scholarly journals Efficacy of sandostatin LAR in type 1 DM; improvement in glycemic control with less insulin. a case report

2011 ◽  
Vol 01 (01) ◽  
pp. 15-16
Author(s):  
James Bonucchi ◽  
Kathy Lilli ◽  
Udaya Kabadi
Keyword(s):  
Case Report ◽  
Glycemic Control ◽  
Type 1 Dm

scholarly journals Different insulin treatment regimens in patient with diabetes mellitus type 1: Effects on quality of life

2012 ◽  
Vol 69 (7) ◽  
pp. 569-575 ◽  
Author(s):  
Jelena Stojanovic ◽  
Dragoslav Milosevic ◽  
Ilija Antovic ◽  
Goran Sekulic ◽  
Teodora Beljic-Zivkovic
Keyword(s):  
Glycemic Control ◽  
Metabolic Control ◽  
Insulin Treatment ◽  
Vascular Complications ◽  
Well Being ◽  
Insulin Analogues ◽  
Treatment Regimens ◽  
Type 1 Dm

Background/Aim. Despite of contemporary diabetes mellitus (DM) treatment, one half of patients do not achieve an optimal metabolic control. Considering great psychological burden of diabetic patients, the purpose of this study was to assess the effect of different insulin treatment regimens, glycemic control and the presence of vascular complications on self-reported well-being and quality of life (QoL) of subjects with type 1 DM. Methods. The patients with type 1 DM (n = 122) recruited from the outpatient Diabetes Endocrinology Clinic of Zvezdara University Medical Center were divided into 4 groups according to the specific treatment regimen: 26 were on continuous subcutaneous insulin infusion (CSII), 30 on conventional insulin therapy, 33 on multiple daily injections (MDI) with human insulins, and 33 on MDI with insulin analogues. QoL was assessed by self-reported well-being with the following questionnaires: WHO-5 item Well Being Index (WHO- 5), 36 item Short Form (SF-36) survey, and Insulin Treatment Appraisal Scale (ITAS). Objective metabolic control was assessed by glycosylated hemoglobin (HbA1c), lipid levels and the presence of vascular complications. Statistical analyses used in this crosssectional study included: descriptive statistics, Student?s t-test, Chisqare test, contingency tables, ANOVA and correlation methods. Results. The patients on CSII had significantly better metabolic control than all other treatment groups, especially when compared to the one on conventional therapy (CSII HbA1c 7.07 ? 1.48% vs conventional therapy, HbA1c 10.04 ? 1.44; p = 0.000). No significant difference in glycemic control was observed between patients on MDI with human insulins and insulin analogues. Good glycemic control significantly influenced the reported QoL. The patients with retinopathy and nephropathy reported significantly lower physical well-being, and the patients with polyneuropathy and cardiovascular complications reported also lower psychological well being. Conclusions. Insulin treatment regiment selection affects not only objective metabolic control, but also QoL.

scholarly journals Distribution of Thyroid Autoantibodies in Saudi Children with Type 1 DM and their Effect on Glycemic Control

2017 ◽  
Vol 10 (1) ◽  
pp. 29-35
Author(s):  
Elhashimi E. Hassan ◽  
Ehab A. M. Elagab ◽  
Hassan B Mohammed ◽  
Ahmed El-basher Abdelgader ◽  
Amar B. Elhussein ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Thyroid Autoantibodies ◽  
Type 1 Dm

scholarly journals MON-086 Various Subcutaneous Continuous Glucose Monitors Comparably Lower HbA1c in Children

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Steven Gold ◽  
Liam McGuirk ◽  
James Haigney ◽  
Jane Torres ◽  
Tara Patale ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Metabolic Control ◽  
Glucose Monitoring ◽  
Initial Visit ◽  
High Hba1c ◽  
The Difference ◽  
Continuous Glucose Monitors ◽  
Type 1 Dm ◽  
Hba1c Levels

Abstract Background: Preliminary studies have demonstrated improvement in metabolic control of patients (PTs) using subcutaneous Continuous Glucose Monitoring systems (CGMs). In this study, we investigated the effect of CGMs on PTs’ glycemic control and compared the change in patient HbA1c levels between sensors. Objective: To determine how CGMs affect metabolic control in PTs and the effect of different sensors on glycemic control. Patients and Methods: 33 PTs with Type 1 diabetes mellitus (DM) who began using a CGM between 2017 and 2019 were selected for inclusion. CGM systems used included DexcomG6™, DexcomG5™, DexcomG4™, Enlite™, Guardian 3™, or Medtronic Sure-T™ sensors. Results: The mean (MN) age of PTs at initial visit was 15.3 ± 5.1 yrs and the MN age at second visit was 15.8 ± 5.1 yrs. The MN time between visits was 5.0 ± 2.4 months (mos). 6 PTs had follow up (F/U) times less than 3 mos, 18 PTs had F/U times between 3 and 6 mos, 6 PTs had F/U times between 6 and 9 mos, and 3 PTs had F/U times greater than 9 mos. The MN and median (MD) HbA1c at the initial visit for all PTs was 8.28% ± 1.48 and 8.10%, respectively. The MN and MD HbA1c at final F/U for all PTs was 7.57% ± 1.11 and 7.50%, respectively. The difference in MN HbA1c was significant (p<0.001). The MN and MD HbA1c at the initial visit for PTs with a F/U time less than 3 mos was 7.55% ± 0.77 and 7.75%, respectively. The MN and MD HbA1c at F/U for these PTs was 7.20% ± 0.79 and 7.20%, respectively. The difference in MN HbA1c was significant (p<0.05). The MN and MD HbA1c at the initial visit for all PTs with a F/U time greater than 3 mos was 8.44% ± 1.53 and 8.10%, respectively. The MN and MD HbA1c at F/U for these PTs was 7.66% ± 1.15 and 7.50%, respectively. The difference in MN HbA1c was significant (p<0.001). The MN change of HbA1c between visits was not significant between PTs who had 3–6 mo, 6–9 mo, and 9+ mo F/U times (p=0.96) 15 PTs had HbA1c levels less than or equal to 8.0%. The MN and MD HbA1c at initial visit for these PTs was 7.20% ± 0.41 and 7.30%, respectively. The MN and MD HbA1c at F/U for these PTs was 6.75% ± 0.47 and 6.80%, respectively. The difference in MN HbA1c was significant (p<0.001). 20 PTs had HbA1c levels greater than 8.0% at initial visit. The MN and MD HbA1c at the initial visit for these PTs was 9.18% ± 1.47 and 8.80%, respectively. The MN and MD HbA1c at F/U for these PTs was 8.26% ± 1.03 and 8.00%, respectively. The difference in MN HbA1c was significant (p<0.001). The MN change in HbA1c between the high HbA1c group (-.92% ± 1.02) and low HbA1c group (-0.45% ± 0.32) was not significant (p>0.05). 25 PTs used a Dexcom™ sensor while 8 PTs used a Medtronic™ sensor. The MN change in HbA1c was not significant between these brands (p>0.05). Conclusion: CGMs improve metabolic control in pediatric PTs with Type 1 DM regardless of initial HbA1c. Further, this improved control is sustained over time. Sensor brands appear to be equally effective at achieving this goal.

scholarly journals The Use of 1.5-Anhydroglucitol for Monitoring Glycemic Control in Islet Transplant Recipients

2014 ◽  
Vol 23 (10) ◽  
pp. 1213-1219 ◽  
Author(s):  
Eduardo Moraes Leao Peixoto ◽  
Nujen Colak Bozkurt ◽  
Shari Messinger ◽  
Maria Isabel Del Olmo García ◽  
Vincenzo Lauriola ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Glucose Variability ◽  
Postprandial Glucose ◽  
Cell Transplant ◽  
Self Monitoring ◽  
Glucose Levels ◽  
Unit Increase ◽  
Capillary Glucose ◽  
Type 1 Dm

We evaluated whether 1,5-anhydroglucitol (1,5-AG) (GlycoMark®), a test for measuring postprandial glucose and glucose variability, could be a tool for assessing short-term glycemic control in islet cell transplant (ICT) subjects. Data of 21 subjects, with type 1 DM and allogenic islet transplantation, who had concomitant fructosamine, HbA1c, 1,5-AG ( n = 85 samples), and capillary glucose self-monitoring measurements ( n = 2,979) were analyzed retrospectively at different time points after ICT. A significant negative association was observed between 1,5-AG and HbA1c ( p = 0.02), but not with fructosamine. When HbA1c was divided in quartiles as <5.6, 5.6–5.9, 5.9–6.2, and >6.2, a decrease of an estimated 0.70 ± 0.30 μg/ml in 1,5-AG was associated with each quartile of increase in HbA1c ( p < 0.0001). There was a significant decline of 1.64 ± 0.3mg/dl in postprandial glucose values for each 1 unit increase in 1,5-AG ( p < 0.0001). For those with HbA1c ≥ 6.0% when 1,5-AG was ≥8.15 μg/ml, the mean estimated glucose level was 103.71 ± 3.66 mg/dl, whereas it was 132.12 ± 3.71 mg/ dl when 1,5-AG was <8.15 μg/ml. The glucose variability (Glumax - Glumin) in subjects with 1,5-AG <8.15 μg/ml was 46.23 mg/dl greater than the subjects with 1,5-AG ≥8.15 μg/ml (HbA1c ≥ 6.0%). There was no significant association between GlycoMark and glucose variability where HbA1c < 6%. 1,5-AG significantly associated with postprandial glucose levels and glucose variability in ICT recipients with near-normal HbA1c (6.0–6.5%) levels. These findings suggest that 1,5-AG can be used to differentiate those ICT subjects with higher glucose variability despite having near-normal HbA1c. However, prospective studies are needed to evaluate the association between GlycoMark levels and the parameters of graft dysfunction/failure.

scholarly journals Glycemic control in children and young adults with different types of diabetes mellitus in Ukraine

2021 ◽  
pp. 7-14
Author(s):  
E. V. Globa ◽  
N. B. Zelinska
Keyword(s):  
Diabetes Mellitus ◽  
Glycemic Control ◽  
Monogenic Diabetes ◽  
Different Types ◽  
Pathogenetic Therapy ◽  
Children And Young Adults ◽  
Type 1 Dm ◽  
First Time

Introduction. Until recently, glycated hemoglobin (HbA1c) has not been studied in children with different types of diabetes mellitus (DM). With the development of molecular genetics, new types of diabetes have been diagnosed, including neonatal (ND) and maturity onset diabetes of the young (MODY), which usually require specific pathogenetic therapy, including sulfonylureas (SU), which improve glycemic control in patients with certain mutations. The aim of this study, which was conducted for the first time in Ukraine, was to analyze glycemic control in patients with different types of DM, including ND and MODY and changing their treatment after genetic testing. Materials and methods. We studied conducted the analysis of glycemic control in patients depending on the type of diabetes, namely: type 1 diabetes (n = 9282), type 2 diabetes (n = 23), ND (n = 16) with mutations KCNJ11, ABCC8 and MODY (n = 16) with mutations in HNF1A/HNF4A and ABCC8 genes. To confirm the nature of monogenic diabetes, targeting next-generation sequencing (tNGS) of all known neonatal and monogenic diabetes genes was performed. Results. According to the Register in 2018, in Ukraine the average age of children with type 1 DM was 11.5 ± 1.4 years, and the level of HbA1c was unsatisfactory (8.8 ± 2.01 %). The proportion of children who had ideal or optimal glycemic control (HbA1c

scholarly journals Glycemic Control after Total Pancreatectomy for Intraductal Papillary Mucinous Neoplasm: An Exploratory Study

HPB Surgery ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Laith H. Jamil ◽  
Ana M. Chindris ◽  
Kanwar R. S. Gill ◽  
Daniela Scimeca ◽  
John A. Stauffer ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Intraductal Papillary Mucinous Neoplasm ◽  
Hemoglobin A1c ◽  
Total Pancreatectomy ◽  
Control Group ◽  
Type I ◽  
Mucinous Neoplasm ◽  
Point Of Interest ◽  
Type 1 Dm

Background. Glycemic control following total pancreatectomy (TP) has been thought to be difficult to manage. Diffuse intraductal papillary mucinous neoplasm (IPMN) is a potentially curable precursor to pancreatic adenocarcinoma, best treated by TP. Objective. Compare glycemic control in patients undergoing TP for IPMN to patients with type 1 diabetes mellitus (DM). Design/Setting. Retrospective cohort. Outcome Measure. Hemoglobin A1C(HbA1C) at 6, 12, 18, and 24 months after TP. In the control group, baseline was defined as 6 months prior to the first HbA1c measure. Results. Mean HgbA1C at each point of interest was similar between TP and type I DM patients (6 months (7.5% versus 7.7%, P=0.52), 12 months (7.3% versus 8.0%, P=0.081), 18 months (7.7% and 7.6%, P=0.64), and at 24 months (7.3% versus 7.8%, P=0.10)). Seven TP patients (50%) experienced a hypoglycemic event compared to 65 type 1 DM patients (65%, P=0.38). Limitations. Small number of TP patients, retrospective design, lack of long-termfollowup. Conclusion. This suggests that glycemic control following TP for IPMNcan be well managed, similar to type 1 DM patients. Fear of DM following TP for IPMN should not preclude surgery when TP is indicated.

scholarly journals Excess risk of lower extremity amputations in people with type 1 diabetes compared with the general population: amputations and type 1 diabetes

2019 ◽  
Vol 7 (1) ◽  
pp. e000602 ◽  
Author(s):  
Arndís Finna Ólafsdóttir ◽  
Ann-Marie Svensson ◽  
Aldina Pivodic ◽  
Soffia Gudbjörnsdottir ◽  
Thomas Nyström ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
General Population ◽  
Lower Extremity ◽  
Excess Risk ◽  
Diabetes Duration ◽  
Renal Complications ◽  
Increased Risk ◽  
Type 1 Dm

ObjectiveThis study investigates how the excess risk of lower extremity amputations (amputations) in people with type 1 diabetes mellitus (DM) differs from the general population by diabetes duration, glycemic control, and renal complications.Research design and methodsWe analyzed data from people with type 1 DM from the Swedish National Diabetes Register without prior amputation from January 1998 to December 2013. Each person (n=36 872) was randomly matched with five controls by sex, age, and county (n=184 360) from the population without diabetes. All were followed until first amputation, death or end of follow-up.ResultsThe overall adjusted HR for all amputation was 40.1 (95% CI 32.8 to 49.1) for type 1 DM versus controls. HR increased with longer diabetes duration. The incidence of amputation/1000 patient-years was 3.18 (95% CI 2.99 to 3.38) for type 1 DM and 0.07 (95% CI 0.05 to 0.08) for controls. The incidence decreased from 1998–2001 (3.09, 95% CI 2.56 to 3.62) to 2011–2013 (2.64, 95% CI 2.31 to 2.98). The HR for major amputations was lower than for minor amputations and decreased over the time period (p=0.0045). Worsening in glycemic control among patients with diabetes led to increased risk for amputation with an HR of 1.80 (95% CI 1.72 to 1.88) per 10 mmol/mol (1%) increase in hemoglobin A1c.ConclusionsAlthough the absolute risk of amputation is relatively low, the overall excess risk was 40 times that of controls. Excess risk was substantially lower for those with good glycemic control and without renal complications, but excess risk still existed and is greatest for minor amputations.

scholarly journals The Role of Continuous Glucose Monitoring, Diabetes Smartphone Applications, and Self-Care Behavior in Glycemic Control: Results of a Multi-National Online Survey

2019 ◽  
Vol 8 (1) ◽  
pp. 109 ◽  
Author(s):  
Mihiretu Kebede ◽  
Cora Schuett ◽  
Claudia Pischke
Keyword(s):  
Glycemic Control ◽  
Glucose Monitoring ◽  
Self Care ◽  
Self Management ◽  
Type 2 Dm ◽  
Type 1 Dm ◽  
Care Behavior

Background: This study investigated the determinants (with a special emphasis on the role of diabetes app use, use of continuous glucose monitoring (CGM) device, and self-care behavior) of glycemic control of type 1 and type 2 diabetes mellitus (DM). Methods: A web-based survey was conducted using diabetes Facebook groups, online patient-forums, and targeted Facebook advertisements (ads). Demographic, CGM, diabetes app use, and self-care behavior data were collected. Glycemic level data were categorized into hyperglycemia, hypoglycemia, and good control. Multinomial logistic regression stratified by diabetes type was performed. Results: The survey URL was posted in 78 Facebook groups and eight online forums, and ten targeted Facebook ads were conducted yielding 1854 responses. Of those owning smartphones (n = 1753, 95%), 1052 (62.6%) had type 1 and 630 (37.4%) had type 2 DM. More than half of the type 1 respondents (n = 549, 52.2%) and one third the respondents with type 2 DM (n = 210, 33.3%) reported using diabetes apps. Increased odds of experiencing hyperglycemia were noted in persons with type 1 DM with lower educational status (Adjusted Odds Ratio (AOR) = 1.7; 95% Confidence Interval (CI): 1.21–2.39); smokers (1.63, 95% CI: 1.15–2.32), and high diabetes self-management concern (AOR = 2.09, 95% CI: 1.15–2.32). CGM use (AOR = 0.66, 95% CI: 0.44–1.00); “general diet” (AOR = 0.86, 95% CI: 0.79–0.94); and “blood glucose monitoring” (AOR = 0.88, 95%CI: 0.80–0.97) self-care behavior reduced the odds of experiencing hyperglycemia. Hypoglycemia in type 1 DM was reduced by using CGM (AOR = 0.24, 95% CI: 0.09–0.60), while it was increased by experiencing a high diabetes self-management concern (AOR = 1.94, 95% CI: 1.04–3.61). Hyperglycemia in type 2 DM was increased by age (OR = 1.02, 95% CI: 1.00–1.04); high self-management concern (AOR = 2.59, 95% CI: 1.74–3.84); and poor confidence in self-management capacity (AOR = 3.22, 2.07–5.00). Conversely, diabetes app use (AOR = 0.63, 95% CI: 0.41–0.96) and “general diet” self-care (AOR = 0.84, 95% CI: 0.75–0.94), were significantly associated with the reduced odds of hyperglycemia. Conclusion: Diabetes apps, CGM, and educational interventions aimed at reducing self-management concerns and enhancing dietary self-care behavior and self-management confidence may help patients with diabetes to improve glycemic control.

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