Diagnosis Of Diabetic Disease Research Articles

Relaxation intervention to improve diabetic foot ulcer healing: protocol for a pilot study with a nested qualitative study.

A mixed-methods approach nested in a pilot three-arm randomised controlled trial (RCT) was conducted to evaluate the feasibility and acceptability of an intervention of progressive muscle relaxation with guided imagery (experimental group) compared to a neutral guided imagery placebo (active control group) and a group that did not receive any psychological intervention (passive control group). The purpose was to inform a future definitive RCT that will test its effectiveness. Qualitatively, this study examined patients and health professionals' perspectives regarding the relaxation intervention, in order to assess the acceptability and applicability of relaxation as an adjuvant therapy. Participants must have had a diagnosis of diabetes and diabetic foot disease; one or two active hard-to-heal ulcers at the time of the assessment; and clinical levels of stress or anxiety or depression. Participants were randomised and assessed at three timepoints after the first hospital consultation for hard-to-heal diabetic foot ulcer (DFU). Rates of eligibility, recruitment, refusal, adherence to study protocol, participation in follow-up and dropout, and patients' satisfaction with the relaxation intervention were assessed as primary outcomes. Secondary outcomes were DFU healing; patients' DFU-related quality of life; physical and mental quality of life; perceived stress; emotional distress; adherence to DFU care; perceptions of DFU; as well as arterial systolic/diastolic pressure and heart rate. The results of this pilot study contributed to clarification and better elucidation of the benefits of relaxation techniques regarding patients' HRQoL and DFU healing. Funding: This study was conducted at the Psychology Research Centre (CIPsi/UM) School of Psychology, University of Minho, Portugal and supported by the Foundation for Science and Technology (FCT) through the Portuguese State Budget (UIDB/01662/2020) and by a PhD fellowship from FCT assigned to GF (SFRH/BD/131780/2017) and an FCT grant (PTDC/PSI-GER/28163/2017) assigned to MGP. The authors have no conflicts of interest to declare.

Monoclonal immunoglobulin deposition disease a spectrum? The treatment of an unusual biopsy presentation

Introduction: Monoclonal gammopathy of renal significance (MGRS) is characterized by clonal cell deposition of monoclonal immunoglobulin causing renal manifestations without overt malignancy. MIDD is a subtype of MGRS characterized by deposition of monoclonal light (LCDD), heavy chains (HCDD), or both (LHCDD) along the renal glomerular and tubular basement membranes. Virtually all organs can be involved, and if left untreated, MIDD can progress to MM and end stage renal disease. Although these patients classically did not receive treatment, current MIDD management is primarily focused on controlling the underlying clonal plasma cell disorder. Case description: We present a 56-year-old male with atypical MIDD treated successfully with plasma cell directed therapy consisting of daratumumab, cyclophosphamide, bortezomib, and dexamethasone (DARA-CYBOR-D). Despite a primary diagnosis of diabetic kidney disease, renal biopsy suggested myeloma-related MIDD based on linear immunofluorescent staining for IgG and kappa light chains along the tubular and glomerular basement membranes. Notably there were no electron dense deposits in the mesangium or tubular basement membranes typical to MIDD electron microscopy. Despite the presentation of MIDD on IF only, DARA-CYBOR-D treatment led to hematologic and renal improvement and remission from MIDD, with a GFR increase from 22 to 59 mL/min/BSA and a drop in urine protein from up to 9 to 0.6 g/dL. Conclusions: In conclusion, our case illustrates the efficacy of the DARA-CYBOR-D regimen in a patient with IF-only MIDD. We highlight the importance of obtaining a kidney biopsy when there are other potential causes for real decline and enhance our understanding of pathological and clinical spectrum of MIDD.

#1669 Gangliosides as biomarkers for early diagnosis of diabetic kidney disease: detection and characterization by high-performance mass spectrometry

Abstract Background and Aims The early identification of diabetic kidney disease (DKD) is crucial as it may facilitate immediate intervention, thus impeding the progression of the condition and the risk of developing end-stage renal disease (ESRD). Enhancing our understanding of the pathophysiology of this microvascular complication as well as developing therapeutic strategies are imperative. Hence, the aim of the current study was to address the problematics of detection and characterization of gangliosides in the urine of type 2 diabetes mellitus (DM) patients with DKD. Method In this cross-sectional study, the urine ganglioside content from 24 h collected urine samples of 60 type 2 DM patients (20 with normal to mildly increased albuminuria—A1 group, 20 with moderately increased albuminuria—A2 group, 20 with severe increased albuminuria—A3 group) was compared to that of 20 healthy controls using a promising technique based on high-resolution (HR) mass spectrometry (MS). Furthermore, for structural elucidation of individual compounds, we isolated the ions GT1 (d18:1/18:0), identified at m/z 708.3379 and, GQ1 (d18:1/18:0) at m/z 812.7068, observed only in the screening analysis of A3 patients, and exposed them to Higher-energy collisional dissociation (HCD MS/MS) in the negative ion mode. Results Patients with type 2 diabetes mellitus display a considerably greater abundance of different species in their urinary gangliosidome, which varies in either glycan or ceramide structure, in comparison to the control group. Even within the A1 group, a greater variety of structures exhibiting varying degrees of sialylation were observed. A wide range of carbohydrate chains were discovered, ranging from short, monosialylated chains (GM) to complex, pentasialylated chains (GP). Additionally, some ganglioside chains were modified with and O-acetyl (O-Ac) attachments. The gangliosidome of the A3 group comprises a higher variety of structures, compared to A1 and A2, differing in their overall sialic acid content, and more complex structures, including various biologically significant modifications, such as O-fucosylation, O-GalNAc and CH3COO− attachments. Both albuminuria and glomerular filtration rate proved to be correlated with the degree of sialylation of species. Furthermore, significant alterations occur also in the ceramide part, with the most noteworthy being the presence of sphingoid base trihydroxylation, which is shown in both A1 and A3 samples. Additionally, A3 exhibits unusual length of the fatty acid chains. GQ1d(d18:1/18:0), GT1α(d18:1/18:0), and GT1b(d18:1/18:0) were identified as predictive for specific isomers linked to the location of Neu5Ac along the oligosaccharide structure using HCD-based MS/MS. Conclusion We concluded that gangliosides may be involved in the development and progression of DKD through the use of mass spectrometry techniques, which provides considerable precision and ultrahigh reproducibility, sensitivity and processing power, and the capability to identify minor elements in complex biological matrices. Thus, a set of promising bioindicators for early detection and progression of DKD was established. Even in the normoalbuminuric stage, the sialylation level of the expressed species appears to be an extremely important biochemical marker of DKD. Moreover, the modifications detected in the composition of ceramide indicate that, alongside the oligosaccharide structure, the lipid component might function as a specific molecular indicator for different stages of DKD. The presence of a few isomers in the A3 group has been discovered to be associated with DKD progression, based on the informative sequence ions obtained from the structural analysis. Moreover, gangliosides might be used as target molecules for the implementation of therapeutic schemes in type 2 DM patients.

#1861 Association of the polymorphisms of the angiotensin converting enzyme and FRMD3 genes in the development of diabetic kidney disease

Abstract Background and Aims Individual genetic biomarkers, called single nucleotide polymorphisms (SNPs), have been proposed that could represent potential non-invasive markers for the early diagnosis of diabetic kidney disease (DKD), in addition to their association with a characteristic phenotype. Aim To determine the association of polymorphisms of the Angiotensin Converting Enzyme and FRMD3 genes with the risk of developing ERD in patients with type 2 diabetes. Method Case-control study, comparative, observational, ambispective and cross-sectional, in which men and women, over 18 years of age with T2D with and without ERD and healthy patients, who underwent DNA extraction, participated. genomic and subsequent genotyping, and detection of SNPs by mass spectrometry. Results A total of 400 patients participated, 199 men and 201 women, within which they were divided into three groups: 100 patients with type 2 diabetes and ERD confirmed by renal biopsy, 100 patients with type 2 diabetes without ERD and 200 healthy controls. A total of 3 polymorphisms of the ACE and FRMD3 genes were studied. Among the polymorphisms analyzed in the logistic regression, rs179975 CA (OR, 6.2; 95% CI: 1.15-7.48, p = 0.03), rs1888747 GA (OR, 6.6; 95% CI: 4.60-8.45, p = 0.002) and rs10868025 resulted. CG (OR, 4.1; 95% CI: 2.40-5.60, p = 0.002) Table 1. Conclusion Our study demonstrated the association of well-established genetic variants of the ACE and FRMD3 gene polymorphisms with the presence of ERD, showing that these SNPs, specifically rs179975 CA, rs1888747 GA and rs10868025 GC, may represent important genetic markers in the development of ERD and could be a predisposing factor due to the high frequency and strength of association that were observed in our studied population, this being the first study in Latin America.

Addressing the growing burden of obesity, diabetes and asthma in children and adolescents: The role of primary health care and the WHO Pocket book in Europe for a healthy future

The burden of obesity, diabetes mellitus and asthma remains a significant public health issue worldwide. These conditions are associated with premature deaths and a reduced quality of life. Primary health care plays a key role in the prevention, detection, and management of noncommunicable diseases in childhood, including diabetes and asthma. Health promotion is crucial for a healthy life from early childhood, preventing from obesity, a sedentary lifestyle, exposure to tobacco smoke, and other risk factors associated to noncommunicable diseases. Asthma and type 1 diabetes mainly begin in childhood; thus, recognition and early detection at the primary health care level are essential. In the long term, management of children with chronic diseases requires regular follow-up and cooperation with a specialized team. Care coordination by the primary health care provider is key for optimal control of the disease and development of the child or adolescent in the physical, emotional, and social spheres. Over-referral for diagnosis and follow-up is associated with unnecessary specialist overload, patient anxiety, and financial burden for the families and the health system. Clear criteria and referral pathways with efficient communication between the professional team members are essential to empower primary health care providers, avoid unnecessary referrals, and optimize the care and quality of life of children and adolescents with chronic diseases.The WHO Pocket book of primary health care for children and adolescents was recently developed to address knowledge gaps and improve the diagnosis and management of children and adolescents at the outpatient level. It dedicates an entire chapter to health promotion and disease prevention with counselling messages addressed to children, adolescents and their families; provides guidance for the diagnosis and management of asthma, diabetes and other chronic diseases; and includes additional considerations for adolescents living with chronic conditions.

The impact of lifestyle, measured with the HLPCQ questionnaire on the prevalence of metabolic syndrome in Poland: a multicenter study

Metabolic syndrome is one of the most common health problems for people around the world. The aim of our study was to assess the prevalence of metabolic syndrome among adults without prior diagnosis of cardiovascular disease, diabetes, and chronic kidney disease. We also plan to assess the influence of certain lifestyle components on prevalence of metabolic syndrome. The study involved cardiovascularly healthy patients undergoing lab tests, measurements, and the HLPCQ questionnaire (The Healthy Lifestyle and Personal Control Questionnaire). The data were used to diagnose metabolic syndrome. Out of 1044 patients from 10 primary care facilities, 23.3% met the metabolic syndrome criteria, showing a strong link with increased blood pressure, cholesterol, and fasting glucose. Lower scores in the Organized physical exercise subscale of the HLPCQ questionnaire were noted in those with metabolic syndrome. Comparing the subscale of HLPCQ questionnaire, the lower results in Organized physical exercise subscale were found among the participants with metabolic syndrome, both male and females. Metabolic syndrome, a significant risk factor for cardiovascular disease, should be screened for actively, even in apparently healthy populations. Results obtained in our study from analysis of HLPCQ show that screening for metabolic syndrome should be preceded by prevention based on regular physical activity and proper eating habits.

Retinal vascular density as a potential biomarker of diabetic cerebral small vessel disease.

The retina and brain share similar anatomical and physiological features. Thus, retinal imaging by optical coherence tomography angiography (OCTA) might be a potential tool for the early diagnosis of diabetic cerebral small vessel disease (CSVD). In this study, we aimed to evaluate retinal vascular density (VD) in diabetic CSVD by OCTA imaging and explore the associations between retinal VD and cerebral magnetic resonance imaging (MRI) markers and cognitive function. In total, 131 patients were enrolled, including CSVD (n = 43) and non-CSVD groups (n = 88). The VD and foveal avascular zone of the retinal capillary plexus were measured with OCTA. A brain MRI was performed. MRI imaging showed that in the diabetic CSVD group, white matter hyperintensities (WMHs), particularly deep WMHs (58.82%), are the most common MRI marker, followed by cerebral microbleeds in the subtentorial and cortical areas (34.78%). The CSVD group showed increases in the prevalence of cognitive dysfunction (p = .034) and depression (p = .033) and decreases in visuospatial/executive ability and delayed recall ability. In the CSVD group, VDs of the macular superficial vascular plexus (32.93 ± 7.15% vs. 36.97 ± 6.59%, p = .002), intermediate capillary plexus (20.87 ± 4.30% vs. 23.08 ± 4.30%, p = .005) and deep capillary plexus (23.54 ± 5.00% vs. 26.05 ± 4.20%, p = .003) were lower than those of the non-CSVD group. Multiple linear regression analysis showed that VD of the macular superficial vascular plexus was independently associated with cerebral microbleeds. Meanwhile, VD of the macular intermediate capillary plexus was associated with white matter lacunar infarcts after adjustment. Diabetic CSVDs are characterized by MRI markers, including deep WMHs and cerebral microbleeds, and showed impaired cognition with decreased visuospatial/executive ability and delayed recall ability. OCTA imaging revealed a significant decrease in retinal microvascular perfusion in diabetic CSVD, which was related to MRI markers and cognitive function. OCTA might be a valuable potential measurement for the early diagnosis of CSVD.

The predictive value of miR-377 and phospholipase A2 in the early diagnosis of diabetic kidney disease and their relationship with inflammatory factors

ObjectiveThe value of novel biomarkers for DKD has received increasing attention, and there is an urgent need for novel biomarkers with sensitivity, specificity and ability to detect kidney damage.miR-377 regulates many basic biological processes, plays a key role in tumor cell proliferation, migration and inflammation, and can also increase the expression of matrix proteins and fibronectin, leading to renal tubulointerstitial inflammation and renal fibrosis. Lipoprotein-associated phospholipase A2, as an inflammatory marker, is involved in the pathological process of microalbuminuria production and renal function decline, and is a predictive factor of microalbuminuria production and renal function decline, and can be used as an indicator to evaluate the progression of DKD.The aim of this study was to investigate the effects of miR-377 and phospholipase A2 on the development of diabetic kidney disease through regulation of inflammatory factors and the mechanism of action.Methods: 80 diabetic patients were divided into two groups according to urinary albumin-to-creatinine ratio (UACR): diabetic normal proteinuria group (n = 42) and diabetic proteinuria group (n = 38). Forty-three healthy people were selected as the normal control group. The serum levels of TGF-β, IL-6, and IL-18 were measured by ELISA, miR-377 was detected by qPCR, and the serum levels of phospholipase A2 were detected by electrochemiluminescence. Analyze the correlation of study group indicators, ROC curve was used to evaluate the diagnostic efficacy of miR-377 and phospholipase A2 in diabetic kidney disease. Results: The average levels of serum TGF-β, IL-6, IL-18, miR-377 and phospholipase A2 in diabetic proteinuria group were significantly higher than those in normal control group and diabetic proteinuria normal group(P < 0.05). miR-377, phospholipase A2 were significantly correlated with inflammatory factors such as glomerular filtration rate and TGF-β. miR-377 and phospholipase A2 are independent predictors of diabetic kidney disease. The area under the curve of miR-377 and phospholipase A2 in the normal diabetic proteinuria group and the diabetic proteinuria group were 0.731 and 0.744, respectively. Conclusion: miR-377 and phospholipase A2 have good diagnostic efficiency for the early diagnosis of diabetic kidney disease. They can be used as early biomarkers.miR-377 and phospholipase A2 were positively correlated with inflammatory factors and involved in the occurrence and development of diabetic kidney disease.

The role of the albumin-to-creatinine ratio in the diagnosis of diabetic kidney disease (literature review and own findings)

Based on our own practical experience and data from scientific literature, we can assert that measuring the ratio of albumin to creatinine and calculating the glomerular filtration rate are important tools for the timely diagnosis of chronic kidney disease (CKD), monitoring treatment effectiveness, and determining the dynamics of a patient’s renal condition. Early diagnosis of CKD allows us to take necessary measures to slow down or even halt the progression of the disease. By timely administering nephroprotective drugs, such as SGLT-2 inhibitors, we can improve the prognosis and quality of life for patients, which holds medical, social, and economic significance.

RCAR-UNet: Retinal vessel segmentation network algorithm via novel rough attention mechanism

The health status of the retinal blood vessels is a significant reference for rapid and non-invasive diagnosis of various ophthalmological, diabetic, and cardio-cerebrovascular diseases. However, retinal vessels are characterized by ambiguous boundaries, with multiple thicknesses and obscured lesion areas. These phenomena cause deep neural networks to face the characteristic channel uncertainty when segmenting retinal blood vessels. The uncertainty in feature channels will affect the channel attention coefficient, making the deep neural network incapable of paying attention to the detailed features of retinal vessels. This study proposes a retinal vessel segmentation via a rough channel attention mechanism. First, the method integrates deep neural networks to learn complex features and rough sets to handle uncertainty for designing rough neurons. Second, a rough channel attention mechanism module is constructed based on rough neurons, and embedded in U-Net skip connection for the integration of high-level and low-level features. Then, the residual connections are added to transmit low-level features to high-level to enrich network feature extraction and help back-propagate the gradient when training the model. Finally, multiple comparison experiments were carried out on three public fundus retinal image datasets to verify the validity of Rough Channel Attention Residual U-Net (RCAR-UNet) model. The results show that the RCAR-UNet model offers high superiority in accuracy, sensitivity, F1, and Jaccard similarity, especially for the precise segmentation of fragile blood vessels, guaranteeing blood vessels’ continuity.

Diagnosis and management of diabetic kidney disease–Part 1

This first of two articles seeks to explain the nature, classification and clinical implications of diabetic kidney disease. The importance of screening and monitoring is discussed. Practical information on avoidance of acute kidney injury and criteria for referral of diabetic kidney disease are covered. By David Morris

FRI434 Long-term Self-reported Outcomes Of Randomized Testosterone (T) vs Placebo (P) Treatment In The T4DM Study

Abstract Disclosure: D.J. Handelsman: None. M. Grossmann: None. B.B. Yeap: Consulting Fee; Self; Bayer, Inc., Lawley. Research Investigator; Self; Lawley. B.G. Stuckey: Speaker; Self; Lawley. N. Shankara-Narayana: None. A.J. Conway: None. W. Inder: None. R.I. McLachlan: None. C.A. Allan: None. A. Jenkins: None. D.R. Jesudason: None. K. Bracken: None. K. Robledo: None. G.A. Wittert: Research Investigator; Self; Bayer, Inc., Lilly USA, LLC. The T4DM study randomized 1007 men (age 50-74 yr, waist ≥95 cm, serum T ≤14.0 nmol/L, no pathological hypogonadism) with impaired glucose tolerance or newly diagnosed type 2 diabetes to T undecanoate (1000 mg) or matching placebo injections every 12 weeks for 24 months with a lifestyle program. At study’s end, T treatment reduced OGTT diabetes diagnosis by 40% without change in HbA1C. After a median of 5 years since last injection, a follow-up email survey obtained 705 responses (70%) comprising 599 completed surveys (316 T, 283 P, 10 deceased, 95 declining). Participants in follow-up survey were similar to non-participants in 23 anthropometric and demographic variables at entry to T4DM, but more in follow-up study were randomized to T (53 vs 46%%, p=0.038), had lower entry weight (107 vs 109 kg, p=0.026) and older school leaving age (16.7 vs 16.5 years, p=0.026) but remaining well matched for work status (46% retired, 35% full-time work, p=0.60), alcohol intake (69% nil or light, 3% heavy; p=0.12) and smoking (3% smoking, p=0.61). At long-term follow-up, randomization to T treatment was associated with stronger belief in benefits during study (64% vs 49%, p&amp;lt;0.001) with less for post-study benefits (44% vs 40%, p=0.07) but overall high interest in future studies (surveys 93%, clinical 76%). At entry, 35% had sleep apnea, most (71%) diagnosed pre-study, with new diagnosis more frequent on T during (9% vs 1%, p=0.03), but not before or after, the study. After study, T treatment was prescribed at a higher rate for men who had study T treatment (6% vs 2.8%, p=0.03), mostly using T injections with 81% continuing at 24 months (median) on post-study T treatment. In the long-term, study T treatment did not influence self-reported new post-T4DM study diagnosis of diabetes (19%, p=0.65) or diabetes drug treatments (22%, p=0.31; oral 18%, injectable 2%, both 2%), prostate disease (p=0.49; cancer 3%, non-cancer 8%) or cardiovascular disease (p=0.95; heart disease 13%, stroke 1%). Both groups had similar weight maintenance (maintained 24%, lost 22%, gain 24%, up/down 30%, p=0.91) and further attempts to lose weight (76%, p=0.29; diet 68%, exercise 57%, drugs 6%, surgery 2%). We conclude that randomized T (vs placebo) treatment for 24 months in men with impaired glucose tolerance or new diabetes but without pathological hypogonadism, was associated with higher rates of (a) self-reported benefits during, but not after the study, (b) of resuming T treatment after the study, consistent with androgen dependence due to withdrawal (androgen deficiency) symptoms and/or recalling perceived benefits of study T treatment, and (c) of sleep apnea diagnosis during, but not before or after the study. Five years after T treatment stopped, there was no difference in the long-term rates of self-reported new diagnosis of diabetes, prostate or cardiovascular disease nor change in weight maintenance or weight loss behaviors. Presentation: Friday, June 16, 2023

Active role of amino acid metabolism in early diagnosis and treatment of diabetic kidney disease.

Diabetic Kidney Disease (DKD) is one of the significant microvascular consequences of type 2 diabetes mellitus with a complex etiology and protracted course. In the early stages of DKD, the majority of patients experience an insidious onset and few overt clinical symptoms and indicators, but they are prone to develop end-stage renal disease in the later stage, which is life-threatening. The abnormal amino acid metabolism is tightly associated with the development of DKD, which involves several pathological processes such as oxidative stress, inflammatory response, and immune response and is also closely related to autophagy, mitochondrial dysfunction, and iron death. With a focus on taurine, branched-chain amino acids (BCAAs) and glutamine, we explored the biological effects of various amino acid mechanisms linked to DKD, the impact of amino acid metabolism in the early diagnosis of DKD, and the role of amino acid metabolism in treating DKD, to offer fresh objectives and guidelines for later early detection and DKD therapy.

Diagnosis of diabetic kidney disease in whole slide images via AI-driven quantification of pathological indicators

Diagnosis of diabetic kidney disease (DKD) mainly relies on screening the morphological variations and internal lesions of glomeruli from pathological kidney biopsy. The prominent pathological alterations of glomeruli for DKD include glomerular hypertrophy and nodular mesangial sclerosis. However, the qualitative judgment of these alterations is inaccurate and inconstant due to the intra- and inter-subject variability of pathologists. It is necessary to design artificial intelligence (AI) methods for accurate quantification of these pathological alterations and outcome prediction of DKD. In this work, we present an AI-driven framework to quantify the volume of glomeruli and degree of nodular mesangial sclerosis, respectively, based on an instance segmentation module and a novel weakly supervised Macro-Micro Aggregation (MMA) module. Subsequently, we construct classic machine learning models to predict the degree of DKD based on three selected pathological indicators via factor analysis. These corresponding modules are trained and tested on a total of 281 whole slide images (WSIs) digitized from two hospitals with different scanners. Our designed AI framework achieved inspiring results with 0.926 mIoU for glomerulus segmentation, and 0.899 F1 score for glomerulus classification in the external testing dataset. Meantime, the visualized results of the MMA module could reflect the location of the lesions. The performance of predicting disease achieved the F1 score of 0.917, which further proved the effectiveness of our AI-driven quantification of pathological indicators. Additionally, the interpretation of the machine learning model with the SHAP method showed similar accordance with the development of DKD in pathology. In conclusion, the proposed auxiliary diagnostic technologies have the feasibility for quantitative analysis of glomerular pathological tissues and alterations in DKD. Pathological quantitative indicators will also make it more convenient to provide doctors with assistance in clinical practice.

DBAN: An improved dual branch attention network combined with serum Raman spectroscopy for diagnosis of diabetic kidney disease

Diabetic kidney disease (DKD) is one of the most common kidney diseases worldwide. It is estimated that approximately 537 million adults worldwide have diabetes, and up to 30%–40% of diabetic patients are at risk of developing nephropathy. The pathogenesis of DKD is complex, and its onset is insidious. Currently, the clinical diagnosis of DKD primarily relies on the increase of urinary albumin and the decrease in glomerular filtration rate in diabetic patients. However, the excretion of urinary albumin is influenced by various factors, such as physical activity, infections, fever, and high blood glucose, making it challenging to achieve an objective and accurate diagnosis. Therefore, there is an urgent need to develop an efficient, fast, and low-cost auxiliary diagnostic technology for DKD. In this study, an improved Dual Branch Attention Network (DBAN) was developed to quickly identify DKD. Serum Raman spectroscopy samples were collected from 32 DKD patients and 32 healthy volunteers. The collected data were preprocessed using the adaptive iteratively reweighted penalized least squares (airPLS) algorithm, and the DBAN was used to classify the serum Raman spectroscopy data of DKD. The model consists of a dual branch structure that extracts features using Convolutional Neural Network (CNN) and bottleneck layer modules. The attention module allows the model to learn features specifically, and lateral connections are added between the dual branches to achieve multi-level and multi-scale fusion of shallow and deep features, as well as local and global features, improving the classification accuracy of the experiment. The results of the study showed that compared to traditional deep learning algorithms such as Artificial Neural Network (ANN), CNN, GoogleNet, ResNet, and AlexNet, our proposed DBAN classification model achieved 95.4% accuracy, 98.0% precision, 96.5% sensitivity, and 97.2% specificity, demonstrating the best classification performance. This is the best method for identifying DKD, and has important reference value for the diagnosis of DKD patients, as well as improving the accuracy of medical auxiliary diagnosis.

Clinical value of miR-23a-3p expression in early diagnosis of diabetic kidney disease.

The objective was to observe the expression of miR-23a-3p in the serum of patients with type 2 diabetic nephropathy (T2DN) and to explore its clinical significance. 112 patients with type 2 diabetes were divided into a simple diabetes mellitus (NON) group, T2DN microalbuminuria (MIC) group, and T2DN macroalbuminuria (MAC) group, according to the urinary protein-creatinine ratio (uACR). Clinical data were collected, miR-23a-3p levels in serum were measured by quantitative reverse transcription polymerase chain reaction (qRT-PCR), and clinical parameters were measured by an automatic biochemical analyser; the influencing factors of diabetic kidney disease (DKD) and the correlation between miR-23a-3p expression and clinical parameters were analysed. The expression of miR-23a-3p in the serum of the DKD group was lower than that of the normal control (CON) and NON groups. Correlation analysis showed that miR-23a-3p was positively correlated with urinary albumin (Albu), glycosylated haemoglobin (HbA1c), total cholesterol (CHOL), glycated albumin (GA-L), serum creatinine (Scr), fasting blood glucose (GLU), and uric acid (UA), negatively correlated with uACR and high-density lipoprotein cholesterol (HDL-C), but not correlated with urinary creatinine (CREA). The area under the receiver operating characteristic (ROC) curve (AUC) of miR-23a-3p for the diagnosis of DKD was 0.686 [95% confidence interval (CI): 0.599-0.773], with a sensitivity of 64.5% and a specificity of 71.2%; the AUC for differentiating NON from DKD was 0.700 (95% CI: 0.598-0.802), with a sensitivity of 61.8% and a specificity of 77.8%. Multivariate logistic regression analysis showed that serum miR-23a-3p levels were not associated with the development of DKD after adjusting for other levels of influence and were not significant for the differentiation of NON and DKD. Serum miR-23a-3p levels are decreased in T2DN patients, and this change becomes more significant with the severity of the disease, which may be a marker for the early diagnosis and progression of T2DN.

The Diagnostic Performance of a Clinical Diagnosis of Diabetic Kidney Disease.

Diabetic kidney disease (DKD), a common cause of CKD and kidney failure, is usually diagnosed clinically. However, there is little evidence comparing the performance of a clinical diagnosis to biopsy-proven diagnosis. Diagnostic performance of a clinical diagnosis was determined in a group of patients with diabetes and chronic kidney disease who underwent kidney biopsy after an initial clinical diagnosis. A data analysis of 54 patients who were part of a study cohort for a prospective analysis of cardiovascular and kidney outcomes and who had undergone kidney biopsy after an initial clinical diagnosis of DKD or non-DKD (NDKD) at enrolment was used. We determined the sensitivity, specificity, and positive and negative predictive values of a clinical diagnosis of DKD. A total of 37 of 43 patients clinically diagnosed with DKD also had biopsy-proven DKD, whilst only 1 of 11 patients who had clinically diagnosed NDKD had biopsy-proven DKD. Sensitivity was 97.4%, specificity was 62.5%, positive predictive value 86%, and negative predictive value 90.9%. Comparable values were obtained when analysis was restricted to those with primary rather than secondary diagnosis of DKD or when restricted to those with only DKD found at biopsy. A clinical diagnosis of DKD has high sensitivity and is unlikely to overlook cases but may lead to overdiagnosis.

The role of tubulointerstitial markers in differential diagnosis and prognosis in patients with type 2 diabetes and biopsy proven diabetic kidney disease

ObjectiveTo evaluate the potential application of tubularinterstitial biomarkers in the differential diagnosis of diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD), as well as investigate key clinical and pathological parameters to help improve the stratification of patients according to end-stage renal disease risk. Methods132 type 2 diabetic patients with chronic kidney disease were enrolled. Patients were categorized into 2 groups according to the renal biopsy results: DKD (n = 61) and NDKD (n = 71).The independent factors of the occurrence of DKD and the diagnostic implications of tubular biomarkers were explored by logistic regression and receiver-operating characteristic curve analysis. Furthermore, predictors were analyzed by least absolute shrinkage and selection operator regression, and constructed a new model for predicting the unfavorable renal outcomes through Cox proportional hazard regression analysis. ResultsSerum neutrophil gelatinase-associated lipocalin (sNGAL) (OR = 1.007; 95%CI = [1.003, 1.012], p = 0.001) was identified as an independent risk factor for the occurrence of DKD in diabetic patients with CKD. Tubular biomarkers including sNGAL, N-acetyl-β-D-glucosaminidase and β2 microglobulin (β2-MG) could complement albuminuria for DKD detection (AUC = 0.926, specificity = 90.14%, sensitivity = 80.33%).Moreover, among of the 47 variables, 4 predictors such as sNGAL, interstitial fibrosis and tubular atrophy (IFTA)score, β2-MG and estimated glomerular filtration rate were selected to construct a new model for predicting the unfavorable renal outcomes through regression analysis. sNGAL (HR = 1.004; 95%CI = [1.001, 1.007], p = 0.013), IFTA score of 2 (HR = 4.283; 95%CI = [1.086, 16.881], p = 0.038), and IFTA score of 3 (HR = 6.855; 95%CI = [1.766, 26.610], p = 0.005) were considered to be independent risk factors for unfavorable renal outcomes. ConclusionsTubulointerstitial injury in DKD is independently associated with renal function decline and routinely detected tubular biomarkers are able to enhance the level of non-invasive diagnosis of DKD beyond traditional factors.

Trends of Concomitant Diabetes and Peripheral Artery Disease and Lower Extremity Amputation in US Medicare Patients, 2007 to 2019.

Previous studies demonstrate geographic and racial/ethnic variation in diagnosis and complications of diabetes and peripheral artery disease (PAD). However, recent trends for patients diagnosed with both PAD and diabetes are lacking. We assessed the period prevalence of concurrent diabetes and PAD across the United States from 2007 to 2019 and regional and racial/ethnic variation in amputations among Medicare patients. Using Medicare claims from 2007 to 2019, we identified patients with both diabetes and PAD. We calculated period prevalence of concomitant diabetes and PAD and incident cases of diabetes and PAD for every year. Patients were followed to identify amputations, and results were stratified by race/ethnicity and hospital referral region. 9 410 785 patients with diabetes and PAD were identified (mean age, 72.8 [SD, 10.94] years; 58.6% women, 74.7% White, 13.2% Black, 7.3% Hispanic, 2.8% Asian/API, and 0.6% Native American). Period prevalence of diabetes and PAD was 23 per 1000 beneficiaries. We observed a 33% relative decrease in annual new diagnoses throughout the study. All racial/ethnic groups experienced a similar decline in new diagnoses. Black and Hispanic patients had on average a 50% greater rate of disease compared with White patients. One- and 5-year amputation rates remained stable at ≈1.5% and 3%, respectively. Native American, Black, and Hispanic patients were at greater risk of amputation compared with White patients at 1- and 5-year time points (5-year rate ratio range, 1.22-3.17). Across US regions, we observed differential amputation rates, with an inverse relationship between the prevalence of concomitant diabetes and PAD and overall amputation rates. Significant regional and racial/ethnic variation exists in the incidence of concomitant diabetes and PAD among Medicare patients. Black patients in areas with the lowest rates of PAD and diabetes are at disproportionally higher risk for amputation. Furthermore, areas with higher prevalence of PAD and diabetes have the lowest rates of amputation.

The construction of a TCM knowledge graph and application of potential knowledge discovery in diabetic kidney disease by integrating diagnosis and treatment guidelines and real-world clinical data.

Background: The complexity and rapid progression of lesions in diabetic kidney disease pose significant challenges for clinical diagnosis and treatment. The advantages of Traditional Chinese Medicine (TCM) in diagnosing and treating this condition have gradually become evident. However, due to the disease's complexity and the individualized approach to diagnosis and treatment in Traditional Chinese Medicine, Traditional Chinese Medicine guidelines have limitations in guiding the treatment of diabetic kidney disease. Most medical knowledge is currently stored in the process of recording medical records, which hinders the understanding of diseases and the acquisition of diagnostic and treatment knowledge among young doctors. Consequently, there is a lack of sufficient clinical knowledge to support the diagnosis and treatment of diabetic kidney disease in Traditional Chinese Medicine. Objective: To build a comprehensive knowledge graph for the diagnosis and treatment of diabetic kidney disease in Traditional Chinese Medicine, utilizing clinical guidelines, consensus, and real-world clinical data. On this basis, the knowledge of Traditional Chinese Medicine diagnosis and treatment of diabetic kidney disease was systematically combed and mined. Methods: Normative guideline data and actual medical records were used to construct a knowledge graph of Traditional Chinese Medicine diagnosis and treatment for diabetic kidney disease and the results obtained by data mining techniques enrich the relational attributes. Neo4j graph database was used for knowledge storage, visual knowledge display, and semantic query. Utilizing multi-dimensional relations with hierarchical weights as the core, a reverse retrieval verification process is conducted to address the critical problems of diagnosis and treatment put forward by experts. Results: 903 nodes and 1670 relationships were constructed under nine concepts and 20 relationships. Preliminarily a knowledge graph for Traditional Chinese Medicine diagnosis and treatment of diabetic kidney disease was constructed. Based on the multi-dimensional relationships, the diagnosis and treatment questions proposed by experts were validated through multi-hop queries of the graphs. The results were confirmed by experts and showed good outcomes. Conclusion: This study systematically combed the Traditional Chinese Medicine diagnosis and treatment knowledge of diabetic kidney disease by constructing the knowledge graph. Furthermore, it effectively solved the problem of "knowledge island". Through visual display and semantic retrieval, the discovery and sharing of diagnosis and treatment knowledge of diabetic kidney disease were realized.