scholarly journals Application of Continuous Glucose Monitoring for Assessment of Individual Carbohydrate Requirement during Ultramarathon Race

Nutrients ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1121
Author(s):  
Kengo Ishihara ◽  
Natsuki Uchiyama ◽  
Shino Kizaki ◽  
Emi Mori ◽  
Tsutomu Nonaka ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring ◽  
Carbohydrate Intake ◽  
Running Speed ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Food And Drink ◽  
Average Glucose Concentration ◽  
Average Glucose

Background: The current study intended to evaluate the feasibility of the application of continuous glucose monitoring to guarantee optimal intake of carbohydrate to maintain blood glucose levels during a 160-km ultramarathon race. Methods: Seven ultramarathon runners (four male and three female) took part in the study. The glucose profile was monitored continuously throughout the race, which was divided into 11 segments by timing gates. Running speed in each segment was standardized to the average of the top five finishers for each gender. Food and drink intake during the race were recorded and carbohydrate and energy intake were calculated. Results: Observed glucose levels ranged between 61.9–252.0 mg/dL. Average glucose concentration differed from the start to the end of the race (104 ± 15.0 to 164 ± 30.5 SD mg/dL). The total amount of carbohydrate intake during the race ranged from 0.27 to 1.14 g/kg/h. Glucose concentration positively correlated with running speeds in segments (P < 0.005). Energy and carbohydrate intake positively correlated with overall running speed (P < 0.01). Conclusion: The present study demonstrates that continuous glucose monitoring could be practical to guarantee optimal carbohydrate intake for each ultramarathon runner.

Hypoglycemia Pathogenesis in Children With Dumping Syndrome

PEDIATRICS ◽  
1987 ◽  
Vol 80 (6) ◽  
pp. 937-942
Author(s):  
Scott A. Rivkees ◽  
John D. Crawford
Keyword(s):  
Glucose Concentration ◽  
Challenge Test ◽  
Dumping Syndrome ◽  
Early Release ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Single Meal ◽  
Average Blood Glucose ◽  
Average Glucose Concentration ◽  
Average Glucose

Three children with severe hypoglycemic reactions secondary to dumping syndrome were studied to discern the mechanism by which hypoglycemia occurred. Symptoms in patient 1 developed after fundoplication, generalized autonomic dysfunction occurred in patient 2, and dumping syndrome developed in patient 3 after malplacement of a feeding gastrostomy tube. Average blood glucose levels studied during and after two to seven meals in each child were 375 ± 97 mg/dL (mean ± SD) 30 minutes postprandially and 35 ± 10 mg/dL &gt;120 minutes later. Swings in glucose values were proportional to the volume of meals. Insulin and glucagon levels were followed during a single meal challenge test in each patient; the average glucose concentration increased to 356 ± 59 mg/dL 30 minutes postprandially and decreased to 32 ± 11 mg/dL at 150 ± 30 minutes. Hormonal analyses indicated (1) inappropriate early release of glucagon (300 pg/mL at 15 minutes) in patient 1, (2) exuberant early release of insulin (maximum 190 ± 15 µU/mL) resulting in rapid decrease in glucose concentration in all patients, (3) development and/or persistence of hypoglycemia after the decline in circulating insulin to undetectable levels, and (4) inadequate glucagon response to hypoglycemia resulting in sustained hypoglycemia. These data indicate that gross disturbances of the insulin-glucagon axis attend childhood dumping syndrome.

scholarly journals Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study

2019 ◽  
Vol 104 (10) ◽  
pp. 4356-4364 ◽  
Author(s):  
Viral N Shah ◽  
Stephanie N DuBose ◽  
Zoey Li ◽  
Roy W Beck ◽  
Anne L Peters ◽  
...  
Keyword(s):  
Prospective Study ◽  
Median Time ◽  
Continuous Glucose Monitoring ◽  
Age Groups ◽  
Glucose Monitoring ◽  
Future Research ◽  
Glucose Levels ◽  
Sensor Glucose ◽  
Multicenter Prospective Study ◽  
Average Glucose

Abstract Context Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes. Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking. Objective To establish reference sensor glucose ranges in healthy, nondiabetic individuals across different age groups using a current generation CGM sensor. Design Multicenter, prospective study. Setting Twelve centers within the T1D Exchange Clinic Network. Patients or Participants Nonpregnant, healthy, nondiabetic children and adults (age ≥6 years) with nonobese body mass index. Intervention Each participant wore a blinded Dexcom G6 CGM, with once-daily calibration, for up to 10 days. Main Outcome Measures CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability. Results A total of 153 participants (age 7 to 80 years) were included in the analyses. Mean average glucose was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (5.8 mmol/L). The median time between 70 to 140 mg/dL (3.9 to 7.8 mmol/L) was 96% (interquartile range, 93 to 98). Mean within-individual coefficient of variation was 17 ± 3%. Median time spent with glucose levels &gt;140 mg/dL was 2.1% (30 min/d), and median time spent with glucose levels &lt;70 mg/dL (3.9 mmol/L) was 1.1% (15 min/d). Conclusion By assessing across age groups in a healthy, nondiabetic population, normative sensor glucose data have been derived and will be useful as a benchmark for future research studies.

scholarly journals Correlation between short- and mid-term hemoglobin A1c and glycemic control determined by continuous glucose monitoring

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

Abstract Background Glucose monitoring is vital for glycemic control in patients with diabetes mellitus (DM). Continuous glucose monitoring (CGM) measures whole-day glucose levels. Hemoglobin A1c (HbA1c) is a vital outcome predictor in patients with DM. Methods This study investigated the relationship between HbA1c and CGM, which remained unclear hitherto. Data of patients with DM (n = 91) who received CGM and HbA1c testing (1–3 months before and after CGM) were retrospectively analyzed. Diurnal and nocturnal glucose, highest CGM data (10%, 25%, and 50%), mean amplitude of glycemic excursions (MAGE), percent coefficient of variation (%CV), and continuous overlapping net glycemic action were compared with HbA1c values before and after CGM. Results The CGM results were significantly correlated with HbA1c values measured 1 (r = 0.69) and 2 (r = 0.39) months after CGM and 1 month (r = 0.35) before CGM. However, glucose levels recorded in CGM did not correlate with the HbA1c values 3 months after and 2–3 months before CGM. MAGE and %CV were strongly correlated with HbA1c values 1 and 2 months after CGM, respectively. Diurnal blood glucose levels were significantly correlated with HbA1c values 1–2 months before and 1 month after CGM. The nocturnal blood glucose levels were significantly correlated with HbA1c values 1–3 months before and 1–2 months after CGM. Conclusions CGM can predict HbA1c values within 1 month after CGM in patients with DM.

Advantages and Disadvantages of Realtime Continuous Glucose Monitoring in People with Type 2 Diabetes

2012 ◽  
Vol 08 (01) ◽  
pp. 22 ◽  
Author(s):  
M Susan Walker ◽  
Stephanie J Fonda ◽  
Sara Salkind ◽  
Robert A Vigersky ◽  
◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Levels ◽  
Advantages And Disadvantages ◽  
Blood Glucose Levels

Previous research has shown that realtime continuous glucose monitoring (RT-CGM) is a useful clinical and lifestyle aid for people with type 1 diabetes. However, its usefulness and efficacy for people with type 2 diabetes is less known and potentially controversial, given the continuing controversy over the efficacy of self-monitoring of blood glucose (SMBG) in this cohort. This article reviews theextantliterature on RT-CGM for people with type 2 diabetes, and enumerates several of the advantages and disadvantages of this technology from the perspective of providers and patients. Even patients with type 2 diabetes who are not using insulin and/or are relatively well controlled on oral medications have been shown to spend a significant amount of time each day in hyperglycemia. Additional tools beyond SMBG are necessary to enable providers and patients to clearly grasp and manage the frequency and amplitude of glucose excursions in people with type 2 diabetes who are not on insulin. While SMBG is useful for measuring blood glucose levels, patients do not regularly check and SMBG does not enable many to adequately manage blood glucose levels or capture marked and sustained hyperglycemic excursions. RT-CGM systems, valuable diabetes management tools for people with type 1 diabetes or insulin-treated type 2 diabetes, have recently been used in type 2 diabetes patients. Theextantstudies, although few, have demonstrated that the use of RT-CGM has empowered people with type 2 diabetes to improve their glycemic control by making and sustaining healthy lifestyle choices.

scholarly journals Outcome of Patients with ST-T Changes in Non STSegment Elevation Myocardial Infarction

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Mohammad Arifur Rahman
Keyword(s):  
Myocardial Infarction ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Measurement Methods ◽  
Glucose Levels ◽  
Sensor Device ◽  
Sensor Glucose ◽  
Average Glucose

This article discusses the fundamental characteristics of measured glucose levels and predicted glycated hemoglobin A1c (HbA1c) values among three sets of collected data, measured finger-piercing and continuous glucose monitoring (CGM) sensor device collected glucose levels at 15-minute (15-min) and 5-minute (5-min) intervals. The average glucose (in milligram per deciliter-mg/dL) is listed below: Finger glucose: 109 mg/dL (100%) Sensor at 15-min: 120 mg/dL (109%) Sensor at 5-min: 117 mg/dL (107%) Using candlestick chart, the comparison of average glucoses during this period between two sensor glucose (mg/dL) data (15-min/5-min) are as follows: Open glucose: 108/111 Close glucose: 115/115 Maximum (max) glucose: 170 /175 Minimum (min) glucose: 85/83 Average glucose: 120/117 Additional analysis of time above range (TAR)≥140 mg/dL for hyperglycemia, time within the range (TIR) from 70-140 mg/dL for normal, time below range (TBR)≤70 mg/dL for hypoglycemia based on two sensor candlesticks revealing the following information in a specific format of TAR%/ TIR%/TBR%. 15-min:18.3%, 80.5%, 1.2% 5-min: 17.0%, 81.9%, 1.1% By evaluating the results of the TIR analysis, the 5-min glucose levels appear to be marginally healthier (1.4%) than the 15-min ones. During the coronavirus pandemic (COVID 19) quarantine period, the author lived a rather unique lifestyle which is extremely calm with regular routines, such as eating home-cooked meals and exercising on a regular basis. As a result, his HbA1c has decreased from 6.6% to 6.3% with an average A1c of 6.4% without taking any diabetes medications. However, these three different measurement methods still provide three different sets of glucoses levels which are within a 10% margin of differences, while the HbA1c values are particularly close to each other between the finger-piercing and CGM 15-min.

scholarly journals Correlation Between Short- and Mid-Term Hemoglobin A1c and Glycemic Control Determined by Continuous Glucose Monitoring

2021 ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

Abstract Background: Glucose monitoring is vital for glycemic control in patients with diabetes mellitus (DM). Continuous glucose monitoring (CGM) measures whole-day glucose levels. Hemoglobin A1c (HbA1c) is a vital outcome predictor in patients with DM. Methods: This study investigated the relationship between HbA1c and CGM, which remained unclear hitherto. Data of patients with DM (n = 91) who received CGM and HbA1c testing (1-3 months before and after CGM) were retrospectively analyzed. Diurnal and nocturnal glucose, highest CGM data (10%, 25%, and 50%), mean amplitude of glycemic excursions (MAGE), percent coefficient of variation (%CV), and continuous overlapping net glycemic action were compared with HbA1c values before and after CGM. Results: The CGM results were significantly correlated with HbA1c values measured 1 (r = 0.69) and 2 (r = 0.39) months after CGM and 1 month (r = 0.35) before CGM. However, glucose levels recorded in CGM did not correlate with the HbA1c values 3 months after and 2-3 months before CGM. MAGE and %CV were strongly correlated with HbA1c values 1 and 2 months after CGM, respectively. Diurnal blood glucose levels were significantly correlated with HbA1c values 1-2 months before and 1 month after CGM. The nocturnal blood glucose levels were significantly correlated with HbA1c values 1-3 months before and 1-2 months after CGM.Conclusions: CGM can predict HbA1c values within 1 month after CGM in patients with DM.

scholarly journals Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

2010 ◽  
Vol 10 (1) ◽  
pp. 36 ◽  
Author(s):  
Cosimo Scuffi ◽  
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Interstitial Fluid ◽  
Glucose Monitoring ◽  
Foreign Body Response ◽  
Monitoring Systems ◽  
Glucose Levels ◽  
Consequent Reduction ◽  
The Impact

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

scholarly journals Continuous glucose monitoring in obese pregnant women with no hyperglycemia on glucose tolerance test

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253047
Author(s):  
Rosa Maria Rahmi ◽  
Priscila de Oliveira ◽  
Luciano Selistre ◽  
Paulo Cury Rezende ◽  
Gabriela Neuvald Pezzella ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glucose Tolerance ◽  
Pregnant Women ◽  
Continuous Glucose Monitoring ◽  
Glucose Tolerance Test ◽  
Glucose Monitoring ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Glucose Levels ◽  
Blood Glucose Levels

Objective The objective of the present study was to compare 24-hour glycemic levels between obese pregnant women with normal glucose tolerance and non-obese pregnant women. Methods In the present observational, longitudinal study, continuous glucose monitoring was performed in obese pregnant women with normal oral glucose tolerance test with 75 g of glucose between the 24th and the 28th gestational weeks. The control group (CG) consisted of pregnant women with normal weight who were selected by matching the maternal age and parity with the same characteristics of the obese group (OG). Glucose measurements were obtained during 72 hours. Results Both the groups were balanced in terms of baseline characteristics (age: 33.5 [28.7–36.0] vs. 32.0 [26.0–34.5] years, p = 0.5 and length of pregnancy: 25.0 [24.0–25.0] vs. 25.5 [24.0–28.0] weeks, p = 0.6 in the CG and in the OG, respectively). Pre-breakfast glycemic levels were 77.77 ± 10.55 mg/dL in the CG and 82.02 ± 11.06 mg/dL in the OG (p<0.01). Glycemic levels at 2 hours after breakfast were 87.31 ± 13.10 mg/dL in the CG and 93.48 ± 18.74 mg/dL in the OG (p<0.001). Daytime blood glucose levels were 87.6 ± 15.4 vs. 93.1 ± 18.3 mg/dL (p<0.001) and nighttime blood glucose levels were 79.3 ± 15.8 vs. 84.7 ± 16.3 mg/dL (p<0.001) in the CG and in the OG, respectively. The 24-hour, daytime, and nighttime values of the area under the curve were higher in the OG when compared with the CG (85.1 ± 0.16 vs. 87.9 ± 0.12, 65.6 ± 0.14 vs. 67.5 ± 0.10, 19.5 ± 0.07 vs. 20.4 ± 0.05, respectively; p<0.001). Conclusion The results of the present study showed that obesity in pregnancy was associated with higher glycemic levels even in the presence of normal findings on glucose tolerance test.

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