<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02214719</url>
  </required_header>
  <id_info>
    <org_study_id>EASI02IDM01</org_study_id>
    <nct_id>NCT02214719</nct_id>
  </id_info>
  <brief_title>Edmonton Automated Sugar Intelligence - Intelligent Diabetes Management, EASI-IDM, App Program to Assist Diabetes Care</brief_title>
  <acronym>EASI-IDM</acronym>
  <official_title>Edmonton Automated Sugar Intelligence for Intelligent Diabetes Management, (EASI-IDM), a Computer Program to Assist People With Diabetes.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Alberta</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Alberta</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      A closed loop system for diabetes care utilizing an insulin pump, continuous glucose sensing&#xD;
      and appropriate mathematical modelling to guide insulin dosing is a goal for those with Type&#xD;
      1 diabetes. Yet the cost of the associated hardware will be prohibitive for many people with&#xD;
      diabetes or their health care payers. Carbohydrate counting, insulin dose correction systems,&#xD;
      basal bolus regimens with or without an insulin pump all facilitate glucose control but&#xD;
      frequent adjustment to a diabetes regimen is a necessary cornerstone to successful diabetes&#xD;
      management; if all that is used is the regimen suggested by the health care provider at a&#xD;
      visit and this regimen is left unchanged until the next visit or contact then success will be&#xD;
      limited. A readily available user friendly program suitable for a smart phone or tablet would&#xD;
      have widespread applicability and benefit. The investigators hypothesize that such an app&#xD;
      linked into a web site that facilitated review of glucose records will be acceptable to&#xD;
      people with diabetes and improve glucose control. Our long term goal is to create an app that&#xD;
      can advise on diabetes management.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Patients with Type 1 diabetes who use a smart phone will keep detailed records of their blood&#xD;
      glucose readings, carbohydrate intake, activity and insulin doses and share them with us. The&#xD;
      investigators have developed a smart phone app to facilitate the recording of glucose&#xD;
      readings, Edmonton Automated Sugar Intelligence (EASI). This EASI app may be used on Android&#xD;
      or iPhone platforms. It will link to a web site (Intelligent Diabetes Management-IDM) that&#xD;
      houses the person's algorithm for their insulin adjustments ie their insulin regimen scale or&#xD;
      correction factor equation, their carbohydrate ratio formula for each meal and snack, their&#xD;
      appropriate adjustment for exercise so that entry of the timed glucose, the carbohydrate&#xD;
      portion to be consumed and any expected activity will allow derivation of the appropriate&#xD;
      insulin dose. This information will be entered into the EASI program associated web site by&#xD;
      the clinical staff at the time off the visit to the diabetes program or recruitment to the&#xD;
      study.&#xD;
&#xD;
      Then, the patient simply enters the current glucose and carbohydrate intake into EASI to&#xD;
      allow the app use their prescribed algorithm and arrive at a suggested insulin dose. It is&#xD;
      simply using the smart phone to do what is done by mental arithmetic or on paper at present.&#xD;
      Thus EASI-IDM is a simple clinical decision support system to assist health management. The&#xD;
      advantage is the information is stored in real time to the IDM web site for both the person&#xD;
      or their caregiver to review.&#xD;
&#xD;
      Since weight, age, gender, renal function, phase of menstrual cycle and ambient glucose may&#xD;
      have an impact on glycemic control the investigators will also record these details.&#xD;
&#xD;
      The first substudy planned is an - Acceptability sub study survey. The team has developed the&#xD;
      EASI app that links in with the IDM web site. The investigators want to study how well it is&#xD;
      accepted by patients with Type 1 diabetes, whether they use it on an ongoing basis, whether&#xD;
      it leads to them adjusting their insulin regimen themselves more frequently and finally does&#xD;
      it improve their A1c.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>August 2014</start_date>
  <completion_date type="Actual">December 31, 2016</completion_date>
  <primary_completion_date type="Actual">December 31, 2016</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Supportive Care</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Glucose control - A1c</measure>
    <time_frame>6 months</time_frame>
    <description>Assess if A1c improves over course of study</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Use of the app</measure>
    <time_frame>6 months</time_frame>
    <description>Number of glucose determinations recorded in the app per week per participant</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Patient initiated changes to insulin regimen</measure>
    <time_frame>6 months</time_frame>
    <description>Number of patient initiated changes in subjects regimen per week</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Acceptance of app</measure>
    <time_frame>6 months</time_frame>
    <description>Score on a visual analogue scale of acceptance of app by participants</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Long term use</measure>
    <time_frame>6 months</time_frame>
    <description>Percentage of participants continuing to use app one month after formal end of intervention</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">31</enrollment>
  <condition>Diabetes, Type 1</condition>
  <arm_group>
    <arm_group_label>Baseline observation for EASI-IDM use</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Baseline observation period to gather information on current practice about diabetes care</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>EASI-IDM use</intervention_name>
    <description>EASI-IDM use is the intervention involving the use of the Edmonton Automated Sugar Intelligence system linked to the Intelligent Diabetes Website by people with type 1 diabetes to facilitate glucose record keeping, clinical monitoring and we will assess if this app helps lead to improved glucose control and more patient involvement with their diabetes management.</description>
    <arm_group_label>Baseline observation for EASI-IDM use</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Type 1 diabetes Smart phone user Resident of Canada&#xD;
&#xD;
        Exclusion Criteria:&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Edmond Ryan, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Alberta</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Alberta</name>
      <address>
        <city>Edmonton</city>
        <state>Alberta</state>
        <zip>T6G 1S2</zip>
        <country>Canada</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Canada</country>
  </location_countries>
  <results_reference>
    <citation>Ryan EA, Holland J, Stroulia E, Bazelli B, Babwik SA, Li H, Senior P, Greiner R. Improved A1C Levels in Type 1 Diabetes with Smartphone App Use. Can J Diabetes. 2017 Feb;41(1):33-40. doi: 10.1016/j.jcjd.2016.06.001. Epub 2016 Aug 25.</citation>
    <PMID>27570203</PMID>
  </results_reference>
  <verification_date>April 2019</verification_date>
  <study_first_submitted>August 1, 2014</study_first_submitted>
  <study_first_submitted_qc>August 8, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 12, 2014</study_first_posted>
  <last_update_submitted>February 10, 2023</last_update_submitted>
  <last_update_submitted_qc>February 10, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">February 14, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>type 1 diabetes, insulin therapy, bolus calculator</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Diabetes Mellitus</mesh_term>
    <mesh_term>Diabetes Mellitus, Type 1</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02214719
org study id: EASI02IDM01
nct id: NCT02214719
lead sponsor: 
has dmc: No
A closed loop system for diabetes care utilizing an insulin pump, continuous glucose sensing
      and appropriate mathematical modelling to guide insulin dosing is a goal for those with Type
      1 diabetes. Yet the cost of the associated hardware will be prohibitive for many people with
      diabetes or their health care payers. Carbohydrate counting, insulin dose correction systems,
      basal bolus regimens with or without an insulin pump all facilitate glucose control but
      frequent adjustment to a diabetes regimen is a necessary cornerstone to successful diabetes
      management; if all that is used is the regimen suggested by the health care provider at a
      visit and this regimen is left unchanged until the next visit or contact then success will be
      limited. A readily available user friendly program suitable for a smart phone or tablet would
      have widespread applicability and benefit. The investigators hypothesize that such an app
      linked into a web site that facilitated review of glucose records will be acceptable to
      people with diabetes and improve glucose control. Our long term goal is to create an app that
      can advise on diabetes management.
Patients with Type 1 diabetes who use a smart phone will keep detailed records of their blood
      glucose readings, carbohydrate intake, activity and insulin doses and share them with us. The
      investigators have developed a smart phone app to facilitate the recording of glucose
      readings, Edmonton Automated Sugar Intelligence (EASI). This EASI app may be used on Android
      or iPhone platforms. It will link to a web site (Intelligent Diabetes Management-IDM) that
      houses the person's algorithm for their insulin adjustments ie their insulin regimen scale or
      correction factor equation, their carbohydrate ratio formula for each meal and snack, their
      appropriate adjustment for exercise so that entry of the timed glucose, the carbohydrate
      portion to be consumed and any expected activity will allow derivation of the appropriate
      insulin dose. This information will be entered into the EASI program associated web site by
      the clinical staff at the time off the visit to the diabetes program or recruitment to the
      study.

      Then, the patient simply enters the current glucose and carbohydrate intake into EASI to
      allow the app use their prescribed algorithm and arrive at a suggested insulin dose. It is
      simply using the smart phone to do what is done by mental arithmetic or on paper at present.
      Thus EASI-IDM is a simple clinical decision support system to assist health management. The
      advantage is the information is stored in real time to the IDM web site for both the person
      or their caregiver to review.

      Since weight, age, gender, renal function, phase of menstrual cycle and ambient glucose may
      have an impact on glycemic control the investigators will also record these details.

      The first substudy planned is an - Acceptability sub study survey. The team has developed the
      EASI app that links in with the IDM web site. The investigators want to study how well it is
      accepted by patients with Type 1 diabetes, whether they use it on an ongoing basis, whether
      it leads to them adjusting their insulin regimen themselves more frequently and finally does
      it improve their A1c.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Supportive Care
masking: None (Open Label)
measure: Glucose control - A1c
time frame: 6 months
description: Assess if A1c improves over course of study
measure: Use of the app
time frame: 6 months
description: Number of glucose determinations recorded in the app per week per participant
measure: Patient initiated changes to insulin regimen
time frame: 6 months
description: Number of patient initiated changes in subjects regimen per week
measure: Acceptance of app
time frame: 6 months
description: Score on a visual analogue scale of acceptance of app by participants
measure: Long term use
time frame: 6 months
description: Percentage of participants continuing to use app one month after formal end of intervention
arm group label: Baseline observation for EASI-IDM use
arm group type: Experimental
description: Baseline observation period to gather information on current practice about diabetes care
intervention type: Behavioral
intervention name: EASI-IDM use
description: EASI-IDM use is the intervention involving the use of the Edmonton Automated Sugar Intelligence system linked to the Intelligent Diabetes Website by people with type 1 diabetes to facilitate glucose record keeping, clinical monitoring and we will assess if this app helps lead to improved glucose control and more patient involvement with their diabetes management.
arm group label: Baseline observation for EASI-IDM use
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Edmond Ryan, MD
role: Principal Investigator
affiliation: University of Alberta
facility: 
country: Canada
citation: Ryan EA, Holland J, Stroulia E, Bazelli B, Babwik SA, Li H, Senior P, Greiner R. Improved A1C Levels in Type 1 Diabetes with Smartphone App Use. Can J Diabetes. 2017 Feb;41(1):33-40. doi: 10.1016/j.jcjd.2016.06.001. Epub 2016 Aug 25.
PMID: 27570203
responsible party type: Sponsor
mesh term: Diabetes Mellitus
mesh term: Diabetes Mellitus, Type 1
sharing ipd: No