Diagnostic value of retinol-binding protein 4 in diabetic nephropathy: a systematic review and meta-analysis.

Objective: Diabetic nephropathy (DN) is a major microvascular complication of diabetes and the leading cause of end-stage renal disease. Early detection and prevention of DN are important. Retinol-binding protein 4 (RBP4) has been considered as a single diagnostic marker for the detection of renal impairment. However, the results have been inconsistent. The present meta-analysis aimed to determine the diagnostic potential of RBP4 in patients in type 2 diabetes mellitus (T2DM) with DN. Methods: We searched PubMed, Web of Science, Embase, Wanfang and CNKI databases from inception until January 2024. The meta-analysis was performed by Stata version 15.0, and sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) were pooled. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was utilized to assess the quality of each included study. In addition, heterogeneity and publication bias were evaluated. Results: Twenty-nine studies were included in the meta-analysis. The pooled sensitivity and specificity were 0.76 [95% confidence interval (CI), 0.71-0.80] and 0.81 (95% CI, 0.76-0.85), respectively. The results showed a pooled PLR of 4.06 (95% CI, 3.16-5.21), NLR of 0.29 (95% CI, 0.24-0.36) and DOR of 13.76 (95% CI, 9.29-20.37). The area under the summarized receiver operating characteristic curve was given a value of 0.85 (95% CI, 0.82-0.88). No obvious publication bias existed in the Deeks' funnel plot asymmetry test. Conclusion: Our findings suggest that RBP4 has a promising diagnostic value with good sensitivity and specificity for patients with T2DM with DN.

Association between lipoprotein(a) plasma levels and diabetic nephropathy in Han Chinese patients with type 2 diabetes mellitus.

The goal of this study was to evaluate the relationship between serum lipoprotein(a) [Lp(a)] levels and diabetic nephropathy (DN) among Han Chinese individuals with type 2 diabetes mellitus (T2DM). This retrospective analysis comprised a consecutive case series of 767 grown-up patients with T2DM (199 among them with DN) hospitalized in the Department of Endocrinology at the The First Affiliated Hospital of Anhui Medical University from February 20220 to February 2021. Clinical data and other laboratory measurements, such as glycated hemoglobin (HbA1c), were extracted from medical records and compared among groups. Clinical characteristics according to Lp(a) quartiles were also studied. Univariate and multivariate regression analysis were used to examine the relationship between serum Lp(a) and DN. Patients with DN had a longer disease duration, higher HbA1c, higher level of Lp(a), and were more likely to have diabetic retinopathy (DR) than those without DN (P < 0.005 for each). With regard to the Lp(a) quartile group, patients with a higher Lp(a) concentration were more likely to have DN and have higher level of HbA1c during the study (P for trend < 0.005 for each). After adjusting for several confounding factors, the development of DN was significantly associated with the serum Lp(a) level (P = 0.026, comparing the 4th vs 1st quartile of Lp(a)) according to multivariate regression analysis. The receiver operating characteristic (ROC) curves for DN development using serum Lp(a) showed that the area under the receiver operating characteristic curves (AUC) was 0.590 (P < 0.001). Findings from this study demonstrated that the DN was independently associated with the serum Lp(a) level in patients with T2DM in this retrospective study.

Insulin sensitivity estimates and their longitudinal association with coronary artery disease in type 1 diabetes. Does it matter?

BACKGROUND: Insulin resistance and chronic kidney disease are both associated with increased coronary artery disease risk. Many formulae estimating glucose disposal rate in type 1 diabetes infer insulin sensitivity from clinical data. We compare associations and performance relative to traditional risk factors and kidney disease severity between three formulae estimating the glucose disposal rate and coronary artery disease in people with type 1 diabetes. METHODS: The baseline glucose disposal rate was estimated by three (Williams, Duca, and Januszewski) formulae in FinnDiane Study participants and related to subsequent incidence of coronary artery disease, by baseline kidney status. RESULTS: In 3517 adults with type 1 diabetes, during median (IQR) 19.3 (14.6, 21.4) years, 539 (15.3%) experienced a coronary artery disease event, with higher rates with worsening baseline kidney status. Correlations between the three formulae estimating the glucose disposal rate were weak, but the lowest quartile of each formula was associated with higher incidence of coronary artery disease. Importantly, only the glucose disposal rate estimation by Williams showed a linear association with coronary artery disease risk in all analyses. Of the three formulae, Williams was the strongest predictor of coronary artery disease. Only age and diabetes duration were stronger predictors. The strength of associations between estimated glucose disposal rate and CAD incidence varied by formula and kidney status. CONCLUSIONS: In type 1 diabetes, estimated glucose disposal rates are associated with subsequent coronary artery disease, modulated by kidney disease severity. Future research is merited regarding the clinical usefulness of estimating the glucose disposal rate as a coronary artery disease risk factor and potential therapeutic target.

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a disease that poses a major threat to women's health. Therefore, studying these two diseases is of practical significance. In the field of spectral analysis, although common Raman spectral feature selection models can effectively extract features, they have the problem of changing the characteristics of the original data. The teacher-student network combined with Raman spectroscopy can perform feature selection while retaining the original features, and transfer the performance of the complex deep neural network structure to another lightweight network structure model. This study selects five flow learning models as the teacher network, builds a neural network as the student network, uses multi-layer perceptron for classification, and selects the optimal features based on the evaluation indicators accuracy, precision, recall, and F1-score. After five-fold cross-validation, the research results show that in the diagnosis of diabetic nephropathy, the optimal accuracy rate can reach 98.3%, which is 14.02% higher than the existing research; in the diagnosis of primary Sjögren's syndrome, the optimal accuracy rate can be reached 100%, which is 10.48% higher than the existing research. This study proved the feasibility of Raman spectroscopy combined with teacher-student network in the field of disease diagnosis by producing good experimental results in the diagnosis of diabetic nephropathy and primary Sjögren's syndrome.

A candidate panel of eight urinary proteins shows potential of early diagnosis and risk assessment for diabetic kidney disease in type 1 diabetes.

Diabetic kidney disease (DKD) poses a significant health challenge for individuals with diabetes. At its initial stages, DKD often presents asymptomatically, and the standard for non-invasive diagnosis, the albumin-creatinine ratio (ACR), employs discrete categorizations (normal, microalbuminuria, macroalbuminuria) with limitations in sensitivity and specificity across diverse population cohorts. Single biomarker reliance further restricts the predictive value in clinical settings. Given the escalating prevalence of diabetes, our study uses proteomic technologies to identify novel urinary proteins as supplementary DKD biomarkers. A total of 158 T1D subjects provided urine samples, with 28 (15 DKD; 13 non-DKD) used in the discovery stage and 131 (45 DKD; 40 pDKD; 46 non-DKD) used in the confirmation. We identified eight proteins (A1BG, AMBP, AZGP1, BTD, RBP4, ORM2, GM2A, and PGCP), all of which demonstrated excellent area-under-the-curve (AUC) values (0.959 to 0.995) in distinguishing DKD from non-DKD. Furthermore, this multi-marker panel successfully segregated the most ambiguous group (microalbuminuria) into three distinct clusters, with 80% of subjects aligning either as DKD or non-DKD. The remaining 20% exhibited continued uncertainty. Overall, the use of these candidate urinary proteins allowed for the better classification of DKD and offered potential for significant improvements in the early identification of DKD in T1D populations.

Association of the systemic immuno-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio with diabetic microvascular complications.

Background: The systemic immuno-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are widely used and have been shown to be predictive indicators of various diseases. Diabetic nephropathy (DN), retinopathy (DR), and peripheral neuropathy (DPN) are the most prominent and common microvascular complications, which have seriously negative impacts on patients, families, and society. Exploring the associations with these three indicators and diabetic microvascular complications are the main purpose. Methods: There were 1058 individuals with type 2 diabetes mellitus (T2DM) in this retrospective cross-sectional study. SII, NLR, and PLR were calculated. The diseases were diagnosed by endocrinologists. Logistic regression and subgroup analysis were applied to evaluate the association between SII, NLP, and PLR and diabetic microvascular complications. Results: SII, NLR, and PLR were significantly associated with the risk of DN [odds ratios (ORs): 1.52, 1.71, and 1.60, respectively] and DR [ORs: 1.57, 1.79, and 1.55, respectively] by multivariate logistic regression. When NLR ≥2.66, the OR was significantly higher for the risk of DPN (OR: 1.985, 95% confidence interval: 1.29-3.05). Subgroup analysis showed no significant positive associations across different demographics and comorbidities, including sex, age, hypertension, HbA1c (glycated hemoglobin), and dyslipidemia. Conclusion: This study found a positive relationship between NLR and DN, DR, and DPN. In contrast, SII and PLR were found to be only associated with DN and DR. Therefore, for the diagnosis of diabetic microvascular complications, SII, NLR and PLR are highly valuable.

Diabetic kidney disease screening status and related factors: a cross-sectional study of patients with type 2 diabetes in six provinces in China.

OBJECTIVE: To understand the awareness and practice of diabetic kidney disease (DKD) or nephropathy screening among community-based patients with type 2 diabetes in six provinces and cities in China, and to analyse the related factors affecting screening practices. METHODS: From December 2021 to March 2022, a cross-sectional survey was conducted using a structured questionnaire in 6230 patients with type 2 diabetes aged 18 years and older. The content of the questionnaire includes three parts: the general situation of diabetic patients (gender, age, ethnicity, marriage, education, occupation, etc.), DKD screening practices, and the evaluation of DKD screening services. RESULTS: 89.70% of the patients had their fasting blood glucose measured every six months, 21.12% of the patients had their glycosylated hemoglobin measured every six months, and only 13.11% and 9.34% of the patients had a urine protein-creatinine ratio test and estimated glomerular filtration rate test every 12 months. The proportions of glycosylated hemoglobin, urine protein-creatinine ratio, and estimated glomerular filtration rate were relatively high in young, northern, highly educated, and long-duration type 2 diabetic patients. CONCLUSION: The results of this survey found that the proportion of urine protein-creatinine ratio testing, estimated glomerular filtration rate testing, and glycosylated hemoglobin testing in Chinese patients with type 2 diabetes was very low. Patients with type 2 diabetes in rural areas, southern areas, with low education level, and short course of disease have lower detection rates for DKD, and hence lower rates of prevention and treatment.

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

BACKGROUND: This 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. METHODS: We 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. RESULTS: A 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. CONCLUSIONS: Elevated 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.

The relationship between weight-adjusted-waist index and diabetic kidney disease in patients with type 2 diabetes mellitus.

Purpose: Obesity, particularly abdominal obesity, is seen as a risk factor for diabetic complications. The weight-adjusted-waist index (WWI) is a recently developed index for measuring adiposity. Our goal was to uncover the potential correlation between the WWI index and diabetic kidney disease (DKD) risk. Methods: This cross-sectional study included adults with type 2 diabetes mellitus (T2DM) who participated in the NHANES database (2007-2018). The WWI index was calculated as waist circumference (WC, cm) divided by the square root of weight (kg). DKD was diagnosed based on impaired estimated glomerular filtration rate (eGFR<60 mL/min/1.73m2), albuminuria (urinary albumin to urinary creatinine ratio>30 mg/g), or both in T2DM patients. The independent relationship between WWI index and DKD risk was evaluated. Results: A total of 5,028 participants with T2DM were included, with an average WWI index of 11.61 ± 0.02. As the quartile range of the WWI index increased, the prevalence of DKD gradually increased (26.76% vs. 32.63% vs. 39.06% vs. 42.96%, P<0.001). After adjusting for various confounding factors, the WWI index was independently associated with DKD risk (OR=1.32, 95%CI:1.12-1.56, P<0.001). The area under the ROC curve (AUC) of the WWI index was higher than that of body mass index (BMI, kg/m2) and WC. Subgroup analysis suggested that the relationship between the WWI index and DKD risk was of greater concern in patients over 60 years old and those with cardiovascular disease. Conclusions: Our findings suggest that higher WWI levels are linked to DKD in T2DM patients. The WWI index could be a cost-effective and simple way to detect DKD, but further prospective studies are needed to confirm this.

Association between lactate dehydrogenase and the risk of diabetic kidney disease in patients with type 2 diabetes.

Objective: This study aims to investigate the association between lactate dehydrogenase (LDH) and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). Methods: The study enrolled patients with diagnosis of T2D between 2009 and 2018 from the National Nutrition and Health Examination Survey (NHANES) database. Demographic information, laboratory test, and diagnostic data were collected. Restricted cubic spline (RCS) plots were used to assess the dose-effect relationship between LDH levels and the risk of DKD in patients with T2D. Based on LDH levels, individuals were divided into higher and lower groups using dichotomy, and multivariate logistic regression analysis was conducted to explore the relationship between different LDH levels and the risk of DKD in T2D patients. Stratified analysis was performed to assess the consistency of the result. Results: A total of 4888 patients were included in the study, with 2976 (60.9%) patients without DKD and 1912 (39.1%) patients with DKD. RCS plots showed that the risk of DKD increased with increasing LDH levels. Multifactorial logistic regression analysis revealed that T2D patients with higher LDH levels had a 45% increased risk of DKD compared to those with lower LDH levels (OR=1.45; 95% CI: 1.11-1.89). Furthermore, each standard deviation increase in LDH level was associated with a 24% increase in DKD incidence among T2D patients (OR=1.24; 95% CI: 1.07-1.44). Stratified analysis consistently supported these findings. Conclusions: LDH can serve as a valuable biomarker for screening DKD in patients with T2D.

Risk factors for chronic kidney disease in middle eastern patients with type 2 diabetes mellitus: A cross-sectional study using the KDIGO classification.

AIMS: Chronic kidney disease (CKD) is prevalent in patients with type 2 diabetes mellitus (T2DM). This study aimed to investigate risk factors for CKD progression across the kidney disease-Improving Global Outcomes (KDIGO)categories in a Middle Eastern population beyond hyperglycemia as emphasized by KDIGO guidelines which classifying CKD by cause and severity. METHODS: This cross-sectional study targeted 1603 patients with T2DM. Risk factors for CKD progression were determined using odds ratios (ORs) and 95 % confidence intervals (CIs). RESULTS: Overall, 35.5 %, 31.7 %, and 32.8 % of patients were classified as low-risk, moderate-risk, and high-/very high-/highest-risk, respectively. Several factors were associated with high/very high/highest risk categorization, including being aged >45 years (OR: 1.85, 95 % CI: 1.36-2.49; P < 0.001), male gender (OR: 1.87, 95 % CI: 1.38-2.54; P < 0.001), hypertension (OR: 3.66, 95 % CI: 2.32-5.78; P < 0.001), and T2DM duration of ≥15 years (OR: 3.2, 95 % CI: 2.27-4.5; P < 0.001). Patients with more concurrent risk factors were notably represented in the high/very high/highest risk category. CONCLUSIONS: Male patients, older patients, and those with comorbid hypertension, longstanding T2DM, and additional concurrent risk factors have a significantly higher risk of advanced CKD. Such findings should be considered when planning management approaches for patients with CKD.

Initial eGFR Changes with SGLT2 Inhibitor in Patients With Type 2 Diabetes and Associations With the Risk of Abnormal Serum Potassium Level.

BACKGROUND: Both high and low levels of serum potassium measurements are linked with a higher risk of adverse clinical events among patients with type 2 diabetes. The study was aimed at evaluating the implications of the various degrees of initial estimated glomerular filtration rate (eGFR) change on subsequent serum potassium homeostasis following sodium-glucose cotransporter-2 inhibitor (SGLT2i) initiation among patients with type 2 diabetes. METHODS AND RESULTS: We used medical data from a multicenter health care provider in Taiwan and recruited 5529 patients with type 2 diabetes with baseline/follow-up eGFR data available after 4 to 12 weeks of SGLT2i treatment from June 1, 2016, to December 31, 2018. SGLT2i treatment was associated with an initial mean (SEM) eGFR decline of -3.5 (0.2) mL/min per 1.73 m2 in overall study participants. A total of 36.7% (n=2028) of patients experienced no eGFR decline, and 57.9% (n=3201) and 5.4% (n=300) of patients experienced an eGFR decline of 0% to 30% and >30%, respectively. Patients with an initial eGFR decline of >30% were associated with higher variability in consequent serum potassium measurement when compared with those without an initial eGFR decline. Participants with a pronounced eGFR decline of >30% were associated with a higher risk of hyperkalemia ≥5.5 (adjusted hazard ratio,4.59 [95% CI, 2.28-9.26]) or use of potassium binder (adjusted hazard ratio, 2.65 [95% CI, 1.78-3.95]) as well as hypokalemia events <3.0 mmol/L (adjusted hazard ratio, 3.21 [95% CI, 1.90-5.42]) or use of potassium supplement (adjusted hazard ratio, 1.87 [95% CI, 1.37-2.56]) following SGLT2i treatment after multivariate adjustment. CONCLUSIONS: Physicians should be aware that the eGFR trough occurs shortly, and consequent serum potassium changes following SGLT2i initiation.

A review regarding the article 'Diabetic peripheral neuropathy is associated with diabetic kidney disease and cardiovascular disease: The silesia diabetes-heart project'.

One of the most common micro vascular complications of diabetes is diabetic peripheral neuropathy (DPN). The well-recognized risk factors for DPN are hyperglycemia, dyslipidemia, and hypertension. DPN is associated with a high mortality rate and poor prognosis. Its pathogenesis is not fully understood, and clinical treatment is focused on relieving its clinical symptoms, as well as improving blood sugar control and cardiovascular risk factors. DPN and its clinically effective treatments need to be studied. Microvascular complications of diabetes present a significant challenge due to their diverse presentations, significant morbidity, and as strong predictors of cardiovascular disease. Prevention and management strategies should focus on lifestyle modification, education and awareness, systematic screening for early complications, and intensive management of modifiable risk factors. There was an association between DPN and DKD as well as CVD, BMI and age demonstrated. These may indicate that in case of having one diabetes complication diagnosed, it is important to screen for others, including macrovascular ones, as they may be undiagnosed due to their "silent" nature. Further studies are expected to strengthen basic research on the subject, reveal modern medical mechanisms, and provide fresh ideas and innovative methods for the treatment of DPN.

Ultrasensitive CCL2 Detection in Urine for Diabetic Nephropathy Diagnosis Using a WS2-Based Plasmonic Biosensor.

The accurate diagnosis of diabetic nephropathy relies on achieving ultrasensitive biosensing for biomarker detection. However, existing biosensors face challenges such as poor sensitivity, complexity, time-consuming procedures, and high assay costs. To address these limitations, we report a WS2-based plasmonic biosensor for the ultrasensitive detection of biomarker candidates in clinical human urine samples associated with diabetic nephropathy. Leveraging plasmonic-based electrochemical impedance microscopy (P-EIM) imaging, we observed a remarkable charge sensitivity in monolayer WS2 single crystals. Our biosensor exhibits an exceptionally low detection limit (0.201 ag/mL) and remarkable selectivity in detecting CC chemokine ligand 2 (CCL2) protein biomarkers, outperforming conventional techniques such as ELISA. This work represents a breakthrough in traditional protein sensors, providing a direction and materials foundation for developing ultrasensitive sensors tailored to clinical applications for biomarker sensing.

Determinants of non-diabetic kidney diseases in type 2 diabetic patients: Twenty years of single center experience.

BACKGROUND: Diabetic nephropathy is one of the most common complications associated with diabetes. However, non-diabetic kidney disease has been reported in patients with type 2 diabetes at varying incidence rates. The objective of our study is to investigate the occurrence, clinicopathological characteristics, and inflammatory markers linked to diabetic and non-diabetic nephropathy (NDN) in patients with type 2 diabetes mellitus (DM). Additionally, we aimed to explore the possibility of identifying non-diabetic pathology using different biopsy indications. MATERIALS AND METHODS: A total of 159 patients with type 2 DM who underwent renal biopsy at a tertiary care nephrology clinic between January 2000 and January 2022 were enrolled in the study. We collected comprehensive data, including patient demographics, co-morbidities, diabetes duration, renal biopsy indications and results, serological markers, renal function, diabetic retinopathy (DRP), full blood count, blood biochemistry, urinalysis, and inflammatory markers. Patients were categorized based on their biopsy indications, and their biopsy results were classified into three groups: isolated NDN, isolated diabetic nephropathy (DN), and mixed nephropathy with concurrent NDN. We evaluated the relationship between biopsy indications and accompanying pathologies and statistically assessed the likelihood of each biopsy indication detecting non-diabetic renal pathology. Additionally, differences in other data, including demographic and laboratory results and medical histories, among the three groups were investigated. RESULTS: The most frequent indication of renal biopsy was atypical presentations of nephrotic syndrome or nephrotic range proteinuria (ANS/ANP) in 25.1% of patients. Other indications included unexplained renal failure (URF) in 22.6%, atypical presentations of non-nephrotic range proteinuria (ANNP) in 18.2%, acute kidney injury or rapidly progressive kidney dysfunction (AKI/RPKD) in 16.9%, microscopic hematuria in 15.7%, URF with ANNP in 11.3%, and severe nephrotic range proteinuria (SNP) in 9.4%. Renal biopsy revealed isolated NDN in 64.8%, DN in 25.1%, and mixed nephropathy in 10.1% of patients. Primary glomerular diseases were the main non-diabetic renal pathology, predominantly focal segmental glomerulosclerosis (FSGS) (36.4%) followed by MN (10.6%) and IgA nephropathy (7.5%). In comparison with the isolated DN and mixed nephropathy groups, patients in the isolated NDN group had significantly shorter diabetes duration, fewer DRP, as well as lower serum creatinine and neutrophil-to-lymphocyte ratio (NLR). Multivariate logistic regression analysis revealed that presence of hematuria (OR 4.40; 95% CI 1.34 - 14.46, p = 0.014), acute nephrotic range proteinuria (OR 11.93; 95% CI 1.56 - 90.77, p = 0.017), and AKI/APKD (OR 41.08; 95% CI 3.40 - 495.39, p = 0.003) were strong predictors of NDN. Lower NLR (OR 0.77; 95% CI 0.60 - 0.98, p = 0.035), shorter duration of diabetes (OR 0.90; 95% CI 0.84 - 0.97, p = 0.010), and absence of DRP (OR 0.35; 95% CI 0.12 - 0.98, p = 0.046) were also found to be independent indicators of NDN. Receiver operating characteristic curve (ROC) analysis revealed a cut-off value of ≤ 3.01 for NLR (sensitivity of 63.1%, specificity of 63.5%) with regards to predicting non-diabetic renal pathology (p = 0.006). CONCLUSION: Renal biopsy findings in patients with type 2 DM highlight that the prevalence of NDN may be higher than assumed, as presented mainly in the form of primary glomerular disease. The presence of AKI/RPKD, hematuria, and ANS/ANP serves as a reliable indicator of non-diabetic renal pathology. In more ambiguous situations, factors such as a shorter duration of diabetes, absence of DRP, and a lower NLR value may assist clinicians in biopsy decision.

Physicians' Practices in Diabetic Nephropathy in Primary Healthcare Centers in Jazan City, Saudi Arabia, 2023.

Background and Objectives: Diabetes is one of the most common diseases dealt with by physicians in primary healthcare centers (PHCs). The disease is associated with macrovascular and microvascular complications, especially in those with long disease duration and uncontrolled diabetic nephropathy, which is one of the most common microvascular complications among diabetic patients. This investigation assessed the practices of physicians working at PHCs in terms of diabetic nephropathy screening, management, and referral. Materials and Methods: This study is a cross-sectional investigation targeting physicians working at PHCs in the Jazan region of Saudi Arabia between March and August of 2023. Data were collected via a self-administered questionnaire, which was distributed via online platforms. The questionnaire included sections measuring physicians' demographic data and associated factors regarding training, the availability of resources, and practices in diabetic nephropathy, including screening, management, and referral. Chi-squared tests were used to assess associations between the practices of physicians and the measured demographics. Result: A total of 234 physicians participated in the investigation. The median age of the participants was 35 years. The adherence level of practice toward diabetic nephropathy according to American Diabetes Association (ADA) guidelines ranged from 40 points (the highest adherence level of participants) to 19 points (the lowest adherence level of participants), with a median of 33 points. Higher adherence levels were noted among physicians in Saudi Arabia, physicians with higher education levels, physicians specializing as family physicians or diabetologists, physicians who reported attending online and on-site training at diabetic centers, physicians who reported continuous access to urine and serum creatinine tests, and physicians who reported continuous access to the American Diabetes Association guidelines (p < 0.05). Conclusions: There are several factors associated with the level of adherence in diabetic nephropathy practice, such as physicians' education level, specialty, training, and access to guidelines. The findings suggest the need for more training for PHC physicians in the care of patients affected by or at risk of diabetic nephropathy.

Secretory leukocyte protease inhibitor as a novel predictive biomarker in patients with diabetic kidney disease.

Background: Secretory leukocyte protease inhibitor (SLPI) is a multifunctional protein involved in the chronic inflammatory process, implicated in the pathogenesis of diabetic kidney disease (DKD). However, its potential as a diagnostic and prognostic biomarker of DKD has yet to be evaluated. This study explored the clinical utility of SLPI in the diagnosis and prognosis of renal endpoint events in patients with DKD. Methods: A multi-center cross-sectional study comprised of 266 patients with DKD and a predictive cohort study comprised of 120 patients with stage IV DKD conducted between December 2016 and January 2022. The clinical parameters were collected for statistical analysis, a multivariate Cox proportional hazards model was used to evaluate the independent risk factors for renal endpoints. Results: Serum SLPI levels gradually increased with DKD progression (p<0.01). A significant correlation was observed between serum SLPI levels and renal function in patients with DKD. The mean follow-up duration in this cohort study was 2.32 ± 1.30 years. Multivariate Cox regression analysis showed SLPI levels≥51.61ng/mL (HR=2.95, 95% CI[1.55, 5.60], p<0.01), 24h urinary protein levels≥3500 mg/24h (HR=3.02, 95% CI[1.66, 5.52], p<0.01), Alb levels<30g/l (HR=2.19, 95% CI[1.12, 4.28], p<0.05), HGB levels<13g/dl (HR=3.18, 95% CI[1.49, 6.80], p<0.01), and urea levels≥7.1 mmol/L (HR=8.27, 95% CI[1.96, 34.93], p<0.01) were the independent risk factors for renal endpoint events in DKD patients. Conclusions: Serum SLPI levels increased with DKD progression and were associated with clinical parameters of DKD. Moreover, elevated SLPI levels showed potential prognostic value for renal endpoint events in individuals with DKD. These findings validate the results of previous studies on SLPI in patients with DKD and provide new insights into the role of SLPI as a biomarker for the diagnosis and prognosis of DKD that require validation.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

Co-differential genes between DKD and aging: implications for a diagnostic model of DKD.

Objective: Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established a diagnostic model of DKD based on these genes. Methods: Differentially expressed genes (DEGs) in DKD were screened using GEO datasets. The intersection of the DEGs of DKD and aging-related genes revealed DKD and aging co-differential genes. Based on this, a genetic diagnostic model for DKD was constructed using LASSO regression. The characteristics of these genes were investigated using consensus clustering, WGCNA, functional enrichment, and immune cell infiltration. Finally, the expression of diagnostic model genes was analyzed using single-cell RNA sequencing (scRNA-seq) in DKD mice (model constructed by streptozotocin (STZ) injection and confirmed by tissue section staining). Results: First, there were 159 common differential genes between DKD and aging, 15 of which were significant. These co-differential genes were involved in stress, glucolipid metabolism, and immunological functions. Second, a genetic diagnostic model (including IGF1, CETP, PCK1, FOS, and HSPA1A) was developed based on these genes. Validation of these model genes in scRNA-seq data revealed statistically significant variations in FOS, HSPA1A, and PCK1 gene expression between the early DKD and control groups. Validation of these model genes in the kidneys of DKD mice revealed that Igf1, Fos, Pck1, and Hspa1a had lower expression in DKD mice, with Igf1 expression being statistically significant. Conclusion: Our findings suggest that DKD and aging co-differential genes are significant in DKD diagnosis, providing a theoretical basis for novel research directions on DKD.

Study of Neutrophil Gelatinase Associated Lipocalin and Kidney Injury Molecule-1 in Patients with Type 2 Diabetes Mellitus Nephropathy.

BACKGROUND: There is a need for accurate and rapid biomarkers for the early diagnosis of diabetic nephropathy (DN). We aimed to study the accuracy of urinary neutrophil gelatinase-associated lipocalin (uNGAL), urinary kidney injury molecule-1 (uKIM-1), and blood NGAL (bNGAL) in type 2 diabetics as biomarkers for diagnosis of DN. METHODS: The study was a retrospective case-control study that included 30 control subjects, 40 diabetics with normo-albuminuria < 30 mg/g and eGFR > 60 mL/minute/1.73 m2, and 30 diabetics with albuminuria > 30mg/g and eGFR < 60mL/minute/1.73 m2. Blood and urine samples were obtained to determine levels of bNGAL, uNAGAL, and uKIM1. RESULTS: There was a significant increase in bNGAL, uNGAL, uKIM 1, uNGAL/creatinine and uKIM 1/creatinine among diabetics with albuminuria compared to diabetics with normoalbuminuria and normal control (p < 0.001 for all markers). For diagnosis of early DN, both bNGAL and uKIM 1 had sensitivity and specificity of 100% for each at cutoff values of 322.5 pg/mL and 74.25 ng/mL, respectively. uNGAL had a sensitivity of 97.5% and a spec-ificity of 100% at a cutoff point of 565 ng/mL. uKIM1/creatinine at a cutoff of 51.2 had a sensitivity of 100% and specificity of 100%. CONCLUSIONS: The present study highlights the accuracy of urinary KIM1 and NGAL and blood NGAL as biomarkers for the diagnosis of nephropathy in the early stage of diabetic nephropathy. There were positive correlations with kidney function tests creatinine, blood urea nitrogen, and the presence of albuminuria.