Seventy two-hour glucose monitoring profiles in mild gestational diabetes mellitus: differences from healthy pregnancies and influence of diet counseling

Objective To study glucose profiles of gestational diabetes (GDM) patients with 72 h of continuous glucose monitoring (CGM) either before (GDM1) or after (GDM2) dietary counseling, comparing them with nondiabetic (NDM) controls. Design and methods We performed CGM on 22 GDM patients; 11 before and 11 after dietary counseling and compared them to 11 healthy controls. Several physiological and clinical characteristics of the glucose profiles were compared across the groups, including comparisons for pooled 24-h measures and hourly median values, summary measures representing glucose exposure (area under the median curves) and variability (amplitude, standard deviation, interquartile range), and time points related to meals. Results Most women (81.8%) in the GDM groups had fasting glucose <95mg/dL, suggesting mild GDM. Variability, glucose levels 1 and 2h after breakfast and dinner, peak values after dinner and glucose levels between breakfast and lunch, were all significantly higher in GDM1 than NDM (P<0.05 for all comparisons). The GDM2 results were similar to NDM in all aforementioned comparisons (P>0.05). Both GDM groups spent more time with glucose levels above 140mg/dL when compared with the NDM group. No differences among the groups were found for: pooled measurements and hourly comparisons, exposure, nocturnal, fasting, between lunch and dinner and before meals, as well as after lunch (P>0.05 for all). Conclusion The main differences between the mild GDM1 group and healthy controls were related to glucose variability and excursions above 140mg/dL, while glucose exposure was similar. Glucose levels after breakfast and dinner also discerned the GDM1 group. Dietary counseling was able to keep glucose levels to those of healthy patients.

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Individual categorisation of glucose profiles using compositional data analysis

Statistical Methods in Medical Research ◽

10.1177/0962280218808819 ◽

2018 ◽

Vol 28 (12) ◽

pp. 3550-3567 ◽

Cited By ~ 2

Author(s):

Lyvia Biagi ◽

Arthur Bertachi ◽

Marga Giménez ◽

Ignacio Conget ◽

Jorge Bondia ◽

...

Keyword(s):

Data Analysis ◽

Compositional Data ◽

Glucose Monitoring ◽

Glucose Variability ◽

Compositional Data Analysis ◽

Relative Information ◽

Glucose Profiles ◽

Patient Groups ◽

The Times

The aim of this study was to apply a methodology based on compositional data analysis (CoDA) to categorise glucose profiles obtained from continuous glucose monitoring systems. The methodology proposed considers complete daily glucose profiles obtained from six patients with type 1 diabetes (T1D) who had their glucose monitored for eight weeks. The glucose profiles were distributed into the time spent in six different ranges. The time in one day is finite and limited to 24 h, and the times spent in each of these different ranges are co-dependent and carry only relative information; therefore, CoDA is applied to these profiles. A K-means algorithm was applied to the coordinates obtained from the CoDA to obtain different patterns of days for each patient. Groups of days with relatively high time in the hypo and/or hyperglycaemic ranges and with different glucose variability were observed. Using CoDA of time in different ranges, individual glucose profiles were categorised into groups of days, which can be used by physicians to detect the different conditions of patients and personalise patient's insulin therapy according to each group. This approach can be useful to assist physicians and patients in managing the day-to-day variability that hinders glycaemic control.

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Potentialities of modern glucose monitoring devices during pregnancy

Russian Medical Inquiry ◽

10.32364/2587-6821-2020-4-6-352-357 ◽

2020 ◽

Vol 4 (6) ◽

pp. 352-357

Author(s):

F.O. Ushanova ◽

◽

T.Yu. Demidova ◽

Keyword(s):

Gestational Diabetes ◽

Pregnant Women ◽

Carbohydrate Metabolism ◽

Continuous Glucose Monitoring ◽

Glucose Monitoring ◽

Nocturnal Hypoglycemia ◽

Glucose Levels ◽

Monitoring Technologies ◽

Diabetes Gestational ◽

Monitoring Devices

Currently, the management of pregnant women with carbohydrate metabolism disorders is challenging due to the high risk of unfavorable events both for the mother and the child even in insignificant deviations from the target value. In addition to the conventional methods of self-monitoring, continuous glucose monitoring (CGM) is an important tool to control diabetes. CGM in pregnant women provides the detailed information on the type and trends of the changes in blood glucose levels and the fluctuations of glucose levels and also identifies the episodes of latent nocturnal hypoglycemia and postprandial hyperglycemia. The analysis of CGM data allows for correcting insulin therapy, taking a decision on its initiation, and modifying diet and exercise plan. Multiple studies demonstrate the efficacy of CGM in terms of compensating manifest diabetes. As to gestational diabetes, the eligibility of modern glucose monitoring technologies for the prevention of various complications is still controversial. Further studies on the potential use of these devices in gestational diabetes could provide a basis for increasing their application in routine clinical practice. This will improve the management of pregnant women with carbohydrate metabolism disorders.KEYWORDS: diabetes, gestational diabetes, continuous glucose monitoring, flash monitoring, pregnancy, macrosomia, self-monitoring.FOR CITATION: Ushanova F.O., Demidova T.Yu. Potentialities of modern glucose monitoring devices during pregnancy. Russian Medical Inquiry. 2020;4(6):352–357. DOI: 10.32364/2587-6821-2020-4-6-352-357.

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Glucose Regulation Beyond HbA1c in Type 2 Diabetes Treated With Insulin: Real-World Evidence From the DIALECT-2 Cohort

10.2337/figshare.14838837.v1 ◽

2021 ◽

Author(s):

Niala den Braber ◽

Miriam M.R. Vollenbroek-Hutten ◽

Kathryn M. Westerik ◽

Stephan J.L. Bakker ◽

Gerjan Navis ◽

...

Keyword(s):

Type 2 Diabetes ◽

Glucose Monitoring ◽

Glucose Variability ◽

Glucose Regulation ◽

Nocturnal Hypoglycemia ◽

Real World Evidence ◽

Freestyle Libre ◽

Time In Range ◽

Design And Methods

OBJECTIVE To investigate glucose variations associated with HbA1c in insulin treated patients with type 2 diabetes. RESEARCH DESIGN AND METHODS Patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT)-2 (n=79) were categorized in three HbA1c categories: low, intermediate and high (≤ 53; 54–62 and ≥ 63 mmol/mol or ≤ 7, 7.1–7.8, ≥ 7.9%). Blood glucose time in range (TIR), time below range (TBR), time above range (TAR), glucose variability parameters, day and night duration and frequency of TBR and TAR episodes were determined by continuous glucose monitoring (CGM), using the FreeStyle Libre sensor and compared between HbA1c categories. RESULTS <a>CGM was performed for a median [interquartile range] of 10 [7-12] days/ patient. </a>TIR was not different for low and intermediate HbA1c categories: (76.8% [68.3–88.2] vs 76.0% [72.5.0–80.1]), whereas in the low category TBR was higher and TAR lower (7.7% [2.4–19.1] vs 0.7% [0.3–6.1], and 8.2% [5.7–17.6] vs 20.4% [11.6–27.0], respectively, p < 0.05). Patients in the highest HbA1c category had lower TIR (52.7% [40.9–67.3]) and higher TAR (44.1% [27.8–57.0]) than the other HbA1c categories (p < 0.05), but did not have less TBR during the night. All patients had more (0.06 ± 0.06/h vs 0.03 ± 0.03/h, p = 0.002) and longer (88.0 [45.0–195.5] vs 53.4 [34.4–82.8] minutes, p < 0.001) TBR episodes during the night than during the day. CONCLUSIONS In this study, a high HbA1c did not reduce the occurrence of nocturnal hypoglycemia and low HbA1c was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.

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

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2018-02384 ◽

2019 ◽

Vol 104 (11) ◽

pp. 5217-5224 ◽

Cited By ~ 6

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.

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The Degree of Hyperglycemia Excursion in Patients of Kidney Transplantation (KT) or Liver Transplantation (LT) Assessed by Continuous Glucose Monitoring (CGM): Pilot Study

Journal of Diabetes Research ◽

10.1155/2019/1757182 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10

Author(s):

Heung Yong Jin ◽

Kyung Ae Lee ◽

Yu Ji Kim ◽

Tae Sun Park ◽

Sik Lee ◽

...

Keyword(s):

Liver Transplantation ◽

Kidney Transplantation ◽

Continuous Glucose Monitoring ◽

Glucose Monitoring ◽

Early Period ◽

Mean Amplitude ◽

Glucose Levels ◽

Normal Glucose ◽

Glucose Profiles

Objective. This study used a continuous glucose monitoring system (CGMS) to investigate the glucose profiles and assess the degree of hyperglycemic excursion after kidney or liver transplantation during the early period after operation. Methods. Patients to whom a CGMS was attached during a postoperative period of approximately one month after transplantation were included. The CGM data of 31 patients including 24 with kidney transplantation (KT) and seven with liver transplantation (LT) were analyzed. Results. Hyperglycemia over 126 mg/dL (fasting) or 200 g/dL (postprandial) occurred in 42.1% (8/19) and 16.7% (1/6) of KT and LT patients, respectively, during this early period after transplantation, except for patients with preexisting diabetes (5 KT, 1 LT). The average mean amplitude of glycemic excursion (MAGE) and mean absolute glucose (MAG) levels were 91.18±26.51 vs. 65.66±22.55 (P<0.05) and 24.62±7.78 vs. 18.18±7.07 (P<0.05) in KT vs. LT patients, respectively, in patients without preexisting DM or PTDM patients who showed normal glucose levels. Average increase from the lowest level to the peak glucose value was higher in KT patients than LT patients (P<0.05). Conclusions. The transplanted organ also needs to be considered as an important factor affecting glucose control and the occurrence of more severe glucose excursions in patients who receive transplantation although immunosuppression agents are well-known important factors; however, our study was limited to the early posttransplantation period. Further studies involving CGM follow-up at regular intervals based on the time since transplantation are needed.

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

10.2337/figshare.14461800.v1 ◽

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

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

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Hypoglycemia after initiating insulin therapy based on the results of structured self-control and monitoring of blood glucose

Medical Council ◽

10.21518/2079-701x-2018-12-112-116 ◽

2018 ◽

pp. 112-116

Author(s):

A. V. Petrov ◽

L. G. Strongin

Keyword(s):

Blood Glucose ◽

Roc Analysis ◽

Optimal Schedule ◽

Glucose Monitoring ◽

Glucose Variability ◽

Self Control ◽

Self Monitoring ◽

Glucose Levels ◽

Diagnostic Threshold ◽

Average Glucose

Hypoglycemia detection in T2DM patients is an important issue which is usually accomplished with self-monitoring of blood glucose (SMBG). Optimal schedule of testing and diagnostic threshold are important for effective SMBG. Aims of study: To evaluate hypoglycemia frequency by SMBG using structured AccuChek 360 View protocol and glucose monitoring and increase SMBG efficacy in the detection of hypoglycemia. Study design: 16 T2DM patients after initiation of insulin treatment were included. Each patient had 3 days of glucose monitoring together with SMBG 7 times a day after hospital discharge and 3 months later. Results: Hypoglycemia was detected in 38% of monitoring periods; this patients had higher glucose variability and lower average glucose. SMBG detected hypoglycemia in 16% of periods. 6 out of 7 unrecognized hypoglycemias were during night. This 6 cases were characterized by minimal daytime glucose levels by SMBG below 5 mmol/l. ROC-analysis demonstrated minimal glucose level during daytime of 4.8 mmol/l to have 92% sensitivity and 74% specificity for detection of any hypoglycemia by glucose monitoring. Conclusion: Structured Accu-Chek 360 View SMBG can reliably detect daytime hypoglycemia but regular nighttime testing is recommended in all T2DM patients using insulin for detection of nighttime hypoglycemia. Minimal glucose levels below 4.8-5 mmol/l during daytime corresponds with high hypoglycemia risk.

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Glucose Fluctuations during Gestation: An Additional Tool for Monitoring Pregnancy Complicated by Diabetes

International Journal of Endocrinology ◽

10.1155/2013/279021 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 19

Author(s):

M. G. Dalfrà ◽

N. C. Chilelli ◽

G. Di Cianni ◽

G. Mello ◽

C. Lencioni ◽

...

Keyword(s):

Type 1 Diabetes ◽

Pregnant Women ◽

Glycemic Index ◽

Glucose Monitoring ◽

Mean Amplitude ◽

Glucose Variability ◽

Healthy Controls ◽

Additional Tool ◽

Glucose Fluctuations

Continuous glucose monitoring (CGM) gives a unique insight into magnitude and duration of daily glucose fluctuations. Limited data are available on glucose variability (GV) in pregnancy. We aimed to assess GV in healthy pregnant women and cases of type 1 diabetes mellitus or gestational diabetes (GDM) and its possible association with HbA1c. CGM was performed in 50 pregnant women (20 type 1, 20 GDM, and 10 healthy controls) in all three trimesters of pregnancy. We calculated mean amplitude of glycemic excursions (MAGE), standard deviation (SD), interquartile range (IQR), and continuous overlapping net glycemic action (CONGA), as parameters of GV. The high blood glycemic index (HBGI) and low blood glycemic index (LBGI) were also measured as indicators of hyperhypoglycemic risk. Women with type 1 diabetes showed higher GV, with a 2-fold higher risk of hyperglycemic spikes during the day, than healthy pregnant women or GDM ones. GDM women had only slightly higher GV parameters than healthy controls. HbA1c did not correlate with GV indicators in type 1 diabetes or GDM pregnancies. We provided new evidence of the importance of certain GV indicators in pregnant women with GDM or type 1 diabetes and recommended the use of CGM specifically in these populations.

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Postprandial walking reduces glucose levels in women with gestational diabetes mellitus

Applied Physiology Nutrition and Metabolism ◽

10.1139/apnm-2017-0494 ◽

2018 ◽

Vol 43 (5) ◽

pp. 531-534 ◽

Cited By ~ 8

Author(s):

Dawn P. Coe ◽

Scott A. Conger ◽

Jo M. Kendrick ◽

Bobby C. Howard ◽

Dixie L. Thompson ◽

...

Keyword(s):

Diabetes Mellitus ◽

Gestational Diabetes ◽

Gestational Diabetes Mellitus ◽

Glucose Monitoring ◽

Postprandial Glucose ◽

Moderate Intensity ◽

Acute Bout ◽

Glucose Levels ◽

High Carbohydrate ◽

Moderate Intensity Activity

The purpose of this study was to investigate blood glucose changes, as measured by a continuous glucose monitoring system, that occur in women with gestational diabetes mellitus (GDM) following an acute bout of moderate-intensity walking after consuming a high-carbohydrate/low-fat meal. This study found that moderate-intensity walking induced greater postprandial glucose control compared with sedentary activity and it appears that moderate-intensity activity may be used to reduce postprandial glucose levels in women with GDM.

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