Diagnosis Of Diabetic Disease Research Articles

Unveiling the utility of artificial intelligence for prediction, diagnosis, and progression of diabetic kidney disease: an evidence-based systematic review and meta-analysis

Objective The purpose of this study was to conduct a systematic investigation of the potential of artificial intelligence (AI) models in the prediction, detection of diagnostic biomarkers, and progression of diabetic kidney disease (DKD). In addition, we compared the performance of non-logistic regression (LR) machine learning (ML) models to conventional LR prediction models. Methods Until January 30, 2024, a comprehensive literature review was conducted by investigating databases such as Medline (via PubMed) and Cochrane. Research that is inclusive of AI or ML models for the prediction, diagnosis, and progression of DKD was incorporated. The area under the Receiver Operating Characteristic Curve (AUROC) served as the principal outcome metric for assessing model performance. A meta-analysis was performed utilizing MedCalc statistical software to calculate pooled AUROC and assess the performance differences between LR and non-LR models. Results A total of 57 studies were included in the meta-analysis. The pooled AUROC of AI or ML model was 0.84 (95% CI = 0.81-0.86, p < 0.0001) for analyzing prediction of DKD, 0.88 (95%CI = 0.84-0.92, p < 0.0001) for detecting diagnostic biomarkers, and 0.80 (95% CI = 0.77-0.82, p < 0.0001) for analyzing progression of DKD. The pooled AUROC of LR and non-LR ML models exhibited no significant differences across all categories (p > 0.05), except for the random forest (RF) model, which displayed a statistically significant increase in predictive accuracy compared to LR for DKD occurrence (p < 0.04). Conclusion ML models showed solid DKD prediction effectiveness, with pooled AUROC values over 0.8, suggesting good performance. These data demonstrated that non-LR and LR models perform similarly in overall CKD management, but the RF model outperforms the LR model, particularly in predicting the occurrence of DKD. These findings highlight the promise of AI technologies for better DKD management. To improve model reliability, future study should include extended follow-up periods as well as external validation.

Independent association between radial secondary access and stroke in patients undergoing transcatheter aortic valve implantation

Abstract Background Radial access has become the primary approach for invasive coronary angiography due to its lower complication rate than femoral access. Transcatheter aortic valve implantation (TAVI) frequently requires a secondary access, which has traditionally been femoral access. However, radial access for TAVI is feasible and gaining popularity, but data on its safety and complication rates is still limited. Purpose To evaluate the occurrence of stroke rate in patients undergoing a TAVI procedure with femoral or radial secondary access. Methods A prospective single-center TAVI registry of 2327 patients who received a TAVI procedure between 2019 and 2022 was conducted. All procedures had the primary access over the femoral route. 337 (14.5%) patients had a secondary access over the radial route, whereas 1990 (85.5%) received a femoral secondary access. The primary endpoint was the occurrence of stroke within the hospital stay. Both groups were compared using the t-test or the Mann-Whitney U test according to the distribution of the data. In a second step, a multivariable model was created in which parameters were included that were associated with the endpoint in the previous analysis, as well as parameters that are known to be associated with stroke. Results: Patients were 81.1 ± 6.3 years old, with a Euroscore II of 5.3 ± 6. A total of 610 (26.2%) patients received a balloon-expandable valve. The primary endpoint (stroke within 30 days of the TAVI procedure) was met by 94 (4%) of all patients. Stroke occurred more often in the group with radial secondary access (6.6% (22) vs. 3.6%(72), p = 0.012). Other significant differences between the two groups included (radial vs. femoral access): burden of atrial fibrillation (36.8% vs. 44.6%, p = 0.007), arterial hypertension (87.4% vs. 92%, p = 0.007), Euroscore II (4.6 vs. 5.5, p = 0.006), and frailty (25.2% vs. 40%, p &amp;lt; 0.001). There were no significant differences between the two groups in terms of secondary diagnosis of diabetes or coronary artery disease, age, occurrence of NYHA class III/IV, gender, or cerebral artery disease. In the multivariate analysis including Age, Euroscore II, NYHA class, gender, secondary diagnosis of arterial Hypertension, diabetes or cerebral artery disease, arterial fibrillation, Frailty and radial secondary access, only radial secondary access was independently associated with in-hospital stroke (p = 0.01). Conclusion Radial secondary access was significantly associated with an increased risk of in-hospital stroke following transcatheter aortic valve implantation (TAVI) in our study population. Intense manipulation of the guidewire and catheter to reach the ascending aorta at the beginning of the procedure and to reach the descending aorta for the final angiogram of the primary access vessel may be causative and should be minimized.

Significance of pyroptosis-related genes in the diagnosis and classification of diabetic kidney disease

Objective This study aimed to identify the potential biomarkers associated with pyroptosis in diabetic kidney disease (DKD). Methods Three datasets from the Gene Expression Omnibus (GEO) were downloaded and merged into an integrated dataset. Differentially expressed genes (DEGs) were filtered and intersected with pyroptosis-related genes (PRGs). Pyroptosis-related DEGs (PRDEGs) were obtained and analyzed using functional enrichment analysis. Random forest, Least Absolute Shrinkage and Selection Operator, and logistic regression analyses were used to select the features of PRDEGs. These feature genes were used to build a diagnostic prediction model, identify the subtypes of the disease, and analyze their interactions with transcription factors (TFs)/miRNAs/drugs and small molecules. We conducted a comparative analysis of immune cell infiltration at different risk levels of pyroptosis. qRT-PCR was used to validate the expression of the feature genes. Results A total of 25 PRDEGs were obtained. These genes were coenriched in biological processes and pathways, such as the regulation of inflammatory responses. Five key genes (CASP1, CITED2, HTRA1, PTGS2, S100A12) were identified and verified using qRT-PCR. The diagnostic model based on key genes has a good diagnostic prediction ability. Five key genes interacted with TFs and miRNAs in 67 and 80 pairs, respectively, and interacted with 113 types of drugs or molecules. Immune infiltration of samples with different pyroptosis risk levels showed significant differences. Thus, CASP1, CITED2, HTRA1, PTGS2 and S100A12 are potential DKD biomarkers. Conclusion Genes that regulate pyroptosis can be used as predictors of DKD. Early diagnosis of DKD can aid in its effective treatment.

Detection and diagnosis of diabetic eye diseases using two phase transfer learning approach.

Early diagnosis and treatment of diabetic eye disease (DED) improve prognosis and lessen the possibility of permanent vision loss. Screening of retinal fundus images is a significant process widely employed for diagnosing patients with DED or other eye problems. However, considerable time and effort are required to detect these images manually. Deep learning approaches in machine learning have attained superior performance for the binary classification of healthy and pathological retinal fundus images. In contrast, multi-class retinal eye disease classification is still a difficult task. Therefore, a two-phase transfer learning approach is developed in this research for automated classification and segmentation of multi-class DED pathologies. In the first step, a Modified ResNet-50 model pre-trained on the ImageNet dataset was transferred and learned to classify normal diabetic macular edema (DME), diabetic retinopathy, glaucoma, and cataracts. In the second step, the defective region of multiple eye diseases is segmented using the transfer learning-based DenseUNet model. From the publicly accessible dataset, the suggested model is assessed using several retinal fundus images. Our proposed model for multi-class classification achieves a maximum specificity of 99.73%, a sensitivity of 99.54%, and an accuracy of 99.67%.

Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-Fe2O3-MWCNT Nanocomposites.

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection device through acetone sensing in EB, based on an α-Fe2O3-multiwalled carbon nanotube (MWCNT) nanocomposite, was successfully developed. Different amounts of α-Fe2O3 were added to the MWCNTs by a simple solution method. The optimized acetone gas sensor showed a response of 5.15 to 10 ppm acetone gas at 200 °C. Also, the fabricated sensor showed very good sensing properties even in an atmosphere with high relative humidity. Since the EB has high humidity, the proposed sensor is a promising device to exactly detect the amount of acetone in EB with high humidity. The sensor was powered by a 3200 mAh battery with the possibility of charging using mains electricity. To increase the reliability and calibration of the sensing device, a practical test was taken to detect acetone EB from 50 volunteers, and a deep learning algorithm (DLA) was used to detect the effect of various factors on the amount of acetone in each person's acetone EB. The proposed device with ±15 errors had almost 85% correct responses. Also, the proposed device had excellent response, short response time, good selectivity, and good repeatability, leading it to be a suitable candidate for noninvasive blood glucose sensing.

DIABETES AND PERIODONTAL DISEASE: INTERCONNECTED PATHOPHYSIOLOGY AND CLINICAL IMPLICATIONS: A COMPREHENSIVE REVIEW

The bidirectional relationship between diabetes mellitus (DM) and periodontal disease is well-documented, with poor glycemic control exacerbating periodontal inflammation and vice versa. Novel therapies, including anti-inflammatory agents, antioxidants, and biologics, show promise in reducing systemic inflammation and improving glycemic control. Advances in identifying salivary biomarkers such as miRNAs 146a/b and 155, IL-1β, MMP8, and IL-6 have improved early detection of periodontitis in diabetic patients. Additionally, innovative imaging techniques like Raman spectroscopy and multiplex hand-held biosensors have enhanced diagnostic accuracy. Longitudinal studies and clinical trials remain essential to validate the long-term benefits and safety of new biomarkers and therapies. Recent studies highlight the importance of integrated care and interdisciplinary collaboration between dental and medical professionals to effectively manage these interrelated conditions. Future research should focus on understanding the biological pathways linking DM and periodontal disease, with a particular emphasis on the roles of inflammatory cytokines, oxidative stress, and the microbiome. Public health initiatives should aim to increase awareness of the bidirectional relationship between DM and periodontal disease through educational campaigns and community-based screening programs. Policy recommendations should encourage integrated health services and interdisciplinary training programs. The integration of artificial intelligence and machine learning in diagnostic tools offers potential for early detection and personalized treatment plans, further improving patient outcomes. Addressing these research gaps through continued investigation and technological innovation is crucial for enhancing the prevention, diagnosis, and management of diabetes and periodontal disease. These efforts will ultimately lead to better health outcomes and quality of life for affected individuals.

Quantitative outcomes of a type 2 single arm hybrid effectiveness implementation pilot study for hypertension-HIV integration in Botswana

BackgroundSuccessful HIV treatment programs have turned HIV into a chronic condition, but noncommunicable diseases such as hypertension jeopardize this progress. Hypertension control rates among people with HIV (PWH) are low owing to gaps in patient awareness, diagnosis, effective treatment, and management of both conditions at separate clinic visits. Integrated management, such as in our study, InterCARE, can enhance HIV-hypertension integration and blood pressure (BP) control.MethodsOur pilot study was conducted in two Botswana HIV clinics between October 2021 and November 2022. Based on our formative work, we adopted three main strategies; Health worker training on HTN/cardiovascular disease (CVD) management, adaptation of HIV Electronic Health Record (EHR) for HTN/CVD care, and use of treatment partners to support PWH with hypertension for implementation. We employed the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework to assess implementation effectiveness and outcomes for BP control at baseline, 6 and 12 months. HIV viral load (VL) suppression was also measured to assess impact of integration on HIV care.ResultsWe enrolled 290 participants; 35 (12.1%) were lost to follow-up, leaving 255 (87.9%) at 12-months. Median age was 54 years (IQR 46–62), and 77.2% were females. Our interventions significantly improved BP control to < 140/90 mmHg (or < 130/80 mmHg if diagnosis of diabetes or chronic kidney disease), from 137/290 participants, 47.2% at baseline to 206/290 participants, 71.0%, at 12 months (p < 0.001). Among targeted providers, 94.7% received training, with an associated significant increase in counseling on exercise, diet, and medication (all p < 0.001) but EHR use for BP medication prescribing and cardiovascular risk factor evaluation showed no adoption. In the intention-to-treat analysis, HIV VL suppression at 12 months decreased (85.5% vs 93.8%, p = 0.002) due to loss to follow-up but the per protocol analysis showed no difference in VL suppression between baseline and 12 months (97.3% vs 93.3%, p = 0.060).ConclusionThe InterCARE pilot study demonstrated that low-cost practical support measures involving the integration of HIV and hypertension/CVD management could lead to improvements in BP control. These results support the need for a large implementation and effectiveness trial.Trial registrationClinicalTrials.gov NCT05414526. Registered 18th May 2022.

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.

Patients With Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease Exhibit Lower Computed Tomography-measured Skeletal Muscle Attenuation Values: A Propensity Score-matched Study

ObjectiveTo investigate the association between computed tomography (CT)-measured quality characteristics of skeletal muscle (SM) and early diagnosis of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). MethodsThis retrospective study included patients diagnosed with T2DM, with and without early DKD, between January 2019 and December 2021. To reduce potential bias, propensity score matching (PSM) was performed. The area and CT attenuation values for SM and different abdominal adipose depots were measured. After PSM, logistic and multiple linear regression analyse were performed to analyse risk factors for early DKD. ResultsA total of 267 patients were enrolled (mean age, 61.67 years ±10.87; 155 men) and divided into two groups: T2DM with early DKD (n=133); and T2DM without DKD (n=134). After PSM, 230 patients were matched (T2DM with early DKD [n=115]; and T2DM without DKD [n=115]), with no statistical differences in general characteristics between the two groups (P>0.05). In multivariate logistic regression analysis, high-density lipoprotein cholesterol (odds ratio [OR] 0.14; 95% confidence interval [CI] 0.04–0.49; P=0.002), uric acid (OR 1.01; 95% CI 1.00–1.01; P=0.006), and SM attenuation value (OR 0.94; 95% CI 0.90–0.98; P=0.003) were independent risk factors for early DKD. Multiple linear regression analysis revealed significant correlations between SM attenuation value and cystatin C (β=-0.39, P=0.004), urine albumin-to-creatinine ratio (β=-0.26, P=0.026), and estimated glomerular filtration rate (β=0.31 P=0.009) after adjustment for confounders. ConclusionT2DM patients with lower SM attenuation values may exhibit a higher risk for early DKD than those with higher values, which provides a potential imaging biomarker for early DKD diagnosis.

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.

Ultrasensitive Hierarchical AuNRs@SiO2@Ag SERS Probes for Enrichment and Detection of Insulin and C-Peptide in Serum.

Insulin and C-peptide played crucial roles as clinical indicators for diabetes and certain liver diseases. However, there has been limited research on the simultaneous detection of insulin and C-peptide in trace serum. It is necessary to develop a novel method with high sensitivity and specificity for detecting insulin and C-peptide simultaneously. A core-shell-satellites hierarchical structured nanocomposite was fabricated as SERS biosensor using a simple wet-chemical method, employing 4-MBA and DTNB for recognition and antibodies for specific capture. Gold nanorods (Au NRs) were modified with Raman reporter molecules and silver nanoparticles (Ag NPs), creating SERS tags with high sensitivity for detecting insulin and C-peptide. Antibody-modified commercial carboxylated magnetic bead@antibody served as the capture probes. Target materials were captured by probes and combined with SERS tags, forming a "sandwich" composite structure for subsequent detection. Under optimized conditions, the nanocomposite fabricated could be used to detect simultaneously for insulin and C-peptide with the detection limit of 4.29 × 10-5 pM and 1.76 × 10-10 nM in serum. The insulin concentration (4.29 × 10-5-4.29 pM) showed a strong linear correlation with the SERS intensity at 1075 cm-1, with high recoveries (96.4-105.3%) and low RSD (0.8%-10.0%) in detecting human serum samples. Meanwhile, the C-peptide concentration (1.76 × 10-10-1.76 × 10-3 nM) also showed a specific linear correlation with the SERS intensity at 1333 cm-1, with recoveries 85.4%-105.0% and RSD 1.7%-10.8%. This breakthrough provided a novel, sensitive, convenient and stable approach for clinical diagnosis of diabetes and certain liver diseases. Overall, our findings presented a significant contribution to the field of biomedical research, opening up new possibilities for improved diagnosis and monitoring of diabetes and liver diseases.

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