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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CGM and Microbiota | Participants will wear a Dexcom continuous glucose monitor (CGM) and activity monitor for two weeks. They will not be aware of sensor glucose values. A stool sample will be collected. The investigators will evaluate relationships between patterns of postprandial glycemia, recorded by CGM, food intake, and microbiome composition. |
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| Measure | Description | Time Frame |
|---|---|---|
| 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. | 2 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | 2 weeks |
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Inclusion Criteria
Exclusion Criteria
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Patients who experience hypoglycemia after bariatric or other upper gastrointestinal surgery or those with reactive hypoglycemia in the absence of surgery.
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| Name | Affiliation | Role |
|---|---|---|
| Mary E Patti, MD | Joslin Diabetes Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Joslin Diabetes Center | Boston | Massachusetts | 02215 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26701701 | Background | Patti ME, Goldfine AB. The rollercoaster of post-bariatric hypoglycaemia. Lancet Diabetes Endocrinol. 2016 Feb;4(2):94-6. doi: 10.1016/S2213-8587(15)00460-X. Epub 2015 Dec 15. No abstract available. | |
| 28868615 | Background | Mulla CM, Middelbeek RJW, Patti ME. Mechanisms of weight loss and improved metabolism following bariatric surgery. Ann N Y Acad Sci. 2018 Jan;1411(1):53-64. doi: 10.1111/nyas.13409. Epub 2017 Sep 3. |
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| ID | Term |
|---|---|
| D007003 | Hypoglycemia |
| ID | Term |
|---|---|
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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Blood or saliva samples are being collected for future genotyping to identify genetic factors linked to risk of hypoglycemia.
| 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. | 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. | 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. | 2 weeks |
| 28392017 | Background | Suhl E, Anderson-Haynes SE, Mulla C, Patti ME. Medical nutrition therapy for post-bariatric hypoglycemia: practical insights. Surg Obes Relat Dis. 2017 May;13(5):888-896. doi: 10.1016/j.soard.2017.01.025. Epub 2017 Jan 16. |