ClinicalTrials.gg
Not yet recruitingNCT07832474RETURNUpdated Sep 22, 2026

Returning to Normoglycemia With Targeted Use of Real-time CGM Data and Nutrition-focused Lifestyle Changes

An interventional study of CGM-guided care in Prediabetes, sponsored by HealthPartners Institute. Not yet recruiting at 1 site in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-22.

Sponsored by HealthPartners Institute · Not applicable, Interventional, and Health services research

Phase
Not applicable
Study type
Interventional
Enrollment
330
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study summary

The purpose of the ReTURN study is to understand how glycemia, specifically percent of time above 140 mg/dL (TA140), changes over time in people who are randomized to receive either continuous glucose monitoring (CGM)-guided care or usual care (UC) for 12 months. CGM-guided care includes daily use of a CGM system along with education and support. The hypothesis is that change in CGM-derived metrics from Baseline to Month 12 will show a larger improvement (reduction) in the CGM-Guided Lifestyle Change arm than the UC arm.

Read the detailed description

The intention of the CGM-Guided Lifestyle Care intervention is to help CGM users make optimal use of their real-time and retrospective CGM data for the purpose of identifying and making behavior changes that reduce TA140. The CGM device will be positioned as a tool that guides its user to develop and maintain a personalized approach to eating, movement, and other behaviors such as sleep and stress management, which can all help bring glucose into a "healthy" range.

The proposed CGM-based intervention aims to explore an alternative approach to caring for people with prediabetes using a flexible, predominantly virtual approach. The emphasis on choosing healthy lifestyle behaviors, such as high-quality eating patterns and engaging in physical activity is similar to existing DPPs, while the mix of synchronous and asynchronous virtual care education, along with the personalized, actionable glycemic data reduces some of the known barriers to participation in current Diabetes Prevention Programs (DPPs) (e.g. rigid schedules, time). The emphasis on encouraging participants to use their own glucose data to see in real-time what healthy lifestyle choices work best for them is also a key differentiator from past approaches, which has the potential to lead to more sustainable behavior changes.

02

Conditions studied

  • Prediabetes

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Keywords

  • Continuous Glucose Monitoring
  • Glucose Metrics
  • Nutrition
  • Lifestyle
03

In context

Prediabetic State

918 studies on the registry are indexed under Prediabetic State; 232 are open to participants now.

This study's planned enrollment of 330 is above the median of 62 across 762 interventional studies indexed under Prediabetic State.

Browse Prediabetic State studies →

Lead sponsor

HealthPartners Institute is the lead sponsor of 167 studies on the registry; 20 are open to participants now.

Of its 17 completed or terminated interventional studies of FDA-regulated products, 16 (94%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  1. Provision of signed and dated form
  2. > 18 years of age
  3. Documented diagnosis of prediabetes based on the most recent A1c of 5.7% to 6.4% (inclusive) collected within the last 12 months; or with investigator approval based on a history of A1c 5.7% to 6.4% (inclusive)
  4. Point-of-care A1c between 5.7% and 6.4% (inclusive) at screening visit
  5. A minimum of 7 days of glucose data with documented % time above 140 mg/dL of > 15% on a study-provided blinded CGM during the baseline assessment period
  6. Ready and able to make lifestyle changes to prevent or delay the onset of T2D; this may include changes to food intake, physical activity, sleep, and stress (e.g. ready to: make dietary changes, willing to aim for > 150 mins of physical activity/week, etc.)
  7. Has a personal smartphone that is compatible with all study-required devices and apps (e.g. FreeStyle Libre family, Fitbit)
  8. Willing to download study-related apps and keep them updated and open on phone as required throughout the study (e.g. FreeStyle Libre family)
  9. Has regular access to Wi-Fi
  10. Willing and able to consistently view and use CGM data on a personal smartphone for up to 54 weeks
  11. Willing and able to continuously wear a study provided CGM sensor (back of the arm) and a study provided Fitbit activity tracker (band around the wrist) for up to 54 weeks
  12. Willing to attend in person and virtual study visits, willing to read MyChart messages, and willing to comply with all other study procedures and lifestyle considerations (Section 5.3, Lifestyle Considerations) for the duration of the study
  13. Speak and read in English

Exclusion criteria

Exclusion Criteria:

  1. Diagnosis of Type 1 diabetes or Type 2 diabetes (A1c >6.4%)
  2. Taking or actively planning to take anti-hyperglycemic medications (e.g. Metformin, SGLT2i, GLP-1 RA)
  3. Taking or actively planning to take prescription weight loss medications (e.g. Phentermine, Topiramate, Naltrexone, Orlistat)
  4. Taking or actively planning to take a GLP-1 RA for any reason
  5. Known allergy to medical grade adhesive or isopropyl alcohol used to disinfect skin
  6. Currently using or actively planning to use personal CGM, or have used personal CGM in last 30 days
  7. Started taking within the last 16 weeks or actively planning to take a (oral or injected), statin, thiazide diuretic, second-generation antipsychotic, or medications, as these agents may increase the risk of developing T2D
  8. Skin conditions that are not compatible with CGM wear
  9. Taking or planning to regularly take more than 500 mg of Vitamin C per day (due to potential for false glucose elevations)
  10. Planning pregnancy, pregnant, or lactating
  11. Actively participating in or planning to participate in a treatment program for prediabetes (e.g. a diabetes prevention program) or a clinical intervention study related to cardiometabolic health
  12. Unsuitable for participation due to any other cause, including but not limited to significant comorbidities, as determined by PI or MD oversight (e.g. examples for consideration, advanced cancer, unstable heart disease, active eating disorders, planned surgeries, cognitive impairments)
Terms in these criteria, in plain language(3)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

Corticosteroids (steroids)

Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.

Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.

HIV

The human immunodeficiency virus, which weakens the immune system.

Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.

05

Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
330 participants (estimated)

Study arms

  • Experimental
    CGM-Guided Lifestyle Care

    The CGM-guided care arm (the study intervention) includes three components 1) daily use of a real-time CGM system, 2) core CGM-guided lifestyle resources, and 3) personalized CGM-guided lifestyle education and support. The education and support is provided via one 60-minute in-person education and counseling session, six 30-minute virtual systematic CGM data review and lifestyle assessment sessions, and three asynchronous systematic CGM data review and lifestyle assessment messages sent via the electronic health record. The intervention content is provided by a registered dietitian nutritionist and focuses on using CGM data to help people optimize food choices, physical activity levels, sleep patterns, and stress management for improved prediabetes management.

    Behavioral: CGM-guided care

  • No intervention
    Usual Care (UC)

    Participants in the UC arm will receive generalized healthy lifestyle guidance and glycemic assessment (e.g. A1c, fasting glucose) at Baseline and at M12. Participants in the UC arm will also receive guidance for finding local diabetes prevention programs. The UC arm aligns with current practice for people with prediabetes.

Interventions

  • BehavioralCGM-guided care

    Participants in the CGM arm use CGM data paired with a theory-informed behavioral intervention to guide personalized nutrition and lifestyle changes. The intervention aims to help CGM users make optimal use of their real-time and retrospective CGM data for the purposes of identifying and making behavior changes that reduce TA140. Participants in the CGM arm will receive support through three main components: 1) daily use of a real-time CGM system, 2) core CGM-guided lifestyle resources, and 3) personalized CGM-guided lifestyle education and support. The intervention focuses on food choices, physical activity, sleep, and stress reduction.

06

What researchers measure

Primary outcomes

  1. Change in CGM-derived % TA140

    Time frame: Baseline to 12 months

07

Study locations

1 site
08

References and documents

Publications

  • Tabak AG, Herder C, Rathmann W, Brunner EJ, Kivimaki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012 Jun 16;379(9833):2279-90. doi: 10.1016/S0140-6736(12)60283-9. Epub 2012 Jun 9. PubMed 22683128 ↗
  • American Diabetes Association Professional Practice Committee for Diabetes*. 3. Prevention or Delay of Diabetes and Associated Comorbidities: Standards of Care in Diabetes-2026. Diabetes Care. 2026 Jan 1;49(Supplement_1):S50-S60. doi: 10.2337/dc26-S003. PubMed 41358891 ↗
  • Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002 Feb 7;346(6):393-403. doi: 10.1056/NEJMoa012512. PubMed 11832527 ↗
  • Knowler WC, Doherty L, Edelstein SL, Bennett PH, Dabelea D, Hoskin M, Kahn SE, Kalyani RR, Kim C, Pi-Sunyer FX, Raghavan S, Shah VO, Temprosa M, Venditti EM, Nathan DM; DPP/DPPOS Research Group. Long-term effects and effect heterogeneity of lifestyle and metformin interventions on type 2 diabetes incidence over 21 years in the US Diabetes Prevention Program randomised clinical trial. Lancet Diabetes Endocrinol. 2025 Jun;13(6):469-481. doi: 10.1016/S2213-8587(25)00022-1. Epub 2025 Apr 28. PubMed 40311647 ↗
  • Kent-Marvick J, Knysheva M, Gibson B, Simonsen SE. Why Do People Choose to Enroll or Not Enroll in the National Diabetes Prevention Program Lifestyle Change Program? A Mixed-Methods Analysis From a Sample of Adults With a Prediabetes Diagnosis. J Prim Care Community Health. 2024 Jan-Dec;15:21501319241282862. doi: 10.1177/21501319241282862. PubMed 39305089 ↗
  • Ackermann RT, O'Brien MJ. Evidence and Challenges for Translation and Population Impact of the Diabetes Prevention Program. Curr Diab Rep. 2020 Feb 20;20(3):9. doi: 10.1007/s11892-020-1293-4. PubMed 32080770 ↗
  • Polonsky WH, Clark TL, Soriano EC, Edgington A, Bennett CM, Fox AE, Grace T. How CGM Use in Adults With Type 2 Diabetes Leads to Glycemic Benefits: The Role of Medication and Behaviour Change. Endocrinol Diabetes Metab. 2026 May;9(3):e70236. doi: 10.1002/edm2.70236. PubMed 42108772 ↗
  • Golovaty I, Ritchie ND, Tuomilehto J, Mohan V, Ali MK, Gregg EW, Bergman M, Moin T. Two decades of diabetes prevention efforts: A call to innovate and revitalize our approach to lifestyle change. Diabetes Res Clin Pract. 2023 Apr;198:110195. doi: 10.1016/j.diabres.2022.110195. Epub 2022 Dec 5. PubMed 36470316 ↗
  • Ritchie ND, Baucom KJW, Sauder KA. Current Perspectives on the Impact of the National Diabetes Prevention Program: Building on Successes and Overcoming Challenges. Diabetes Metab Syndr Obes. 2020 Aug 19;13:2949-2957. doi: 10.2147/DMSO.S218334. eCollection 2020. PubMed 32903871 ↗
  • Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011 Apr 23;6:42. doi: 10.1186/1748-5908-6-42. PubMed 21513547 ↗
  • Bannuru RR, Bellini NJ, Bergenstal RM, Beverly EA, Christofides EA, Cox D, Ehrhardt N, Fazioli K, Hess Fischl A, Kerr D, Kirksey OW, Lau KHK, Martens TW, Noble M, Ranade PK, Shah VN, Willis HJ, ElSayed NA. Continuous Glucose Monitoring to Guide Lifestyle Choices With a Focus on Nutrition in the Management of Type 2 Diabetes: A Systematic Review and Meta-Analysis. J Diabetes Sci Technol. 2025 Oct 18:19322968251384318. doi: 10.1177/19322968251384318. Online ahead of print. PubMed 41109846 ↗
  • Fermin-Martinez CA, Bello-Chavolla OY, Paz-Cabrera CD, Ramirez-Garcia D, Perezalonso-Espinosa J, Fernandez-Chirino L, Vargas-Vazquez A, Diaz-Sanchez JP, Mendez-Labra PN, Nunez-Luna A, Basile-Alvarez MR, Sanchez-Castro P, Bragg F, Friedrichs LG, Aguilar-Ramirez D, Emberson JR, Berumen J, Kuri-Morales P, Tapia-Conyer R, Alegre-Diaz J, Seiglie JA, Antonio-Villa NE. Prediabetes and Risk of All-Cause and Cause-Specific Mortality: A Prospective Study of 114 062 Adults in Mexico City. J Clin Endocrinol Metab. 2025 Nov 18;110(12):3451-3460. doi: 10.1210/clinem/dgaf225. PubMed 40208106 ↗
  • Schlesinger S, Neuenschwander M, Barbaresko J, Lang A, Maalmi H, Rathmann W, Roden M, Herder C. Prediabetes and risk of mortality, diabetes-related complications and comorbidities: umbrella review of meta-analyses of prospective studies. Diabetologia. 2022 Feb;65(2):275-285. doi: 10.1007/s00125-021-05592-3. Epub 2021 Oct 31. PubMed 34718834 ↗
  • Echouffo-Tcheugui JB, Chakkalakal RJ, Ali MK. Is the Current Lifestyle Modification Approach to Diabetes Prevention in the U.S. a Success? Diabetes Care. 2025 Jun 1;48(6):863-870. doi: 10.2337/dci24-0040. PubMed 40267363 ↗
  • Rakoczi G, Nagy J, Jozaee S, Jozaee S, Szentes BL, Lee J, Rancz A, Hegyi P, Agocs G, Sipter E. Differences in Continuous Glucose Monitoring Metrics Between Prediabetes and Normoglycemia: A Systematic Review and Meta-Analysis. J Diabetes Sci Technol. 2026 Mar 3:19322968261426384. doi: 10.1177/19322968261426384. Online ahead of print. PubMed 41773692 ↗
  • Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, Hu ZX, Lin J, Xiao JZ, Cao HB, Liu PA, Jiang XG, Jiang YY, Wang JP, Zheng H, Zhang H, Bennett PH, Howard BV. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997 Apr;20(4):537-44. doi: 10.2337/diacare.20.4.537. PubMed 9096977 ↗
  • Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M; Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001 May 3;344(18):1343-50. doi: 10.1056/NEJM200105033441801. PubMed 11333990 ↗

Individual participant data

Plan to share: Yes — De-identified individual participant-level data may be requested after the completion of the primary endpoint analysis, and reasonable requests to provide data will be considered. Any identifiers linking to the participant will be excluded. De-identified data may be used for secondary research purposes and may be shared with researchers not affiliated with the institution conducting the research project when appropriate contractual agreements are in place. The study consent denotes that de-identified personal data may be used by researchers for secondary research purposes, presentations, or publications without additional permission from the study participant.

Supporting information: Study protocol

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 22, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07832474
Responsible party
Sponsor
First posted
Sep 22, 2026
Start date
Oct 1, 2026 (estimated)
Primary completion
Dec 2028 (estimated)
Completion
May 2029 (estimated)
Last update
Sep 22, 2026

Study contacts

Holly Willis, PhD, RDN, CDCES
Contact
Holly.J.Willis@Healthpartners.com
952-993-3219

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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