Current Diabetes Reviews - Volume 19, Issue 9, 2023

Background: Diabetic peripheral neuropathy is a severe complication of type 2 diabetes mellitus. The most common symptoms are neuropathic pain and altered sensorium due to damage to small nerve fibers. Altered plantar pressure distribution is also a major risk factor in diabetic peripheral neuropathy, leading to diabetic foot ulcers. Objective: The objective of this systematic review was to analyze the various studies involving photobiomodulation therapy on neuropathic pain and plantar pressure distribution in diabetic peripheral neuropathy. Methods: We conducted a systematic review (PubMed, Web of Science, CINAHL, and Cochrane) to summarise the evidence on photobiomodulation therapy for Diabetic Peripheral Neuropathy with type 2 diabetes mellitus. Randomized and non-randomized studies were included in the review. Results: This systematic review included eight studies in which photobiomodulation therapy showed improvement in neuropathic pain and nerve conduction velocity. It also reduces plantar pressure distribution, which is a high risk for developing foot ulcers. Conclusion: We conclude that photobiomodulation therapy is an effective, non-invasive, and costefficient means to improve neuropathic pain and altered plantar pressure distribution in diabetic peripheral neuropathy.

Due to the gravity of postprandial hyperglycemia in the development of microvascular and macrovascular diseases in diabetics, many medicinal plants are tested to determine their effectiveness in glycemic control and the mechanisms of action of the products. Consequently, various diabetic models have been developed and enhanced over the years. The objective of this review is to describe some of the experimental models to study the effect of medicinal plants used to control postprandial hyperglycemia. Data was collected from PubMed, ScienceDirect, Scopus, and Google scholar (1953-2021). Fiftyseven (57) studies were included in this review article. Ten models were identified and described. For each model, we described the targets involved and their roles in postprandial blood glucose control. The experimental design and procedures described the targets such as an α-glucosidase enzyme, SGLT1, GLUT2, DPP-IV, Na+/K+ ATPase pump, or intestinal motility in the models, experiment design and procedures were described. This review will facilitate the selection of the most appropriate model for studying agents used to investigate postprandial blood glucose.

Diabetes and its associated complications including diabetic neuropathy have become a menacing headache for health workers and scientists all over the world. The number of diabetic individuals has been growing exponentially every day while the entire medical fraternity feels crippled and unable to handle such an enormous and anarchical scenario. The disease also demonstrates itself in the patients in numerous ways ranging from a little discomfort to death. Diabetic neuropathy has a poor prognosis since it might go unnoticed for years after the onset of diabetes. The etiology of the disease has been linked to oxidative stress caused by increased free radical production. Hyperglycemia causes multiple metabolic pathways to be activated, as well as significant oxidative stress, which becomes the major cause of cell death, culminating in Diabetic Neuropathy. So, it is the need of the hour to find out permanent treatment for this life-threatening disease. The primary goal of this study is to emphasize the potential importance of numerous processes and pathways in the development of diabetic neuropathy as well as the possible role of plant metabolites to control the disease at a molecular level. A possible mechanism was also summarized in the study about scavenging the reactive oxygen species by a flavonoid component. The study also covered the in vivo data of various plants and some of the flavonoid compounds actively studied against Diabetic Neuropathy by inhibiting or reducing the contributing factors such as proinflammatory cytokines, ROS, RNS inhibition, and upregulating the various cellular antioxidants such as GSH, SOD, and CAT.

Background: Diabetic retinopathy (DR) is a chronic diabetes complication. People with Type 2 Diabetes Mellitus (T2DM) have two times the risk for dementia, suggesting it is a new chronic diabetes complication. Objective: Evaluate the association of DR with cognitive performance in a T2DM population. Methods: Cross-sectional study with 400 T2DM adults from whom socio-demographic, clinical, laboratory data were collected, and screening test for depression symptoms (Patient Health Questionaire- 9 (PHQ-9)), Mini-Mental State Examination (MMSE), Semantic Verbal Fluency Test, Trail Making Test A and B, Word Memory test were performed. All cognitive test scores were converted into Global Cognition z-Score (GCS(z)). The association between GCS(z) < 0 with DR was performed using a multivariate binary logistic regression model adjusted for age ≥ 65 years, school years ≤ 6 years, DM duration ≥ 10 years, depression symptoms score > 9 at PHQ-9, arterial hypertension, physical activity, diabetic retinopathy, macular edema, and cardiovascular disease. Results: After exclusions, the 251 eligible patients were 56.6% female, with a mean age of 61.1 (±9.8) years, DM duration of 12.6 (±8.9) years, and 7.6 (±4.2) years of school education. DR prevalence was 46.5%. Multivariate Logistic Regression Model showed an association between DR and GCS(z) < 0, with odds ratio (CI95%) of 2.50 (1.18-5.34), adjusted for age, low education level, arterial hypertension and depression symptoms (OD and CI95% respectively: 5.46(2.42-12.34); 12.19 (5.62-26.46); 2.55 (0.88-7.39); 3.53 (1.55-8.07)). Conclusion: In this T2DM population, having DR increased the chance for worse cognitive performance even when adjusted for age, low education level, presence of arterial hypertension, and depression symptoms.

Diabetes is a chronic disease that is not easily curable but can be managed efficiently. Artificial Intelligence is a powerful tool that may help in diabetes prediction, continuous glucose monitoring, Insulin injection guidance, and other areas of diabetes care. Diabetes, if not appropriately managed, leads to secondary complications like retinopathy, nephropathy, and neuropathy. Artificial intelligence helps minimize the risk of these complications through software and Artificial Intelligence-based devices. Artificial Intelligence can also help physicians in the early diagnosis and management of diabetes while reducing medical errors. Here we review the advancement of Artificial Intelligence in diabetes management.

The lack of currently available drugs for treating diabetes complications has stimulated our interest in finding new Aldose Reductase inhibitors (ARIs) with more beneficial biological properties. One metabolic method uses aldose reductase inhibitors in the first step of the polyol pathway to control excess glucose flux in diabetic tissues. Computer-aided drug discovery (CADD) is key in finding and optimizing potential lead substances. AR inhibitors (ARI) have been widely discussed in the literature. For example, Epalrestat is currently the only ARI used to treat patients with diabetic neuropathy in Japan, India, and China. Inhibiting R in patients with severe to moderate diabetic autonomic neuropathy benefits heart rate variability. AT-001, an AR inhibitor, is now being tested in COVID-19 to see how safe and effective it reduces inflammation and cardiac damage. In summary, these results from animal and human studies strongly indicate that AR can cause cardiovascular complications in diabetes. The current multi-center, large-scale randomized human study of the newly developed powerful ARI may prove its role in diabetic cardiovascular disease to establish therapeutic potential. During the recent coronavirus disease (COVID-19) outbreak in 2019, diabetes and cardiovascular disease were risk factors for severely negative clinical outcomes in patients with COVID19. New data shows that diabetes and obesity are among the strongest predictors of COVID-19 hospitalization. Patients and risk factors for severe morbidity and mortality of COVID- 19.

Currently, when the world is fighting against the rapidly spreading pandemic of COVID-19, the silent epidemic of diabetes should not be set aside. In comparison, while COVID- 19 led to about 6 million deaths in 2021, diabetes caused 6.7 million deaths in the same year. Diabetes mellitus is a serious risk factor for worse outcomes in COVID-19 patients. Moreover, it seems that there is a bidirectional relationship between pre-existing diabetes pandemic and the rapidly spreading COVID-19 pandemic. In this article, we summarize mechanisms by which SARS-CoV-2 infects the host cell and discuss the bidirectional relationship between diabetes and COVID-19. We also focus on clinical variables in which diabetic patients differ from non-diabetic patients and which could have promising predictive value for the course and outcome of diabetic COVID-19 patients’ therapy management.

Diabetes mellitus, defined as long-standing hyperglycemic conditions caused by a defect in insulin production and activity, has become a major healthcare burden as the number of catastrophic and life-threatening complications rises. Microvascular complications (neuropathy, retinopathy, and nephropathy), and also diabetes-related macrovascular complications are common problems that arise as the life expectancy of diabetic patients has increased despite improved treatment options. While it is impossible to pinpoint the specific crucial timing when the complications become fully entrenched, looking for novel sensitive biomarkers to identify physiological changes in the initial stages would be needed. An increasing amount of data shows that miRNAs, particularly miRNA146a, are stable in a range of body fluids and can be used to identify pathogenic changes at the cellular or tissue level. In this brief review, we highlight the important functioning of miRNA146a and its putative target of action in diabetic microvascular and cardiovascular complications. A decrease in miRNA146a levels may play a critical role in the onset and development of diabetes complications, whereas its anti-inflammatory properties were revealed to be associated with the pathogenesis of numerous diabetic complications, including diabetic nephropathy, retinopathy, neuropathy, and diabetes-related cardiovascular disorders, even tending to be a potential biomarker of the disease's inflammatory status.

Background and Aims: Hypoglycemia and insulin-related adverse events are crucial barriers to effective diabetes management, particularly in the elderly, people with renal impairment, people with diabetes fasting during Ramadan, or people with type 1 diabetes mellitus (T1DM). There is a scarcity of clinical and real-world evidence assessing the effectiveness and safety of insulin glargine 300 U/mL (Gla-300) in these special populations. To understand the entirety of evidence, this mini-review elaborates on the use of Gla-300 in diabetes management among special populations. Methods: Clinical and real-world evidence related to the use of Gla-300 among special populations with diabetes were retrieved using PUBMED and Google Scholar. Results: Gla-300 has shown improved glycemic control with stable insulin action and low risk of hypoglycemia in diverse groups with diabetes. It also appears to have an acceptable safety profile during Ramadan fasting. However, adequate monitoring and adjustment of insulin dose on an individual basis should be considered. Conclusion: Gla-300 is a second-generation basal insulin with proven benefits of reduced risk of hypoglycemia and improved glycemic control in special populations of people with diabetes.

Type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD) are two cardinal manifestations of the metabolic syndrome, which is becoming a growing global pandemic and a health care burden. They constitute a pathogenetic duo, with complex interplay through interrelated, but still partly understood, pathophysiological pathways, which mainly involve lipid toxicity (expressed through increased hepatic de novo lipogenesis, hepatic and peripheral insulin resistance, upregulated lipolysis, lipoprotein abnormalities, hyperinsulinemia), impaired autophagy, mitochondrial dysfunction, endoplasmic reticulum stress, adipose tissue dysfunction with a consequent latent inflammatory state, inflammasome activation, genetic and epigenetic factors, altered gut microbiota and finally dietary factors. In this review, based on data from recent studies and focusing mainly on common molecular mechanisms, we will highlight the common pathophysiological grounds and the interplay between NAFLD and T2DM.

Inadequate glycaemic control post-discharge is the root cause of readmission in people with diabetes mellitus (DM) and is often linked to improper discharge planning (DP). A structured DP plays a crucial role in ensuring continuing home care and avoiding readmissions. DP should help patients in self-care and provide appropriate guidance to maintain optimal glycaemic control. There is a scarcity of reports and recommendations on the proper DP for people with DM on insulin therapy. The present review provides important consideration based on experts’ opinions from the National Insulin and Incretin summit (NIIS), focusing on the effective treatment strategies at the time of discharge, especially for insulin therapy. A review of literature from PubMed and Embase was conducted. The consensus was derived, and recommendations were made on effective DP for patients with DM. Recommendations were drawn at the NIIS for post-discharge treatment for medical and surgical cases, stress-induced hyperglycaemia, elderly, pregnant women, and coronavirus disease 2019 (COVID-19) cases. The committee also recommended a comprehensive checklist to assist the physicians during discharge.

Objectives: The aim of this study is to assess the general health of diabetic type 2 patients by using SF-36 and also to find if there was an association between the scores of eight domains of this tool with disease-specific and demographic variables. Methods: A cross-sectional study was conducted to evaluate the general health of patients with diabetes mellitus type 2. The participants of the present study were randomly selected from rural and urban areas. The diabetic patients visiting community pharmacies in these areas were invited to participate in this study after explaining the goal of the study. A self-reported questionnaire in the Arabic version of the medical outcome survey, the Short-Form (36-item), was conducted. However, uneducated patients were interviewed by trained pharmacists in the community pharmacies. Results and Discussion: Two hundred confirmed DM patients were enrolled in this study with a mean age of (50.65 ± 8.914 years). 142 (71%) were male and the remaining 58 (29%) were female. The scores of all domains of SF-36 were significantly lower (p < 0.05) in female patients in comparison to that recorded in men. In addition, diabetic patients aged more than 50 years showed significantly lower scores of most domains of SF-36 (p < 0.05) except for emotional well-being (p > 0.05). The multivariate linear regression analysis demonstrated that gender, age, and treatment type were independent of health status based on the SF-36 survey, while emotional well-being, social functioning, and pain were exceptional. Conclusion: The outcomes of this study showed a negative correlation between diabetes mellitus and the health status as measured by SF-36. Furthermore, excluding emotional well-being, social functioning, and pain domains, the other parameters of gender, age, and treatment type showed a significant correlation with health status.