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| Name | Class |
|---|---|
| LA CaTS Clinical Research Resources Core | UNKNOWN |
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We will recruit 20 severely obese participants at Metamor Institute. Participants with obesity who are eligible for MBS will be randomized to either CGM group or self-monitoring of blood glucose (SMBG) group before the surgery based on a 1:1 ratio. All participants live in Baton Rouge, Louisiana. The surgeon in Metamor will introduce our study to the patients. If the patients are interested, the evaluation process includes verifying basic personal information, assessing health status and medical history, and evaluating specific eligibility criteria relevant to the study. The study coordinator will be discussing informed consent, ensuring participants understand the study's purpose, procedures, and any associated risks or benefits. Participants are encouraged to ask questions, ensuring clarity and comfort with the study. All collected data is documented and securely stored, respecting data privacy protocols. Eligible individuals are informed about the screening visit, while those not suitable are considered for future studies.
Obesity is listed as the most important risk factor associated with organ dysfunctions. More than 42% of US are classified as obese and 9.4% have severe obesity. About 30% of patients with T2D have severe obesity. The combination of severe obesity and T2D significantly increases the risk of CVD, non-alcoholic fatty liver disease, and other comorbidities, which contribute to higher mortality rates. To tackle this heavy burden, there's a need for coordinated efforts that encompass prevention, early diagnosis, effective treatment, and patient education. The management of obesity faces several persistent challenges, including achieving sustainable weight loss and maintaining long-term glycemic control. While lifestyle interventions and pharmacotherapy often lead to initial improvements, weight regain remains a significant issue, undermining long-term success. In this context, metabolic bariatric surgery (MBS), including procedures such as Roux-en-Y gastric bypass (RYGB) and vertical sleeve gastrectomy (VSG), has emerged as one of the most effective interventions for significant weight loss. Its metabolic benefits extend beyond weight reduction, directly improving insulin sensitivity and glycemic control. Therefore, integrating metabolic surgery into treatment guidelines and expanding access to eligible patients are critical steps toward addressing the limitations of conventional approaches. CGM is now emerging as a more precise tool for assessing glucose patterns after metabolic surgery. However, available data on CGM outcomes in patients receiving MBS remain limited, highlighting the need for further research. CGM holds significant potential for improving the assessment and management of obese patients with T2D undergoing metabolic surgery. Unlike traditional measures such as HbA1c, CGM provides real-time, continuous data on glucose levels, offering a detailed picture of glucose variability, postprandial spikes, and hypoglycemic events. This granular insight enables better tracking of short-term metabolic changes immediately after surgery and facilitates early detection of glycemic patterns that may be influenced by the changes in GI tract and dietary patterns after surgery. In addition, post-bariatric hypoglycemia (PBH) is an increasingly recognized complication that can arise following metabolic and bariatric procedures. CGM will enable a better understanding of hypoglycemia unawareness, where patients fail to perceive symptoms despite critically low glucose levels. CGM may have the potential to revolutionize the management of PBH. Despite its promise, research on CGM among patients receiving metabolic surgery remains limited. Several studies have demonstrated the advantages of CGM in identifying post-bariatric hypoglycemia. However, limitations of prior studies include their cross-sectional or retrospective design, small sample sizes, a lack of pre-surgery CGM data, and a short GDM monitoring period (most <10 days) with only one GDM measurement taken after surgery. As a result, there is a growing need for more robust studies, such as RCTs, to validate the effectiveness of this approach and optimize its integration into clinical practice.
Objectives Aim 1: To identify the glycemic patterns by using CGM in patients with severe obesity receiving bariatric surgeries before and after the procedures. Hypothesis: CGM will reveal distinct glycemic patterns in obese patients undergoing metabolic surgery, with significant improvements in mean glucose control but not glycemic variability compared to baseline measures.
Aim 2: To investigate if the metrics that are derived from CGM data before and after the surgery can predict post bariatric hypoglycemia. Hypothesis: Metrics derived from CGM data, such as time in range, glycemic variability, and mean glucose levels, can reliably predict the likelihood of post bariatric hypoglycemia, with specific thresholds or patterns serving as robust predictors of long-term glycemic control.
Aim 3: To investigate the effect of CGM use on the prevention of post bariatric hypoglycemia, as well as the influence of dietary content, formulation, and patterns on glycemic responses. Hypothesis: Dietary content, formulation, and patterns significantly influence glycemic responses in patients with obesity, with higher fiber and protein intake, balanced macronutrient formulation, and consistent meal patterns associated with improved glycemic control and reduced risk of post bariatric hypoglycemia as measured by CGM after the surgeries.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CGM group | Experimental |
| |
| SMBG group | No Intervention |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Abbot Freestyle Libre CGM | Device | Participants assigned to the CGM group will receive the Libre 2+ systems (Abbott Diabetes Care, Alameda, CA) upon randomization. This will include comprehensive training provided by a qualified healthcare professional. The training will cover detailed instructions on sensor placement, how to download and use the associated smartphone application, and guidance on interpreting the glucose data effectively. To ensure continuous and accurate monitoring, the CGM sensor will be routinely replaced every 14 days following randomization. Additionally, in the event of sensor detachment or loss, immediate replacement will be arranged to maintain uninterrupted glucose tracking. Regular sessions are conducted to analyze glucose trends, refine management strategies, and provide additional support or education on device usage. |
| Measure | Description | Time Frame |
|---|---|---|
| Differences in coefficient of variance (CV) evaluated by CGM | Differences in coefficient of variance (CV) evaluated by CGM | 9 months |
| Measure | Description | Time Frame |
|---|---|---|
| Differences in HbA1c | 9 months | |
| Total number of hypoglycemia events | 9 months |
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Inclusion criteria: (1) age 20 to 60 years; (2) body mass index (BMI) ≥35 kg/m2
Exclusion Criteria:
(1) age <20 or >60 years; (2) confirmed type 1 diabetes; (3) pregnancy or breastfeeding; (4) history of hypersensitivity to any of the components of the subcutaneous infusions; (5) without access at home to a telephone or other factor likely to interfere with ability to participate reliably in the study; (6) history of any medical, psychological or other condition, or use of any medications, including over-the-counter products, which, in the opinion of the investigators, would either interfere with the study or potentially cause harm to the volunteer; (7) patients on insulin therapy before surgery; and (8) patients receiving revisional surgery.
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yun Shen, MD | Contact | +1 2253486652 | yun.shen@pbrc.edu |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Pennington Biomedical Research Center | Baton Rouge | Louisiana | 70808 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31986081 | Background | Hanipah ZN, Schauer PR. Bariatric Surgery as a Long-Term Treatment for Type 2 Diabetes/Metabolic Syndrome. Annu Rev Med. 2020 Jan 27;71:1-15. doi: 10.1146/annurev-med-053117-123246. | |
| 36493795 | Background | Battelino T, Alexander CM, Amiel SA, Arreaza-Rubin G, Beck RW, Bergenstal RM, Buckingham BA, Carroll J, Ceriello A, Chow E, Choudhary P, Close K, Danne T, Dutta S, Gabbay R, Garg S, Heverly J, Hirsch IB, Kader T, Kenney J, Kovatchev B, Laffel L, Maahs D, Mathieu C, Mauricio D, Nimri R, Nishimura R, Scharf M, Del Prato S, Renard E, Rosenstock J, Saboo B, Ueki K, Umpierrez GE, Weinzimer SA, Phillip M. Continuous glucose monitoring and metrics for clinical trials: an international consensus statement. Lancet Diabetes Endocrinol. 2023 Jan;11(1):42-57. doi: 10.1016/S2213-8587(22)00319-9. Epub 2022 Dec 6. |
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Specific IPD to be shared:
The following individual participant data will be shared upon reasonable request and approval:
Demographic Information: Age, sex, race/ethnicity, BMI.
Clinical Data: Baseline and follow-up clinical parameters, including diabetes diagnosis, diabetes duration, HbA1c levels, blood glucose measures, medication use, and relevant comorbidities.
Surgical Information: Type of metabolic surgery performed, date of surgery, and perioperative outcomes.
Continuous Glucose Monitoring (CGM) Data: Raw and analyzed CGM data including glucose variability, time in range, episodes of hypoglycemia, and hyperglycemia.
Outcomes Data: Weight loss, diabetes remission status, insulin sensitivity measures, and occurrence of post-bariatric hypoglycemia (PBH).
Safety Data: Adverse events related to metabolic surgery or CGM device use
IPD will be available following the publication of the primary study results. Data will be available for up to 5 years post-publication.
Access to IPD requires a formal, scientifically valid request detailing the intended analyses and ethical justification. Requests will be reviewed by the original research team to ensure compliance with ethical standards and data protection regulations.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Mar 11, 2025 | Mar 11, 2026 | Prot_SAP_001.pdf |
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| ID | Term |
|---|---|
| D009765 | Obesity |
| D009767 | Obesity, Morbid |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
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| 22449319 | Background | Schauer PR, Kashyap SR, Wolski K, Brethauer SA, Kirwan JP, Pothier CE, Thomas S, Abood B, Nissen SE, Bhatt DL. Bariatric surgery versus intensive medical therapy in obese patients with diabetes. N Engl J Med. 2012 Apr 26;366(17):1567-76. doi: 10.1056/NEJMoa1200225. Epub 2012 Mar 26. |
| 39645377 | Background | GBD 2021 US Burden of Disease and Forecasting Collaborators. Burden of disease scenarios by state in the USA, 2022-50: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet. 2024 Dec 7;404(10469):2341-2370. doi: 10.1016/S0140-6736(24)02246-3. |
| D001835 |
| Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |