Development of an Algorithm to Assess Metabolic Health of Non-diabetic and Pre-diabetic South-Asian Population Using Continuous Glucose Monitoring Systems and Ultrahuman Health Platform
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 100
- 试验地点
- 9
- 主要终点
- CGM-based glucose indices over 14 days of period
研究概览
简要总结
In this prospective observational study, eligible subjects willing to participate in the study will be screened, and the subjects meeting the eligibility criteria will be enrolled in the study. Based on the ADA criteria of Screening and Diagnostic Tests for Prediabetes, the subjects will be assigned to either group A (healthy non-diabetic subjects) or group B (pre-diabetic subjects). After the screening of the subjects, urine, stool, and blood samples will be collected for baseline investigations. All the enrolled subjects will be provided with the CGM device and trained by the on-site staff on applying it to their arms. The CGM data-collection period will be 14 days (2 weeks). Based on GV Indices, Activity & Sleep data, the UH platform will provide Nudges related to GV Indices trend. Participants can modify their diet & activities accordingly. The glucose readings will be collected by the Abbott freestyle libre CGM device, which will be scanned with the subject’s phone and the supplied Abbott CGM reader. The daily food consumption will be logged on the UH application. The activity tracker will log the physical activities, sleeping, and waking time. All participants will be provided with the necessary training to familiarize themselves with the App’s features and use.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 25.00 Year(s) 至 50.00 Year(s)（—）
- 性别
- All
入选标准
- •General inclusion criteria for healthy and prediabetic population: Subjects within the age group of 25-50 years.
- •Subjects willing to participate in the study.
- •BMI within 20 – 30 kg per m2 Willing to comply to the advised use of CGM, activity tracker, CGM reader and the UH Application.
- •Inclusion criteria for healthy population: Fasting blood glucose level at screening 79-99 mg/dl HbA1c range 4.0-5.6 percentage 2-hour plasma glucose during 75-g OGTT below 140 mg/dL (less than 7.8 mmol/L) Inclusion criteria for prediabetic population: Fasting blood glucose level at screening 100-125 mg/dl OR HbA1c range 5.7-6.4 percentage OR 2-hour plasma glucose during 75-g OGTT 140–199 mg/dL (7.8–11.0 mmol/L).
排除标准
- •History of acute or subacute infection in the last three months.
- •History of chronic illnesses and autoimmune conditions.
- •Subjects on antimicrobial drug agents, including antibiotics, antivirals, or antifungals Subjects pre-diagnosed with Type 1 Diabetes Subjects pre-diagnosed with Type 2 Diabetes Mellitus according to the ADA (American Diabetes Association) criteria.
- •Subjects with anemia [less than male 13 grams per dL and females less than 12 grams per dL] Documented known medical history of any impaired renal and liver function.
- •Subjects diagnosed with cardiac disease, including angina, heart failure, arrhythmias, valvular heart disease, or congenital heart disease.
- •Subjects with regular alcohol consumption of more than eight drinks per week and 15 drinks per week in women and men, respectively.
- •Enrolment in any kind of weight reduction program in the last six months Unexplained intentional or unintentional weight loss of more than 10 percent of average weight in the previous six months Subjects currently on diet plans such as keto, low carb and intermittent fasting.
- •Pregnant and lactating females Out of range results in any of the screening tests carried out for blood glucose measurements (FBG, HbA1c and OGTT tests).
结局指标
主要结局
CGM-based glucose indices over 14 days of period
时间窗: Day 1 and Day 14
Mean glucose levels described by a 24-hour profile during 2 weeks
时间窗: Day 1 and Day 14
Time in glucose ranges
时间窗: Day 1 and Day 14
Glycaemic variability as measured by the standard deviation, coefficient of variation, MAGE
时间窗: Day 1 and Day 14
次要结局
- Changes in FBS from day 0 to day 15(Assessing the correlations between the biomarkers and metabolic health metrics, the key relationships to explore are:)