Adaptive, Real-time, Intelligent System to Enhance Self-care of Chronic Disease

NCT03643692 | Completed Results

• 1 other identifier: 18HH4410
• Study Type: interventional
• Target: 12
• Locations: 1 country
• Sites: 1

Brief Summary

The Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases (ARISES) project will use type 1 diabetes (T1DM) as an exemplary case study to demonstrate safety, technical proof of concept and efficacy of a novel mobile platform. Combining wearable sensors and smartphone technology, a range of biological, environmental and behavioural data will be analysed to provide real-time therapeutic and lifestyle decision support. Using Case-Based-Reasoning (CBR), the system will be adaptive and personalised with the ability to learn from previously encountered scenarios. Ultimately, ARISES aims to empower self-management of chronic illness and limit the complications associated suboptimal treatment.

Conditions

Diabetes Mellitus, Type 1

Keywords

Diabetes Mellitus; blood glucose; environmental case parameters

Outcome Measures

Primary Outcomes (1)

• Time in Range (%)

  % time in target range (3.9 - 10 mmol/L) without insulin dose increase

  6 weeks

Study Arms (1)

ARISES

EXPERIMENTAL

Observational study using wearable technologies to collect data and evaluate blood glucose correlations against physiological and environmental case parameters. Useful associations will assist the development of the CBR/machine learning algorithm and identify wearable devices for the final ARISES platform.

Device: ARISES

Interventions

ARISES DEVICE

The Adaptive, Real-time, Intelligent System to Enhance Self-care of chronic diseases (ARISES) project will use type 1 diabetes (T1DM) as an exemplary case study to demonstrate safety, technical proof of concept and efficacy of a novel mobile platform. Combining wearable sensors and smartphone technology, a range of biological, environmental and behavioural data will be analysed to provide real-time therapeutic and lifestyle decision support. Using Case-Based-Reasoning (CBR), the system will be adaptive and personalised with the ability to learn from previously encountered scenarios. Ultimately, ARISES aims to empower self-management of chronic illness and limit the complications associated suboptimal treatment.

ARISES

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adults ≥18years of age
• Diagnosis of T1DM for \> 1 year
• Structured education completed in last 3 years and capable of CHO counting
• CBG measured at least twice daily for CGM calibration
• Capacity to follow the protocol and sign the informed consent
• Access to a personal computer/laptop

You may not qualify if:

• Severe episode of hypoglycaemia (requiring 3rd party assistance) in last 6 months
• Diabetic ketoacidosis in the last 6 months prior to enrolment
• Impaired awareness of hypoglycaemia (based on Gold score)
• Pregnant or planning pregnancy over time of study procedures
• Breastfeeding
• Enrolled in other clinical trials
• Active malignancy or being investigated for malignancy
• Suspected or diagnosed endocrinopathy like adrenal insufficiency, unstable thyroidopathy, endocrine tumour
• Gastroparesis
• Autonomic neuropathy
• Macrovascular complications (acute coronary syndrome, transient ischaemic attack, cerebrovascular event within the last 12 months prior to enrolment in the study)
• Visual impairment including unstable proliferative retinopathy
• Reduced manual dexterity
• Inpatient psychiatric treatment
• Abnormal renal function test results (calculated GFR \<40 mL/min/1.73m2)

Sponsors & Collaborators

• Imperial College London: lead

Study Sites (1)

Imperial College Clinical Research Facility

London, United Kingdom

Location

MeSH Terms

Conditions

Diabetes Mellitus, Type 1; Diabetes Mellitus

Condition Hierarchy (Ancestors)

Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases

Results Point of Contact

• Title: Nick Oliver
• Organization: Imperial College London

nick.oliver@imperial.ac.uk

02033111093

Study Officials

• Nick Oliver

  Imperial College London

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 13, 2018
• First Posted: August 23, 2018
• Study Start: February 26, 2019
• Primary Completion: July 1, 2019
• Study Completion: July 1, 2019
• Last Updated: August 6, 2020
• Results First Posted: August 6, 2020

Record last verified: 2020-08

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)