Comparative analysis of diabetic nephropathy and non-diabetic nephropathy disease

Development of a clinical automatic calculation of hypoglycemia during hemodialysis risk in patients with diabetic nephropathy

BACKGROUND

Hypoglycemia is one of the most common complications in patients with DN during hemodialysis. The purpose of the study is to construct a clinical automatic calculation to predict risk of hypoglycemia during hemodialysis for patients with diabetic nephropathy.

METHODS

In this cross-sectional study, patients provided information for the questionnaire and received blood glucose tests during hemodialysis. The data were analyzed with logistic regression and then an automated calculator for risk prediction was constructed based on the results. From May to November 2022, 207 hemodialysis patients with diabetes nephropathy were recruited. Patients were recruited at blood purifying facilities at two hospitals in Beijing and Inner Mongolia province, China. Hypoglycemia is defined according to the standards of medical care in diabetes issued by ADA (2021). The blood glucose meter was used uniformly for blood glucose tests 15 minutes before the end of hemodialysis or when the patient did not feel well during hemodialysis.

RESULTS

The incidence of hypoglycemia during hemodialysis was 50.2% (104/207). The risk prediction model included 6 predictors, and was constructed as follows: Logit (P) = 1.505×hemodialysis duration 8~15 years (OR = 4.506, 3 points) + 1.616×hemodialysis duration 16~21 years (OR = 5.032, 3 points) + 1.504×having hypotension during last hemodialysis (OR = 4.501, 3 points) + 0.788×having hyperglycemia during the latest hemodialysis night (OR = 2.199, 2 points) + 0.91×disturbance of potassium metabolism (OR = 2.484, 2 points) + 2.636×serum albumin<35 g/L (OR = 13.963, 5 points)-4.314. The AUC of the prediction model was 0.866, with Matthews correlation coefficient (MCC) of 0.633, and Hosmer-Lemeshow χ2 of 4.447(P = 0.815). The automatic calculation has a total of 18 points and four risk levels.

CONCLUSIONS

The incidence of hypoglycemia during hemodialysis is high in patients with DN. The risk prediction model in this study had a good prediction outcome. The hypoglycemia prediction automatic calculation that was developed using this model can be used to predict the risk of hypoglycemia in DN patients during hemodialysis and also help identify those with a high risk of hypoglycemia during hemodialysis.

Renal Resistive Index: Revisited

Introduction Chronic kidney disease (CKD) is universally considered a public health burden and the majority of cases are found to be diabetic at the time of diagnosis. Renal biopsy is the prime modality for the complete evaluation of renal injuries but is invasive. Duplex Doppler sonography can help to determine renal resistive index (RRI), which is an excellent marker for demonstrating dynamic or structural changes of intrarenal vessels. In this study, we evaluated the intrarenal hemodynamic abnormalities with RRI in diabetic and non-diabetic kidney disease patients. Also, RRI was correlated with the established parameters of renal dysfunction, i.e., estimated glomerular filtration rate (eGFR) and other biochemical parameters. Results There was a significant correlation of RRI with eGFR and serum creatinine indicating its role as a Doppler parameter, which can be used as complementary to biochemical parameters. A remarkable difference was noted in the RRI values between diabetic and non-diabetic groups in the early stages of CKD, revealing its ability to arrive at etiopathogenesis in the early stages. The renal resistive index increases in a sequential pattern and is an indicator of declining renal function. Conclusions The addition of sonographic parameters like renal resistive index could help in the complete evaluation of chronic kidney disease in diabetic and non-diabetic groups. A sequential increase in renal resistive index is a better indicator of the progressive worsening of renal function as opposed to an absolute cut-off value.

Coupling annealed silver nanoparticles with a porous silicon Bragg mirror SERS substrate and machine learning for rapid non-invasive disease diagnosis

Ag₂O-Ag-porous silicon Bragg mirror (PSB) composite SERS substrates were successfully synthesized by using a combination of electrochemical and thermochemical methods. Test results showed that the SERS signal increased and decreased as the annealing temperature used for the substrate increased, where the most intense SERS signal was obtained using a substrate annealed at 300 °C. Stability test results showed substantial enhancement of the SERS signal intensity of the Ag₂O-Ag-PSB composite one month after preparation compared with that of conventional Ag-PSB. We conclude that Ag₂O nanoshells play an essential role in SERS signal enhancement. Ag₂O prevents natural oxidation of Ag nanoparticles (AgNPs) and has a solid localized surface plasmon resonance (LSPR). SERS signal enhancement was tested using this substrate for serum from patients with Sjögren's syndrome (SS) and Diabetic nephropathy (DN), as well as from healthy controls (HC). SERS feature extraction was performed using principal component analysis (PCA). The extracted features were analyzed by a support vector machine (SVM) algorithm. Finally, a rapid screening model for SS and HC, as well as DN and HC, was developed and used to perform controlled experiments. The results showed that the diagnostic accuracy, sensitivity and selectivity for SERS technology combined with machine learning algorithms reached 90.7%, 93.4% and 86.7% for SS/HC and 89.3%, 95.6% and 80% for DN/HC, respectively. The results of this study show that the composite substrate has excellent potential to be developed into a commercially available SERS chip for medical testing.

Sitagliptin ameliorates diabetic nephropathy by upregulating renal nephrin and podocin expression through modulation of adipokines levels

Diabetic nephropathy is the leading cause of end-stage renal failure, but the effectiveness of currently available strategies for preventing diabetic nephropathy remains unsatisfactory. This study was designed to evaluate the changes in adipokines levels caused by dipeptidyl peptidase-4 inhibitor sitagliptin therapy as one of the possible mechanisms of sitagliptin's amelioration of diabetic nephropathy. Twenty-four male Wistar rats weighing 180-200 g were taken and divided into three groups, that is, control, diseased, and treatment group. High-fat diet and streptozotocin-induced Type 2 diabetic rats were divided into diseased and treatment groups. The treatment group was given sitagliptin orally, 10 mg/kg per day for 6 weeks. Serum glucose, serum insulin, serum blood urea nitrogen, serum creatinine, and 24-h urinary protein levels were measured in serum and urine samples. mRNA expression levels of podocin, nephrin, and adipokines in renal tissues were determined. Results showed that sitagliptin treatment effectively reduced serum glucose, serum creatinine, serum blood urea nitrogen, and 24-h proteinuria, along with partial prevention of insulinopenia, in the treatment group as compared to the diseased group. The renal mRNA expression levels of podocin, nephrin, and adiponectin were significantly upregulated, while those of leptin and resistin were significantly downregulated in the diabetic rats receiving sitagliptin therapy compared to the non-treated diabetic rats. Based on these findings, it is suggested that sitagliptin, via mediating the modulation of adipokines levels, upregulates renal nephrin and podocin expression, which leads to the amelioration of diabetic nephropathy.

Analysis of a machine learning-based risk stratification scheme for acute kidney injury in vancomycin

Vancomycin-associated acute kidney injury (AKI) continues to pose a major challenge to both patients and healthcare providers. The purpose of this study is to construct a machine learning framework for stratified predicting and interpreting vancomycin-associated AKI. Our study is a retrospective analysis of medical records of 724 patients who have received vancomycin therapy from 1 January 2015 through 30 September 2020. The basic clinical information, vancomycin dosage and days, comorbidities and medication, laboratory indicators of the patients were recorded. Machine learning algorithm of XGBoost was used to construct a series risk prediction model for vancomycin-associated AKI in different underlying diseases. The vast majority of sub-model performed best on the corresponding sub-dataset. Additionally, the aim of this study was to explain each model and to explore the influence of clinical variables on prediction. As the results of the analysis showed that in addition to the common indicators (serum creatinine and creatinine clearance rate), some other underappreciated indicators such as serum cystatin and cumulative days of vancomycin administration, weight and age, neutrophils and hemoglobin were the risk factors for cancer, diabetes mellitus, heptic insufficiency respectively. Stratified analysis of the comorbidities in patients with vancomycin-associated AKI further confirmed the necessity for different patient populations to be studied.

Transforming Growth Factorβ1 Overexpression Is Associated with Insulin Resistance and Rapidly Progressive Kidney Fibrosis under Diabetic Conditions

Diabetes mellitus is a global health problem. Diabetic nephropathy is a common complication of diabetes mellitus and the leading cause of end-stage renal disease. The clinical course, response to therapy, and prognosis of nephropathy are worse in diabetic than in non-diabetic patients. The role of transforming growth factorβ1 in kidney fibrosis is undebatable. This study assessed whether the overexpression of transforming growth factorβ1 is associated with insulin resistance and the rapid progression of transforming growth factorβ1-mediated nephropathy under diabetic conditions. Diabetes mellitus was induced with streptozotocin in wild-type mice and transgenic mice with the kidney-specific overexpression of human transforming growth factorβ1. Mice treated with saline were the controls. Glucose tolerance and kidney fibrosis were evaluated. The blood glucose levels, the values of the homeostasis model assessment for insulin resistance, and the area of kidney fibrosis were significantly increased, and the renal function was significantly impaired in the diabetic transforming growth factorβ1 transgenic mice compared to the non-diabetic transgenic mice, diabetic wild-type mice, and non-diabetic mice. Transforming growth factorβ1 impaired the regulatory effect of insulin on glucose in the hepatocyte and skeletal muscle cell lines. This study shows that transforming growth factorβ1 overexpression is associated with insulin resistance and rapidly progressive kidney fibrosis under diabetic conditions in mice.

Double Pump Sequential Constant Citrate Anticoagulation in General Hemodialysis

Objective

To investigate the safety and efficacy of single-pump and double-pump sequential anticoagulation in general hemodialysis under the condition of constant citrate.

Methods

A total of 32 patients with end-stage renal disease complicated with hemorrhage admitted by Zigong Third People's Hospital from December 2019 to December 2020 were collected. Randomly divided into single pump group (n = 17) and double pump group (n = 15). The coagulation of dialyzer and intravenous pot was compared between the two groups. Then, the changes of serum calcium before treatment, after 2 h treatment, and after the completion of the treatment, and the front of the blood pump and intravenous pot, as well as behind the intravenous pot were observed and recorded in the two groups. Then, single-pool clearance of urea/volume (spKt/V) was compared between the two groups.

Results

There were few differences in dialyzer coagulation between the single pump group and double pump group. However, the single pump group had a significant increase in the number of intravenous pot coagulations than the double pump group. At 2 h for dialysis, the serum calcium level behind the intravenous pot in the double pump group was notably lower than that in the single pump group. And after the completion of dialysis, the serum calcium returned to pretreatment level. The Kt/v in both groups reached the normal standard without statistically significant difference. And there were no adverse reactions in the patients of both groups after dialysis.

Conclusion

For hemodialysis patients with bleeding, dual-pump segmented anticoagulation is superior to single-pump anticoagulation in intravenous pot anticoagulation. Double pump segmented sequential constant citrate anticoagulation can be utilized as a new simple and effective anticoagulation method for clinical hemodialysis.

Combination of mulberry leaf active components possessed synergetic effect on SD rats with diabetic nephropathy by mediating metabolism, Wnt/β-catenin and TGF-β/Smads signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Mulberry leaf has attracted much attention due to its excellent curative effect on diabetes and its complications, whether the combination of its effective components have protective and synergistic effect on diabetic nephropathy (DN) in vivo remain unclear.

AIM OF THE STUDY

The aim of this study was to investigate the protective and synergistic effect of the combination (MAF_1:1 and MAF_1:5) of mulberry leaf alkaloids (MA) and flavonoids extract (MF) on DN.

MATERIALS AND METHODS

A step by step method consisted of network pharmacological prediction, animal in vivo validation and metabolic mechanism research was used to construct the multi-component-target-pathway network of mulberry leaf against DN. Firstly, the potential components and mechanism of mulberry leaf against DN was explored by network pharmacology analysis. Secondly, DN animal model was established to validate the anti-DN activity of these potential compounds. Thirdly, the metabolomics of serum and urine samples from animal experiments was analyzed to explore the anti-DN mechanism of these potential compounds.

RESULTS

The results of network pharmacology demonstrated that a total of 7 compounds detected in MA and MF exhibited anti-DN activity, their mechanism were strongly in connection with metabolic pathways, arachidonic acid metabolism, sphingolipid signaling pathway, etc. The results of animal experiment indicated that MAF_1:1 and MAF_1:5 significantly relieved metabolic disorders through regulating Wnt/β-catenin and TGF-β/Smads signaling pathway, just like MF or MA alone. Metabolomics suggested they could regulate 16 serum and 7 urine endogenous metabolites through arachidonic acid metabolism, phenylalanine metabolism and sphingolipid metabolism, thus alleviated DN. Significantly, MAF_1:1 and MAF_1:5 might possess synergistic effect considering their therapeutic effects on DN rats were superior to the single use of MA or MF.

CONCLUSIONS

MAF_1:1 and MAF_1:5 possessed protective and synergistic effect on DN rats through multi-target and multi-pathways. These findings were of great scientific significance and application value to reveal the advantage of mulberry leaf in preventing and treating DN.

Urinary sediment microRNAs can be used as potential noninvasive biomarkers for diagnosis, reflecting the severity and prognosis of diabetic nephropathy

BACKGROUND

Patients with both diabetes mellitus (DM) and kidney disease could have diabetic nephropathy (DN) or non-diabetic renal disease (NDRD). IgA nephropathy (IgAN) and membranous nephropathy (MN) are the major types of NDRD. No ideal noninvasive diagnostic model exists for differentiating them. Our study sought to construct diagnostic models for these diseases and to identify noninvasive biomarkers that can reflect the severity and prognosis of DN.

METHODS

The diagnostic models were constructed using logistic regression analysis and were validated in an external cohort by receiver operating characteristic curve analysis method. The associations between these microRNAs and disease severity and prognosis were explored using Pearson correlation analysis, Cox regression, Kaplan-Meier survival curves, and log-rank tests.

RESULTS

Our diagnostic models showed that miR-95-3p, miR-185-5p, miR-1246, and miR-631 could serve as simple and noninvasive tools to distinguish patients with DM, DN, DM with IgAN, and DM with MN. The areas under the curve of the diagnostic models for the four diseases were 0.995, 0.863, 0.859, and 0.792, respectively. The miR-95-3p level was positively correlated with the estimated glomerular filtration rate (p < 0.001) but was negatively correlated with serum creatinine (p < 0.01), classes of glomerular lesions (p < 0.05), and scores of interstitial and vascular lesions (p < 0.05). However, the miR-631 level was positively correlated with proteinuria (p < 0.001). A low miR-95-3p level and a high miR-631 level increased the risk of progression to end-stage renal disease (p = 0.002, p = 0.011).

CONCLUSIONS

These four microRNAs could be noninvasive tools for distinguishing patients with DN and NDRD. The levels of miR-95-3p and miR-631 could reflect the severity and prognosis of DN.

The potential risk factors of nephrotoxicity during vancomycin therapy in Chinese adult patients

OBJECTIVE

To evaluate potential risk factors that may make patients susceptible to nephrotoxicity in those concomitantly receiving vancomycin in the hospital.

METHODS

This was a single-centre retrospective analysis of patients treated with vancomycin for gram-positive or mixed infections in the Renmin Hospital of Wuhan University from January 2017 to May 2018. All of them were treated for ≥48 hours and had no kidney disease. Nephrotoxicity refers to acute kidney diseases and disorders after the use of vancomycin, and includes acute kidney injury. Univariate analysis and binary logistic regression analysis with the forward stepwise method were used to assess the risk factors associated with nephrotoxicity.

RESULTS

Of the 790 patients treated with vancomycin, only 257 patients met the inclusion criteria, and 40 (15.6%) subjects developed nephrotoxicity. Significant differences (p<0.05) were seen in the number of combined antimicrobials (p=0.012), dose adjustment (p<0.001), more than three antimicrobials (p=0.015), monitoring trough concentrations (p=0.001), furosemide (p<0.001), torasemide (p<0.001), cefoperazone sodium tazobactam sodium (p=0.039), voriconazole (p=0.012) and ganciclovir (p=0.008). Regression analysis further indicated that furosemide (OR 7.983, p<0.001) and torasemide (OR 3.496, p<0.001) were risk factors for vancomycin nephrotoxicity. Diabetes mellitus (OR 3.062, p=0.035), voriconazole (OR 3.515, p=0.020) and fluconazole (OR 3.326, p=0.018) might be also risk factors.

CONCLUSION

Fluconazole and voriconazole might be potential risk factors for vancomycin nephrotoxicity, besides furosemide and torasemide. It is not recommended to use imipenem cilastatin sodium and vancomycin at the same time. If necessary, meropenem may be safer. Appropriate combination drugs, cautious initial dose or timely dose adjustment might reduce the occurrence of nephrotoxicity when using vancomycin.