Trial Outcomes & Findings for Adaptive, Real-time, Intelligent System to Enhance Self-care of Chronic Disease (NCT NCT03643692)
NCT ID: NCT03643692
Last Updated: 2020-08-06
Results Overview
% time in target range (3.9 - 10 mmol/L) without insulin dose increase
Recruitment status
COMPLETED
Study phase
NA
Target enrollment
12 participants
Primary outcome timeframe
6 weeks
Results posted on
2020-08-06
Participant Flow
Participant milestones
| Measure |
ARISES
ARISES: 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 complic
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|---|---|
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Overall Study
STARTED
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12
|
|
Overall Study
COMPLETED
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12
|
|
Overall Study
NOT COMPLETED
|
0
|
Reasons for withdrawal
Withdrawal data not reported
Baseline Characteristics
Adaptive, Real-time, Intelligent System to Enhance Self-care of Chronic Disease
Baseline characteristics by cohort
| Measure |
ARISES
n=12 Participants
ARISES: 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 complic
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|---|---|
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Age, Continuous
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38 years
n=99 Participants
|
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Sex: Female, Male
Female
|
6 Participants
n=99 Participants
|
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Sex: Female, Male
Male
|
6 Participants
n=99 Participants
|
|
Race (NIH/OMB)
American Indian or Alaska Native
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0 Participants
n=99 Participants
|
|
Race (NIH/OMB)
Asian
|
0 Participants
n=99 Participants
|
|
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
|
0 Participants
n=99 Participants
|
|
Race (NIH/OMB)
Black or African American
|
1 Participants
n=99 Participants
|
|
Race (NIH/OMB)
White
|
11 Participants
n=99 Participants
|
|
Race (NIH/OMB)
More than one race
|
0 Participants
n=99 Participants
|
|
Race (NIH/OMB)
Unknown or Not Reported
|
0 Participants
n=99 Participants
|
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Insulin Modality: Insulin pump (CSII), Multiple daily injections (MDI)
CSII
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6 Participants
n=99 Participants
|
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Insulin Modality: Insulin pump (CSII), Multiple daily injections (MDI)
MDI
|
6 Participants
n=99 Participants
|
PRIMARY outcome
Timeframe: 6 weeks% time in target range (3.9 - 10 mmol/L) without insulin dose increase
Outcome measures
| Measure |
ARISES
n=12 Participants
ARISES: 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 complic
|
|---|---|
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Time in Range (%)
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64 percentage of time (minutes)
Interval 54.4 to 77.3
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Adverse Events
ARISES
Serious events: 0 serious events
Other events: 1 other events
Deaths: 0 deaths
Serious adverse events
Adverse event data not reported
Other adverse events
| Measure |
ARISES
n=12 participants at risk
ARISES: 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 complic
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|---|---|
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Skin and subcutaneous tissue disorders
Rash
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8.3%
1/12 • Number of events 1 • 6 weeks
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Additional Information
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place