scholarly journals Measurement Of Peak C-Peptide At Diagnosis Informs Glycemic Control But Not Hypoglycemia In Adults With Type 1 Diabetes

2021 ◽  
Author(s):  
Alice L J Carr ◽  
Richard A Oram ◽  
Shannon M Marren ◽  
Timothy J McDonald ◽  
Parth Narendran ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Dose ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Newly Diagnosed ◽  
C Peptide ◽  
Glucose Levels ◽  
Normal Glucose ◽  
The Impact

Abstract Context High residual C-peptide in longer duration type 1 diabetes associates with fewer hypoglycemic events and reduced glycemic variability. Little is known about the impact of C-peptide close-to-diagnosis. Objective Using continuous glucose monitoring (CGM) data from a study of newly diagnosed adults with type 1 diabetes, we aimed to explore if variation in C-peptide close-to-diagnosis influenced glycemic variability and risk of hypoglycemia. Design We studied newly diagnosed adults with type 1 diabetes who wore a Dexcom G4 CGM for 7 days as part the EXTOD study. We examined the relationship between peak stimulated C-peptide and glycemic metrics of variability and hypoglycemia for 36 CGM traces from 23 participants. Results For every 100 pmol/l increase in peak C-peptide, percentage time spent range 3.9-10 mmol/l was increased by 2.4% [95% CI: 0.5,4.3], p=0.01) with a reduction in time spent in level 1 hyperglycemia (> 10 mmol/l) and level 2 hyperglycemia (> 13.9 mmol/l) by 2.6% [95% CI: -4.9, -0.4, p=0.02) and 1.3% [95% CI: -2.7, -0.006], p= 0.04) respectively. Glucose levels were on average lower by 0.19 mmol/l ([95 % CI: -0.4,0.02], p=0.06) and standard deviation reduced by 0.14 [95% CI: -0.3, -0.02], p=0.02). Hypoglycemia was not common in this group and no association was observed between time spent in hypoglycemia (p=0.97) or hypoglycemic risk (p=0.72). There was no association between peak C-peptide and insulin dose adjusted HbA1c (IDAA1c, p=0.45). Conclusions C-peptide associates with time spent in normal glucose range and with less hyperglycemia, but not risk of hypoglycemia in newly diagnosed people with type 1 diabetes.

scholarly journals Insulin-Like Growth Factor-1 at Diagnosis and during Subsequent Years in Adolescents with Type 1 Diabetes

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Simona I. Chisalita ◽  
J. Ludvigsson
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Secretion ◽  
Insulin Treatment ◽  
Insulin Dose ◽  
Newly Diagnosed ◽  
Blood Samples ◽  
C Peptide ◽  
Endogenous Insulin ◽  
High Hba1c

Background. Type 1 diabetes (T1D) in adolescents is associated with alterations in the insulin-like factor system probably caused both by a deranged metabolism and insulinopenia in the portal vein. Objective. To study how the circulating IGF-1 is affected at diagnosis and during subsequent years in adolescents with T1D. Methods. Ten girls and ten boys with type 1 diabetes (T1D), aged 13.0 ± 1.4 (mean ± SD) years at diagnosis, took part in the study. Blood samples were drawn at diagnosis and after 3, 9, 18, and 48 months. HbA1c, total IGF-1, and C-peptide were measured. Results. At diagnosis, the patients had high HbA1c, low IGF-1, and measurable C-peptide. After the start of insulin treatment, maximal improvement in glycemic control and IGF-1 occurred within 3 months and then both tended to deteriorate, that is, HbA1c to increase and IGF-1 to decrease. C-peptide decreased with time, and after 4 years, half of the patients were C-peptide negative. At diagnosis, C-peptide correlated positively to IGF-1 (r=0.50; p<0.03). C-peptide correlated negatively with insulin dose (U/kg) after 18 and 48 months from diagnosis (r=−0.48; p<0.03 and r=−0.72; p<0.001, resp.). Conclusions. In conclusion, our results show that in newly diagnosed adolescents with type 1 diabetes and deranged metabolism, the IGF-1 level is low and rapidly improves with insulin treatment but later tends to decrease concomitantly with declining endogenous insulin secretion.

scholarly journals Liraglutide as additional treatment for type 1 diabetes

2011 ◽  
Vol 165 (1) ◽  
pp. 77-84 ◽  
Author(s):  
Ajay Varanasi ◽  
Natalie Bellini ◽  
Deepti Rawal ◽  
Mehul Vora ◽  
Antoine Makdissi ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Insulin Dose ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Additional Treatment ◽  
The Body ◽  
The Mean ◽  
Bolus Insulin

ObjectiveTo determine whether the addition of liraglutide to insulin to treat patients with type 1 diabetes leads to an improvement in glycemic control and diminish glycemic variability.Subjects and methodsIn this study, 14 patients with well-controlled type 1 diabetes on continuous glucose monitoring and intensive insulin therapy were treated with liraglutide for 1 week. Of the 14 patients, eight continued therapy for 24 weeks.ResultsIn all the 14 patients, mean fasting and mean weekly glucose concentrations significantly decreased after 1 week from 130±10 to 110±8 mg/dl (P<0.01) and from 137.5±20 to 115±12 mg/dl (P<0.01) respectively. Glycemic excursions significantly improved at 1 week. The mean s.d. of glucose concentrations decreased from 56±10 to 26±6 mg/dl (P<0.01) and the coefficient of variation decreased from 39.6±10 to 22.6±7 (P<0.01). There was a concomitant fall in the basal insulin from 24.5±6 to 16.5±6 units (P<0.01) and bolus insulin from 22.5±4 to 15.5±4 units (P<0.01).In patients who continued therapy with liraglutide for 24 weeks, mean fasting, mean weekly glucose concentrations, glycemic excursions, and basal and bolus insulin dose also significantly decreased (P<0.01). HbA1c decreased significantly at 24 weeks from 6.5 to 6.1% (P=0.02), as did the body weight by 4.5±1.5 kg (P=0.02).ConclusionLiraglutide treatment provides an additional strategy for improving glycemic control in type 1 diabetes. It also leads to weight loss.

scholarly journals Post-exercise glycemic control in type 1 diabetes is associated with residual ꞵ-cell function

2020 ◽  
Author(s):  
Guy S Taylor ◽  
Kieran Smith ◽  
Tess E Capper ◽  
Jadine H Scragg ◽  
Ayat Bashir ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Acute Exercise ◽  
Cell Function ◽  
Glycemic Variability ◽  
Free Living ◽  
Continuous Glucose Monitor ◽  
Post Exercise ◽  
C Peptide ◽  
The Impact

Objective<b> </b> <p>To investigate the impact of residual ꞵ-cell function on continuous glucose monitor (CGM) outcomes following acute exercise in people with Type 1 diabetes.</p> <p>Research<b> </b>Design and Methods<b> </b></p> <p>Thirty participants with type 1 diabetes for ≥3 years were recruited. Firstly, participants wore a blinded CGM for 7 days of free-living data capture. Secondly, a 3 hour mixed meal test, assessed stimulated C-peptide and glucagon. Peak C-peptide was used to allocate participants into undetectable (Cpep<sub>und</sub> <3 pmol/L), low (Cpep<sub>low</sub> 3–200 pmol/L) or high C-peptide groups (Cpep<sub>high</sub> >200 pmol/L). Finally, participants completed 45 minutes of incline treadmill walking at 60%VO<sub>2peak</sub> followed by a further 48 hours’ CGM capture.</p> <p>Results<b> </b></p> <p>CGM parameters were comparable across groups during the free-living observation week. In the 12 (12hr) and 24 hours (24hr) post-exercise periods the Cpep<sub>high</sub> group had significantly greater amount of time spent with glucose 3.9-10 mmol/L (12hr: 73.5±27.6%, 24hr: 76.3±19.2%) compared to Cpep<sub>low</sub> (12hr: 43.6±26.1%, p=0.027, 24hr: 52.3±25.0%, p=0.067) or Cpep<sub>und</sub> (40.6±17.0%, p=0.010, 24hr: 51.3±22.3%, p=0.041). Time spent in hyperglycemia (12hr and 24hr glucose >10 and >13.9 mmol/L, p<0.05) and glycemic variability (12hr and 24hr SD, p<0.01) were significantly lower in the Cpep<sub>high</sub> group compared to Cpep<sub>und</sub> and Cpep<sub>low</sub>. Change in CGM outcomes from pre to 24hr post-exercise was divergent: Cpep<sub>und</sub> and Cpep<sub>low</sub> experienced worsening (glucose 3.9-10 mmol/L: -9.1% and -16.2% respectively), with Cpep<sub>high</sub> experiencing improvement (+12.1%)(p=0.017). </p> <p>Conclusions<b> </b></p> <p>Residual ꞵ-cell function may partially explain the inter-individual variation in the acute glycemic benefits of exercise in individuals with type 1 diabetes. Quantifying C-peptide could aid in providing personalized and targeted support for exercising patients.</p>

scholarly journals Impact of COVID-19 Lockdown on Glycemic Control in Adults with Type 1 Diabetes Mellitus

2020 ◽  
Vol 4 (12) ◽  
Author(s):  
Begoña Pla ◽  
Alfonso Arranz ◽  
Carolina Knott ◽  
Miguel Sampedro ◽  
Sara Jiménez ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Type 1 Diabetes Mellitus ◽  
Glycosylated Hemoglobin ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Glucose Management ◽  
The Impact

Abstract Aim To examine the impact of the lockdown caused by the COVID-19 pandemic on both the glycemic control and the daily habits of a group of patients with type 1 diabetes mellitus (T1DM) using flash continuous glucose monitoring devices (flash CGMs). Methods Retrospective analysis based on all the information gathered in virtual consultations from a cohort of 50 adult patients with T1DM with follow-up at our site. We compared their CGM metrics during lockdown with their own previous data before the pandemic occurred, as well as the potential psychological and therapeutic changes. Results We observed a reduction of average glucose values: 160.26 ± 22.55 mg/dL vs 150 ± 20.96 mg/dL, P = .0009; estimated glycosylated hemoglobin: 7.21 ± 0.78% vs 6.83 ± 0.71%, P = .0005; glucose management indicator 7.15 ± 0.57% vs 6.88 ± 0.49%; P = .0003, and glycemic variability: 40.74 ± 6.66 vs 36.43 ± 6.09 P &lt; .0001. Time in range showed an improvement: 57.46 ± 11.85% vs a 65.76 ± 12.09%, P &lt; .0001, without an increase in percentage of time in hypoglycemia. Conclusions COVID-19 lockdown was associated with an improvement in glycemic control in patients with T1DM using CGMs.

scholarly journals Glycemic Variability and Hypoglycemic Excursions With Continuous Glucose Monitoring Compared to Intermittently Scanned Continuous Glucose Monitoring in Adults With Highest Risk Type 1 Diabetes

2019 ◽  
Vol 14 (3) ◽  
pp. 567-574 ◽  
Author(s):  
Parizad Avari ◽  
Vanessa Moscardo ◽  
Narvada Jugnee ◽  
Nick Oliver ◽  
Monika Reddy
Keyword(s):  
Type 1 Diabetes ◽  
High Risk ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Glycemic Variability ◽  
Clinical Trial Registration ◽  
Freestyle Libre ◽  
The Impact

Background: The I-HART CGM study has shown that real-time continuous glucose monitoring (rtCGM) has greater beneficial impact on hypoglycemia than intermittently scanned continuous glucose monitoring (iscCGM) in adults with type 1 diabetes at high risk (Gold score ≥4 or recent severe hypoglycemia using insulin injections). In this subanalysis, we present the impact of rtCGM and iscCGM on glycemic variability (GV). Methods: Forty participants were recruited to this parallel group study. Following two weeks of blinded rtCGM (DexcomG4), participants were randomized to rtCGM (Dexcom G5; n = 20) or iscCGM (Freestyle Libre; n = 20) for eight weeks. An open-extension phase enabled participants on rtCGM to continue for a further eight weeks and those on iscCGM to switch to rtCGM over this period. Glycemic variability measures at baseline, 8- and 16-week endpoints were compared between groups. Results: At the eight-week endpoint, between-group differences demonstrated significant reduction in several GV measures with rtCGM compared to iscCGM (GRADE%hypoglycemia, index of glycemic control [IGC], and average daily risk range [ADRR]; P < .05). Intermittently scanned continuous glucose monitoring reduced mean average glucose and glycemic variability percentage and GRADE%hyperglycemia compared with rtCGM ( P < .05). At 16 weeks, the iscCGM group switching to rtCGM showed significant improvement in GRADE%hypoglycemia, personal glycemic status, IGC, and ADRR. Conclusion: Our data suggest most, but not all, GV measures improve with rtCGM compared with iscCGM, particularly those measures associated with the risk of hypoglycemia. Selecting appropriate glucose monitoring technology to address GV in this high-risk cohort is important to minimize the risk of glucose extremes and severe hypoglycemia. Clinical trial registration: ClinicalTrials.gov NCT03028220

scholarly journals Evaluating the Infuence of Mood and Stress on Glycemic Variability in T1DM Patients using Glucose Monitoring Sensors and Pools

2020 ◽  
Author(s):  
Sergio Contador Pachón ◽  
Marta Botella Serrano ◽  
Aranzazu Aramendi Zurimendi ◽  
Remedios Rodríguez Martínez ◽  
Esther Maqueda Villaizán ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
P Value ◽  
Glucose Levels ◽  
Blood Glucose Levels

Objective: Assess in a sample of patients with type 1 diabetes mellitus whether mood and stress influence blood glucose levels and variability. Material and Methods: Continuous glucose monitoring was performed on 10 patients with type 1 diabetes, where interstitial glucose values were recorded every 15 minutes. A daily survey was conducted through Google Forms, collecting information on mood and stress. The day was divided into 6 slots of 4-hour each, asking the patient to assess each slot in relation to mood (sad, normal or happy) and stress (calm, normal or nervous). Different measures of glycemic control (arithmetic mean and percentage of time below/above the target range) and variability (standard deviation, percentage coefficient of variation, mean amplitude of glycemic excursions and mean of daily differences) were calculated to relate the mood and stress perceived by patients with blood glucose levels and glycemic variability. A hypothesis test was carried out to quantitatively compare the data groups of the different measures using the Student's t-test. Results: Statistically significant differences (p-value < 0.05) were found between different levels of stress. In general, average glucose and variability decrease when the patient is calm. There are statistically significant differences (p-value < 0.05) between different levels of mood. Variability increases when the mood changes from sad to happy. However, the patient's average glucose decreases as the mood improves. Conclusions: Variations in mood and stress significantly influence blood glucose levels, and glycemic variability in the patients analyzed with type 1 diabetes mellitus. Therefore, they are factors to consider for improving glycemic control. The mean of daily differences does not seem to be a good indicator for variability. Keywords: Diabetes mellitus, continuous glucose monitoring, glycemic variability, average glycemia, glycemic control, stress, mood.

scholarly journals Post-exercise glycemic control in type 1 diabetes is associated with residual ꞵ-cell function

2020 ◽  
Author(s):  
Guy S Taylor ◽  
Kieran Smith ◽  
Tess E Capper ◽  
Jadine H Scragg ◽  
Ayat Bashir ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Acute Exercise ◽  
Cell Function ◽  
Glycemic Variability ◽  
Free Living ◽  
Continuous Glucose Monitor ◽  
Post Exercise ◽  
C Peptide ◽  
The Impact

Objective<b> </b> <p>To investigate the impact of residual ꞵ-cell function on continuous glucose monitor (CGM) outcomes following acute exercise in people with Type 1 diabetes.</p> <p>Research<b> </b>Design and Methods<b> </b></p> <p>Thirty participants with type 1 diabetes for ≥3 years were recruited. Firstly, participants wore a blinded CGM for 7 days of free-living data capture. Secondly, a 3 hour mixed meal test, assessed stimulated C-peptide and glucagon. Peak C-peptide was used to allocate participants into undetectable (Cpep<sub>und</sub> <3 pmol/L), low (Cpep<sub>low</sub> 3–200 pmol/L) or high C-peptide groups (Cpep<sub>high</sub> >200 pmol/L). Finally, participants completed 45 minutes of incline treadmill walking at 60%VO<sub>2peak</sub> followed by a further 48 hours’ CGM capture.</p> <p>Results<b> </b></p> <p>CGM parameters were comparable across groups during the free-living observation week. In the 12 (12hr) and 24 hours (24hr) post-exercise periods the Cpep<sub>high</sub> group had significantly greater amount of time spent with glucose 3.9-10 mmol/L (12hr: 73.5±27.6%, 24hr: 76.3±19.2%) compared to Cpep<sub>low</sub> (12hr: 43.6±26.1%, p=0.027, 24hr: 52.3±25.0%, p=0.067) or Cpep<sub>und</sub> (40.6±17.0%, p=0.010, 24hr: 51.3±22.3%, p=0.041). Time spent in hyperglycemia (12hr and 24hr glucose >10 and >13.9 mmol/L, p<0.05) and glycemic variability (12hr and 24hr SD, p<0.01) were significantly lower in the Cpep<sub>high</sub> group compared to Cpep<sub>und</sub> and Cpep<sub>low</sub>. Change in CGM outcomes from pre to 24hr post-exercise was divergent: Cpep<sub>und</sub> and Cpep<sub>low</sub> experienced worsening (glucose 3.9-10 mmol/L: -9.1% and -16.2% respectively), with Cpep<sub>high</sub> experiencing improvement (+12.1%)(p=0.017). </p> <p>Conclusions<b> </b></p> <p>Residual ꞵ-cell function may partially explain the inter-individual variation in the acute glycemic benefits of exercise in individuals with type 1 diabetes. Quantifying C-peptide could aid in providing personalized and targeted support for exercising patients.</p>

The impact of real-time continuous glucose monitoring on metabolic control in children with type 1 diabetes

2020 ◽  
Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
The Impact

Glycemic Variability and Insulin Needs in Patients with Type 1 Diabetes Mellitus Supplemented with Vitamin D: A Pilot Study Using Continuous Glucose Monitoring System

2018 ◽  
Vol 14 (4) ◽  
pp. 395-403 ◽  
Author(s):  
Karem Mileo Felício ◽  
Ana Carolina Contente Braga de Souza ◽  
Joao Felicio Abrahao Neto ◽  
Franciane Trindade Cunha de Melo ◽  
Carolina Tavares Carvalho ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Vitamin D ◽  
Type 1 Diabetes ◽  
Pilot Study ◽  
Type 1 Diabetes Mellitus ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability
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