Trial Review

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Trial details imported from ClinicalTrials.gov

For full trial details, please see the original record at https://clinicaltrials.gov/ct2/show/NCT04946188




Registration number
NCT04946188
Ethics application status
Date submitted
22/04/2021
Date registered
30/06/2021
Date last updated
22/07/2021

Titles & IDs
Public title
Translating Biometric Data Into Blood Glucose Levels
Scientific title
Non-invasive Monitoring to Translate the Biometric Data of Participants With Diabetes Into Blood Glucose Levels
Secondary ID [1] 0 0
2020-02-099
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Diabetes Type 2 0 0
Condition category
Condition code
Metabolic and Endocrine 0 0 0 0
Diabetes

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Treatment: Devices - Opuz NICGM

Experimental: Opuz NICGM - Participants will be provided with one non-invasive, custom-built prototype device (study device), which they will use throughout their day-to-day life/activities over the study period.


Treatment: Devices: Opuz NICGM
A wearable and non-invasive prototype device that allows for measurement of bioimpedance data with the aim to help develop a mathematical model to predict blood glucose levels.
Intervention code [1] 0 0
Treatment: Devices
Comparator / control treatment
Control group

Outcomes
Primary outcome [1] 0 0
Generation of a predictive models for determining blood glucose levels
Timepoint [1] 0 0
at 14 days post introduction of intervention
Primary outcome [2] 0 0
Validation of predictive model for determining blood glucose levels
Timepoint [2] 0 0
at 14 days post introduction of intervention

Eligibility
Key inclusion criteria
- Aged 18 - 70 years

- Physician diagnosis of Type 2 diabetes

- Haemoglobin A1c (HbA1c) range between 7 - 10%

- Body mass index between 20 - 40

- Regularly eats 3 meals per day (breakfast, lunch, and dinner)

- Technologically literate (e.g. able to use Apps, smart phones)

- Able to commit to attending the Sponsor site

- Able to commit to wearing a non-invasive, custom-built device through most daily
activities

- Currently self-monitoring their BGL and able to commit to taking measurements at least
6 times per day

- Proficiency in reading and writing in English
Minimum age
18 Years
Maximum age
70 Years
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
- Currently on insulin therapy (other than long-acting insulin therapy)

- Currently pregnant, pregnant in the last 6 months, or planning a pregnancy

- Currently breastfeeding

- Current smoker

- Any other confounding major disease or condition as deemed appropriate by
investigator, determined by review of medical history and/or patient reported medical
history

- Clinically unstable or rapidly progressing diabetic retinopathy, neuropathy, and/or
frequent nausea, bloating or vomiting, sever gastroesophageal reflux, or early
satiety.

- Multiple medications (taking more than 10 medications is often an indicator of having
multiple major comorbidities which is an exclusion criteria. Furthermore, we want to
exclude potential multiple drug interactions with blood glucose levels which may
impact results of study)

- Currently on active curative treatments for cancer

- Currently receiving systemic glucocorticoid therapy

- Using lipid-lowering medication at a dose that has not been stable for the past 3
months

- History of reactions to alcohol wipes, antiseptics, or adhesives (isobornyl acrylate
which is the adhesive used for attachment of Freestyle Libre sensors and may cause
contact dermatitis)

- Using an insulin pump

- Pacemaker fitted

- Fasting C-peptide levels below 0.5 ng/mL or above 2.0 ng/mL

- Has had an episode of diabetic ketoacidosis in the past 6 months

- Has had an episode of severe hypoglycemia within the past 6 months

- Currently unstable blood glucose control

- Receiving dialysis treatment

- Has had a blood transfusion or severe blood loss within the past 3 months

- Unwilling to self-monitor their BGL (at least 6 measurement, daily)

- Currently participating in another clinical study

- Known to the Investigators

- Other investigator-determined criteria making participants unsuitable for
participation

Study design
Purpose of the study
Other
Allocation to intervention
N/A
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Single group
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis

Recruitment
Recruitment status
Completed
Data analysis
Reason for early stopping/withdrawal
Other reasons
Date of first participant enrolment
Anticipated
Actual
21/07/2020
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
14/12/2020
Sample size
Target
Accrual to date
Final
14
Recruitment in Australia
Recruitment state(s)
NSW
Recruitment hospital [1] 0 0
Scimita Operations - Sydney
Recruitment postcode(s) [1] 0 0
2044 - Sydney

Funding & Sponsors
Primary sponsor type
Commercial sector/Industry
Name
Scimita Operations Pty Ltd.
Address
Country

Ethics approval
Ethics application status

Summary
Brief summary
This study is designed to assist with the development of a first, truly non-invasive
technology for blood glucose monitoring, which will have the potential to eliminate the need
for painful finger pricking or expensive continuous blood glucose monitor use. The purpose of
this study is to collect biometric data, such as bioimpedance (how well the body impedes
electric current flow), from participants who are living with type 2 diabetes. A
proof-of-concept prototype (non-invasive continuous glucose monitor; NI-CGM) will be used to
collect this biometric data. The data will then be used to develop and refine a computer
model that can be used to predict blood glucose levels (BGLs). Individuals with diabetes
experience a great range of blood BGLs throughout their daily life and activities, therefore
it is essential to gather biometric data corresponding to this large range to build a
computer model, to ensure model reliability.
Trial website
https://clinicaltrials.gov/ct2/show/NCT04946188
Trial related presentations / publications
Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018 Apr;138:271-281. doi: 10.1016/j.diabres.2018.02.023. Epub 2018 Feb 26.
Villena Gonzales W, Mobashsher AT, Abbosh A. The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. Sensors (Basel). 2019 Feb 15;19(4):800. doi: 10.3390/s19040800.
D. K. Kamat, D. Bagul, and P. M. Patil, "Blood Glucose Measurement Using Bioimpedance Technique," Adv. Electron., vol. 2014, pp. 1-5, 2014, doi: 10.1155/2014/406257
Tura A. Noninvasive glycaemia monitoring: background, traditional findings, and novelties in the recent clinical trials. Curr Opin Clin Nutr Metab Care. 2008 Sep;11(5):607-12. doi: 10.1097/MCO.0b013e328309ec3a.
P. Daarani & A.Kavithamani, "Blood glucose level monitoring by noninvasive method using near infra red sensor," Int. J. Latest Trends Eng. Technol., vol. IRES, no. 1, 2017, doi: 10.21172/1.ires.19
N. D. Nanayakkara, S. C. Munasingha, and G. P. Ruwanpathirana, "Non-invasive blood glucose monitoring using a hybrid technique," in MERCon 2018 - 4th International Multidisciplinary Moratuwa Engineering Research Conference, pp. 7-12, 2018, doi: 10.1109/MERCon.2018.8421885
Ding S, Schumacher M. Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors (Basel). 2016 Apr 23;16(4):589. doi: 10.3390/s16040589.
Valensi P, Extramiana F, Lange C, Cailleau M, Haggui A, Maison Blanche P, Tichet J, Balkau B; DESIR Study Group. Influence of blood glucose on heart rate and cardiac autonomic function. The DESIR study. Diabet Med. 2011 Apr;28(4):440-9. doi: 10.1111/j.1464-5491.2010.03222.x.
Mueller M, Talary MS, Falco L, De Feo O, Stahel WA, Caduff A. Data processing for noninvasive continuous glucose monitoring with a multisensor device. J Diabetes Sci Technol. 2011 May 1;5(3):694-702. doi: 10.1177/193229681100500324.
Public notes

Contacts
Principal investigator
Name 0 0
Thomas Telfer, PhD (Med)
Address 0 0
Scimita Operations
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for public queries
Name 0 0
Address 0 0
Country 0 0
Phone 0 0
Fax 0 0
Email 0 0
Contact person for scientific queries



Summary Results

For IPD and results data, please see https://clinicaltrials.gov/ct2/show/NCT04946188