scholarly journals Morning (Fasting) vs Afternoon Resistance Exercise in Individuals With Type 1 Diabetes: A Randomized Crossover Study

2019 ◽  
Vol 104 (11) ◽  
pp. 5217-5224 ◽  
Author(s):  
Saeed Reza Toghi-Eshghi ◽  
Jane E Yardley
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Resistance Exercise ◽  
Blood Glucose Concentration ◽  
Venous Blood ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Interstitial Glucose ◽  
Design And Methods

Abstract Objective To determine the effect of morning exercise in the fasting condition vs afternoon exercise on blood glucose responses to resistance exercise (RE). Research Design and Methods For this randomized crossover design, 12 participants with type 1 diabetes mellitus [nine females; aged 31 ± 8.9 years; diabetes duration, 19.1 ± 8.3 years; HbA1c, 7.4% ± 0.8% (57.4 ± 8.5 mmol/mol)] performed ∼40 minutes of RE (three sets of eight repetitions, seven exercises, at the individual’s predetermined eight repetition maximum) at either 7 am (fasting) or 5 pm. Sessions were performed at least 48 hours apart. Venous blood samples were collected immediately preexercise, immediately postexercise, and 60 minutes postexercise. Interstitial glucose was monitored overnight postexercise by continuous glucose monitoring (CGM). Results Data are presented as mean ± SD. Blood glucose rose during fasting morning exercise (9.5 ± 3.0 to 10.4 ± 3.0 mmol/L), whereas it declined with afternoon exercise (8.2 ± 2.5 to 7.4 ± 2.6 mmol/L; P = 0.031 for time-by-treatment interaction). Sixty minutes postexercise, blood glucose concentration was significantly higher after fasting morning exercise than after afternoon exercise (10.9 ± 3.2 vs 7.9 ± 2.9 mmol/L; P = 0.019). CGM data indicated more glucose variability (2.7 ± 1.1 vs 2.0 ± 0.7 mmol/L; P = 0.019) and more frequent hyperglycemia (12 events vs five events; P = 0.025) after morning RE than after afternoon RE. Conclusions Compared with afternoon RE, morning (fasting) RE was associated with distinctly different blood glucose responses and postexercise profiles.

scholarly journals Glycemic Variability in Type 1 Diabetes Mellitus Saudis Using Ambulatory Glucose Profile

2021 ◽  
Vol 14 ◽  
pp. 117955142110137
Author(s):  
Bader Alzahrani ◽  
Saad Alzahrani ◽  
Mussa H Almalki ◽  
Souha S Elabd ◽  
Shawana Abdulhamid Khan ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Mean Amplitude ◽  
Glucose Variability ◽  
International Standards ◽  
Medical City ◽  
Interstitial Glucose

Background: Glucose variability (GV) is a common and challenging clinical entity in the management of people with type 1 diabetes (T1DM). The magnitude of GV in Saudi people with T1DM was not addressed before. Therefore, we aimed to study GV in a consecutive cohort of Saudis with T1DM. Methods: We prospectively assessed interstitial glucose using FreeStyle® Libre flash glucose monitoring in people with TIDM who attended follow-up in the diabetes clinics at King Fahad Medical City between March and June 2017. Glycemia profile, standard deviation (SD), coefficient of variation (CV), mean of daily differences (MODD), and mean amplitude of glucose excursion (MAGE) were measured using the standard equations over a period of 2 weeks. Results: Fifty T1DM subjects (20 males) with mean age 20.2 ± 6.1 years and mean fortnight glucose 192 ± 42.3 mg/dl were included. The mean SD of 2-week glucose readings was 100.4 ± 36.3 mg/dl and CV was 52.1% ± 13%. Higher levels of glucose excursions were also observed. MODD and MAGE were recorded as 104.5 ± 51.7 and 189 ± 54.9 mg/dl, respectively which is 2 to 4 times higher than the international standards. Higher MODD and MAGE were observed on weekends compared to weekdays (111.3 ± 62.1 vs 98.6 ± 56.2 mg/dl and 196.4 ± 64.6 vs 181.7 ± 52.4 mg/dl, respectively; P ⩽ .001). Conclusion: Higher degree of glycemic variability was observed in this cohort of TIDM Saudis. Weekends were associated with higher glucose swings than weekdays. More studies are needed to explore these findings further.

scholarly journals Is the Consensual Threshold for Defining High Glucose Variability Implementable in Clinical Practice?

2021 ◽  
Author(s):  
Jean-Baptiste Julla ◽  
Pauline Jacquemier ◽  
Guy Fagherazzi ◽  
Tiphaine Vidal-trecan ◽  
Vanessa Juddoo ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Clinical Practice ◽  
Research Design ◽  
High Glucose ◽  
Coefficient Of Variation ◽  
Calculation Method ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Design And Methods

<b><i>Objective:</i></b> Estimating glucose variability (GV) through within-day coefficient of variation (%CV<sub>w</sub>) is recommended for patients with type-1 Diabetes (T1D). High-GV (hGV) is defined as %CV<sub>w</sub>>36%. However, continuous glucose monitoring (CGM) devices provide exclusively total-CV (%CV<sub>T</sub>). We aimed to assess consequences of this disparity. <p><b><i>Research Design and Methods:</i></b> We retrospectively calculated both %CV<sub>T</sub> and %CV<sub>W </sub>of consecutive T1D patients from their CGM raw data during 14 days. Patients with hGV with %CV<sub>T</sub>>36% and %CV<sub>w</sub>≤36% were called the “inconsistent-GV group”.</p> <p><b><i>Results:</i></b> 104 patients were included. Mean %CV<sub>T</sub> and %CV<sub>w</sub> were 42.4+/-8% and 37.0+/-7.4% respectively (p<0.0001). Using %CV<sub>T</sub>, 81 patients (73.6%) were classified as hGV whereas 59 (53.6%) using %CV<sub>W </sub>(p<0.0001) corresponding to 22 patients (21%) in the “<i>inconsistent-GV</i> population”.</p> <p><b><i>Conclusions:</i></b> Evaluation of GV through %CV in patients with T1D is highly dependent on the calculation method and then must be standardized.</p>

scholarly journals Is the Consensual Threshold for Defining High Glucose Variability Implementable in Clinical Practice?

2021 ◽  
Author(s):  
Jean-Baptiste Julla ◽  
Pauline Jacquemier ◽  
Guy Fagherazzi ◽  
Tiphaine Vidal-trecan ◽  
Vanessa Juddoo ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Clinical Practice ◽  
Research Design ◽  
High Glucose ◽  
Coefficient Of Variation ◽  
Calculation Method ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Design And Methods

<b><i>Objective:</i></b> Estimating glucose variability (GV) through within-day coefficient of variation (%CV<sub>w</sub>) is recommended for patients with type-1 Diabetes (T1D). High-GV (hGV) is defined as %CV<sub>w</sub>>36%. However, continuous glucose monitoring (CGM) devices provide exclusively total-CV (%CV<sub>T</sub>). We aimed to assess consequences of this disparity. <p><b><i>Research Design and Methods:</i></b> We retrospectively calculated both %CV<sub>T</sub> and %CV<sub>W </sub>of consecutive T1D patients from their CGM raw data during 14 days. Patients with hGV with %CV<sub>T</sub>>36% and %CV<sub>w</sub>≤36% were called the “inconsistent-GV group”.</p> <p><b><i>Results:</i></b> 104 patients were included. Mean %CV<sub>T</sub> and %CV<sub>w</sub> were 42.4+/-8% and 37.0+/-7.4% respectively (p<0.0001). Using %CV<sub>T</sub>, 81 patients (73.6%) were classified as hGV whereas 59 (53.6%) using %CV<sub>W </sub>(p<0.0001) corresponding to 22 patients (21%) in the “<i>inconsistent-GV</i> population”.</p> <p><b><i>Conclusions:</i></b> Evaluation of GV through %CV in patients with T1D is highly dependent on the calculation method and then must be standardized.</p>

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 Anxiety, depression, and glycemic control during Covid-19 pandemic in youths with type 1 diabetes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Maria Cusinato ◽  
Mariangela Martino ◽  
Alex Sartori ◽  
Claudia Gabrielli ◽  
Laura Tassara ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Psychological Impact ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Well Being ◽  
Glucose Variability ◽  
Threshold Score ◽  
The Impact

Abstract Objectives Our study aims to assess the impact of lockdown during the coronavirus disease 2019 pandemic on glycemic control and psychological well-being in youths with type 1 diabetes. Methods We compared glycemic metrics during lockdown with the same period of 2019. The psychological impact was evaluated with the Test of Anxiety and Depression. Results We analyzed metrics of 117 adolescents (87% on Multiple Daily Injections and 100% were flash glucose monitoring/continuous glucose monitoring users). During the lockdown, we observed an increase of the percentage of time in range (TIR) (p<0.001), with a significant reduction of time in moderate (p=0.002), and severe hypoglycemia (p=0.001), as well as the percentage of time in hyperglycemia (p<0.001). Glucose variability did not differ (p=0.863). The glucose management indicator was lower (p=0.001). 7% of youths reached the threshold-score (≥115) for anxiety and 16% for depression. A higher score was associated with lower TIR [p=0.028, p=0.012]. Conclusions Glycemic control improved during the first lockdown period with respect to the previous year. Symptoms of depression and anxiety were associated with worse glycemic control; future researches are necessary to establish if this improvement is transient and if psychological difficulties will increase during the prolonged pandemic situation.

scholarly journals The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day

2018 ◽  
Vol 12 (2) ◽  
pp. 273-281 ◽  
Author(s):  
Roberto Visentin ◽  
Enrique Campos-Náñez ◽  
Michele Schiavon ◽  
Dayu Lv ◽  
Martina Vettoretti ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
In Silico ◽  
Artificial Pancreas ◽  
Real Life ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Self Monitoring ◽  
Inhaled Insulin ◽  
Single Meal

Background: A new version of the UVA/Padova Type 1 Diabetes (T1D) Simulator is presented which provides a more realistic testing scenario. The upgrades to the previous simulator, which was accepted by the Food and Drug Administration in 2013, are described. Method: Intraday variability of insulin sensitivity (SI) has been modeled, based on clinical T1D data, accounting for both intra- and intersubject variability of daily SI. Thus, time-varying distributions of both subject’s basal insulin infusion and insulin-to-carbohydrate ratio were calculated and made available to the user. A model of “dawn” phenomenon based on clinical T1D data has been also included. Moreover, the model of subcutaneous insulin delivery has been updated with a recently developed model of commercially available fast-acting insulin analogs. Models of both intradermal and inhaled insulin pharmacokinetics have been included. Finally, new models of error affecting continuous glucose monitoring and self-monitoring of blood glucose devices have been added. Results: One hundred in silico adults, adolescent, and children have been generated according to the above modifications. The new simulator reproduces the intraday glucose variability observed in clinical data, also describing the nocturnal glucose increase, and the simulated insulin profiles reflect real life data. Conclusions: The new modifications introduced in the T1D simulator allow to extend its domain of validity from “single-meal” to “single-day” scenarios, thus enabling a more realistic framework for in silico testing of advanced diabetes technologies including glucose sensors, new insulin molecules and artificial pancreas.

Accuracy and precision assessment of a new blood glucose monitoring system

2016 ◽  
Vol 54 (1) ◽  
Author(s):  
Li-Nong Ji ◽  
Li-Xin Guo ◽  
Li-Bin Liu
Keyword(s):  
Blood Glucose ◽  
Glucose Concentration ◽  
Blood Glucose Concentration ◽  
Venous Blood ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Blood Samples ◽  
Glucose Testing ◽  
Blood Tests ◽  
Accuracy And Precision

AbstractBlood glucose self-monitoring by individuals with diabetes is essential in controlling blood glucose levels. The International Organization for Standardization (ISO) introduced new standards for blood glucose monitoring systems (BGMS) in 2013 (ISO 15197: 2013). The CONTOUR PLUSThis study evaluated the accuracy and precision of CONTOUR PLUS BGMS in quantitative glucose testing of capillary and venous whole blood samples obtained from 363 patients at three different hospitals.Results of fingertip and venous blood glucose measurements by the CONTOUR PLUS system were compared with laboratory reference values to determine accuracy. Accuracy was 98.1% (96.06%–99.22%) for fingertip blood tests and 98.1% (96.02%–99.21%) for venous blood tests. Precision was evaluated across a wide range of blood glucose values (5.1–17.2 mmol/L), testing three blood samples repeatedly 15 times with the CONTOUR PLUS blood glucose meter using test strips from three lots. All within-lot results met ISO criteria (i.e., SD<0.42 mmol/L for blood glucose concentration <5.55 mmol/L; CV<7.5% for blood glucose concentration ≥5.55 mmol/L). Between-lot variations were 1.5% for low blood glucose concentration, 2.4% for normal and 3.4% for high.Accuracy of both fingertip and venous blood glucose measurements by the CONTOUR PLUS system was >95%, confirming that the system meets ISO 15197: 2013 requirements.

scholarly journals Continuous glucose monitoring use and glucose variability in pre-school children with type 1 diabetes

2019 ◽  
Vol 147 ◽  
pp. 76-80 ◽  
Author(s):  
Klemen Dovc ◽  
Kevin Cargnelutti ◽  
Anze Sturm ◽  
Julij Selb ◽  
Natasa Bratina ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
School Children ◽  
Glucose Monitoring ◽  
Glucose Variability

Use of the Internet to optimize self-management of type 1 diabetes: Preliminary experience with DiasNet

2003 ◽  
Vol 9 (1_suppl) ◽  
pp. 50-52 ◽  
Author(s):  
D A Cavan ◽  
J Everett ◽  
S Plougmann ◽  
O K Hejlesen
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Blood Glucose Concentration ◽  
Pilot Trial ◽  
Data Entry ◽  
Food Diary ◽  
Collection Period ◽  
Use Of The Internet ◽  
Further Development

summary Six patients with type 1 diabetes participated in a pilot trial. Their median age was 36 years (range 29–61) and the median duration of diabetes was 10 years (range 3–29). They were asked to enter, from their home or work PC, blood glucose values, insulin doses and a food diary. From the data entered, a computer model generated a simulation of the blood glucose concentration for the data collection period. It could then suggest alternative insulin doses (or regimes), or meal sizes, to reduce the risk of hypo- and hyperglycaemia. During a six-month study, patients entered a median of five sets of data (range two to eight). Feedback from participants revealed that while the system was helpful, difficulties with data entry hindered its use. Information gained from this exercise is shaping further development of the system.

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