Use of Continuous Glucose Monitoring in Non-Diabetic Population to Compliment Signos Mobile Health Platform

Metabolic Syndrome Clinical Trial

Official title:

Use of Continuous Glucose Monitoring in Non-Diabetic Population to Compliment Signos Mobile Health Platform: Comprehensive Weight Optimization Program and Customized Lifestyle Modifications

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05121844
• Other study ID #: 195165
• Status: Recruiting
• Phase: N/A
• Start date: November 2, 2021
• Est. completion date: November 1, 2027

Study information

• Verified date: June 2024
• Source: Signos Inc
• Contact: Study Administration
• Phone: 6502634502
• Email: clinicaltrials[@]signos.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100000
• Est. completion date: November 1, 2027
• Est. primary completion date: November 1, 2026
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Central Obesity
• Glucose Intolerance
• Glucose Metabolism Disorders
• Metabolic Glucose Disorders
• Metabolic Syndrome
• Obesity, Abdominal
• Pre-diabetes
• Prediabetic State
• Weight Loss

Intervention

Device:
• Continuous Glucose Monitor Device
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.

Locations

Country	Name	City	State
United States	Signos	Palo Alto	California

Sponsors (1)

Lead Sponsor	Collaborator
Signos Inc

Country where clinical trial is conducted

United States, 

References & Publications (51)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 51 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Average fasting glucose	Daily fasting glucose, averaged periodically	During enrollment in the trial for a maximum of 5 years, including a 1 year follow up period, for a maximum of 6 years.
Primary	Change in weight	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	Body composition	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.
Secondary	Time in range	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.