This study is designed to evaluate individuals who are currently experiencing symptoms of hypoglycemia, in order to discern correlations between microbiome composition and patterns of postprandial glycemia.
Recent studies have shown that analysis of the gastrointestinal microbiome can be used to predict glycemic response to dietary intake. Specifically, integrative analysis of dietary consumption, anthropometrics, physical activity and gut microbiota composition can be used to predict postprandial glycemic excursions. The investigators hypothesize that individualized assessment of glycemic responses to food, together with analysis of the gut microbiome, will allow the design of a personalized dietary approach to minimize glycemic excursions for patients with post-bariatric and other forms of largely postprandial hypoglycemia. Identification of factors predictive of glycemic excursions and subsequent hypoglycemia may ultimately allow individuals to tailor their diet towards foods which would not induce hypersecretion of insulin and subsequent hypoglycemia.
Study Type
OBSERVATIONAL
Enrollment
28
Joslin Diabetes Center
Boston, Massachusetts, United States
Analysis of cumulative duration of hypoglycemia
Duration of hypoglycemia will be assessed by: (1) the number of minutes per day with hypoglycemia, defined as sensor glucose \<70 mg/dl, and (2) the number of minutes per day of severe hypoglycemia, defined as sensor glucose \<55 mg/dl. Data will be captured for the entire 24 hour period as well as day and night subsets.
Time frame: 2 weeks
Analysis of frequency of glycemic excursions
Hypoglycemia frequency will be assessed by: (1) number of episodes of hypoglycemia, both moderate (55-70 mg/dl) and severe (\<55 mg/dl), (2) number of episodes requiring assistance, and (4) number of episodes of hyperglycemia (\>180 mg/dl). All data will be averaged and reported as episodes per day.
Time frame: 2 weeks
Impact of activity on glycemic patterns in post-bariatric hypoglycemia
Activity measures (total step number per day) will be analyzed to determine relationship to changes in sensor glucose levels. Data will be integrated to determine relationships between glycemic patterns, diet, and microbiome.
Time frame: 2 weeks
Impact of diet on glycemic patterns in post-bariatric hypoglycemia
Dietary information will be transcribed and recorded from participants' food diaries. Data will be integrated to determine relationships between glycemic patterns, diet, and microbiome.
Time frame: 2 weeks
Analysis of microbiome in individuals with post-bariatric hypoglycemia
Stool samples will be analyzed to determine microbiome community by 18S sequencing. Data will be integrated to determine relationships between glycemic patterns, diet, and microbiome.
Time frame: 2 weeks
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