Effect of Real-time Continuous Glucose Monitoring System in Overweight or Obese Adults With Prediabetes
Primary Purpose
Continuous Glucose Monitoring, Prediabetic State, Obesity
Status
Unknown status
Phase
Not Applicable
Locations
Korea, Republic of
Study Type
Interventional
Intervention
RT-CGM
SMBG
Sponsored by
About this trial
This is an interventional prevention trial for Continuous Glucose Monitoring
Eligibility Criteria
Inclusion Criteria:
- ≥ BMI 23 kg/m2
- impaired fasting glucose (fasting glucose 100 to 125 mg/dL) or impaired glucose tolerance (2-h plasma glucose during oral glucose tolerance test (OGTT) 140 - 199 mg/dl) or HbA1c 5.7% to 6.4%
Exclusion Criteria:
- type 1 diabetes or type 2 diabetes or undergoing treatment for diabetes
- clinical history including malignancy
- fast history of cardiovascular disease (e.g. myocardial infarction, stroke), surgery, and trauma which may affect blood glucose within last 6 months
- taking medication (e.g. glucocorticoid, antipsychotics, anticholinergic drug etc.) which affect blood glucose
- acute infection within last 1 month
- pregnancy
Sites / Locations
- Jeong Mi KimRecruiting
Arms of the Study
Arm 1
Arm 2
Arm Type
Active Comparator
Experimental
Arm Label
SMBG with lifestyle intervention
RT-CGM with lifestyle intervention
Arm Description
All participants receive a 12-week lifestyle intervention (diet and exercise). The control group was monitored self-monitoring blood glucose (SMBG) at least 2 times a day for initial 1-week.
All participants receive a 12-week lifestyle intervention (diet and exercise). The intervention group was monitored initial 1-week with a RT-CGM.
Outcomes
Primary Outcome Measures
HbA1C change
All participants receive lifestyle intervention at week 0, week 4, and week 8. The intervention group was monitored initial 1 weeks with a RT-CGM and th control group continued self-monitoring blood glucose (SMBG) at least 2 times a day for 1 week.
HbA1c at baseline (week 0) and end of intervention (week 12).
Weight (Kg) change
weight change (Kg) at baseline (week 0) and end of intervention (week 12)
Secondary Outcome Measures
lipid profile
both groups were assessed fasting lipid profile (total cholesterol, triglyceride and HDL-cholesterol) at baseline (week 0) and end of intervention (week 12)
Full Information
NCT ID
NCT04099550
First Posted
September 10, 2019
Last Updated
April 23, 2020
Sponsor
Pusan National University Hospital
1. Study Identification
Unique Protocol Identification Number
NCT04099550
Brief Title
Effect of Real-time Continuous Glucose Monitoring System in Overweight or Obese Adults With Prediabetes
Official Title
Effect of Real-time Continuous Glucose Monitoring System in Overweight or Obese Adults With Prediabetes
Study Type
Interventional
2. Study Status
Record Verification Date
April 2020
Overall Recruitment Status
Unknown status
Study Start Date
December 6, 2019 (Actual)
Primary Completion Date
December 2020 (Anticipated)
Study Completion Date
December 2021 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Pusan National University Hospital
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
5. Study Description
Brief Summary
In Korea, 5 million adults aged 30 years or older have diabetes. The development and expansion of Korea's economy and society, has led to dramatic chances in people's lifestyle and diet habits, and an increase in life expectancy. However, changes in lifestyle and diet habits related to the improvements of socioeconomic status may contribute to an increased diabetes burden in Korea. Therefore, it is important to prevent diabetes.
The purpose of this study was to evaluate the effects of real time-continuous glucose measurement (RT-CGM) system compared to only lifestyle modification group on blood glucose, lipid profile and diabetes prevention in prediabetic adults with overweight or obesity.
Detailed Description
Optimising patient adherence to prescribed lifestyle interventions to achieve improved blood glucose control remains a challenge. Combined use of real-time continuous glucose monitoring (RT-CGM) systems may promote improved glycaemic control.
Thirty adult with overweight or obesity and pre-diabetes are randomised to using either RT-CGM or self monitoring of blood glucose (SMBG) for 1 week with lifestyle intervention.
After 3 month, outcomes were glycemic control (HbA1c, fasting glucose), weight, and lipid profile assessed pre- and post-intervention.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Continuous Glucose Monitoring, Prediabetic State, Obesity
7. Study Design
Primary Purpose
Prevention
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
participants were randomised to undertake a 12-week lifestyle intervention with either RT-CGM or SMBG
Masking
None (Open Label)
Allocation
Randomized
Enrollment
30 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
SMBG with lifestyle intervention
Arm Type
Active Comparator
Arm Description
All participants receive a 12-week lifestyle intervention (diet and exercise). The control group was monitored self-monitoring blood glucose (SMBG) at least 2 times a day for initial 1-week.
Arm Title
RT-CGM with lifestyle intervention
Arm Type
Experimental
Arm Description
All participants receive a 12-week lifestyle intervention (diet and exercise). The intervention group was monitored initial 1-week with a RT-CGM.
Intervention Type
Device
Intervention Name(s)
RT-CGM
Intervention Description
The group was monitored blood glucose initial 1-week with a RT-CGM.
Intervention Type
Other
Intervention Name(s)
SMBG
Intervention Description
The group was monitored self-monitoring blood glucose (SMBG) at least 2 times a day for initial 1-week.
Primary Outcome Measure Information:
Title
HbA1C change
Description
All participants receive lifestyle intervention at week 0, week 4, and week 8. The intervention group was monitored initial 1 weeks with a RT-CGM and th control group continued self-monitoring blood glucose (SMBG) at least 2 times a day for 1 week.
HbA1c at baseline (week 0) and end of intervention (week 12).
Time Frame
Outcomes were assessed at baseline (week 0) and end of intervention (week 12)
Title
Weight (Kg) change
Description
weight change (Kg) at baseline (week 0) and end of intervention (week 12)
Time Frame
baseline (week 0) and end of intervention (week 12)
Secondary Outcome Measure Information:
Title
lipid profile
Description
both groups were assessed fasting lipid profile (total cholesterol, triglyceride and HDL-cholesterol) at baseline (week 0) and end of intervention (week 12)
Time Frame
baseline (week 0) and end of intervention (week 12)
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
≥ BMI 23 kg/m2
impaired fasting glucose (fasting glucose 100 to 125 mg/dL) or impaired glucose tolerance (2-h plasma glucose during oral glucose tolerance test (OGTT) 140 - 199 mg/dl) or HbA1c 5.7% to 6.4%
Exclusion Criteria:
type 1 diabetes or type 2 diabetes or undergoing treatment for diabetes
clinical history including malignancy
fast history of cardiovascular disease (e.g. myocardial infarction, stroke), surgery, and trauma which may affect blood glucose within last 6 months
taking medication (e.g. glucocorticoid, antipsychotics, anticholinergic drug etc.) which affect blood glucose
acute infection within last 1 month
pregnancy
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
JEONG MI KIM, M.D
Phone
82-10-9431-3733
Email
marse007@hanmail.net
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
JEONG MI KIM, M.D
Organizational Affiliation
Pusan National University Hospital
Official's Role
Principal Investigator
Facility Information:
Facility Name
Jeong Mi Kim
City
Busan
ZIP/Postal Code
49241
Country
Korea, Republic of
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Jeong M Kim, MD
Phone
82-10-9431-3733
Email
marse007@hanmail.net
12. IPD Sharing Statement
Plan to Share IPD
No
Citations:
PubMed Identifier
25917335
Citation
Gehlaut RR, Dogbey GY, Schwartz FL, Marling CR, Shubrook JH. Hypoglycemia in Type 2 Diabetes--More Common Than You Think: A Continuous Glucose Monitoring Study. J Diabetes Sci Technol. 2015 Apr 27;9(5):999-1005. doi: 10.1177/1932296815581052.
Results Reference
background
PubMed Identifier
18818254
Citation
Murphy HR, Rayman G, Lewis K, Kelly S, Johal B, Duffield K, Fowler D, Campbell PJ, Temple RC. Effectiveness of continuous glucose monitoring in pregnant women with diabetes: randomised clinical trial. BMJ. 2008 Sep 25;337:a1680. doi: 10.1136/bmj.a1680.
Results Reference
background
PubMed Identifier
15595336
Citation
Tanenberg R, Bode B, Lane W, Levetan C, Mestman J, Harmel AP, Tobian J, Gross T, Mastrototaro J. Use of the Continuous Glucose Monitoring System to guide therapy in patients with insulin-treated diabetes: a randomized controlled trial. Mayo Clin Proc. 2004 Dec;79(12):1521-6. doi: 10.4065/79.12.1521.
Results Reference
background
PubMed Identifier
11158450
Citation
Chase HP, Kim LM, Owen SL, MacKenzie TA, Klingensmith GJ, Murtfeldt R, Garg SK. Continuous subcutaneous glucose monitoring in children with type 1 diabetes. Pediatrics. 2001 Feb;107(2):222-6. doi: 10.1542/peds.107.2.222.
Results Reference
background
PubMed Identifier
11679447
Citation
Boland E, Monsod T, Delucia M, Brandt CA, Fernando S, Tamborlane WV. Limitations of conventional methods of self-monitoring of blood glucose: lessons learned from 3 days of continuous glucose sensing in pediatric patients with type 1 diabetes. Diabetes Care. 2001 Nov;24(11):1858-62. doi: 10.2337/diacare.24.11.1858.
Results Reference
background
PubMed Identifier
24876453
Citation
Salkind SJ, Huizenga R, Fonda SJ, Walker MS, Vigersky RA. Glycemic variability in nondiabetic morbidly obese persons: results of an observational study and review of the literature. J Diabetes Sci Technol. 2014 Sep;8(5):1042-7. doi: 10.1177/1932296814537039. Epub 2014 May 29.
Results Reference
background
PubMed Identifier
20357497
Citation
Dagogo-Jack S, Egbuonu N, Edeoga C. Principles and practice of nonpharmacological interventions to reduce cardiometabolic risk. Med Princ Pract. 2010;19(3):167-75. doi: 10.1159/000285280. Epub 2010 Mar 29.
Results Reference
background
PubMed Identifier
21389976
Citation
Hedayati SS, Elsayed EF, Reilly RF. Non-pharmacological aspects of blood pressure management: what are the data? Kidney Int. 2011 May;79(10):1061-70. doi: 10.1038/ki.2011.46. Epub 2011 Mar 9.
Results Reference
background
PubMed Identifier
23093136
Citation
Lindstrom J, Peltonen M, Eriksson JG, Ilanne-Parikka P, Aunola S, Keinanen-Kiukaanniemi S, Uusitupa M, Tuomilehto J; Finnish Diabetes Prevention Study (DPS). Improved lifestyle and decreased diabetes risk over 13 years: long-term follow-up of the randomised Finnish Diabetes Prevention Study (DPS). Diabetologia. 2013 Feb;56(2):284-93. doi: 10.1007/s00125-012-2752-5. Epub 2012 Oct 24.
Results Reference
background
PubMed Identifier
19150019
Citation
Marquez-Celedonio FG, Texon-Fernandez O, Chavez-Negrete A, Hernandez-Lopez S, Marin-Rendon S, Berlin-Lascurain S. [Clinical effect of lifestyle modification on cardiovascular risk in prehypertensives: PREHIPER I study]. Rev Esp Cardiol. 2009 Jan;62(1):86-90. Spanish.
Results Reference
background
PubMed Identifier
22959500
Citation
Yoon U, Kwok LL, Magkidis A. Efficacy of lifestyle interventions in reducing diabetes incidence in patients with impaired glucose tolerance: a systematic review of randomized controlled trials. Metabolism. 2013 Feb;62(2):303-14. doi: 10.1016/j.metabol.2012.07.009. Epub 2012 Sep 7.
Results Reference
background
PubMed Identifier
28541998
Citation
Rosenberg K. Prediabetes Increases Risk of Cardiovascular Disease. Am J Nurs. 2017 Jun;117(6):71. doi: 10.1097/01.NAJ.0000520262.18448.1c. No abstract available.
Results Reference
background
PubMed Identifier
28402773
Citation
Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, Imperatore G, Linder B, Marcovina S, Pettitt DJ, Pihoker C, Saydah S, Wagenknecht L; SEARCH for Diabetes in Youth Study. Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med. 2017 Apr 13;376(15):1419-1429. doi: 10.1056/NEJMoa1610187.
Results Reference
background
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Effect of Real-time Continuous Glucose Monitoring System in Overweight or Obese Adults With Prediabetes
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