- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05121844
Use of Continuous Glucose Monitoring in Non-Diabetic Population to Compliment Signos Mobile Health Platform
May 16, 2023 updated by: Stephanie Kim, M.D., MPH, Signos Inc
Use of Continuous Glucose Monitoring in Non-Diabetic Population to Compliment Signos Mobile Health Platform: Comprehensive Weight Optimization Program and Customized Lifestyle Modifications
Metabolic syndrome and resulting downstream health effects remains a growing health concern.
In published trials, the use of continuous glucose monitoring (CGM) assists behavioral changes efforts, leading to improved adherence and results from diet and exercise changes in individuals with obesity, pre-diabetes and diabetes.
Mobile health (mHealth) platforms provide satisfactory, easy-to-use tools that help participants in the pursuit of weight change goals.
We hypothesize that the use of CGM data and targeted coaching and nutrition education will assist with weight optimization goals in the general (non-diabetic) population using the Signos mHealth platform, with associated health benefits.
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Detailed Description
The scope of this study is to enroll existing and new Signos users in a volunteer study that utilizes a continuous glucose monitor (CGM) and mobile health application [Signos] to optimize general wellness and body weight and composition.
This is a no more than minimal risk study.
Study Type
Interventional
Enrollment (Anticipated)
50000
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Study Administration
- Phone Number: 6502634502
- Email: clinicaltrials@signos.com
Study Locations
-
-
California
-
Palo Alto, California, United States, 94306
- Recruiting
- Signos
-
Contact:
- Study Administrator
- Phone Number: 650-263-4502
- Email: clinicaltrials@signos.com
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
Yes
Study Population
Study population will include adults over the age of 18 who desire to lose weight or optimize body composition, who are generally healthy, who have a smartphone and ability to use it, and are willing to interact with a digital health application in pursuit of improved health.
Description
Inclusion Criteria:
- 18 years and above
- Own a smartphone and be willing to install the Signos App to use the app, receive messages or notifications, and input weight and other data.
- Willingness to complete questionaries or other surveys
- Able to speak and read English
Exclusion Criteria:
- Medical diagnosis of Type 1 Diabetes
- Medical diagnosis of Type 2 Diabetes
- Current medical diagnosis of an eating disorder (anorexia or bulimia) or previously struggled with disordered eating behaviors with current BMI less than 24
- Medical conditions (e.g., such as seizure disorder) requiring a specific medical diet.
- Inborn errors of metabolism such as phenylketonuria (PKU), glycogen storage disease, fructose intolerance, Maple Sugar Urine Disease (MSUD).
- Chronic or severe disease (e.g, chronic obstructive pulmonary disease [COPD], coronary artery disease, cerebrovascular accident [CVA], or cardiac arrhythmia) that would preclude a subject from safely participating in dietary recommendations and/or physical activity
- History of Gastric bypass or other bariatric surgery
- History of 10 or more soft tissue skin infections (such as cellulitis or abscesses)
- Intolerable skin reaction from adhesive
- Currently taking any of the following medications: Hydroxyurea, insulin, sulfonylureas, or medications prescribed specifically for the treatment of diagnosed diabetes
- Vulnerable populations such as minors, prisoners, or pregnant women will not be enrolled in this study. Women who become pregnant will be excluded at that time.
- Inability or unwillingness of subject to give informed consent
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Signos digital health app and CGM
For all consented participants, the Signos app will use CGM data to provide recommendations customized to users for promoting general health and wellness.
|
Continuous glucose monitoring automatically tracks blood glucose levels, also called blood sugar, throughout the day and night.
You can see your glucose level anytime at a glance.
You can also review how your glucose changes over a few hours or days to see trends.
Seeing glucose levels in real time can help you make more informed decisions throughout the day about how to balance your food and physical activity.
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Average fasting glucose
Time Frame: During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
Daily fasting glucose, averaged periodically
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During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
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Change in weight
Time Frame: During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
Change in number of pounds
|
During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Body composition
Time Frame: During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
User input data including percentage of body fat or other measurements of body composition
|
During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
Time in range
Time Frame: During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
percentage of time spent "in range" glucose level less than 140 or as determined by other parameters
|
During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Guyenet SJ, Schwartz MW. Clinical review: Regulation of food intake, energy balance, and body fat mass: implications for the pathogenesis and treatment of obesity. J Clin Endocrinol Metab. 2012 Mar;97(3):745-55. doi: 10.1210/jc.2011-2525. Epub 2012 Jan 11.
- Yoo HJ, An HG, Park SY, Ryu OH, Kim HY, Seo JA, Hong EG, Shin DH, Kim YH, Kim SG, Choi KM, Park IB, Yu JM, Baik SH. Use of a real time continuous glucose monitoring system as a motivational device for poorly controlled type 2 diabetes. Diabetes Res Clin Pract. 2008 Oct;82(1):73-9. doi: 10.1016/j.diabres.2008.06.015. Epub 2008 Aug 12.
- Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001.
- Monnier L, Mas E, Ginet C, Michel F, Villon L, Cristol JP, Colette C. Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. JAMA. 2006 Apr 12;295(14):1681-7. doi: 10.1001/jama.295.14.1681.
- Allen NA, Fain JA, Braun B, Chipkin SR. Continuous glucose monitoring counseling improves physical activity behaviors of individuals with type 2 diabetes: A randomized clinical trial. Diabetes Res Clin Pract. 2008 Jun;80(3):371-9. doi: 10.1016/j.diabres.2008.01.006. Epub 2008 Mar 4.
- Cox DJ, Taylor AG, Moncrief M, Diamond A, Yancy WS Jr, Hegde S, McCall AL. Continuous Glucose Monitoring in the Self-management of Type 2 Diabetes: A Paradigm Shift. Diabetes Care. 2016 May;39(5):e71-3. doi: 10.2337/dc15-2836. Epub 2016 Mar 17. No abstract available.
- Di Flaviani A, Picconi F, Di Stefano P, Giordani I, Malandrucco I, Maggio P, Palazzo P, Sgreccia F, Peraldo C, Farina F, Frajese G, Frontoni S. Impact of glycemic and blood pressure variability on surrogate measures of cardiovascular outcomes in type 2 diabetic patients. Diabetes Care. 2011 Jul;34(7):1605-9. doi: 10.2337/dc11-0034. Epub 2011 May 24.
- Turk MW, Elci OU, Wang J, Sereika SM, Ewing LJ, Acharya SD, Glanz K, Burke LE. Self-monitoring as a mediator of weight loss in the SMART randomized clinical trial. Int J Behav Med. 2013 Dec;20(4):556-61. doi: 10.1007/s12529-012-9259-9.
- Hall H, Perelman D, Breschi A, Limcaoco P, Kellogg R, McLaughlin T, Snyder M. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 2018 Jul 24;16(7):e2005143. doi: 10.1371/journal.pbio.2005143. eCollection 2018 Jul.
- Brynes AE, Adamson J, Dornhorst A, Frost GS. The beneficial effect of a diet with low glycaemic index on 24 h glucose profiles in healthy young people as assessed by continuous glucose monitoring. Br J Nutr. 2005 Feb;93(2):179-82. doi: 10.1079/bjn20041318.
- Freckmann G, Hagenlocher S, Baumstark A, Jendrike N, Gillen RC, Rossner K, Haug C. Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals. J Diabetes Sci Technol. 2007 Sep;1(5):695-703. doi: 10.1177/193229680700100513.
- Liao Y, Schembre S. Acceptability of Continuous Glucose Monitoring in Free-Living Healthy Individuals: Implications for the Use of Wearable Biosensors in Diet and Physical Activity Research. JMIR Mhealth Uhealth. 2018 Oct 24;6(10):e11181. doi: 10.2196/11181.
- Bailey KJ, Little JP, Jung ME. Self-Monitoring Using Continuous Glucose Monitors with Real-Time Feedback Improves Exercise Adherence in Individuals with Impaired Blood Glucose: A Pilot Study. Diabetes Technol Ther. 2016 Mar;18(3):185-93. doi: 10.1089/dia.2015.0285. Epub 2016 Feb 17.
- Adams OP. The impact of brief high-intensity exercise on blood glucose levels. Diabetes Metab Syndr Obes. 2013;6:113-22. doi: 10.2147/DMSO.S29222. Epub 2013 Feb 27.
- Baron AD. Impaired glucose tolerance as a disease. Am J Cardiol. 2001 Sep 20;88(6A):16H-9H. doi: 10.1016/s0002-9149(01)01832-x.
- Brown A, McArdle P, Taplin J, Unwin D, Unwin J, Deakin T, Wheatley S, Murdoch C, Malhotra A, Mellor D. Dietary strategies for remission of type 2 diabetes: A narrative review. J Hum Nutr Diet. 2022 Feb;35(1):165-178. doi: 10.1111/jhn.12938. Epub 2021 Sep 1.
- Chin SO, Keum C, Woo J, Park J, Choi HJ, Woo JT, Rhee SY. Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity. Sci Rep. 2016 Nov 7;6:34563. doi: 10.1038/srep34563.
- Ebbeling CB, Knapp A, Johnson A, Wong JMW, Greco KF, Ma C, Mora S, Ludwig DS. Effects of a low-carbohydrate diet on insulin-resistant dyslipoproteinemia-a randomized controlled feeding trial. Am J Clin Nutr. 2022 Jan 11;115(1):154-162. doi: 10.1093/ajcn/nqab287. Erratum In: Am J Clin Nutr. 2022 Jan 11;115(1):310.
- Ehrhardt N, Al Zaghal E. Behavior Modification in Prediabetes and Diabetes: Potential Use of Real-Time Continuous Glucose Monitoring. J Diabetes Sci Technol. 2019 Mar;13(2):271-275. doi: 10.1177/1932296818790994. Epub 2018 Aug 1.
- The Lancet Diabetes Endocrinology. Metabolic health: a priority for the post-pandemic era. Lancet Diabetes Endocrinol. 2021 Apr;9(4):189. doi: 10.1016/S2213-8587(21)00058-9. Epub 2021 Mar 4. No abstract available.
- Galderisi A, Giannini C, Weiss R, Kim G, Shabanova V, Santoro N, Pierpont B, Savoye M, Caprio S. Trajectories of changes in glucose tolerance in a multiethnic cohort of obese youths: an observational prospective analysis. Lancet Child Adolesc Health. 2018 Oct;2(10):726-735. doi: 10.1016/S2352-4642(18)30235-9. Epub 2018 Aug 24.
- Gonzalez-Rodriguez M, Pazos-Couselo M, Garcia-Lopez JM, Rodriguez-Segade S, Rodriguez-Garcia J, Tunez-Bastida C, Gude F. Postprandial glycemic response in a non-diabetic adult population: the effect of nutrients is different between men and women. Nutr Metab (Lond). 2019 Jul 17;16:46. doi: 10.1186/s12986-019-0368-1. eCollection 2019.
- Hamley S, Kloosterman D, Duthie T, Dalla Man C, Visentin R, Mason SA, Ang T, Selathurai A, Kaur G, Morales-Scholz MG, Howlett KF, Kowalski GM, Shaw CS, Bruce CR. Mechanisms of hyperinsulinaemia in apparently healthy non-obese young adults: role of insulin secretion, clearance and action and associations with plasma amino acids. Diabetologia. 2019 Dec;62(12):2310-2324. doi: 10.1007/s00125-019-04990-y. Epub 2019 Sep 6.
- Hyde PN, Sapper TN, Crabtree CD, LaFountain RA, Bowling ML, Buga A, Fell B, McSwiney FT, Dickerson RM, Miller VJ, Scandling D, Simonetti OP, Phinney SD, Kraemer WJ, King SA, Krauss RM, Volek JS. Dietary carbohydrate restriction improves metabolic syndrome independent of weight loss. JCI Insight. 2019 Jun 20;4(12):e128308. doi: 10.1172/jci.insight.128308. eCollection 2019 Jun 20.
- Jagannathan R, Sevick MA, Fink D, Dankner R, Chetrit A, Roth J, Buysschaert M, Bergman M. The 1-hour post-load glucose level is more effective than HbA1c for screening dysglycemia. Acta Diabetol. 2016 Aug;53(4):543-50. doi: 10.1007/s00592-015-0829-6. Epub 2016 Jan 21.
- Jakubowicz D, Barnea M, Wainstein J, Froy O. High caloric intake at breakfast vs. dinner differentially influences weight loss of overweight and obese women. Obesity (Silver Spring). 2013 Dec;21(12):2504-12. doi: 10.1002/oby.20460. Epub 2013 Jul 2.
- Ludwig DS, Aronne LJ, Astrup A, de Cabo R, Cantley LC, Friedman MI, Heymsfield SB, Johnson JD, King JC, Krauss RM, Lieberman DE, Taubes G, Volek JS, Westman EC, Willett WC, Yancy WS, Ebbeling CB. The carbohydrate-insulin model: a physiological perspective on the obesity pandemic. Am J Clin Nutr. 2021 Dec 1;114(6):1873-1885. doi: 10.1093/ajcn/nqab270.
- Neri D, Martinez-Steele E, Monteiro CA, Levy RB. Consumption of ultra-processed foods and its association with added sugar content in the diets of US children, NHANES 2009-2014. Pediatr Obes. 2019 Dec;14(12):e12563. doi: 10.1111/ijpo.12563. Epub 2019 Jul 30.
- Page KA, Seo D, Belfort-DeAguiar R, Lacadie C, Dzuira J, Naik S, Amarnath S, Constable RT, Sherwin RS, Sinha R. Circulating glucose levels modulate neural control of desire for high-calorie foods in humans. J Clin Invest. 2011 Oct;121(10):4161-9. doi: 10.1172/JCI57873. Epub 2011 Sep 19.
- Painter SL, Lu W, Schneider J, James R, Shah B. Drivers of weight loss in a CDC-recognized digital diabetes prevention program. BMJ Open Diabetes Res Care. 2020 Jul;8(1):e001132. doi: 10.1136/bmjdrc-2019-001132.
- Suh S, Kim JH. Glycemic Variability: How Do We Measure It and Why Is It Important? Diabetes Metab J. 2015 Aug;39(4):273-82. doi: 10.4093/dmj.2015.39.4.273.
- Wang Y, Xue H, Huang Y, Huang L, Zhang D. A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management. Adv Nutr. 2017 May 15;8(3):449-462. doi: 10.3945/an.116.014100. Print 2017 May.
- Wyatt P, Berry SE, Finlayson G, O'Driscoll R, Hadjigeorgiou G, Drew DA, Khatib HA, Nguyen LH, Linenberg I, Chan AT, Spector TD, Franks PW, Wolf J, Blundell J, Valdes AM. Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nat Metab. 2021 Apr;3(4):523-529. doi: 10.1038/s42255-021-00383-x. Epub 2021 Apr 12. Erratum In: Nat Metab. 2021 Jul;3(7):1032.
- Yang X, Zhu Y, Luo S, Chen L, Yan J, Zeng L, Xu W, Weng J. [Glucose characteristics in normal glucose tolerance subjects with metabolic syndrome]. Zhonghua Yi Xue Za Zhi. 2015 Apr 14;95(14):1070-3. Chinese.
- Azami Y, Funakoshi M, Matsumoto H, Ikota A, Ito K, Okimoto H, Shimizu N, Tsujimura F, Fukuda H, Miyagi C, Osawa S, Osawa R, Miura J. Long working hours and skipping breakfast concomitant with late evening meals are associated with suboptimal glycemic control among young male Japanese patients with type 2 diabetes. J Diabetes Investig. 2019 Jan;10(1):73-83. doi: 10.1111/jdi.12852. Epub 2018 May 30.
- Hatamoto Y, Goya R, Yamada Y, Yoshimura E, Nishimura S, Higaki Y, Tanaka H. Effect of exercise timing on elevated postprandial glucose levels. J Appl Physiol (1985). 2017 Aug 1;123(2):278-284. doi: 10.1152/japplphysiol.00608.2016. Epub 2017 Apr 13.
- Jakubowicz D, Wainstein J, Ahren B, Landau Z, Bar-Dayan Y, Froy O. Fasting until noon triggers increased postprandial hyperglycemia and impaired insulin response after lunch and dinner in individuals with type 2 diabetes: a randomized clinical trial. Diabetes Care. 2015 Oct;38(10):1820-6. doi: 10.2337/dc15-0761. Epub 2015 Jul 28.
- Juanola-Falgarona M, Salas-Salvado J, Ibarrola-Jurado N, Rabassa-Soler A, Diaz-Lopez A, Guasch-Ferre M, Hernandez-Alonso P, Balanza R, Bullo M. Effect of the glycemic index of the diet on weight loss, modulation of satiety, inflammation, and other metabolic risk factors: a randomized controlled trial. Am J Clin Nutr. 2014 Jul;100(1):27-35. doi: 10.3945/ajcn.113.081216. Epub 2014 Apr 30.
- Kolb H, Stumvoll M, Kramer W, Kempf K, Martin S. Insulin translates unfavourable lifestyle into obesity. BMC Med. 2018 Dec 13;16(1):232. doi: 10.1186/s12916-018-1225-1.
- Kong LC, Wuillemin PH, Bastard JP, Sokolovska N, Gougis S, Fellahi S, Darakhshan F, Bonnefont-Rousselot D, Bittar R, Dore J, Zucker JD, Clement K, Rizkalla S. Insulin resistance and inflammation predict kinetic body weight changes in response to dietary weight loss and maintenance in overweight and obese subjects by using a Bayesian network approach. Am J Clin Nutr. 2013 Dec;98(6):1385-94. doi: 10.3945/ajcn.113.058099. Epub 2013 Oct 30.
- Rynders CA, Blanc S, DeJong N, Bessesen DH, Bergouignan A. Sedentary behaviour is a key determinant of metabolic inflexibility. J Physiol. 2018 Apr 15;596(8):1319-1330. doi: 10.1113/JP273282. Epub 2017 Jul 4.
- Lin HJ, Lee BC, Ho YL, Lin YH, Chen CY, Hsu HC, Lin MS, Chien KL, Chen MF. Postprandial glucose improves the risk prediction of cardiovascular death beyond the metabolic syndrome in the nondiabetic population. Diabetes Care. 2009 Sep;32(9):1721-6. doi: 10.2337/dc08-2337. Epub 2009 Jun 5.
- Shukla AP, Dickison M, Coughlin N, Karan A, Mauer E, Truong W, Casper A, Emiliano AB, Kumar RB, Saunders KH, Igel LI, Aronne LJ. The impact of food order on postprandial glycaemic excursions in prediabetes. Diabetes Obes Metab. 2019 Feb;21(2):377-381. doi: 10.1111/dom.13503. Epub 2018 Sep 10.
- Soliman A, DeSanctis V, Yassin M, Elalaily R, Eldarsy NE. Continuous glucose monitoring system and new era of early diagnosis of diabetes in high risk groups. Indian J Endocrinol Metab. 2014 May;18(3):274-82. doi: 10.4103/2230-8210.131130.
- Velasquez-Mieyer PA, Cowan PA, Arheart KL, Buffington CK, Spencer KA, Connelly BE, Cowan GW, Lustig RH. Suppression of insulin secretion is associated with weight loss and altered macronutrient intake and preference in a subset of obese adults. Int J Obes Relat Metab Disord. 2003 Feb;27(2):219-26. doi: 10.1038/sj.ijo.802227.
- Haxhi J, Scotto di Palumbo A, Sacchetti M. Exercising for metabolic control: is timing important? Ann Nutr Metab. 2013;62(1):14-25. doi: 10.1159/000343788. Epub 2012 Nov 27.
- Mendes-Soares H, Raveh-Sadka T, Azulay S, Edens K, Ben-Shlomo Y, Cohen Y, Ofek T, Bachrach D, Stevens J, Colibaseanu D, Segal L, Kashyap P, Nelson H. Assessment of a Personalized Approach to Predicting Postprandial Glycemic Responses to Food Among Individuals Without Diabetes. JAMA Netw Open. 2019 Feb 1;2(2):e188102. doi: 10.1001/jamanetworkopen.2018.8102.
- Penckofer S, Quinn L, Byrn M, Ferrans C, Miller M, Strange P. Does glycemic variability impact mood and quality of life? Diabetes Technol Ther. 2012 Apr;14(4):303-10. doi: 10.1089/dia.2011.0191. Epub 2012 Feb 10.
- Steinberg DM, Bennett GG, Askew S, Tate DF. Weighing every day matters: daily weighing improves weight loss and adoption of weight control behaviors. J Acad Nutr Diet. 2015 Apr;115(4):511-8. doi: 10.1016/j.jand.2014.12.011. Epub 2015 Feb 12.
- Chandler-Laney PC, Morrison SA, Goree LL, Ellis AC, Casazza K, Desmond R, Gower BA. Return of hunger following a relatively high carbohydrate breakfast is associated with earlier recorded glucose peak and nadir. Appetite. 2014 Sep;80:236-41. doi: 10.1016/j.appet.2014.04.031. Epub 2014 May 10.
- Kim J, Lam W, Wang Q, Parikh L, Elshafie A, Sanchez-Rangel E, Schmidt C, Li F, Hwang J, Belfort-DeAguiar R. In a Free-Living Setting, Obesity Is Associated With Greater Food Intake in Response to a Similar Premeal Glucose Nadir. J Clin Endocrinol Metab. 2019 Sep 1;104(9):3911-3919. doi: 10.1210/jc.2019-00240.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
November 2, 2021
Primary Completion (Anticipated)
November 1, 2026
Study Completion (Anticipated)
November 1, 2027
Study Registration Dates
First Submitted
November 4, 2021
First Submitted That Met QC Criteria
November 4, 2021
First Posted (Actual)
November 16, 2021
Study Record Updates
Last Update Posted (Actual)
May 18, 2023
Last Update Submitted That Met QC Criteria
May 16, 2023
Last Verified
May 1, 2023
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Metabolic Diseases
- Endocrine System Diseases
- Diabetes Mellitus
- Overnutrition
- Nutrition Disorders
- Body Weight
- Insulin Resistance
- Hyperinsulinism
- Body Weight Changes
- Hyperglycemia
- Obesity
- Metabolic Syndrome
- Weight Loss
- Prediabetic State
- Glucose Intolerance
- Obesity, Abdominal
- Glucose Metabolism Disorders
Other Study ID Numbers
- 195165
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
Yes
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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