Cerebral Infarction After Switching From Roxadustat to Daprodustat in a Patient With Renal Anemia.

Renal anemia is generally caused by a decrease in the production of erythropoietin in kidney due to renal dysfunction, and this may be associated with the increase in mortality and cardiovascular events in addition to subjective symptoms such as fatigue and wobbliness. We report a case of an 87-year-old man with type 2 diabetes, hypertension, and dyslipidemia who had received roxadustat (a hypoxia-inducible factor (HIF) prolyl hydroxylase (PH) inhibitor) for renal anemia due to diabetic nephropathy and in whom roxadustat was switched to daprodustat (another HIF-PH inhibitor) due to the onset of central hypothyroidism. About three weeks after this change, the patient developed acute asymptomatic cerebral infarction with an elevation of hemoglobin (Hb). It is unclear if the change to daprodustat was involved in the onset of cerebral infarction. However, this case suggests that particular caution should be paid to unexpected acute elevation of Hb after a change from one HIF-PH inhibitor to another, especially in a patient at high risk for cardiovascular events.

Euglycemic Ketoacidosis and Lactic Acidosis Associated With Metformin Toxicity.

In patients with diabetes, diabetic ketoacidosis (DKA) is a well-documented potential complication, usually presenting with hyperglycemia, anion gap acidosis, and positive ketones. Metformin toxicity in the setting of acute renal failure is also a well-known cause of lactic acidosis. However, metformin-induced euglycemic ketoacidosis is less well-known or studied. We report a case of metformin toxicity in the setting of acute renal failure with both lactic acidosis and ketosis and an initial confounded clinical presentation of sulphonylurea-induced hypoglycemia. A high index of suspicion for metformin-associated lactic acidosis (MALA) and metformin-associated lactic acidosis with euglycemic ketoacidosis (MALKA) should be in place in patients who are taking metformin and presenting with acute renal failure and euglycemia.

Titration of Basal and Prandial Insulin Doses With the Initiation of Glucagon-Like Peptide-1 Receptor Agonist Therapy.

Objective Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have demonstrated significant efficacy in improving glycemic control in type 2 diabetes mellitus, which often results in decreased insulin dose requirements. The purpose of this study was to examine the changes in basal and prandial insulin dose requirements from baseline to three months following initiation of a GLP-1 RA. Methodology A retrospective chart review was conducted of adult insulin-treated patients at the Chertow Diabetes Center, Huntington, WV, who were started on GLP-1 RAs for 24 months. Results Mean daily basal insulin doses decreased by 8.7 units (P = 0.29; mean 8.3% change) and mean daily prandial insulin doses decreased by 9.4 units (P = 0.10; mean 18.4% change) from baseline to three months after starting a GLP-1 RA. Average hemoglobin A1c significantly decreased from 8.8% (73 mmol/mol) at baseline to 8.0% (64 mmol/mol) at three months (P < 0.001). Significant decreases from baseline to three months were also observed in mean body weight, mean low-density lipoprotein (LDL) cholesterol, and mean total cholesterol. Conclusions GLP-1 RA therapy was associated with a significant decrease in hemoglobin A1c, body weight, and LDL-cholesterol from baseline to three months after initiation. Therapy with GLP-1 RAs was also associated with an overall decrease in daily basal and prandial insulin dose requirements, although this finding did not reach statistical significance.

Evaluation of Factors Affecting Neuropathy in Patients With Type 2 Diabetes Using Artificial Neural Networks.

INTRODUCTION: Neuropathy is a common and debilitating complication in type 2 diabetes, affecting quality of life and increasing healthcare costs. Identifying risk factors is essential for early intervention and management. This study aims to evaluate the factors influencing the occurrence of neuropathy in patients with type 2 diabetes using artificial neural networks. METHODS: In this cohort study, data from 371 patients with type 2 diabetes from Fereydunshahr, Iran, were analyzed over a 12-year follow-up period. Participants were selected based on diabetes screenings conducted in 2008 and 2009. Artificial neural networks with varying architectures were trained and validated, and their performance was compared to logistic regression models using receiver operating characteristic (ROC) curve analysis. RESULTS: The prevalence of neuropathy in this cohort study was 31.2%. The best-fitted artificial neural network and logistic regression model had area under the curve (AUC) values of 0.903 and 0.803, respectively. Significant risk factors identified included gender, race, family history of diabetes, type of diabetes treatment, cholesterol levels, triglyceride levels, high-density lipoprotein (HDL) levels, and duration of diabetes. Notably, women, patients with a family history of diabetes, and those using injectable or combined injectable and oral medications were at higher risk of developing neuropathy. CONCLUSION: These findings highlight the importance of vigilant monitoring and proactive management of neuropathy risk factors, especially in women, patients with a family history of diabetes, and those using injectable or combined diabetic medications.

Interplay Between the American Diabetes Association's ABC Targets for Diabetes, Insulin Resistance Indices, and Dyslipidemia in Indian Type 2 Diabetes Patients.

Background The increasing incidence of type 2 diabetes (T2D) in India underscores the pressing need for effective management strategies. Meeting the American Diabetes Association (ADA) ABC targets for diabetes (glycated hemoglobin (HbA1c), blood pressure, and serum low-density lipoprotein cholesterol (LDL-C)) is crucial for effectively managing T2D, as it reflects the optimal control of key metabolic parameters. Insulin resistance (IR) and impaired beta cell function (BCF) have been found to have a significant impact on glycemic control, lipid metabolism, and hypertension, contributing to the complex cardiovascular risk profile of patients with T2D. This study aimed to explore the association between ABC targets for diabetes, IR, BCF, and dyslipidemia in a cross-sectional cohort of T2D patients. Methods This retrospective study examined data from 681 T2D patients with comorbid hypertension and dyslipidemia. The patients were part of a one-year online lifestyle intervention program for diabetes management at the Freedom from Diabetes Clinic in Pune, India, between January 2021 and December 2022. Baseline data (at the time of enrollment in the program) on medical history and anthropometric and biochemical parameters were retrospectively extracted from medical records and used to assess ABC targets and other clinical parameters. The ABC targets for diabetes include three goals: an HbA1c level of less than 7.0%, a blood pressure level of less than 140/90 mmHg, and an LDL-C level of less than 100 mg/dL. Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Homeostatic Model Assessment of Beta Cell Function (HOMA-B), and Quantitative Insulin Sensitivity Check Index (QUICKI) were calculated using standard formulas. Results Cross-sectional analysis at baseline showed that 152 (22.3%) participants met all three ABC targets, 306 (45.0%) and 183 (26.8%) participants met two or one targets, respectively, and 40 (5.9%) did not meet any of the ABC targets. Participants meeting all three targets showed significantly lower IR, higher sensitivity (HOMA-IR, median 2.1; QUICKI, median 0.34), higher BCF (HOMA-B, median 62.9), and healthier lipid profiles (mg/dL) (total cholesterol, median 126; triglycerides, median 114; and non-high-density lipoprotein (HDL), median 84) than those who did not meet any of the ABC targets (HOMA-IR, median 3.4; QUICKI, median 0.31; HOMA-B, median 31.7; total cholesterol, median 221; triglycerides, median 187; and non-HDL, median 182) (p < 0.01). A significant association was observed between lower BMI (< 25 kg/m2), lower IR (HOMA-IR <2.5), and meeting all three ABC targets (p < 0.01). No significant association was observed between the duration of diabetes and ABC target status (p > 0.1). Lower IR was identified as a predictor of achievement of all three ABC targets (p < 0.01). Conclusion This study highlights the significance of meeting ABC targets for diabetes in relation to not only a better lipid profile but also lower IR and higher BCF. These preliminary findings provide novel insights into the interplay between IR, BCF, dyslipidemia, and meeting ABC targets in an Indian T2D population. These findings highlight the need for effective diabetes management strategies and improved patient outcomes, considering factors such as BMI and IR indices.

Factors affecting continuous participation in follow-up evaluations during a lifestyle intervention programme for type 2 diabetes prevention: The Feel4Diabetes-study.

AIMS: Community- and school-based lifestyle interventions are an efficient method of preventing type 2 diabetes in vulnerable populations. Many participants, however, fail to complete the necessary follow-ups. We investigated factors affecting the continuous participation in follow-up evaluations during the Feel4Diabetes-study, a multilevel intervention programme implemented across Europe. METHODS: Socioeconomic, sociodemographic and clinical factors were assessed for 2702 participants within six participating countries: Bulgaria and Hungary (low-to-middle-income countries, LMIC), Belgium and Finland (high-income countries, HIC) and Greece and Spain (high-income countries under austerity measures, HICAM). RESULTS: Statistically significant differences were detected with respect to sex, control group, education level, employment status, BMI and blood pressure measurements (systolic and diastolic blood pressure). Post hoc analysis revealed significant differences within socioeconomic regions. Higher levels of education were associated with significantly lower attrition in HIC (p < 0.05) and HICAM (p < 0.001), higher employment status was associated with lower attrition in HICAM (p < 0.001) and being female was associated with lower attrition in LMIC (p < 0.001). Surprisingly, the intervention group exhibited higher-than-expected attrition in HIC (p < 0.001) and HICAM (p = 0.003), and lower attrition in LMIC (p = 0.007). When tested together in the same multivariable predictive model, all sociodemographic and socioeconomic variables along with higher BMI retained their statistical significance, while systolic and diastolic blood pressure failed to remain significant. CONCLUSIONS: Key socioeconomic and sociodemographic factors along with BMI play a significant role in determining continuous participation in follow-up evaluations during school- and community-based intervention programmes.

Exploring the in vitro stability of insulin degrading enzyme as a potential biomarker for neurocognitive disorders and Alzheimer's disease risk.

Insulin degrading enzyme (IDE) plays a critical role in degrading insulin and beta-forming proteins, implicating its significance as a biomarker in metabolic dysfunction and neurocognitive disorders, including Alzheimer's disease (AD). Understanding the impact of pre-analytic conditions of in vitro IDE levels is imperative for reliable biomarker assessment. This study explored the influence of freeze-thaw cycles, storage temperature, and storage time on IDE levels in human serum. Serum samples from seven healthy volunteers were subjected to various storage conditions, including refrigeration (4 °C) and freezing (-20 °C and -80 °C) for 24 h and six months, with differing freeze-thaw cycles. In vitro IDE levels were measured at 24 h and after 6 months using ELISA. Results indicate that while short-term storage at either -20 °C or -80 °C yielded similar IDE levels, prolonged storage and multiple freeze-thaw cycles significantly impacted IDE stability, with colder temperatures exhibiting better preservation. Although further research with larger cohorts and longer storage time is warranted to establish clinical significance, our study suggests preferential use of unthawed samples or consistent freeze-thaw conditions for accurate IDE assessment. Thus, optimizing sample storage conditions is paramount for reliable IDE biomarker analysis in clinical and research settings.

Diabetes and Stroke: Impact of Novel Therapies for the Treatment of Type 2 Diabetes Mellitus.

Type 2 diabetes mellitus (T2DM) is a significant risk factor for stroke. Nevertheless, the evidence supporting stringent glycemic control to reduce macrovascular complications, particularly stroke, is not as clear as for microvascular complications. Presently, risk reduction strategies are based on controlling multiple risk factors, including hypertension, dyslipidemia, glycemia, smoking, and weight. Since 2008, new pharmacological therapies for treating T2DM have been required to undergo trials to ensure their cardiovascular safety. Remarkably, several novel therapies have exhibited protective effects against the combined endpoint of major cardiovascular events. Evidence from these trials, with stroke as a secondary endpoint, along with real-world data, suggests potential benefits in stroke prevention, particularly with glucagon-like peptide 1 receptor agonists. Conversely, the data on sodium-glucose cotransporter type 2 inhibitors remains more controversial. Dipeptidyl peptidase 4 inhibitors appear neutral in stroke prevention. More recent pharmacological therapies still lack significant data on this particular outcome. This article provides a comprehensive review of the evidence on the most recent T2DM therapies for stroke prevention and their impact on clinical practice.

Association of Anxiety and Depressive Symptoms and Treatment Adherence Among Patients With Type 2 Diabetes Mellitus in Jazan, Saudi Arabia: A Cross-Sectional Study.

BACKGROUND: Diabetes mellitus is a serious public health concern. It is associated with many psychological problems, such as depression, anxiety, and eating disorders. These co-morbidities are associated with improper adherence to treatment, self-care, poor glycemic control, more complications, and worse outcomes. METHODS: This study aimed to measure the level of medication adherence among type 2 diabetics in Jazan, Saudi Arabia, and to find its association with their psychological status (specifically, depression and anxiety). A cross-sectional descriptive design was used among adults with type 2 diabetes at the Diabetes and Endocrinology Center in Jazan, Saudi Arabia. The estimated sample size was 480 patients. The General Medication Adherence Scale and Patient Health Questionnaire-4 (PHQ-4) were used as tools to achieve the study objectives. RESULTS: A total of 449 diabetic patients completed the survey (93.5% response rate). Patients with poor, low, and partial adherence account for 337 (75%) of patients and only 112 (25%) have good and high medication adherence. Employment and duration of illness were highly significant with a positive relationship to treatment adherence (p = 0.010 and 0.000, respectively). On the other hand, age and disease duration had a significant relationship with psychological disorders (p = 0.029 and 0.002, respectively). Of the patients, 64 (14.3%) had high scores on the PHQ-4, with depressive symptoms in 46 (10.24%) and anxiety symptoms in 75 (16.7%). Correlation analysis reveals that there is a highly significant negative correlation between psychological disorders and adherence to medications (r = -0.288, p = 0.000). CONCLUSION: A negative correlation between psychological disorders and adherence to medications was found. The findings indicate the importance of psychological support for diabetic patients for better treatment adherence.

Pancreas Β-Cells in Type 1 and Type 2 Diabetes: Cell Death, Oxidative Stress and Immune Regulation. Recently Appearing Changes in Diabetes Consequences.

Diabetes mellitus type 1 (T1D) and type 2 (T2D) develop due to dysfunction of the Langerhans islet ß-cells in the pancreas, and this dysfunction is mediated by oxidative, endoplasmic reticulum (ER), and mitochondrial stresses. Although the two types of diabetes are significantly different, ß-cell failure and death play a key role in the pathogenesis of both diseases, resulting in hyperglycemia due to a reduced ability to produce insulin. In T1D, ß-cell apoptosis is the main event leading to hyperglycemia, while in T2D, insulin resistance results in an inability to meet insulin requirements. It has been suggested that autophagy promotes ß-cell survival by delaying apoptosis and providing adaptive responses to mitigate the detrimental effects of ER stress and DNA damage, which is directly related to oxidative stress. As people with diabetes are now living longer, they are more susceptible to a different set of complications. There has been a diversification in causes of death, whereby a larger proportion of deaths among individuals with diabetes is attributable to nonvascular conditions; on the other hand, the proportion of cancer-related deaths has remained stable or even increased in some countries. Due to the increasing cases of both T1D and T2D, these diseases become even more socially significant. Hence, we believe that search for any opportunities for control of this disease is an overwhelmingly important target for the modern science. We focus on two differences that are characteristic of the development of diabetes's last periods. One of them shows that all-cause death rates have declined in several diabetes populations, driven in part by large declines in vascular disease mortality but large increases in oncological diseases. Another hypothesis is that some T2D medications could be repurposed to control glycemia in patients with T1D.

Correlation of Blood Urea and Creatinine Levels With Thiamin Levels in Type 1 and Type 2 Diabetic Patients.

Introduction Serum urea and creatinine levels are the most commonly recognized parameters for evaluating renal impairment in patients with diabetes mellitus (DM). Therefore, this study evaluated the correlation between urea and creatinine levels and thiamin levels in patients with type 1 DM (T1DM) and type 2 DM (T2DM). Methods This multi-center, cross-sectional study was conducted at diabetic outpatient clinics in Karachi. The duration of the study was six months, from 1st January 2023 to 30th June 2023. A total of 60 patients were enrolled and divided into two groups, i.e., T1DM and T2DM, each containing 30 patients of both genders between the ages of 24 and 42 years. Demographic data and biochemical variables, such as urea, creatinine, random blood sugar, fasting blood sugar, hemoglobin A1c, and serum thiamin levels, were assessed. The Mann-Whitney U test and independent t-test were used to associate the means between the two study groups. The chi-square test and Spearman's correlation coefficient were used to determine the associations between the variables and T1DM and T2DM. Results The study results revealed that patients with T2DM had a significantly higher frequency of hypertension (p = 0.039), neuropathy (p = 0.038), and coronary artery disease (p = 0.010) than those with T1DM, in both genders. The level of serum thiamin was found to be significantly higher (p < 0.001) in T2DM (14.8 ± 4.82) than in T1DM patients (7.34 ± 1.90). Similarly, serum creatinine was higher in T2DM than in T1DM patients (0.83 ± 0.12 vs. 0.76 ± 0.17, p = 0.025). Moreover, the correlation of urea and creatinine with thiamin levels in T1DM and T2DM patients revealed that in T1DM and T2DM patients, urea and creatinine showed an insignificant positive correlation with thiamin levels. Conclusion We found a significantly higher level of serum creatinine and thiamin levels in T2DM patients than in T1DM; however, there was no significant correlation between urea and creatinine levels and thiamin status in T1DM and T2DM patients. Therefore, we conclude that although serum urea, creatinine, and serum thiamin are important disease biomarkers in diabetic patients, there is no correlation between them.

WhatsApp-based intervention for people with type 2 diabetes: A randomized controlled trial.

Diabetes mellitus is a metabolic disease characterized by prolonged elevated blood glucose levels. Diabetes self-management education and support programs are widely used in western countries. The impact of social media education and support interventions such as a WhatsApp-based program and the nurses' role in supporting and implementing this self-management program unclear. Using a WhatsApp-based program, we evaluated the effects of a 6-week program in improving self-efficacy and education among people with type 2 diabetes mellitus in Saudi Arabia. Eligible participants (n = 80) were recruited with the support of nurses into a randomized controlled trial and randomly assigned into self-management intervention and control groups. The intervention group (n = 40) received the self-management program support and the usual care. The control group (n = 40) received only the usual care with nurses' support. Results from generalized estimating equation analysis showed a significant increase in self-efficacy, self-management, and education in the WhatsApp-based intervention support group compared with the control group at 6 and 12 weeks (follow-up). Implementing the program via social media improves self-efficacy. The use of social media platforms should be promoted for global diabetes management.

Continuous glucose monitoring for glycaemic control and cardiovascular risk reduction in patients with type 2 diabetes not on insulin therapy: A clinical trial.

AIM: To evaluate the impact of the Dexcom G6 continuous glucose monitoring (CGM) device on glycaemic control and cardiometabolic risk in patients with type 2 diabetes mellitus (T2DM) at high cardiovascular risk who are not on insulin therapy. MATERIALS AND METHODS: Adults with T2DM with glycated haemoglobin (HbA1c) >7% and body mass index (BMI) ≥30 kg/m2 not using insulin were enrolled in a two-phase cross-over study. In phase 1, CGM data were blinded, and participants performed standard glucose self-monitoring. In phase 2, the CGM data were unblinded, and CGM, demographic and cardiovascular risk factor data were collected through 90 days of follow-up and compared using paired tests. RESULTS: Forty-seven participants were included (44% women; 34% Black; mean age 63 years; BMI 37 kg/m2; HbA1c 8.4%; 10-year predicted atherosclerotic cardiovascular disease risk 24.0%). CGM use was associated with a reduction in average glucose (184.0 to 147.2 mg/dl, p < .001), an increase in time in range (57.8 to 82.8%, p < .001) and a trend towards lower glucose variability (26.2 to 23.8%). There were significant reductions in HbA1c, BMI, triglycerides, blood pressure, total cholesterol, diabetes distress and 10-year predicted risk for atherosclerotic cardiovascular disease (p < .05 for all) and an increase in prescriptions for sodium-glucose cotransporter 2 inhibitors (36.2 to 83.0%) and glucagon-like peptide-1 receptor agonists (42.5 to 87.2%, p < .001 for both). CONCLUSIONS: Dexcom G6 CGM was associated with improved glycaemic control and cardiometabolic risk in patients with T2DM who were not on insulin. CGM can be a safe and effective tool to improve diabetes management in patients at high risk for adverse cardiovascular outcomes.

Ensemble machine learning reveals key features for diabetes duration from electronic health records.

Diabetes is a metabolic disorder that affects more than 420 million of people worldwide, and it is caused by the presence of a high level of sugar in blood for a long period. Diabetes can have serious long-term health consequences, such as cardiovascular diseases, strokes, chronic kidney diseases, foot ulcers, retinopathy, and others. Even if common, this disease is uneasy to spot, because it often comes with no symptoms. Especially for diabetes type 2, that happens mainly in the adults, knowing how long the diabetes has been present for a patient can have a strong impact on the treatment they can receive. This information, although pivotal, might be absent: for some patients, in fact, the year when they received the diabetes diagnosis might be well-known, but the year of the disease unset might be unknown. In this context, machine learning applied to electronic health records can be an effective tool to predict the past duration of diabetes for a patient. In this study, we applied a regression analysis based on several computational intelligence methods to a dataset of electronic health records of 73 patients with diabetes type 1 with 20 variables and another dataset of records of 400 patients of diabetes type 2 with 49 variables. Among the algorithms applied, Random Forests was able to outperform the other ones and to efficiently predict diabetes duration for both the cohorts, with the regression performances measured through the coefficient of determination R2. Afterwards, we applied the same method for feature ranking, and we detected the most relevant factors of the clinical records correlated with past diabetes duration: age, insulin intake, and body-mass index. Our study discoveries can have profound impact on clinical practice: when the information about the duration of diabetes of patient is missing, medical doctors can use our tool and focus on age, insulin intake, and body-mass index to infer this important aspect. Regarding limitations, unfortunately we were unable to find additional dataset of EHRs of patients with diabetes having the same variables of the two analyzed here, so we could not verify our findings on a validation cohort.

Comparative Study of Azithromycin Versus Doxycycline Effect on the Resistin Level in Periodontitis Patients With Type 2 Diabetes: A Randomized Controlled Clinical Trial.

AIM: The present study aimed to determine if azithromycin (AZM) and doxycycline therapy, as an adjunct to scaling and root planning (SRP), modulate host response and improve clinical outcomes in periodontitis patients with type 2 diabetes mellitus (T2DM). PATIENTS AND METHODS: Forty-five periodontal sites in 15 periodontitis patients with T2DM received nonsurgical periodontal therapy (NSPT). In Group I, patients were placebo (not receiving any medication), Group II patients received systemic AZM therapy (AZM 250 mg/day for five days), and Group III patients received doxycycline (20 mg twice per day for three months. The resistin level was collected and measured by enzyme-linked immunosorbent assay (ELISA). Gingival index (GI), probing depth (PD), and clinical attachment level (CAL) were recorded at baseline, one-month, and three-month intervals. RESULTS: All groups showed improvement in clinical parameters and resistin levels throughout the study. The mean resistin level at three months was the highest in Group I and the lowest in Group III. Patients in Group II showed a larger decrease in mean PD than those in Group I and III. Group III had the highest gain in mean CAL, with an increase of 1.78 mm in attachment. CONCLUSION: Resistin might be a useful indicator of current disease status. In addition, benefits from adjunctive systemic use of AZM and doxycycline have been administered with non-surgical periodontal therapy.

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta-analysis.

AIM: To conduct a systematic review with meta-analysis to provide a comprehensive synthesis of randomized controlled trials (RCTs) and prospective cohort studies investigating the effects of currently available bolus advisors on glycaemic parameters in adults with diabetes. MATERIALS AND METHODS: An electronic search of PubMed, Embase, CINAHL, Cochrane Library and ClinicalTrials.gov was conducted in December 2022. The risk of bias was assessed using the revised Cochrane Risk of Bias tool. (Standardized) mean difference (MD) was selected to determine the difference in continuous outcomes between the groups. A random-effects model meta-analysis and meta-regression were performed. This systematic review was registered on PROSPERO (CRD42022374588). RESULTS: A total of 18 RCTs involving 1645 adults (50% females) with a median glycated haemoglobin (HbA1c) concentration of 8.45% (7.95%-9.30%) were included. The majority of participants had type 1 diabetes (N = 1510, 92%) and were on multiple daily injections (N = 1173, 71%). Twelve of the 18 trials had low risk of bias. The meta-analysis of 10 studies with available data on HbA1c showed that the use of a bolus advisor modestly reduced HbA1c compared to standard treatment (MD -011%, 95% confidence interval -0.22 to -0.01; I2 = 0%). This effect was accompanied by small improvements in low blood glucose index and treatment satisfaction, but not with reductions in hypoglycaemic events or changes in other secondary outcomes. CONCLUSION: Use of a bolus advisor is associated with slightly better glucose control and treatment satisfaction in people with diabetes on intensive insulin treatment. Future studies should investigate whether personalizing bolus advisors using artificial intelligence technology can enhance these effects.

Diagnosing Osteoporosis in Diabetes-A Systematic Review on BMD and Fractures.

PURPOSE OF REVIEW: Recently, the American Diabetes Association updated the 2024 guidelines for Standards of Care in Diabetes and recommend that a T-score of - 2.0 in patients with diabetes should be interpreted as equivalent to - 2.5 in people without diabetes. We aimed to evaluate the most recent findings concerning the bone mineral density (BMD)-derived T-score and risk of fractures related to osteoporosis in subjects with diabetes. RECENT FINDINGS: The dual-energy X-ray absorptiometry (DXA) scan is the golden standard for evaluating BMD. The BMD-derived T-score is central to fracture prediction and signifies both diagnosis and treatment for osteoporosis. However, the increased fracture risk in diabetes is not sufficiently explained by the T-score, complicating the identification and management of fracture risk in these patients. Recent findings agree that subjects with type 2 diabetes (T2D) have a higher T-score and higher fracture risk compared with subjects without diabetes. However, the actual number of studies evaluating the direct association of higher fracture risk at higher T-score levels is scant. Some studies support the adjustment based on the 0.5 BMD T-score difference between subjects with T2D and subjects without diabetes. However, further data from longitudinal studies is warranted to validate if the T-score treatment threshold necessitates modification to prevent fractures in subjects with diabetes.

Mitochondrial bioenergetics, metabolism, and beyond in pancreatic ß-cells and diabetes.

In Type 1 and Type 2 diabetes, pancreatic ß-cell survival and function are impaired. Additional etiologies of diabetes include dysfunction in insulin-sensing hepatic, muscle, and adipose tissues as well as immune cells. An important determinant of metabolic health across these various tissues is mitochondria function and structure. This review focuses on the role of mitochondria in diabetes pathogenesis, with a specific emphasis on pancreatic ß-cells. These dynamic organelles are obligate for ß-cell survival, function, replication, insulin production, and control over insulin release. Therefore, it is not surprising that mitochondria are severely defective in diabetic contexts. Mitochondrial dysfunction poses challenges to assess in cause-effect studies, prompting us to assemble and deliberate the evidence for mitochondria dysfunction as a cause or consequence of diabetes. Understanding the precise molecular mechanisms underlying mitochondrial dysfunction in diabetes and identifying therapeutic strategies to restore mitochondrial homeostasis and enhance ß-cell function are active and expanding areas of research. In summary, this review examines the multidimensional role of mitochondria in diabetes, focusing on pancreatic ß-cells and highlighting the significance of mitochondrial metabolism, bioenergetics, calcium, dynamics, and mitophagy in the pathophysiology of diabetes. We describe the effects of diabetes-related gluco/lipotoxic, oxidative and inflammation stress on ß-cell mitochondria, as well as the role played by mitochondria on the pathologic outcomes of these stress paradigms. By examining these aspects, we provide updated insights and highlight areas where further research is required for a deeper molecular understanding of the role of mitochondria in ß-cells and diabetes.

HbA1c and fasting plasma glucose levels are equally related to incident cardiovascular risk in a high CVD risk population without known diabetes.

OBJECTIVES: Type 2 diabetes (T2DM) is associated with increased risk for cardiovascular disease (CVD). Whether screen-detected T2DM, based on fasting plasma glucose (FPG) or on HbA1c, are associated with different risks of incident CVD in high-risk populations and which one is preferable for diabetes screening in these populations, remains unclear. METHODS: 8,274 high-risk CVD participants were included from the UCC-SMART cohort. Participants were divided into groups based on prior T2DM diagnosis, and combinations of elevated/non-elevated FPG and HbA1c (cut-offs at 7 mmol/L and 48 mmol/mol, respectively): Group 0: known T2DM; group 1: elevated FPG/HbA1c; group 2: elevated FPG, non-elevated HbA1c; group 3: non-elevated FPG, elevated HbA1c; group 1 + 2: elevated FPG, regardless of HbA1c; group 1 + 3: elevated HbA1c, regardless of FPG; and group 4 (reference), non-elevated FPG/HbA1c. RESULTS: During a median follow-up of 6.3 years (IQR 3.3-9.8), 712 cardiovascular events occurred. Compared to the reference (group 4), group 0 was at increased risk (HR 1.40; 95 % CI 1.16-1.68), but group 1 (HR 1.16; 95 % CI 0.62-2.18), 2 (HR 1.18; 95 % CI 0.84-1.67), 3 (HR 0.61; 95 % CI 0.15-2.44), 1 + 2 (HR 1.17; 95 % CI 0.86-1.59) and 1 + 3 (HR 1.01; 95 % CI 0.57-1.79) were not. However, spline interpolation showed a linearly increasing risk with increasing HbA1c/FPG, but did not allow for identification of other cut-off points. CONCLUSIONS: Based on current cut-offs, FPG and HbA1c at screening were equally related to incident CVD in high-risk populations without known T2DM. Hence, neither FPG, nor HbA1c, is preferential for diabetes screening in this population with respect to risk of incident CVD.