Successful Glycemic Control Research Articles

The Effectiveness of Lifestyle Changes in Glycemic Control among Pregnant Women with Gestational Diabetes Mellitus.

Background and Objectives: Gestational diabetes mellitus (GDM) is a type of diabetes that develops during pregnancy and affects approximately 10% of pregnant women worldwide. Understanding the impact of lifestyle changes on glycemic control in GDM is important for improving maternal and fetal outcomes and reducing the risk of diabetes in both the mother and child. The aim of this study is to evaluate the effectiveness as well as the factors affecting glycemic control by lifestyle changes in pregnant women with GDM. Materials and Methods: A descriptive cross-sectional study was conducted at three hospitals in the Thai Binh Province from June 2021 to May 2022. All pregnant women at 24-28 weeks of gestation, aged 18 years or older, were enrolled. GDM was diagnosed according to the guidelines of the International Association of the Diabetes and Pregnancy Study Groups. Lifestyle changes including diet and physical exercise were carried out for two weeks. The main outcome measured was successful glycemic control according to the 2018 ADA Recommendations for the Management and Treatment of GDM. Results: 1035 women were included and 20.2% diagnosed with GDM. After two weeks of lifestyle change intervention, 82.6% of the pregnant women with GDM had successful glycemic control. Pregnant women aged under 35 years had a 3.2 times higher rate of gestational glycemic control than those older than 35 (aOR = 3.22, p-value = 0.004). Women with a pre-pregnancy BMI of less than 25 had a higher rate of gestational glycemic control than those with a BMI of over 25 (aOR = 10.84, p-value < 0.001). Compared to women who had all three diagnostic criteria for gestational diabetes, those with two diagnostic criteria and one criterion were 3.8 times and 3 times more likely to have successful blood sugar control (aOR = 3.78, p-value = 0.01 and aOR = 3.03, p-value = 0.03, respectively). Conclusion: Lifestyle changes can be an effective measure for achieving glycemic control in women with GDM. Healthcare providers should consider individualized treatment plans based on the specific needs of each patient.

Current Status of Weekly Insulin Analogs and Their Pharmacokinetic/Pharmacodynamic Evaluation by the Euglycemic Clamp Technique.

Diabetes mellitus represents a significant global health threat characterized by hyperglycemia caused by inadequate insulin secretion and/or insulin resistance. Exogenous insulin supplements had been recognized as a crucial treatment for achieving successful glycemic control in patients with Type 1 and most patients with Type 2 diabetes. Over the past century, substantial progress has been made in the development of novel insulin formulations, including the super-fast-acting and long-acting basal insulin analogs, of which the latter is indispensable for the management of nocturnal fasting and intraprandial blood glucose within the normal physiological range. Recently, combining chemical and genetic engineering with drug optimization have resulted in a formidable evolution in ultra-long-acting weekly insulin. Here, the current state of once-weekly insulin analogs and the euglycemic clamp technique used in the early clinical development to elucidate the pharmacokinetics and pharmacodynamics of this type of novel weekly insulin analogs were systematically overviewed.

Fasting plasma c-peptide level predicts the response of glucagon-like peptide-1 agonist (exenatide) add on to metformin monotherapy in obese type 2 diabetics

We aimed to evaluate the ability of serum C-peptide levels to predict glycemic control in obese type 2 diabetes (T2DM) patients in which a glucagon-like peptide-1 receptor agonist (GLP1-RA), an exenatide, was added to metformin monotherapy. This was a retrospective study, in which we enrolled 44 consecutives obese, type 2 diabetic patients receiving metformin monotherapy and have inadequate glycemic control (HbA1c &gt;7% and &lt;10%). Twice daily GLP1-RA (10 mcg exenatide injection) was added to the treatment. Weight, height and body mass index (BMI), in addition to fasting plasma glucose, hemoglobin A1c (HbA1c), and C-peptide levels measured baseline and at the sixth months post treatment. Regardless of the initial HbA1c level, treatment success was considered a HbA1c level below 7%. Predictors of successful glycemic control were assessed by a regression analysis. The fasting plasma C-peptide level was used as a marker of β cell function. After adding the GLP-1 RA, fasting glucose, C-peptide, BMI, and body weight decreased significantly (p &lt; 0.01 for all). 27 (61.4%) patients were achieved treatment success, who have HbA1c level &lt; 7% at the sixth month. The baseline C-peptide level was correlated with the HbA1c level 6 months post-treatment (r: 0.4, p: 0.01). Multivariate logistic regression analysis showed that the baseline fasting plasma C-peptide level was an independent predictor of successful glycemic control [exp.B: 6.6 (1.63-26-9) p: 0.008]. In a receiver operating characteristics (ROC) curve analysis, a baseline plasma C-peptide level of 2.56 ng/mL was the best cut-off value. Initial fasting plasma C-peptide levels can predict the treatment response of the GLP1-RA (exenatide 10 mcg, twice daily) add on to metformin monotherapy in obese type 2 diabetics.

Identification of a novel hepatocyte nuclear factor-1 alpha (HNF1A) variant in maturity onset diabetes of the young type 3 (HNF1A-MODY).

SummaryWe identified an adolescent young woman with new-onset diabetes. Due to suspicious family history, she underwent genetic testing for common monogenic diabetes (MODY) genes. We discovered that she and her father carry a novel variant of uncertain significance in the HNF1A gene. She was successfully transitioned from insulin to a sulfonylurea with excellent glycemic control. Based on her family history and successful response to sulfonylurea, we propose that this is a novel pathogenic variant in HNF1A. This case highlights the utility of genetic testing for MODY, which has the potential to help affected patients control their diabetes without insulin.Learning pointsHNF1A mutations are a common cause of monogenic diabetes in patients presenting with early-onset diabetes and significant family history.Genetic testing in suspected patients allows for the identification of mutations causing monogenic diabetes.First-degree relatives of the affected individual should be considered for genetic testing.The use of sulfonylurea agents in patients with HNF1A-MODY can reduce dependence on insulin therapy and provide successful glycemic control.

The relationship between postprandial C peptide-glucose ratio, beta-cell function and treatment success in type 2 diabetes mellitus

Objectives: This study aims to investigate the relationship between postprandial C-peptide-to-glucose ratio (PCGR), β-cell function and successful glycemic glycemic control in type 2 diabetes mellitus (DM) and determine the efficacy and feasibility of the PCGR index in the individualization of diabetes treatment. Materials and methods: This prospective study included a total of 49 patients (17 males, 32 females; mean age: 56±10 years; range, 32 to 75 years) under follow-up in Istanbul Medeniyet University Göztepe Training and Research Hospital Department of Internal Medicine with the diagnosis of type 2 DM between June and December 2016. Patients receiving insulin or insulin secretagogues were excluded. Data including age, sex, weight, height, waist circumference, hip circumference, date of DM diagnosis, serum hemoglobin A1c (HbA1c), and creatinine levels were recorded. All patients underwent a mixed meal test and their fasting blood glucose, C-peptide, postprandial glucose, and C-peptide levels were measured and recorded. Patients with a serum HbA1c level of 7% or lower were considered to have good glycemic control while patients with a serum HbA1c level of higher than 7% were considered to have uncontrolled diabetes. The relationship between C-peptide index (CPI), PCGR index, and parameters related to glycemia and β cell function was investigated. Results: Mean diabetes duration was 6.6±6 years and mean serum HbA1c level was 7.9±1.8%. There was a weak correlation between CPI and Homeostasis Model Assessment-β (HOMA-β), a moderate correlation between fasting C-peptide, delta C-peptide, and HOMA-β, and a strong correlation between fasting C-peptide, postprandial C-peptide, PCGR, and HOMA-β (p&lt;0.05, p&lt;0.05, p&lt;0.001, respectively). There was a moderate negative correlation between postprandial C-peptide, delta C-peptide, fasting C-peptide-to-glucose ratio (FCGR), and serum HbA1c level (p&lt;0.05). There was no correlation between fasting C-peptide and serum HbA1c level while there was a strong negative correlation between PCGR and serum HbA1c level (p&lt;0.001). Comparison of the patient groups with and without glycemic control revealed that mean PCGR was significantly higher in the former group than the latter (p&lt;0.001). Conclusion: We conclude that PCGR is significantly associated with glycemic control and variability. Our data suggest that PCGR is a useful index indicating β-cell function, and it can be used in the individualization of DM treatment.

Association between Diabetes Mellitus and Sepsis for the Glycemic Control Outcome of Two Intensive Care Units in Malaysia

Close monitoring and tight glycemic control are required among critically ill patients as they have dynamic metabolism which may precipitate stress-induced hyperglycemia. Clinically, diabetes mellitus (DM) patient with sepsis indicated a high mortality rate. This study investigates the association between DM and non-DM related to sepsis and non-sepsis patients from different insulin infusion therapy management. This study used 128 retrospective data from Hospital A, and 37 retrospective data from Hospital B. ICU patients who received insulin infusion therapy during their stay in the ICU were selected. Both centres implement the sliding scale-based insulin infusion therapy with the target range for blood glucose (BG) level within 6.0 - 10.0 mmol/L. The retrospective clinical data were compared among cohorts for DM and non-DM associated with sepsis and non-sepsis conditions. Findings showed that the DM group had higher insulin sensitivity than non-DM for both cohorts. Meanwhile, cohort B had higher insulin sensitivity than cohort A for all classes. Cohort A (DM+Sepsis) had low insulin sensitivity (66.7 L/(mU.min) and worst condition with sepsis which resulted from the lowest percentage (30.81%) of BG measurement within the target range. The (nonDM+nonSepsis) class had the tightest glycemic control for cohort A (3.4 mmol/L) and cohort B (2.2 mmol/L), as observed by the BG interquartile range. Furthermore, cohort A (nonDM+nonSepsis) had a 41.55% of severe hyperglycemia and 0.12% for severe hypoglycemia. Contrary, cohort B (nonDM+nonSepsis) had the highest percentage within the target range (74.31%) and the lowest percentage of hyperglycemia (18.78%). There was significantly different (p-values &lt;0.05) between cohort A and cohort B in BG level and glucose intake, likewise between sepsis and non-sepsis of non-DM for both cohorts. The findings indicate that a successful glycemic control protocol is much influenced by insulin sensitivity, patient variability, diabetes condition, and patient sepsis status.

Adherence and Persistence to Insulin Therapy in People with Diabetes: Impact of Connected Insulin Pen Delivery Ecosystem.

Diabetes is an increasing public health problem, and insulin is the mainstay for treatment of type 1 diabetes. In type 2 diabetes treatment, insulin therapy is used after oral or other injectable agents become inadequate to achieve glycemic control. Despite the advances in insulin therapy, management of diabetes remains challenging. Numerous studies have reported low adherence and persistence to insulin therapy, which acts as a barrier to successful glycemic control and diabetes management. The aim of this targeted review article is to provide an overview of adherence and persistence to insulin therapy in people with diabetes and to discuss the impact of the emergence of a new connected ecosystem of increasingly sophisticated insulin pens, glucose monitoring systems, telemedicine, and mHealth on diabetes management. With the emergence of a connected diabetes ecosystem, we have entered an era of advanced personalized insulin delivery, which will have the potential to enhance diabetes self-management and clinical management. Early systems promise to unlock the potential to address missed or late bolus insulin delivery, which should help to address non-adherence and non-persistence. Over time, improvements in this ecosystem have the potential to combine insulin data with previously missing contextualized patient data, including meal, glucose, and activity data to support personalized clinical decisions and ultimately revolutionize insulin therapy.

Swimming Program on Mildly Diabetic Rats in Pregnancy.

The present study aims to confirm if the moderate-intensity swimming has successful glycemic control and non-toxic oxidative stress levels and to verify the influence on pancreatic adaptations, embryo implantation, and placental efficiency. Female Wistar rats were randomly distributed to obtain mildly diabetic by streptozotocin induction at birth and the non-diabetic females given vehicle. At adulthood, pregnant rats were put at random into sedentary non-diabetic rats (ND); exercise non-diabetic rats (NDEx); sedentary diabetic rats (D); and exercise diabetic rats (DEx). The rats of the groups submitted to moderate intensity carried loads equivalent to 4% of body weight. On day 17 of gestational day, all rats were submitted to oral glucose tolerance test (OGTT). Next day (GD18), the rats were anesthetized and killed to count implantation sites and to collect placentas, blood, and muscle samples for biochemical biomarkers and pancreas for immunohistochemical analysis. The moderate exercise used was not sufficient to stimulate the aerobic pathway but presented positive results on glucose metabolism, lower embryo postimplantation loss, and pancreatic morphology compared with the sedentary diabetic group. However, the DEx group showed muscular damage, decreased antioxidant defense, and lipid peroxidation. Thus, the moderate-intensity exercise reduces glycemic levels during OGTT and causes no damage to non-diabetic rats related to other analyzed parameters in this study. The exercised diabetic rats present better glycemic metabolism in OGTT, islet pancreatic morphology, and embryofetal development. However, it is necessary an adjustment in this exercise intensity to improve the effectiveness of aerobic training for reduction of maternal muscular and lipid membrane damages.

The Effect of Pituitary Gland Disorders on Glucose Metabolism: From Pathophysiology to Management.

This review aims to explore, present, and discuss disorders of glucose metabolism implicated in pituitary gland diseases, the appropriate interventions, as well as the therapeutic challenges that may arise. Pituitary pathologies may dysregulate glucose homeostasis, as both the excess and deficiency of various pituitary hormones can affect glucose metabolism. Increased circulating levels of growth hormone, glucocorticoids or prolactin have been shown to mainly provoke hyperglycemic states, while hypopituitarism can be associated with both hyperglycemia and hypoglycemia. Addressing the primary cause of these disorders with the use of surgery, medical treatment or radiotherapy forms the cornerstone of current management strategies. Physicians should bear in mind that some such medications have an unfavorable effect on glucose metabolism too. When unsuccessful, or until the appropriate treatment of the underlying pituitary problem, the addition of established antidiabetic therapies might prove useful. Further studies aiming to discover more accurate and effective drug preparations in combination with optimal lifestyle management models will contribute to achieving a more successful glycemic control in these patients.

Effect of Glycemic Control on Right Heart Functions in Type 2 Diabetes Mellitus Patients Free of Clinical Cardiovascular Disease

Diabetes mellitus (DM) is one of the most common endocrine disorders. 90% percent of all diabetics are diagnosed with type 2 DM. DM is closely associated with various vascular diseases, and successful glycemic control prevents micro and macrovascular complications. Although there is data about the relation between glycemic control and left ventricle function, there is hardly any data about the relation between the right ventricular function. We analyzed the relationship between glycemic control and right ventricle function in type 2 DM patients free of clinical cardiovascular diseases (CVD). Patients were selected from the cardiology outpatient clinic. 53 patients formed the DM group; 51 patients formed the control group. All patients' demographic data were recorded. Biochemical tests and echocardiographic examinations were performed. RA and RV diameters were significantly higher in DM group (3.36±0.32 vs 3.13±0.34, P=0.015; 2.80±0.32 vs 2.56±0.22 P=0.005 respectively). Myocardial velocity during isovolumetric contraction (RV/IVV) and myocardial acceleration during Isovolumetric contraction (RV/IVA) were significantly lower in the DM group (14.4±3.17 vs 16.04±4.13 P=0,019; 3.25±0.75 vs 3.95±1,25 P=0.015). There was an intermediate negative correlation between RV/IVV and HBA1C (r=-0.406; P=0.036). HBA1C level was an independent risk factor for RV IVV (β=-0.406; P=0.036). It is shown that RA, RV diameter were significantly higher; RV/IVV and RV/IVA were significantly lower in diabetes mellitus patients free of CVD. Furthermore, there was a significant negative correlation between RV/IVV and HBA1C levels. HBA1C level was an independent risk factor for RV/IVV.

The Gut Microbiota in Women Suffering from Gestational Diabetes Mellitus with the Failure of Glycemic Control by Lifestyle Modification.

Gestational diabetes mellitus (GDM) is prevalent worldwide, leading to a high risk of significant morbidity for both the mother and offspring with complications. Increasing evidences suggest that gut microbiota plays a role in the pathogenesis of GDM. Lifestyle modification is the cornerstones of GDM treatment. However, a number of patients whose blood glucose is not controlled by lifestyle modification still require exogenous insulin to control blood glucose. No observational study is available about the relationship between the gut microbiota in GDM patients and lifestyle modifications. Thus, we investigated the differences in gut microbiota between GDM patients with successful glycemic control (GDM1) and failure of glycemic control (GDM2) by lifestyle modifications. We sequenced the V3-V4 regions of 16S ribosomal ribonucleic acid (rRNA) gene from stool samples of 52 singleton pregnant women with 24–28 weeks of gestation. Our results showed that Blautia, Eubacterium_hallii_group, and Faecalibacterium in the gut microbiota showed significant differences among the normoglycemic mother, GDM1, and GDM2 groups, respectively. The combined diagnostic performance of Blautia, Eubacterium_hallii_group, and Faecalibacterium in differentiating GDM2 from GDM was considered as the most reasonable identification indicator. Gut bacteria may participate in the pathological development of GDM2 through the peroxisome proliferator-activated receptor (PPAR) signaling pathway. These results indicated that Blautia, Eubacterium_hallii_group, and Faecalibacterium had important characteristic changes in the gut microbiota of women with GDM2.

Study of type 2 diabetes management among patients in a Macau primary care setting

In the primary care setting in Macau, type 2 diabetes mellitus (T2DM) is the seventh most common reason for consultation. Inadequate glycaemic control constitutes a major public health problem and...

The Effect of Two Types of Pasta Versus White Rice on Postprandial Blood Glucose Levels in Adults with Type 1 Diabetes: A Randomized Crossover Trial.

Background: Food choices are essential to successful glycemic control for people with diabetes. We compared the impact of three carbohydrate-rich meals on the postprandial glycemic response in adults with type 1 diabetes (T1D). Methods: We performed a randomized crossover study in 12 adults with T1D (age 58.7 ± 14.2 years, baseline hemoglobin A1c 7.5% ± 1.3%) comparing the postprandial glycemic response to three meals using continuous glucose monitoring: (1) "higher protein" pasta containing 10 g protein/serving, (2) regular pasta with 7 g protein/serving, and (3) extra-long grain white rice. All meals contained 42 g carbohydrate; were served with homemade tomato sauce, green salad, and balsamic dressing; and were repeated twice in random order. After their insulin bolus, subjects were observed in clinic for 5 h. Linear mixed effects models were used to assess the glycemic response. Results: Compared with white rice, peak glucose levels were significantly lower for higher protein pasta (-32.6 mg/dL; 95% CI -48.4 to -17.2; P < 0.001) and regular pasta (-43.2 mg/dL, 95% CI -58.7 to -27.7; P < 0.001). The difference between the two types of pastas did not reach statistical significance (-11 mg/dL; 95% CI -24.1 to 3.4; P = 0.17). Total glucose area under the curve was also significantly higher for white rice compared with both pastas (P < 0.001 for both comparisons). Conclusions: This exploratory study concluded that different food types of similar macronutrient content (e.g., rice and pasta) generate significantly different postprandial glycemic responses in persons with T1D. These results provide useful insights into the impact of food choices on and optimization of glucose control. Clinical Trial Registry: clinicaltrials.gov NCT03362151.

779-P: Comparative Effects of Two Types of Pasta vs. White Rice on Postprandial Glucose Levels in Adults with Type 1 Diabetes

Background: Food choices are essential to successful glycemic control in persons with diabetes. Methods: Twelve adults with type 1 diabetes (T1D) (age 58.7±14.2 years, HbA1c 7.5±1.3%) completed an in-clinic double-blinded crossover study comparing the glycemic response to higher protein pasta (10 grams protein/serving), regular pasta (7 grams protein/serving), and white rice. All meals contained 42 grams carbohydrate, were served with homemade tomato sauce, green salad and balsamic dressing, and were repeated in random order. Linear mixed effects models assessed the 5 h postprandial glycemic response. Results: Compared to white rice, peak glucose levels were significantly lower for higher protein pasta (-32.6 mg/dL; 95% CI -48.4, -17.2; p&amp;lt;0.001) and for regular pasta (-43.2 mg/dL, 95% CI -58.7, -27.7; p&amp;lt;0.001). The difference between the two types of pastas did not reach statistical significance (-11 mg/dL; 95% CI -24.1, 3.4; p=0.17). Total glucose area under the curve for the 5 h postprandial period was significantly higher for white rice compared to both pastas (p&amp;lt;0.001) (Table 1). Conclusions: There is a significant difference in postprandial glycemic response in persons with T1D between rice and both types of pasta when consumed in equal amounts of carbohydrate. Persons with T1D need to be aware of the relative impact of commonly consumed carbohydrates in the setting of real-life meals. Disclosure J.E. Pinsker: Research Support; Self; Ascensia Diabetes Care, Dexcom, Inc., Insulet Corporation, LifeScan, Inc., Roche Diabetes Care, Tandem Diabetes Care. Speaker's Bureau; Self; Tandem Diabetes Care. S. Zavitsanou: Employee; Self; Novo Nordisk A/S. J.S. Massa: None. S. Deshpande: None. M. Church: None. C.C. Andre: None. F.J. Doyle: Consultant; Self; ModeAGC. Other Relationship; Self; Insulet Corporation. A. Michelson: None. J. Creason: None. E. Dassau: Consultant; Self; Eli Lilly and Company, Insulet Corporation. Research Support; Self; Dexcom, Inc., DreaMed Diabetes, Ltd., Insulet Corporation, Roche Diabetes Care, Tandem Diabetes Care, Xeris Pharmaceuticals, Inc. Speaker's Bureau; Self; Roche Diabetes Care. Other Relationship; Self; ModAGC. D.M. Eisenberg: Advisory Panel; Self; Barilla Center for Food &amp; Nutrition Foundation. Consultant; Self; Campus for H (Japan), Infinitus (China) Company LTD., Nutrition Development Group, LLC. Funding Barilla Center for Food &amp; Nutrition Foundation

Successful Diabetic Control as Measured by Hemoglobin A1c Is Associated with Lower Urine Risk Factors for Uric Acid Calculi.

To examine the association of glycemic control, including strict glycemic control, with 24-hour urine risk factors for uric acid and calcium calculi. With institutional review board (IRB) approval, we identified 183 stone formers (SFs) with 459 twenty-four-hour urine collections. Hemoglobin A1c (HgbA1c) measures were obtained within 3 months of the urine collection. Collections were categorized into normoglycemic (NG, HgbA1c < 6.5) and hyperglycemic (HG, HgbA1c ≥ 6.5) cohorts; 24-hour urine parameters were compared. The NG cohort was further divided into patients with and without a history of diabetes mellitus (DM) type 2. Variables were analyzed using chi-square, Welch's t-test and multivariate linear regression to adjust for clustering, body mass index (BMI), age, gender, thiazide use, and potassium citrate use. Patients in the HG group were older with higher BMI. Multivariate analysis of the total study population revealed that hyperglycemia correlated with lower pH, higher uric acid relative saturation (RS), lower brushite RS, and higher citrate. NG SFs with and without a history of DM had similar risk factors for uric acid stone formation. Among NG SFs, those with DM had higher urine calcium and calcium oxalate RS than those without DM. However, this difference may be related to other factors since neither parameter correlated with DM on multivariate regression (p > 0.05). Successful glycemic control may be associated with reduced urinary risk factors for uric acid stone formation. Patients with well-controlled DM had equivalent risk factors to those without DM. Glycemic control should be considered a target of the multidisciplinary medical management of stone disease.

Glycemic control in type 2 diabetes: from medication nonadherence to residual vascular risk.

Despite the availability of many new treatment options for type 2 diabetes, the proportion of patients achieving the HbA1c target < 7.0% remains around 50%. We put forward the hypothesis that the unchanged HbA1c results, observed in the last decade in type 2 diabetes patients, are also a consequence of medication nonadherence and clinical inertia. Poor medication-taking behavior is usually defined as medication nonadherence and is responsible for uncontrolled hemoglobin A1c level in 23% of cases. Medication nonadherence may also affect clinical outcomes, as diabetic patients with good adherence (≥80%) had a significant 10% lower rate of hospitalization events and a significant 28% lower rate of all-cause mortality when compared with patients with poor adherence (<80%). Residual vascular risk may be defined as the risk of macrovascular (major cardiovascular events) and microvascular (retinopathy, nephropathy, neuropathy) complications that remains after intensive and successful glycemic control in type 2 diabetes. For major cardiovascular events, risk reduction following intensive glycemic control is 9% and, therefore, residual vascular risk is 91%. For microvascular complications, as nephropathy, residual vascular risk is as high as 80%. Residual vascular risk remains high in type 2 diabetes despite intensive glycemic control. Medication nonadherence by the diabetic patient and clinical inertia by the clinician may have contributed to the high level of residual vascular risk (both macro and microvascular) of type 2 diabetic patients.

Barrier of Self Care Management on Urban Type 2 Diabetic Patients in Bali

Successful glycaemic control could be achieved by diabetes self-care management. The purpose of this study was to explore the barrier of diabetes self-care management to type 2 diabetes patients in urban living. This study used a descriptive phenomenology design. The study was conducted at Mengwi village, Badung regency, Bali, with 20 participants was selected through purposive sampling. The data was collected using the in-depth interview. The result of the study showed most of the participant was male, the age was ranged between 45–60 years old and have been suffering from diabetes mellitus for 5–12 years. Three factors were found related to being the barrier of diabetes self-care management: lack of knowledge of diabetes management, lack of glycemic control, and complications of diabetes management. From the results, it can be concluded that patients with type 2 diabetes mellitus have been having trouble with doing self-care management. The type 2 diabetes mellitus patients experienced difficulties in performing diabetes self-care management.

Successful glycemic control using a flash glucose monitoring system for a pregnant woman with diabetes: a case report

BackgroundGlucose control for pregnant women with glucose intolerance is important, as hyperglycemia may adversely affect the mother and the fetus.Case presentationWe report the case of a pregnant Japanese woman who experienced gestational diabetes mellitus during her first pregnancy and developed impaired glucose tolerance after the delivery. During her second pregnancy with twins, she required up to 75 units of injected insulin to control her postprandial hyperglycemia and occasionally experienced hypoglycemia. We used a newly developed flash glucose monitoring system, which allowed her to successfully achieve ideal glycemic control and experience an uncomplicated delivery.ConclusionWe suggest that this flash glucose monitoring system may be clinically effective for similar cases that involve pregnant women with abnormal glucose tolerance.

Rational Design of Glucose-Responsive Insulin Using Pharmacokinetic Modeling.

A glucose responsive insulin (GRI) is a therapeutic that modulates its potency, concentration, or dosing of insulin in relation to a patient's dynamic glucose concentration, thereby approximating aspects of a normally functioning pancreas. Current GRI design lacks a theoretical basis on which to base fundamental design parameters such as glucose reactivity, dissociation constant or potency, and in vivo efficacy. In this work, an approach to mathematically model the relevant parameter space for effective GRIs is induced, and design rules for linking GRI performance to therapeutic benefit are developed. Well-developed pharmacokinetic models of human glucose and insulin metabolism coupled to a kinetic model representation of a freely circulating GRI are used to determine the desired kinetic parameters and dosing for optimal glycemic control. The model examines a subcutaneous dose of GRI with kinetic parameters in an optimal range that results in successful glycemic control within prescribed constraints over a 24 h period. Additionally, it is demonstrated that the modeling approach can find GRI parameters that enable stable glucose levels that persist through a skipped meal. The results provide a framework for exploring the parameter space of GRIs, potentially without extensive, iterative in vivo animal testing.

MP90-01 SUCCESSFUL DIABETIC CONTROL AS MEASURED BY HEMOGLOBIN A1C DECREASES URINE RISK FACTORS FOR URIC ACID CALCULI

You have accessJournal of UrologyStone Disease: Medical & Dietary Therapy1 Apr 2017MP90-01 SUCCESSFUL DIABETIC CONTROL AS MEASURED BY HEMOGLOBIN A1C DECREASES URINE RISK FACTORS FOR URIC ACID CALCULI Kimberly A Maciolek, Kristina L Penniston, and Sara L Best Kimberly A MaciolekKimberly A Maciolek More articles by this author , Kristina L PennistonKristina L Penniston More articles by this author , and Sara L BestSara L Best More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.2820AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Patients with diabetes mellitus (DM) have lower urine pH and a higher prevalence of uric acid calculi. It is unknown if glycemic control by patients with DM improves urinary risk factors for stones. We examined the association of hemoglobin A1c (HgbA1c), a measure of long-term DM control, with 24hr urine risk factors for uric acid and calcium calculi. METHODS With IRB approval, we identified 278 stone formers (SF) with 24h urine collections and HgbA1c measures obtained within 3 months of the urine collection. Relative saturation indices (RS) were calculated using EQUIL2. Patients were separated by glycemic status: normoglycemic (NG, HgbA1c<6.5) and hyperglycemic (HG, HgbA1c≥6.5); 24-h urine parameters were compared. The NG cohort was further divided into those with no history of DM and those with well controlled DM, characterized by HgbA1c<6.5 near the time of their 24-h urine collection. Variables were analyzed using chi squared, Welch′s t-test and multivariate linear regression to adjust for BMI, age, gender, and for thiazide and/or potassium citrate use. RESULTS Patients in the HG group were older (63 vs 60, p<0.01) and had higher BMI (35.1 vs 31.5, p<0.01). Multivariate analysis revealed that, overall, hyperglycemia was associated with lower pH (5.85 vs 6.30, p<0.001), higher uric acid RS (1.39 vs 0.69, p<0.001), and lower brushite RS (0.85 vs 1.60, p<0.001). SFs with history of DM who were well controlled had similar risk factors for uric acid stone to SFs with no history of DM (pH 6.2 vs 6.4, p=0.50, and uric acid RS 0.87 vs 0.56, p=0.85). Patients with a history of DM had a higher median urine calcium (223 mg/d vs 160, p=0.05) and corresponding higher calcium oxalate RS (1.90 vs 1.46, p=0.02) than SFs with normal HgbA1c. CONCLUSIONS Our study suggests that successful glycemic control may be associated with reduced urinary risk factors for uric acid stone formation. With good glycemic control, patients with DM had equivalent uric acid risk factors to those with no DM history and a subclinical increase in urinary risk factors for calcium stones. Our findings support promoting glycemic control as a component of the multidisciplinary medical management of stone disease. This provides us with the direction needed to reveal whether glycemic control reduces stone risk factors. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e1210 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Kimberly A Maciolek More articles by this author Kristina L Penniston More articles by this author Sara L Best More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...