Continuous Glucose Monitor for Kids Is Approved

Background: With the development of continuous glucose monitoring systems (CGMS), detailed glycemic data are now available for analysis. Yet analysis of this data-rich information can be formidable. The power of CGMS-derived data lies in its characterization of glycemic variability. In contrast, many standard glycemic measures like hemoglobin A1c (HbA1c) and self-monitored blood glucose inadequately describe glycemic variability and run the risk of bias toward overreporting hyperglycemia. Methods that adjust for this bias are often overlooked in clinical research due to difficulty of computation and lack of accessible analysis tools. Methods: In response, we have developed a new R package rGV, which calculates a suite of 16 glycemic variability metrics when provided a single individual’s CGM data. rGV is versatile and robust; it is capable of handling data of many formats from many sensor types. We also created a companion R Shiny web app that provides these glycemic variability analysis tools without prior knowledge of R coding. We analyzed the statistical reliability of all the glycemic variability metrics included in rGV and illustrate the clinical utility of rGV by analyzing CGM data from three studies. Results: In subjects without diabetes, greater glycemic variability was associated with higher HbA1c values. In patients with type 2 diabetes mellitus (T2DM), we found that high glucose is the primary driver of glycemic variability. In patients with type 1 diabetes (T1DM), we found that naltrexone use may potentially reduce glycemic variability. Conclusions: We present a new R package and accompanying web app to facilitate quick and easy computation of a suite of glycemic variability metrics.

Download Full-text

Some pearl millet-based foods promote satiety or reduce glycaemic response in a crossover trial

British Journal Of Nutrition ◽

10.1017/s0007114520005036 ◽

2020 ◽

pp. 1-31

Author(s):

Anna M.R. Hayes ◽

Fanny Gozzi ◽

Aminata Diatta ◽

Tom Gorissen ◽

Clay Swackhamer ◽

...

Keyword(s):

Gastric Emptying ◽

Pearl Millet ◽

Octanoic Acid ◽

Crossover Trial ◽

Normal Weight ◽

Glycaemic Response ◽

Continuous Glucose Monitor ◽

Gastric Emptying Rate ◽

White Rice ◽

Traditionally Prepared

Abstract In a previous trial in Mali, we showed traditional pearl millet couscous and thick porridge delayed gastric emptying (~5 h half-emptying times) in a normal weight population compared to non-traditional carbohydrate-based foods (pasta, potatoes, white rice; ~3 h half-emptying times), and in a gastric simulator we showed millet couscous had slower digestion than wheat couscous. In light of these findings, we tested the hypothesis in a normal weight U.S. population (n=14) that millet foods would reduce glycaemic response (continuous glucose monitor), improve appetitive sensations (Visual Analog Scale ratings), as well as reduce gastric emptying rate (13C octanoic acid breath test). Five carbohydrate-based foods (millet couscous – commercial and self-made, millet thick porridge, wheat couscous, white rice) were fed in a crossover trial matched on available carbohydrate basis. Significantly lower overall glycaemic response was observed for all millet-based foods and wheat couscous compared to white rice (p≤0.05). Millet couscous (self-made) had significantly higher glycaemic response than millet couscous (commercial) and wheat couscous (p<0.0001), but as there were no differences in peak glucose values (p>0.05) an extended glycaemic response was indicated for self-made couscous. Millet couscous (self-made) had significantly lower hunger ratings (p<0.05) and higher fullness ratings (p<0.01) than white rice, millet thick porridge, and millet couscous (commercial). A normal gastric emptying rate (<3 h half-emptying times) was observed for all foods, with no significant differences among them (p>0.05). In conclusion, some traditionally prepared pearl millet foods show the potential to reduce glycaemic response and promote satiety.

Download Full-text

Continuous Ketone Monitoring: A New Paradigm for Physiologic Monitoring

Journal of Diabetes Science and Technology ◽

10.1177/19322968211009860 ◽

2021 ◽

pp. 193229682110098

Author(s):

Jennifer Y. Zhang ◽

Trisha Shang ◽

Suneil K. Koliwad ◽

David C. Klonoff

Keyword(s):

Interstitial Fluid ◽

Good Accuracy ◽

Physiologic Monitoring ◽

New Paradigm ◽

Continuous Glucose Monitor ◽

Sensor Platform ◽

Wired Enzyme ◽

First Time

In this issue of JDST, Alva and colleagues present for the first time, development of a continuous ketone monitor (CKM) tested both in vitro and in humans. Their sensor measured betahydroxybutyrate (BHB) in interstitial fluid (ISF). The sensor was based on wired enzyme electrochemistry technology using BHB dehydrogenase. The sensor required only a single retrospective calibration without a need for further adjustments over 14 days. The device produced a linear response over the 0-8 mM range with good accuracy. This novel CKM could provide a new dimension of useful automatically collected information for managing diabetes. Passively collected ISF ketone information would be useful for predicting and managing ketoacidosis in patients with type 1 diabetes, as well as other states of abnormal ketonemia. Although additional studies of this CKM will be required to assess performance in intended patient populations and prospective factory calibration will be required to support real time measurements, this novel monitor has the potential to greatly improve outcomes for people with diabetes. In the future, a CKM might be integrated with a continuous glucose monitor in the same sensor platform.

Download Full-text

Continuous Glucose Monitor Systems

Encyclopedia of Behavioral Medicine ◽

10.1007/978-1-4614-6439-6_102021-1 ◽

2019 ◽

pp. 1-1

Author(s):

Janine Sanchez

Keyword(s):

Continuous Glucose Monitor

Download Full-text

Hypothesis on the glucose production’s communication model between thebrain and other internal organs, especially the stomach and liver

Journal of Psychology and Neuroscience ◽

10.47485/2693-2490.1027 ◽

2020 ◽

Keyword(s):

Glucose Production ◽

Internal Communication ◽

Cooking Methods ◽

Communication Model ◽

Internal Organs ◽

Continuous Glucose Monitor ◽

Solid Meal ◽

Liquid Meal ◽

Postprandial Plasma Glucose ◽

Lower Glucose

After reviewing the research results for six months, from September 2019 through February 2020, the author identified a probable internal communication model between the nervous system and certain vital internal organs, specifically the stomach and liver regarding postprandial plasma glucose (PPG) production. The author used a continuous glucose monitor device to collect 50,000 glucose data during the past 665 days. He focused on studying the relationships among different food nutritional contents, cooking methods, food material’s physical phases, and different characteristics and variants from his glucose waveform patterns. In this study, he focused on the three major meal groups based on food nutritional ingredients, meal’s preparation, and cooking methods of eggs, squash, and cabbage to create soup-based (liquid) meal and pan-fried (solid) meal. The PPG waveforms from these three meal groups demonstrated that soup-based liquid food produced a much lower glucose value than the pan-fried solid food. Although both liquid and solid meals have similar identical nutritional ingredients, he questions why did this occur? His hypothesis is that his PPG differences are due to specific physical phase of his finished meal either “liquid” or “solid”, which is his ready-to-eat meal’s final physical “phase” that determines his PPG characteristics and waveforms. The author utilized his GH-Method: math-physical medicine (MPM) approach to explore a T2D patient’s glucose production situation from a scientific view of the brain and nervous system’s functionalities. If this specific approach and above interpretation are accurate, we can then “trick” our brain into producing a “lesser” amount of glucose after food intake without altering or sacrificing the needed food nutritional balance. As a result, T2D patients can simply change their cooking method in order to lower both of their peak PPG values and their average PPG levels.

Download Full-text

Substantial Intra-Individual Variability in Post-Prandial Time to Peak in Controlled and Free-Living Conditions in Children with Type 1 Diabetes

Nutrients ◽

10.3390/nu13114154 ◽

2021 ◽

Vol 13 (11) ◽

pp. 4154

Author(s):

Emily Bell ◽

Sabrina Binkowski ◽

Elaine Sanderson ◽

Barbara Keating ◽

Grant Smith ◽

...

Keyword(s):

Type 1 Diabetes ◽

Individual Variability ◽

Living Conditions ◽

Optimal Time ◽

Daily Routine ◽

Free Living ◽

Continuous Glucose Monitor ◽

Time To Peak ◽

Free Living Conditions

The optimal time to bolus insulin for meals is challenging for children and adolescents with type 1 diabetes (T1D). Current guidelines to control glucose excursions do not account for individual differences in glycaemic responses to meals. This study aimed to examine the within- and between-person variability in time to peak (TTP) glycaemic responses after consuming meals under controlled and free-living conditions. Participants aged 8–15 years with T1D ≥ 1 year and using a continuous glucose monitor (CGM) were recruited. Participants consumed a standardised breakfast for six controlled days and maintained their usual daily routine for 14 free-living days. CGM traces were collected after eating. Linear mixed models were used to identify within- and between-person variability in the TTP after each of the controlled breakfasts, free-living breakfasts (FLB), and free-living dinners (FLD) conditions. Thirty participants completed the study (16 females; mean age and standard deviation (SD) 10.5 (1.9)). The TTP variability was greater within a person than the variability between people for all three meal types (between-person vs within-person SD; controlled breakfast 18.5 vs 38.9 minutes; FLB 14.1 vs 49.6 minutes; FLD 5.7 vs 64.5 minutes). For the first time, the study showed that within-person variability in TTP glycaemic responses is even greater than between-person variability.

Download Full-text