scholarly journals Increased spontaneous CCL2 (MCP‐1) and CCL5 (RANTES) secretion in vitro in LADA compared to type 1 diabetes and type 2 diabetes: Action LADA 14

2020 ◽  
Author(s):  
Mark Ooms ◽  
Alexander Strom ◽  
Klaus Strassburger ◽  
Barbara Menart ◽  
Richard D. Leslie ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes

scholarly journals Islet Amyloid Polypeptide: Structure, Function, and Pathophysiology

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Rehana Akter ◽  
Ping Cao ◽  
Harris Noor ◽  
Zachary Ridgway ◽  
Ling-Hsien Tu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cell Death ◽  
Type 1 Diabetes ◽  
Islet Amyloid Polypeptide ◽  
Amyloid Formation ◽  
Islet Amyloid

The hormone islet amyloid polypeptide (IAPP, or amylin) plays a role in glucose homeostasis but aggregates to form islet amyloid in type-2 diabetes. Islet amyloid formation contributes toβ-cell dysfunction and death in the disease and to the failure of islet transplants. Recent work suggests a role for IAPP aggregation in cardiovascular complications of type-2 diabetes and hints at a possible role in type-1 diabetes. The mechanisms of IAPP amyloid formationin vivoorin vitroare not understood and the mechanisms of IAPP inducedβ-cell death are not fully defined. Activation of the inflammasome, defects in autophagy, ER stress, generation of reactive oxygen species, membrane disruption, and receptor mediated mechanisms have all been proposed to play a role. Open questions in the field include the relative importance of the various mechanisms ofβ-cell death, the relevance of reductionist biophysical studies to the situationin vivo, the molecular mechanism of amyloid formationin vitroandin vivo, the factors which trigger amyloid formation in type-2 diabetes, the potential role of IAPP in type-1 diabetes, the development of clinically relevant inhibitors of islet amyloidosis toxicity, and the design of soluble, bioactive variants of IAPP for use as adjuncts to insulin therapy.

Causes of diabetic ketoacidosis: type 1 diabetes versus type 2 diabetes

2017 ◽  
Author(s):  
Marwa Omri ◽  
Rayene Ben Mohamed ◽  
Imen Rezgani ◽  
Sana Mhidhi ◽  
Aroua Temessek ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Diabetic Ketoacidosis

1746-P: Obese Youth with Type 1 Diabetes (T1D) Have Worse Hepatic Insulin Resistance (IR) Than Youth with Type 2 Diabetes (T2D)

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1746-P
Author(s):  
PATTARA WIROMRAT ◽  
MELANIE CREE-GREEN ◽  
BRYAN C. BERGMAN ◽  
KALIE L. TOMMERDAHL ◽  
AMY BAUMGARTNER ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Hepatic Insulin Resistance ◽  
Obese Youth

1264-P: Distinguishing between Obese Patients with Type 1 Diabetes (T1DMob) and Type 2 Diabetes in Adolescence (T2DMad) at Presentation

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1264-P
Author(s):  
FABRIZIO BARBETTI ◽  
RICCARDO BONFANTI ◽  
MAURIZIO DELVECCHIO ◽  
DARIO IAFUSCO ◽  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Obese Patients

110-OR: Type 2 Diabetes (T2D)–Associated TCF7L2 Genetic Variants and Indices of Insulin Secretion and Sensitivity in Individuals at Risk for Type 1 Diabetes (T1D)

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 110-OR
Author(s):  
MARIA J. REDONDO ◽  
MEGAN V. WARNOCK ◽  
LAURA E. BOCCHINO ◽  
SUSAN GEYER ◽  
ALBERTO PUGLIESE ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
At Risk ◽  
Type 1 Diabetes ◽  
Insulin Secretion ◽  
Genetic Variants

Model estimates of the results of diabetes patients using modern glucometers with tri-color technology for displaying test results

2019 ◽  
pp. 81-89
Author(s):  
Larisa Dmitrievna Popovich ◽  
Svetlana Valentinovna Svetlichnaya ◽  
Aleksandr Alekseevich Moiseev
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Economic Benefits ◽  
Test Results ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Impact

Diabetes – a disease in which the effect of the treatment substantially depends on the patient. Known a study showed that the use of glucometers with the technology of three-color display of test results facilitates self-monitoring of blood sugar and leads to a decrease in glycated hemoglobin (HbAlc). Purpose of the study: to modeling the impact of using of a glucometer with a color-coded display on the clinical outcomes of diabetes mellitus and calculating, the potential economic benefits of reducing the hospitalization rate of patients with diabetes. Material and methods. Based on data from two studies (O. Schnell et al. and M. Baxter et al.) simulation of the reduction in the number of complications with the use of a glucometer with a color indication. In a study by O. Schnell et al. a decrease of HbA1c by 0.69 percent is shown when using the considered type of glucometers, which was the basis of the model. Results. In the model, the use of a glucometer with a color-coded display for type 1 diabetes led to a decrease in the total number of complications by 9.2 thousand over 5 years per a cohort of 40 thousand patients with different initial levels of HbA1c. In a cohort of 40 thousand patients with type 2 diabetes, the simulated number of prevented complications was 1.7 thousand over 5 years. When extrapolating these data to all patients with diabetes included in the federal register of diabetes mellitus (FRD), the number of prevented complications was 55.4 thousand cases for type 1 diabetes and 67.1 thousand cases for type 2 diabetes. The possible economic effect from the use of the device by all patients with a diagnosis of diabetes, which are included in the FRD, estimated at 1.5 billion rubles for a cohort of patients with type 1 diabetes and 5.3 billion rubles for patients with type 2 diabetes. Conclusion. Improving the effectiveness of self-monitoring, which is the result of the use of glucometers with color indicators, can potentially significantly reduce the incidence of complications in diabetes and thereby provide significant economic benefits to society.

The Role of Physical Exercise in Obesity and Diabetes

2018 ◽  
Vol 66 (3) ◽  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Physical Exercise ◽  
Treatment Guidelines ◽  
Treatment Guideline ◽  
Obesity And Diabetes ◽  
Regular Physical Exercise

The prevalence of obesity is increasing world-wide. Obesity is associated with a plethora of metabolic and clinical constraints, which result in a higher risk for the development of cardiovascular complications and metabolic disease, particularly insulin resistance and type 2 diabetes. Obesity is an acknowledged determinant of glycemic control in patients with type 1 diabetes and accounts for the majority of premature death due to cardiovascular events. Physical exercise is generally recommended in patients with diabetes in order to prevent the development of or reduce existing obesity, as adopted by every international treatment guideline so far. Regular physical exercise has a beneficial impact on body composition, cardiovascular integrity, insulin sensitivity and quality of life. However, only a minority of patients participates in regular physical exercise, due to individual or ­disease-related barriers. In type 2 diabetes, there is robust evidence for beneficial effects of physical exercise on glycemic control, cardiovascular health and the development of diabetes-related long-term complications. In type 1 diabetes and patients treated with insulin, a higher risk for exercise-­related hypoglycemia has to be considered, which requires certain prerequisites and adequate adaptions of insulin ­dosing. Current treatment guidelines do only incompletely address the development of exercise-related hypoglycemia. However, every patient with diabetes should participate in regular physical exercise in order to support and enable ­sufficient treatment and optimal glycemic control.

Type 1 Diabetes-related Autoantibodies in Different Forms of Diabetes

2019 ◽  
Vol 15 (3) ◽  
pp. 199-204 ◽  
Author(s):  
Elin Pettersen Sørgjerd
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Autoimmune Diabetes ◽  
Acid Decarboxylase ◽  
Adult Onset ◽  
Latent Autoimmune Diabetes ◽  
Childhood Type 1 Diabetes ◽  
Childhood Type

Autoantibodies against Glutamic Acid Decarboxylase (GADA), insulinoma antigen-2 (IA- 2A), insulin (IAA) and the most recently Zinc Transporter 8 (ZnT8A) are one of the most reliable biomarkers for autoimmune diabetes in both children and adults. They are today the only biomarkers that can distinguish Latent Autoimmune Diabetes in Adults (LADA) from phenotypically type 2 diabetes. As the frequency of autoantibodies at diagnosis in childhood type 1 diabetes depends on age, GADA is by far the most common in adult onset autoimmune diabetes, especially LADA. Being multiple autoantibody positive have also shown to be more common in childhood diabetes compared to adult onset diabetes, and multiple autoantibody positivity have a high predictive value of childhood type 1 diabetes. Autoantibodies have shown inconsistent results to predict diabetes in adults. Levels of autoantibodies are reported to cause heterogeneity in LADA. Reports indicate that individuals with high levels of autoantibodies have a more type 1 diabetes like phenotype and individuals with low levels of autoantibody positivity have a more type 2 diabetes like phenotype. It is also well known that autoantibody levels can fluctuate and transient autoantibody positivity in adult onset autoimmune diabetes have been reported to affect the phenotype.

An Approach to diabetic ketoacidosis in an emergency setting.

2020 ◽  
Vol 15 ◽  
Author(s):  
Dario Pitocco ◽  
Mauro Di Leo ◽  
Linda Tartaglione ◽  
Emanuele Gaetano Rizzo ◽  
Salvatore Caputo ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Diabetic Ketoacidosis ◽  
Blood Glucose Concentration ◽  
Diabetic Complication ◽  
Emergency Setting ◽  
Online Activity

Background: Diabetic Ketoacidosis (DKA) is one of the most commonly encountered diabetic complication emergencies. It typically affects people with type 1 diabetes at the onset of the disease. It can also affect people with type 2 diabetes, although this is uncommon. Methods: Research and online content related to diabetes online activity is reviewed. DKA is caused by a relative or absolute deficiency of insulin and elevated levels of counter regulatory hormones. Results: Goals of therapy are to correct dehydration, acidosis and to reverse ketosis, gradually restoring blood glucose concentration to near normal. Conclusion: Furthermore it is essential to monitor potential complications of DKA and if necessary, to treat them and any precipitating events.

scholarly journals Clinical decision support to improve management of diabetes and dysglycemia in the hospital: a path to optimizing practice and outcomes

2021 ◽  
Vol 9 (1) ◽  
pp. e001557
Author(s):  
Ariana Pichardo-Lowden ◽  
Guillermo Umpierrez ◽  
Erik B Lehman ◽  
Matthew D Bolton ◽  
Christopher J DeFlitch ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Stress Hyperglycemia ◽  
Inappropriate Use ◽  
Academic Center

IntroductionInnovative approaches are needed to design robust clinical decision support (CDS) to optimize hospital glycemic management. We piloted an electronic medical record (EMR), evidence-based algorithmic CDS tool in an academic center to alert clinicians in real time about gaps in care related to inpatient glucose control and insulin utilization, and to provide management recommendations.Research design and methodsThe tool was designed to identify clinical situations in need for action: (1) severe or recurrent hyperglycemia in patients with diabetes: blood glucose (BG) ≥13.88 mmol/L (250 mg/dL) at least once or BG ≥10.0 mmol/L (180 mg/dL) at least twice, respectively; (2) recurrent hyperglycemia in patients with stress hyperglycemia: BG ≥10.0 mmol/L (180 mg/dL) at least twice; (3) impending or established hypoglycemia: BG 3.9–4.4 mmol/L (70–80 mg/dL) or ≤3.9 mmol/L (70 mg/dL); and (4) inappropriate sliding scale insulin (SSI) monotherapy in recurrent hyperglycemia, or anytime in patients with type 1 diabetes. The EMR CDS was active (ON) for 6 months for all adult hospital patients and inactive (OFF) for 6 months. We prospectively identified and compared gaps in care between ON and OFF periods.ResultsWhen active, the hospital CDS tool significantly reduced events of recurrent hyperglycemia in patients with type 1 and type 2 diabetes (3342 vs 3701, OR=0.88, p=0.050) and in patients with stress hyperglycemia (288 vs 506, OR=0.60, p<0.001). Hypoglycemia or impending hypoglycemia (1548 vs 1349, OR=1.15, p=0.050) were unrelated to the CDS tool on subsequent analysis. Inappropriate use of SSI monotherapy in type 1 diabetes (10 vs 22, OR=0.36, p=0.073), inappropriate use of SSI monotherapy in type 2 diabetes (2519 vs 2748, OR=0.97, p=0.632), and in stress hyperglycemia subjects (1617 vs 1488, OR=1.30, p<0.001) were recognized.ConclusionEMR CDS was successful in reducing hyperglycemic events among hospitalized patients with dysglycemia and diabetes, and inappropriate insulin use in patients with type 1 diabetes.

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