Type 2 Diabetes Patients Research Articles

Association between Protein Intake and Diabetes Complications Risk Following Incident Type 2 Diabetes: The EPIC-Potsdam Study.

Our knowledge about the connection between protein intake and diabetes-related complications comes largely from studies among those already diagnosed with type 2 diabetes (T2D). However, there is a lack of information on whether changing protein intake after diabetes diagnosis affects complications risk. We aimed to explore the association between protein intake (total, animal, and plant) and vascular complications in incident T2D patients considering pre-diagnosis intake and changes in intake after diagnosis. This prospective cohort study included 1064 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort who developed T2D during follow-up (physician-verified). Dietary protein intake was measured with a food frequency questionnaire at baseline and follow-up. We included physician-reported incident diabetes complications (myocardial infarction, stroke, nephropathy, and neuropathy). A total of 388 participants developed complications, 82 macrovascular complications, and 343 microvascular complications. Substituting carbohydrates with protein showed a trend towards lower complications risk, although this association was not statistically significant (hazard ratio (HR) for 5% energy (E) substitution: 0.83; 95% confidence intervals (CI): 0.60-1.14). Increasing protein intake at the expense of carbohydrates after diabetes diagnosis was not associated with total and microvascular complications (HR for 5% E change substitution: 0.98; 95% CI: 0.89-1.08 and HR for 5% E change substitution: 1.02; 95% CI: 0.92-1.14, respectively). Replacing carbohydrates with protein did not elevate the risk of diabetes complications in incident T2D cases.

Correlation of uric acid with microalbuminuria in Type-2 diabetic patients with normal creatinine.

To find the correlation of serum uric acid with microalbuminuria in Type-2 diabetic patients with normal creatinine. This cross-sectional study was conducted in the Department of Diabetes, Endocrinology and Metabolic diseases, Hayatabad Medical Complex, Peshawar, Pakistan from 1st April, 2022 to 30th September, 2022. Total 160 diabetic patients between the age of 30 and 65 years were enrolled in the study. Type-2 diabetic patients with microalbuminuria between 2.5 and 30 mg/mmol were included. The demographic details of patients were recorded in the questionnaire after taking consent. Fasting Uric acid, lipid profile and glucose along with creatinine and HbA1C were estimated from patient's venous blood samples. Ratio of albumin to creatinine (ACR) in the random spot urine sample was used to detect microalbuminuria. Out of 160 participants enrolled in the study there were 86 (54%) males and 74 (46%) females with the mean age of 50.15 ± 11.1 years and BMI of 20.93 kg/m2. Ninety six (60%) of the patients had Type-2 DM for less than five years, while remaining 64 (40%) were more than five years diabetic. Mean serum uric acid calculated was 6.85±2.06(mg/dl), while microalbuminuria was calculated as 8.02±0.78 (mg/mmol). The Pearson correlation of serum uric acid and microalbuminuria based on sex and age was statistically significant(p<0.05). We found that uric acid level was significantly associated with microalbuminuria in people with Type-2 diabetes with normal serum creatinine. Uric acid level can be a potential screening tool for early detection of DKD.

Irisin delays the onset of type 1 diabetes in NOD mice by enhancing intestinal barrier

Type 1 diabetes (T1D), a complex autoimmune disease, is intricately linked to the gut's epithelial barrier function. Emerging evidence emphasizes the role of irisin, an exercise-related hormone, in preserving intestinal integrity. This study investigates whether irisin could delay T1D onset by enhancing the colon intestinal barrier. Impaired colon intestinal barriers were observed in newly diagnosed T1D patients and non-obese diabetic (NOD) mice, worsening with age and accompanied by islet inflammation. Using an LPS-induced colonic inflammation model, a dose-dependent impact of LPS on colon cells irisin expression, secretion, and barrier function was revealed. Exogenous irisin demonstrated remarkable effects, mitigating islet insulitis, enhancing energy expenditure, and alleviating autoimmune symptoms by reducing colon intestinal permeability. Single-cell RNA sequencing (scRNA-seq) highlighted irisin's positive impact on colon epithelial cell clusters, effectively restoring the intestinal barrier. Irisin also selectively modulated bacterial composition, averting potential bacterial translocation. Mechanistically, irisin enhanced colon intestinal barrier tight junction proteins through the AMPK/PI3K/AKT pathway, with FAM120A playing a crucial role. Irisin upregulated MUC3 expression, a protector against damage and inflammation. Harnessing irisin's exercise-mimicking properties suggests therapeutic potential in clinical settings for preventing T1D progression, offering valuable insights into fortifying the colon's intestinal barrier and managing autoimmune conditions associated with T1DM.

Sex-dependent effect of socioeconomic status on cardiovascular event risk in a population-based cohort of patients with type 2 diabetes.

Socioeconomic status (SES) factors often result in profound health inequalities among populations, and their impact may differ between sexes. The aim of this study was to estimate and compare the effect of socioeconomic status indicators on incident cardiovascular disease (CVD)-related events among males and females with type 2 diabetes (T2D). A population-based cohort from a southern European region including 24,650 patients with T2D was followed for five years. The sex-specific associations between SES indicators and the first occurring CVD event were modeled using multivariate Fine-Gray competing risk models. Coronary Heart Disease (CHD) and stroke were considered secondary outcomes. Patients without a formal education had a significantly higher risk of CVD than those with a high school or university education, with adjusted hazard ratios (HRs) equal to 1.24 (95%CI: 1.09-1.41) for males and 1.50 (95%CI: 1.09-2.06) for females. Patients with <18000€ income had also higher CVD risk than those with ≥18000€, with HRs equal to 1.44 (95%CI: 1.29-1.59) for males and 1.42 (95%CI: 1.26-1.60) for females. Being immigrant showed a HR equal to 0.81 (95%CI: 0.66-0.99) for males and 1.13 (95%CI: 0.68-1.87) for females. Similar results were observed for stroke, but differed for CHD when income is used, which had higher effect in females. Socioeconomic inequalities in CVD outcomes are present among T2D patients, and their magnitude for educational attainment is sex-dependent, being higher in females, suggesting the need to consider them when designing tailored primary prevention and management strategies.

Effect of Reiki and Qi-gong therapy on improving negative emotional states of anxiety, depression, and stress among Type-2 Diabetic patients

Effect of Reiki and Qi-gong therapy on improving negative emotional states of anxiety, depression, and stress among Type-2 Diabetic patients

The Reasons for the Low Uptake of New Antidiabetic Drugs with Cardiovascular Effects-A Family Doctor Perspective.

Chronic diseases, such as type 2 diabetes (T2D), are difficult to manage because they demand continuous therapeutic review and monitoring. Beyond achieving the target HbA1c, new guidelines for the therapy of T2D have been introduced with the new groups of antidiabetics, glucagon-like peptide-1 receptor agonists (GLP-1ra) and sodium-glucose cotransporter-2 inhibitors (SGLT2-in). Despite new guidelines, clinical inertia, which can be caused by physicians, patients or the healthcare system, results in T2D not being effectively managed. This opinion paper explores the shift in T2D treatment, challenging assumptions and evidence-based recommendations, particularly for family physicians, considering the patient's overall situation in decision-making. We looked for the possible reasons for clinical inertia and the poor application of guidelines in the management of T2D. Guidelines for antidiabetic drugs should be more precise, providing case studies and clinical examples to define clinical contexts and contraindications. Knowledge communication can improve confidence and should include clear statements on areas of decision-making not supported by evidence. Precision medicine initiatives in diabetes aim to identify subcategories of T2D patients (including frail patients) using clustering techniques from data science applications, focusing on CV and poor treatment outcomes. Clear, unconditional recommendations for personalized T2D management may encourage drug prescription, especially for family physicians dealing with diverse patient contexts and clinical settings.

SGLT2 Inhibitors vs GLP-1 Receptor Agonists and Clinical Outcomes in Patients With Diabetes With/Without Atrial Fibrillation.

The coexistence of diabetes mellitus and atrial fibrillation (AF) is associated with substantial risks of adverse cardiovascular events. The relevant outcomes associated with the use of a sodium-glucose cotransporter-2 inhibitor (SGLT2i) vs glucagon-like peptide-1 receptor agonists (GLP-1RAs) among patients with type 2 diabetes (T2D) with/without concomitant AF remain unknown. In this nationwide retrospective cohort study from the Taiwan National Health Insurance Research Database, there were 344 392 and 31 351 patients with T2D without AF, and 11 462 and 816 T2D patients with AF treated with SGLT2is and GLP-1RAs, respectively, from May 1, 2016, to December 31, 2019. Patients were followed from the drug index date until the occurrence of study events, discontinuation of the index drug, or the end of the study period (December 31, 2020), whichever occurred first. We used propensity score-stabilized weight to balance covariates across the 2 medication groups. The incidence rate of all study outcomes in patients with concomitant AF was much higher than in those without concomitant AF. For the AF cohort, SGLT2i vs GLP-1RA was associated with a lower risk of hospitalization for heart failure (HF) (2.32 vs 4.74 events per 100 person-years; hazard ratio [HR] 0.48, 95% CI 0.36-0.66), with no benefit seen for the non-AF cohort (P for homogeneity < .01). SGLT2i vs GLP-1RA was associated with a lower risk of composite kidney outcomes both in the AF (0.38 vs 0.79 events per 100 person-years; HR 0.47; 95% CI 0.23-0.96) and the non-AF cohorts (0.09 vs 0.18 events per 100 person-years; HR 0.53; 95% CI 0.43-0.64). There were no significant differences in the risk of major adverse cardiovascular events and all-cause mortality in those who received SGLT2i compared with GLP-1RA for the AF or non-AF cohorts. Considering the high risk of developing HF and/or high prevalence of concomitant HF in patients with concomitant diabetes and AF, whether SGLT2is should be the preferred treatment to GLP-1RAs for such a high-risk population requires further investigation.

Association of Vitamin D Deficiency and Vitamin D Receptor Gene Polymorphisms with Type 1 Diabetes Risk: A South Indian Familial Study

Vitamin D is a potent immune modulator and is associated with autoimmune diseases, including type 1 diabetes (T1D). The vitamin D levels and its receptor gene polymorphisms together in T1D are not yet investigated in the South Indian population. The present study focused on exploring the significance of vitamin D levels and vitamin D receptor (VDR) gene polymorphisms with the risk of developing T1D in the South Indian population. Patients with T1D and unaffected first-degree relatives (FDRs) were included in this study. Genotyping of VDR polymorphisms at four different loci (FokI- F/f, BsmI- B/b, TaqI- T/t, and ApaI- A/a) was assessed through the amplification refractive mutation system-polymerase chain reaction method. Serum vitamin D levels were measured in 98 T1D patients and 75 age- and sex-matched siblings. A total of 120 patients with T1D and 214 FDRs were included. Vitamin D deficiency (VDD) was observed in a higher proportion of T1D patients than in controls (52% vs. 32%; p<0.03). The frequency of the FokI-FF genotype was significantly higher [odds ratio (OR)=1.66; p<0.03] in T1D patients conferring a susceptible association with the disease. Nevertheless, the increased frequency of heterozygous Ff genotype (OR=0.57; p<0.02) among controls may confer a protective association with T1D. Furthermore, the transmission disequilibrium test revealed over-transmission of ApaI-A (T: U=15/5; p<0.006) and BsmI-B alleles (T: U=17/5; p<0.01) and under-transmission of BsmI-b/ApaI-a/TaqI-T haplotype (T: U=5.4/14.4; p=0.04) from parents to T1D patients. The present study concludes that VDD is the major contributing risk factor to T1D development in the South Indian population. Furthermore, the FokI-FF genotype, BsmI-B, and ApaI-A alleles were positively associated with T1D. In contrast, the FokI-Ff genotype and BsmI-b/ApaI-a/TaqI-T haplotype were negatively associated with T1D.

High throughput biological sequence analysis using machine learning-based integrative pipeline for extracting functional annotation and visualization

The Differential Gene Expression (DGE) approach to find out the expressed genes relies on measures such as log-fold change and adjusted p-values. Although fold change is commonly employed in gene expression studies, especially in microarray and RNA sequencing experiments to quantify alterations in a gene’s expression level, a limitation and potential hazard of relying on fold change in this context is its inherent bias. As a consequence, it might incorrectly categorize genes that have significant differences but minor ratios, resulting in poor detection of mutations in genes with high expression levels. In contrast, machine learning offers a more comprehensive view, adept at capturing the non-linear complexities of gene expression data and providing robustness against noise that inspired us to utilize machine learning models to explore differential gene expression based on feature importance in Type 2 Diabetes (T2D), a significant global health concern, in this study. Moreover, we validated biomarkers based on our findings expressed genes with previous studies to ensure the effectiveness of our ML models in this work which led us to go through to analysis pathways, gene ontologies, protein-protein interactions, transcription factors, miRNAs, and drug predictions to deal with T2D. This study aims to consider the machine learning technique as a good way to know about expressed genes profoundly not relying on the DGE approach, and to control or reduce the risk of T2D patients by helping drug developer researchers.

Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes: an IMI-RHAPSODY Study.

Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D.

A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data.

Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically significant hypoglycemia within one week. We developed a machine learning model to estimate the probability that a patient will experience a clinically significant hypoglycemic event, defined as CGM readings below 54 mg/dL for at least 15 consecutive minutes, within one week. The model takes as input the patient's CGM time series over a given week, and outputs the predicted probability of a clinically significant hypoglycemic event the following week. We used 10-fold cross-validation and external validation (testing on cohorts different from the training cohort) to evaluate performance. We used CGM data from three different cohorts of patients with T1D: REPLACE-BG (226 patients), Juvenile Diabetes Research Foundation (JDRF; 355 patients) and Tidepool (120 patients). In 10-fold cross-validation, the average area under the receiver operating characteristic curve (ROC-AUC) was 0.77 (standard deviation [SD]: 0.0233) on the REPLACE-BG cohort, 0.74 (SD: 0.0188) on the JDRF cohort, and 0.76 (SD: 0.02) on the Tidepool cohort. In external validation, the average ROC-AUC across the three cohorts was 0.74 (SD: 0.0262). We developed a machine learning algorithm to estimate the probability of a clinically significant hypoglycemic event within one week. Predictive algorithms may provide diabetes care providers using RPM with additional context when prioritizing T1D patients for review.

Temporal trends in the starting of insulin therapy in type 2 diabetes in Italy: data from the AMD Annals initiative

AimsOpportunities and needs for starting insulin therapy in Type 2 diabetes (T2D) have changed overtime. We evaluated clinical characteristics of T2D subjects undergoing the first insulin prescription during a 15-year-observation period in the large cohort of the AMD Annals Initiative in Italy.MethodsData on clinical and laboratory variables, complications and concomitant therapies and the effects on glucose control after 12 months were evaluated in T2D patients starting basal insulin as add-on to oral/non-insulin injectable agents, and in those starting fast-acting in add-on to basal insulin therapy in three 5-year periods (2005–2019).ResultsWe evaluated data from 171.688 T2D subjects who intensified therapy with basal insulin and 137.225 T2D patients who started fast-acting insulin. Overall, intensification with insulin occurred progressively earlier over time in subjects with shorter disease duration. Moreover, the percentage of subjects with HbA1c levels > 8% at the time of basal insulin initiation progressively decreased. The same trend was observed for fast-acting formulations. Clinical characteristics of subjects starting insulin did not change in the three study-periods, although all major risk factors improved overtime. After 12 months from the starting of basal or fast-acting insulin therapy, mean HbA1c levels decreased in all the three investigated time-periods, although mean HbA1c levels remained above the recommended target.ConclusionsIn this large cohort of T2D subjects, a progressively earlier start of insulin treatment was observed during a long observation period, suggesting a more proactive prescriptive approach. However, after 12 months from insulin prescription, in many patients, HbA1c levels were still out-of-target.

Carbohydrate counting knowledge and ambulatory glucose profile in persons living with type 1 diabetes

Context.The amount of consumed carbohydrates is the strongest factor influencing glucose levels during the four hours following a meal.Our aim was to evaluate the association between carbohydrate counting knowledge and continuous glucose monitoring (CGM) parameters in patients with type 1 diabetes (T1D) using different insulin regimens. MethodIn this multicenter prospective study, the GluciQuizz questionnaire was used to evaluate carbohydrate knowledge. CGM data for the 14 days preceding completion of the questionnaire were analyzed.The primary endpoint was evaluation of the correlation between the GluciQuizz total score and time in range (TIR) in the study population. ResultsThe mean age of the 170 participants was 40.7 ± 14.8 years and duration of T1D 18.8 ± 12.1 years. The mean GluciQuizz total score for all participants was 66 ± 13 %. Mean TIR was 58.6 ± 18.7 %. GluciQuizz total score positively correlated with TIR (r = 0.3001; p < 0.0001). This correlation was observed in CSII users (r = 0.2526; p < 0.05) but not in MDI (r = 0.2510; p = 0.1134) and HCL users (r = -0.1065; p = 0.4914). TIR was also negatively correlated with the mean carb count error in all study participants (r = -0.2317; p < 0.01). ConclusionIn conclusion, as the Gluciquizz score was associated with metabolic control, this easy-to-use self-administered questionnaire could be used widely on a routine basis to assess the carbohydrate knowledge of T1D patients and to offer them targeted education tailored to their needs.

T1D and T2D predispose to higher Nd:YAG capsulotomy rates following cataract surgery: analysis of 53,471 consecutive cases

PurposeTo assess the effect of diabetes type on Nd:YAG capsulotomy rates following cataract surgery. DesignA retrospective cohort study. MethodsAll patients who underwent cataract extraction at the Department of Ophthalmology, Bristol Eye Hospital, Bristol, UK, between 2003 and 2017 were included. The Nd:YAG capsulotomy rate following cataract surgery was assessed and compared between nondiabetic, type 1 diabetes (T1D), and type 2 diabetes (T2D) patients. Multivariate Cox regression analysis controlling for age and sex was used to estimate hazard ratios for Nd:YAG laser capsulotomies. ResultsIncluded were 53,471 consecutive cataract surgeries. Overall, 42,651 eyes (79.8%) were in nondiabetic patients, 823 eyes (1.5%) were in T1D patients, and 9,997 eyes (18.7%) were in T2D patients. The mean follow-up time was 6.8 ± 4.2 years. In univariate analysis, the eyes of T1D patients (p < 0.001) and T2D patients (p = 0.003) had significantly higher Nd:YAG laser capsulotomy rates than the eyes of nondiabetic patients. In Cox regression analysis adjusted for the patient's age and sex, DM1 (HR 1.692, 95%CI 1.390-2.059, P<0.001) and DM2 (HR 1.157, 95%CI 1.075-1.244, P<0.001) remained significantly predictive for higher Nd:YAG laser capsulotomy rates. ConclusionIn our large cohort study, patients with T1D and T2D were predisposed to high risk for Nd:YAG capsulotomy following cataract surgery. This study may be beneficial and raise awareness regarding the assessment of posterior capsular opacification development in pseudophakic diabetic patients, particularly those with T1D. The significance of ophthalmology screening for diabetes individuals is further supported by this issue.

Causal effects of inflammatory bowel disease on risk of type 2 diabetes: a two-sample multivariable Mendelian randomization study.

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study. Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated. The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL). IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

Hidden hunger in patients with type 2 diabetes (T2D) and its effect on glycaemic control: a protocol for systematic review and meta-analysis

IntroductionHidden hunger or micronutrient deficiencies are quite common in many parts of the world, particularly in the countries of sub-Saharan Africa and South Asia. Micronutrient deficiencies may impact insulin signalling...

A Critical Review on the Long-Term COVID-19 Impacts on Patients With Diabetes

BackgroundThe world is currently grappling with the potentially life-threatening coronavirus disease 2019 (COVID-19), marking it as the most severe health crisis in the modern era. COVID-19 has led to a pandemic, with the World Health Organization (WHO) predicting that individuals with diabetes are at a higher risk of contracting the virus compared to the general population. This review aims to provide a practical summary of the long-term impacts of COVID-19 on patients with diabetes. Specifically, it focuses on the effects of SARS-CoV-2 on different types of diabetic patients, the associated mortality rate, the underlying mechanisms, related complications, and the role of vitamin D and zinc in therapeutic and preventive approaches. MethodsRelevant literature was identified through searches on PubMed, Web of Science, and Science Direct in English, up to April 2023. ResultsCOVID-19 can lead to distressing symptoms and pose a significant challenge for individuals living with diabetes. Older individuals and those with pre-existing conditions such as diabetes, coronary illness, and asthma are more susceptible to COVID-19 infection. Managing COVID-19 in individuals with diabetes presents challenges, as it not only complicates the fight against the infection but also potentially prolongs the recovery time. Moreover, the virus may thrive in individuals with high blood glucose levels. Various therapeutic approaches, including antidiabetic drugs, are available to help prevent COVID-19 in diabetic patients. ConclusionsDiabetes increases the morbidity and mortality risk for patients with COVID-19. Efforts are globally underway to explore therapeutic interventions aimed at reducing the impact of diabetes on COVID-19.

Seroepidemiology of Toxoplasma gondii in diabetic patients type 2 by enzyme-linked immunosorbent assay method in Zabol City, 2017-2018.

Type 2 diabetes mellitus (T2DM) is prone to opportunistic infections, including toxoplasmosis, due to an immunodeficiency system. This study aimed to evaluate the serum of people with T2DM to determine the titer of anti-toxoplasma antibodies in patients and compare it with the control group. 720 blood samples have been carried out between October and the end of January 2017 in Sistan, and Baluchestan provinces in southeastern Iran, of these, 360 samples were related to healthy individuals (control), and 360 samples were related to T2DM individuals. The immunoglobulin (Ig) M and IgG enzyme-linked immunosorbent assay methods have been used to detect toxoplasmosis. The data were analyzed using SPSS-19, Chi-square, and Fisher's exact test to compare statistical parameters. In this cross-sectional study, out of 360 samples of T2DM by ELISA method, 60% samples in diabetic patients and 48.1% in control group were IgG positive (P < 0.05). Nearly 2.5% samples in diabetic patients and 0.3% in control group were IgM positive (P < 0.05). Anti-toxoplasma antibodies including IgG and IgM were higher in diabetic patient in comparison to control group.

Clinical risk factors and features on computed tomography angiography in high-risk carotid artery plaque in patients with type 2 diabetes.

High-risk carotid artery plaque (HPR) is associated with a markedly increased risk of ischemic stroke. The aims of this study were: 1) to examine the prevalence of HRP in a cohort of asymptomatic adults with type 2 diabetes (T2D); 2) to investigate the relationship between HRP, established cardiovascular risk factors and computed tomography angiography (CTA) profile; and 3) to assess whether the presence of HRP is associated with an increased risk of major adverse cardiovascular events (MACE). This was a retrospective cohort study of T2D asymptomatic patients who underwent carotid endarterectomy (CEA) from January 2018 to July 2021. The carotid atherosclerotic plaque (CAP) was assessed for the presence of ulceration, the presence of lipids, fibrosis, thrombotic deposits, hemorrhage, neovascularization, and inflammation. A CAP presenting at least five of these histological features was defined as a HRP (Group A); in all other cases it was defined as a mild to moderate heterogeneous plaque and no-HRP (Group B). CTA features included the presence of rim sign consisting of thin peripheral adventitial calcification (<2 mm) and internal soft plaque (≥2 mm), NASCET percent diameter stenosis, maximum plaque thickness, ulceration, calcification, and intraluminal thrombus were recorded. Binary logistic regression with Uni- and Multivariate was used to evaluate possible predictors for HRP while multivariable Cox Proportional Hazards was used to assess independent predictors for MACE. One hundred eighty-five asymptomatic patients (mean age 73±8 years, 131 men), undergoing carotid endarterectomy, were included. Of these, 124 (67%) had HRP, and the 61 (33%) did not. Diabetic complications (OR 2.4, 95% CI: 1.1-5.1, P=0.01), NASCET stenosis ≥75% (OR 2.4, 95% CI: 1.2-3.7, P=0.02) and carotid RIM sign (OR 4.3, 95% CI: 3.9-7.3, P<0.001) were independently associated with HRP. However, HRP was not associated with a higher risk of MACE (freedom from MACE at 5 years: HRP 83.4% vs. non HRP 87.8%, P=0.72) or a reduction of survival (5-year survival estimates: HRP 96.4% vs. non HRP: 94.6%, P=0.76). A high prevalence of HRP (67%) was observed in asymptomatic and elderly T2D patients. Independent predictors of HRP were diabetic complications, NASCET stenosis ≥75% and carotid RIM sign (OR 4.3, 95% CI: 3.9-7.3, P<0.001). HRP was not associated with an increased risk of MACE during a mean follow-up of 39±24 years.

Knowledge, Attitudes, and Behaviors Toward Proper Nutrition and Lifestyles in Kosovar’s Diabetic Patients

Background: The aim of our study was to assess the knowledge and attitudes about type 2 diabetes (T2D) in Kosovars patients, as well as self-efficacy toward eating behavior, and determine the impact of diabetes on patients' daily work and lifestyle practices.Methods and Results: This analytical cross-sectional survey was performed among 400 T2D patients (203 males and 197 females) to assess their knowledge, attitude, and practice regarding diabetic diet and eating habits. It was conducted from February to May 2023 in Kosovo's rural and urban areas. Knowledge, attitudes, and eating behavior were assessed using the self-administered 28-item sets related to glycemic control, physical activity, risk of complications, foot care, and food and nutrition. The largest proportion (42.3%) was made up of the patients over 60 years of age; 41.5% were 40-60 years of age, and only 16.3% were 30-40 years old. Most of the patients were males (50.8%); more than 87% were married. Interviewed participants did not have enough knowledge about the consumption of foods with more fruits, beverages, and sweets. Generally, participants had poor knowledge about the impact of DM on health. Most diabetics in Kosovo still have suboptimal diet practices, choosing to base their main meals around carbohydrates containing food with a high glycemic index, such as white bread and potatoes most of the time. In our case, 38.8% of participants never exercised during the week because they did not know the importance of exercise to treat their disease. In our study, we found no association between the level of diabetes-related knowledge and age, gender, or the years since the patient was diagnosed. A worrying fact for Kosovar patients is that there are no diabetes counseling centers in the regions where they live. Conclusion: There is a need to increase awareness of the complications of diabetes and consequently improve nutrition knowledge, attitudes, and practices. The benefits of early detection of T2D through screening in the general population are needed in Kosovo.