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Completed

NCT Number: NCT03643692

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

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.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Imperial College Clinical Research Facility

London, United Kingdom

About this study

ARISES will target self-management to optimise glucose control through insulin dose recommendation (therapeutic advice), exercise and stress support, hypoglycaemia prevention through timely snack recommendation and behavioural change through educational support (lifestyle advice).

Semi-structured focus meetings comprised of patients with T1DM, clinicians, engineers and experts in human-computer interaction will provide a forum to establish the essential usability requirements to incorporate into the ARISES mobile interface. The design will focus on ensuring access to decision support is intuitive and efficient while maintaining sight of real-time glycaemia outcomes. The design and implementation of the user-interface will be assessed in a series of usability validation studies.

Clinical studies will be conducted in two phases. The first phase will be an 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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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

Exclusion criteria

  • 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)
  • Liver cirrhosis
  • Not tributary to optimization to insulin therapy
  • Abuse of alcohol or recreational drugs
  • Oral steroids
  • Regular use of the paracetamol, beta-blockers or any other medication that the investigator believes is a contraindication to the participant's participation.

Treatment and study plan

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.

Primary outcomes

  1. Time in Range (%)

    Time frame: 6 weeks

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

Sponsors and collaborators

Lead sponsor

Imperial College London

Other

Registry information

Acronym: ARISES

Important dates

Study start
2019
Primary completion
2019
Study completion
2019
First posted
Aug 23, 2018
Registry last updated
Aug 6, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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