidentified electronic health record data and new-user design, we conducted a nationwide retrospective cohort of patients with T2DM aged 40 years or older across China. The study outcomes included the development of diabetic kidney disease (DKD) and a sustained ≥40% decline in estimated glomerular filtration rate (eGFR). Cox proportional hazards regression was used to evaluate the relationships between statin initiation and kidney outcomes Analyses were conducted using propensity overlap weighting to balance the characteristics. Results Among 7272 statin initiators and 12 586 noninitiators in the weighted cohort, statin initiation was associated with lower risks of incident DKD (hazard ratio [HR], 0.72; 95% confidence interval [CI] 0.62-0.83), new-onset eGFR &amp;lt;60 ml/min/1.73 m2 (HR 0.63, 95% CI 0.50-0.79), new-onset proteinuria (HR, 0.70; 95% CI 0.59-0.84) and kidney function decline (HR 0.60, 95% CI 0.44-0.81). Among statin initiators, intensive control of LDL-C (&amp;lt;1.8 mmol/L) had a lower risk of incident DKD (HR 0.51, 95% CI 0.32-0.81) than that in non-control group (LDL-C ≥ 3.4 mmol/L). Similar results were obtained for participants with differing patterns of dyslipidemia, those using different statins, and after stratification according to the characteristics of the participants. Conclusion Statin initiation is significantly associated with a lower risk of kidney disease development in patients with diabetes. This reno-protective effect was more prominent in patients with intensive control of LDL-C.

Time to Diabetic Nephropathy and its Predictors Among Diabetic Patients Treated in Wolaita and Dawuro Zone Hospitals, Ethiopia: A Retrospective Cohort Study.

Diabetic kidney disease (DKD) develops in nearly half of patients with type 2 diabetes mellitus (DM) and one-third of those with type 1 DM during their lifetime. The incidence of DKD as a cause of end stage renal disease is increasing each year. So this study aimed to assess the time to develop diabetic nephropathy and predictors among diabetic patients treated in Wolaita zone hospitals. A ten-year retrospective cohort study had conducted among 614 diabetic patients using systematic random sampling in Wolaita and Dawuro zone hospitals. Bivariable and multivariable Cox proportional hazards regression had used to identify the possible associations between variables. Those variables with a p-value of less than 0.25 in bivariable analysis exported to multivariable Cox regression analysis. Finally, variables with p-value less than 0.05 at multivariable Cox regression were considered significantly significant. The Cox-proportional hazard model assumption had checked using the Schoenfeld residual test. Of the total participants, 93 (15.3%; 95% CI = 12.45-18.14) patients had developed nephropathy in 820,048 people year observation. A mean time to diabetic nephropathy in this study was 189.63 (95% CI, 185.01, 194.25) months. Being illiterate (AHR: 2.21, 95% CI: 1.34-3.66), being hypertensive (AHR: 5.76, 95% CI: 3.39-9.59), and being urban dwellers (AHR: 2.25, 95% CI: 1.34-3.77) increases the hazard of nephropathy. According to this follow-up study, the overall incidence rate is substantially high over ten year follow-up period. The mean time to develop diabetic nephropathy was sixteen years. Educational status, place of residence, and being hypertensive were the predictors. So stakeholders should work on complication reduction measures and awareness creation of the impact of comorbidities.

Statin initiation and risk of incident kidney disease in patients with diabetes.

The role of statin therapy in the development of kidney disease in patients with type 2 diabetes mellitus (DM) remains uncertain. We aimed to determine the relationships between statin initiation and kidney outcomes in patients with type 2 DM. Through a new-user design, we conducted a multicentre retrospective cohort study using the China Renal Data System database (which includes inpatient and outpatient data from 19 urban academic centres across China). We included patients with type 2 DM who were aged 40 years or older and admitted to hospital between Jan. 1, 2000, and May 26, 2021, and excluded those with pre-existing chronic kidney disease and those who were already on statins or without follow-up at an affiliated outpatient clinic within 90 days after discharge. The primary exposure was initiation of a statin. The primary outcome was the development of diabetic kidney disease (DKD), defined as a composite of the occurrence of kidney dysfunction (estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m2 and > 25% decline from baseline) and proteinuria (a urinary albumin-to-creatinine ratio ≥ 30 mg/g and > 50% increase from baseline), sustained for at least 90 days; secondary outcomes included development of kidney function decline (a sustained > 40% decline in eGFR). We used Cox proportional hazards regression to evaluate the relationships between statin initiation and kidney outcomes, as well as to conduct subgroup analyses according to patient characteristics, presence or absence of dyslipidemia, and pattern of dyslipidemia. For statin initiators, we explored the association between different levels of lipid control and outcomes. We conducted analyses using propensity overlap weighting to balance the participant characteristics. Among 7272 statin initiators and 12 586 noninitiators in the weighted cohort, statin initiation was associated with lower risks of incident DKD (hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.62-0.83) and kidney function decline (HR 0.60, 95% CI 0.44-0.81). We obtained similar results to the primary analyses for participants with differing patterns of dyslipidemia, those prescribed different statins, and after stratification according to participant characteristics. Among statin initiators, those with intensive control of high-density lipoprotein cholesterol (LDL-C) (< 1.8 mmol/L) had a lower risk of incident DKD (HR 0.51, 95% CI 0.32-0.81) than those with inadequate lipid control (LDL-C ≥ 3.4 mmol/L). For patients with type 2 DM admitted to and followed up in academic centres, statin initiation was associated with a lower risk of kidney disease development, particularly in those with intensive control of LDL-C. These findings suggest that statin initiation may be an effective and reasonable approach for preventing kidney disease in patients with type 2 DM.

Early diabetic kidney disease: Focus on the glycocalyx

The incidence of diabetic kidney disease (DKD) is sharply increasing worldwide. Microalbuminuria is the primary clinical marker used to identify DKD, and its initiating step in diabetes is glomerular endothelial cell dysfunction, particularly glycocalyx impairment. The glycocalyx found on the surface of glomerular endothelial cells, is a dynamic hydrated layer structure composed of pro-teoglycans, glycoproteins, and some adsorbed soluble components. It reinforces the negative charge barrier, transduces the shear stress, and mediates the interaction of blood corpuscles and podocytes with endothelial cells. In the high-glucose environment of diabetes, excessive reactive oxygen species and proinflammatory cytokines can damage the endothelial glycocalyx (EG) both directly and indirectly, which induces the production of microalbuminuria. Further research is required to elucidate the role of the podocyte glycocalyx, which may, together with endothelial cells, form a line of defense against albumin filtration. Interestingly, recent research has confirmed that the negative charge barrier function of the glycocalyx found in the glomerular basement membrane and its repulsion effect on albumin is limited. Therefore, to improve the early diagnosis and treatment of DKD, the potential mechanisms of EG degradation must be analyzed and more responsive and controllable targets must be explored. The content of this review will provide insights for future research.

Early detection methods of chronic diabetic nephropathy in diabetes mellitus patients in primary health services

Introduction: The prevalence of diabetic kidney disease increases along with the increase in the number of patients with diabetes mellitus. Early detection of diabetic nephropathy in DM patients is an essential step in preventing the incidence of diabetic kidney disease. The study aimed to obtain a method of early detection of diabetic kidney disease in DM patients in primary health care via identifying factors associated with decreased glomerular filtration rate (GFR). Methods: We conducted a case-controlled study at the public health center in Bantul. The research subjects were patients at Kasihan 1 public health center aged 18-75 years. In-depth interviews will be conducted to obtain clinical and social risk factors for GFR decreasing as an early detection tool for diabetic nephropathy (DN) incidence. The IGF-1 levels were checked using ELISA. The Pearson correlation test observed a significant association between patient risk factors and GFR. Results: This study is expected to obtain a model of the method of early detection of chronic diabetic kidney disease in diabetes mellitus patients in primary health services. The results showed that the GFR was related to systolic blood pressure, diastolic blood pressure, hyperglycemia, nicotine levels, and IGF-1 levels (P&lt;0.00). Increased nicotine levels, increased blood pressure, hyperglycemia, and decreased levels of IGF-1 are associated with decreased GFR. Identifying factors related to the glomerular filtration rate can be used to predict impaired renal function. Conclusion: Reduced glomerular filtration rates are linked to higher nicotine levels, higher blood pressure, hyperglycemia, and lower IGF-1 levels.

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.

Diabetic kidney disease in pediatric patients: A current review.

In the last decades, a significant increase in the incidence of diabetic kidney disease (DKD) was observed concomitant with rising diabetes mellitus (DM) incidence. Kidney disease associated with DM in children and adolescents is represented by persistent albuminuria, arterial hypertension, progressive decline in estimated glomerular filtration rate to end-stage renal disease and increased cardiovascular and all-cause morbidity and mortality of these conditions. In medical practice, the common and still the “gold standard” marker for prediction and detection of diabetic kidney involvement in pediatric diabetes is represented by microalbuminuria screening even if it has low specificity to detect early stages of DKD. There are some known limitations in albuminuria value as a predictor biomarker for DKD, as not all diabetic children with microalbuminuria or macroalbuminuria will develop end-stage renal disease. As tubular damage occurs before the glomerular injury, tubular biomarkers are superior to the glomerular ones. Therefore, they may serve for early detection of DKD in both type 1 DM and type 2 DM. Conventional and new biomarkers to identify diabetic children and adolescents at risk of renal complications at an early stage as well as renoprotective strategies are necessary to delay the progression of kidney disease to end-stage kidney disease. New biomarkers and therapeutic strategies are discussed as timely diagnosis and therapy are critical in the pediatric diabetic population.

Exploration of Noninvasive Detection of Advanced Glycation End Products in the Lens to Screen for Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is a complication of diabetes, which is the most common cause of end-stage renal disease (dialysis). DKD has a high mortality rate, and only early detection can nip this disease in the bud. Advanced glycation end products (AGEs)are generally believed to be involved in the occurrence of DKD. Studies have shown that the lens AGEs fluorescence for noninvasive detection has high consistency with the gold standard OGTT, has high sensitivity and specificity, and could be used as a practical tool for the early screening of type 2 diabetes mellitus (T2DM).Therefore, we speculated that the noninvasive lens AGEs fluorescence detection method can be used to predict the occurrence of DKD. This study detected levels of AGEs in multiple cellular and tissues and analyzed the relationships between AGEs and lens, eyeballs, peripheral blood mononuclear cell (PBMC), serum, and kidney. Additionally, we examined the possible role of lens AGEs fluorescence in DKD screening. Our preexperimental study found that lens AGE levels in patients with T2DM were positively correlated with PBM and serum AGE levels. Lens AGE levels in patients with T2DM were negatively correlated with eGFR and positively correlated with urinary ACR. The animal and cell experiments showed that the AGE levels in the eyeballs of DM mice were also positively correlated with those in the serum and kidney. To increase the reliability of the experiment, we increased the sample size. In our results, lens AGEs levels were positively correlated with the occurrence of DKD, and the incidence of DKD in the high lens AGEs group was 2.739 times that in the low lens AGEs group. The receiver operating characteristic (ROC) curves showed that patients with T2DM with a lens AGEs value ≥ 0.306 were likely to have DKD. The area under the ROC curve of the noninvasive technique for identifying DKD was 0.757 (95% Cl: 0.677-0.838, p<0.001), and the sensitivity and specificity were 70.0% and 78.7%, respectively. These results suggest that noninvasive lens AGEs detection technology has certain clinical value in diagnosing whether patients with T2DM have DKD.

Serum Cystatin C Trajectory Is a Marker Associated With Diabetic Kidney Disease.

ObjectiveTo explore the association of the trajectory of serum Cystatin C (Cysc) with diabetic kidney disease (DKD), a retrospective cohort study of Chinese subjects was carried out.MethodA review of 2,928 diabetes mellitus (DM) patients admitted to the clinic and ward of the Endocrinology Department, Shengjing Hospital of China Medical University from January 1, 2014 to December 31, 2014 was performed. Subsequent visits to the hospital were followed until December 31, 2020. The primary endpoint was the incidence of DKD as diagnosed by urinary albumin/creatinine ratio ≥30 mg/g and/or estimated glomerular filtration rate <60 ml/min per 1.73 m2. Healthy control subjects were identified from a health checkup database in Shengjing Hospital from 2016 to 2019. The latent class growth mixed modeling (LCGMM) method was used to analyze latent classes of serum Cysc in healthy and DM subjects. Finally, the hazard ratios (HRs) of latent classes of Cysc in DM subjects were analyzed by Cox regression analysis.ResultsA total of 805 type 2 diabetes mellitus (T2DM) and 349 healthy subjects were included in the trial. The HRs of quartiles of baseline Cysc in T2DM subjects were 7.15 [95% confidence interval (CI), 2.79 to 25.57], 2.30 (95% CI, 1.25 to 4.24), and 2.05 (95% CI, 1.14 to 3.70), respectively, for quartile 4 (Q4), Q3, and Q2 when compared with Q1. Through LCGMM, a 1-class linear model was selected for the Cysc latent class in healthy subjects. In contrast, a 3-class linear model was selected for that in DM subjects. The slopes of the three latent classes in T2DM subjects were larger than the slope in healthy subjects. The HRs of incident DKD were 3.43 (95% CI, 1.93 to 6.11) for the high-increasing class and 1.80 (95% CI, 1.17 to 2.77) for the middle-increasing class after adjusting for confounding variables.ConclusionsPatients with T2DM had a higher velocity of increase in Cysc than healthy subjects. Patients with high baseline Cysc values and high latent increasing velocity of Cysc had a higher risk of developing DKD in later life. More attention should be paid to patients with these high-risk factors.

Association between Vitamin D Status and Mortality among Adults with Diabetic Kidney Disease.

Objective Emerging evidence demonstrates that vitamin D status contributes to the incidence of diabetic kidney disease (DKD). However, the causal relationships between vitamin D and mortality among individuals with DKD are inconclusive. Our study is aimed at exploring the relationship between serum 25-hydroxyvitamin D (25(OH)D) concentrations and mortality among adults with DKD. Research Design and Methods. Our study included 1,202 adult participants with DKD from the National Health and Nutrition Examination Survey (NHANES) 2001–2014. Cox and competing-risks regression were used to estimate hazard ratios (HRs) and 95% CIs for associations between 25(OH)D concentrations and survival. Results The overall mean serum 25(OH)D concentration was 55.9 ± 26.3. Vitamin D deficiency (25(OH)D < 50 nmol/l), insufficiency group (50 ≤ 25(OH)D < 75 nmol/l), and sufficiency group (25(OH)D ≥ 75 nmol/l) were observed in 552 (45.9%), 409 (34.0%), and 241 (20.0%) participants, respectively. Higher levels of vitamin D were significantly associated with improved all-cause and nonaccident- and malignant neoplasm-cause mortality among individuals with DKD after adjusting for the potential confounding factors. Conclusions We observed widespread vitamin D deficiency or insufficiency in DKD patients. Higher 25(OH)D values were significantly correlated with lower risk of mortality after adjusting for confounding variables.

Osteocalcin and Risks of Incident Diabetes and Diabetic Kidney Disease: A 4.6-Year Prospective Cohort Study.

OBJECTIVEWe aimed to examine the relationship between osteocalcin (OC) and the risk of incident diabetes and the risk of incident diabetic kidney disease (DKD).RESEARCH DESIGN AND METHODSWe followed 5,396 participants without diabetes (nondiabetes subcohort) and 1,174 participants with diabetes and normal kidney function (diabetes subcohort) at baseline. Logistic regression and modified Poisson regression models were used to estimate the relative risk (RR) of baseline OC levels with incident diabetes and DKD.RESULTSDuring a mean 4.6-year follow-up period, 296 cases of incident diabetes and 184 cases of incident DKD were identified. In the nondiabetes subcohort, higher OC levels were linearly associated with a decreased risk of diabetes (RR for 1-unit increase of loge-transformed OC 0.51 [95% CI 0.35–0.76]; RR for highest vs. lowest quartile 0.65 [95% CI 0.44–0.95]; P for trend < 0.05). In the diabetes subcohort, OC levels were linearly inversely associated with incident DKD (RR for 1-unit increase of loge-transformed OC 0.49 [95% CI 0.33–0.74]; RR for highest vs. lowest quartile 0.56 [95% CI 0.38–0.83]; P for trend < 0.05), even independent of baseline estimated glomerular filtration rate and urinary albumin-to-creatinine ratio. No significant interactions between OC and various subgroups on incident diabetes or DKD were observed.CONCLUSIONSLower OC levels were associated with an increased risk of incident diabetes and DKD.

Cardiovascular autonomic neuropathy and incident diabetic kidney disease in patients with type 2 diabetes

AimsWe investigated the association between cardiovascular autonomic neuropathy (CAN) and incident diabetic kidney disease (DKD). MethodsThis retrospective longitudinal study included 2,033 patients with type 2 diabetes (mean age 57.2 years, 57.4% male, and median diabetes duration 8.0 years), free of renal dysfunction or cardiovascular disease at initiation. Cardiovascular autonomic reflex tests were performed once at baseline, and CAN was defined as ≥ 2 abnormal parasympathetic test results. Urine ACR and eGFR were concurrently measured at baseline and every 3–6 months thereafter. Incident DKD was defined as the development of ACR ≥ 30 mg/g at two or more follow-up examinations or eGFR < 60 ml/min/1.73 m2 with ≥ 25% decrease from baseline. ResultsDuring a median follow-up of 2.9 years (1.1 – 4.8), 290 (14.3%) patients developed DKD, comprising 79.7% (N = 231) cases of new-onset albuminuria alone, 14.5% (N = 42) cases of eGFR decline alone, and 5.8% (N = 17) cases of both. Compared to those without CAN, patients with CAN had a significantly higher risk of incident DKD in a multivariable Cox regression model (HR 1.56, 95% CI 1.15 – 2.12; P = 0.005). ConclusionCAN is may be a useful marker for long-term complications including DKD in patients with type 2 diabetes. Monitoring of CAN helps to identify high risk patients of future renal impairment.

GLP-1 Receptor Agonists in Diabetic Kidney Disease: From Physiology to Clinical Outcomes.

Diabetic kidney disease (DKD) is one of the most common complications in type 2 diabetes mellitus (T2D) and a major cause of morbidity and mortality in diabetes. Despite the widespread use of nephroprotective treatment of T2D, the incidence of DKD is increasing, and it is expected to become the fifth cause of death worldwide within 20 years. Previous studies have demonstrated that GLP-1 receptor agonists (GLP-1 RA) have improved macrovascular and microvascular outcomes independent of glycemic differences, including DKD. GLP-1Ras’ improvement on kidney physiology is mediated by natriuresis, reduction in hyperfiltration and renin-angiotensin-aldosterone system (RAAS) activity and anti-inflammatory properties. These findings translate into improved clinical outcomes such as an enhanced urine albumin-to-creatinine ratio (UACR) and a reduction in renal impairment and the need for renal replacement therapies (RRT). In this article, we review the role of GLP-1RAs on the mechanisms and effect in DKD and their clinical efficacy.