<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/NCT04439903</url>
  </required_header>
  <id_info>
    <org_study_id>200157</org_study_id>
    <nct_id>NCT04439903</nct_id>
  </id_info>
  <brief_title>Web-Based Simulation Tool For Self-Management Support In Type 1 Diabetes Mellitus</brief_title>
  <acronym>WST</acronym>
  <official_title>Web-Based Simulation Tool For Self-Management Support In Type 1 Diabetes Mellitus</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Virginia</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Juvenile Diabetes Research Foundation</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Tandem Diabetes Care, Inc.</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Virginia</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This project focuses on embedding the participants' own diabetes data into state-of-the-art&#xD;
      technology platforms to constitute a novel educational simulation interface for&#xD;
      decision-support in Type 1 Diabetes (T1D) - the Web-based Simulation Tool (WST).&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The Web-based Simulation Tool (WST) allows patients with Type 1 Diabetes (T1D) to not only&#xD;
      visualize their data, but also to explore changes to their meals and insulin parameters, and&#xD;
      easily estimate their potential clinical impact. WST is an educational tool, and as such, it&#xD;
      does not have prescriptive power. This platform collects glucose, insulin and meal data from&#xD;
      the participants' insulin pump, and generates personalized models of their glucose&#xD;
      metabolism. Both data collection and model personalization are backend processes, that is,&#xD;
      without user intervention.&#xD;
&#xD;
      Participants can interact with WST through a user interface (UI) that is equipped with a&#xD;
      dashboard page, where they can:&#xD;
&#xD;
      (i) select a particular date range using a calendar to visualize their historical glucose&#xD;
      control, such as glucose traces, and time in range;&#xD;
&#xD;
      (ii) control the amount of information on the screen - users can show/hide more details, such&#xD;
      as glucose variability;&#xD;
&#xD;
      (iii) select different insulin therapy parameters: basal rate, insulin sensitivity factor,&#xD;
      and carbohydrate ratio;&#xD;
&#xD;
      (iv) change their values by moving a slider;&#xD;
&#xD;
      (v) select informed meals within the selected date range, and modify their time and size by&#xD;
      moving a slider;&#xD;
&#xD;
      (vi) run a simulation with the modified insulin therapy parameters and meals by tapping a&#xD;
      button;&#xD;
&#xD;
      (vii) save the insulin and meal settings of the simulations to compare multiple&#xD;
      configurations; and&#xD;
&#xD;
      (viii) generate a report from the selected simulation, comparing both original and simulated&#xD;
      or replay data.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">October 12, 2020</start_date>
  <completion_date type="Actual">February 22, 2021</completion_date>
  <primary_completion_date type="Actual">February 22, 2021</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>
    <intervention_model_description>Single-arm, single center, non-randomized, uncontrolled pilot clinical trial</intervention_model_description>
    <primary_purpose>Other</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Technology Expectation and Technology Acceptance Questionnaires</measure>
    <time_frame>5 weeks</time_frame>
    <description>Technology Expectation (TE) and Technology Acceptance (TA) questionnaires are based on the Bionic Pancreas User Opinion Survey. They were tailored on WST and are made of 27 items scored on a 5-point Likert scale. The items in each questionnaire are almost identical; however, TE questions are in the future tense while TA questions are in the past tense. Participants will be asked to provide their expectation and evaluation regarding ease of use, trustworthy and usefulness of the system. The items in each questionnaire yield to two scores (burdens and benefits), each one is computed as the mean item score converted into a percentage. The TA questionnaire also includes four items that are not part of the standard questionnaire, but will investigate the participants' interaction with WST from a time perspective and assess if they modified their insulin therapy using WST as a source of information.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Diabetes Distress Scale</measure>
    <time_frame>5 weeks</time_frame>
    <description>The Diabetes Distress Scale (DDS) is a 17-item scale that yields a total diabetes distress score plus 4 subscale scores: Emotional burden, regimen distress, interpersonal distress and physician distress. To score, the participants' responses to the appropriate items are summed and divided by the number of items in that scale. A mean item score &lt;2.0 is considered little or no distress, 2.0 - 2.9 is considered moderate distress, and &gt;3.0 is considered high distress.</description>
  </secondary_outcome>
  <other_outcome>
    <measure>Potential Correlation Between System Use and Changes in Treatment Satisfaction and Glucose Control</measure>
    <time_frame>5 weeks</time_frame>
    <description>Weekly glucose metrics from continuous glucose monitoring (CGM) data will be computed as per current consensus guidelines, and used along with the scores of the questionnaires in regression analysis to infer the impact of the duration and frequency of participants' interaction with the application (predictor variables) on variations in metabolic control and treatment satisfaction (response variables).</description>
  </other_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">15</enrollment>
  <condition>Type 1 Diabetes</condition>
  <arm_group>
    <arm_group_label>Web-based Simulation Tool (WST)</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Web-based Simulation Tool</intervention_name>
    <description>Glucose, insulin and meal data from the participants' insulin pump will be collected and entered into the WST, which will generate personalized models of the participants' glucose metabolism to enable replay simulations.</description>
    <arm_group_label>Web-based Simulation Tool (WST)</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Age ≥21 and ≤65 years old at time of consent.&#xD;
&#xD;
          -  Clinical diagnosis, based on investigator assessment, of T1D for at least one year.&#xD;
&#xD;
          -  Using insulin for at least 1 year prior to study enrollment.&#xD;
&#xD;
          -  Using an insulin pump for at least 6 months prior to study enrollment.&#xD;
&#xD;
          -  Currently using a CGM for at least 6 months.&#xD;
&#xD;
          -  Willingness to use a Dexcom G6 CGM during the study; a study Dexcom CGM will be&#xD;
             provided if needed.&#xD;
&#xD;
          -  Current user of the Tandem t:slim X2 insulin pump.&#xD;
&#xD;
          -  Willingness to switch to lispro (Humalog) or aspart (Novolog) if not using already,&#xD;
             and to use no other insulin besides lispro (Humalog) or aspart (Novolog) during the&#xD;
             study.&#xD;
&#xD;
          -  Total daily insulin (TDI) dose at least 10 U/day.&#xD;
&#xD;
          -  HbA1c ≤9.0% at screening; if HbA1c &lt;6.0%, then TDI must be ≥ 0.5 U/kg.&#xD;
&#xD;
          -  Having access to internet (Wi-Fi or 3G, 4G, 5G, or similar).&#xD;
&#xD;
          -  Willingness to interact with a computer program.&#xD;
&#xD;
          -  An understanding of and willingness to follow the protocol and sign the informed&#xD;
             consent form (ICF).&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Participants who are not able to read and complete questionnaires on the computer or&#xD;
             interact with a program for which they will be trained because of language, reading,&#xD;
             or cognitive issues.&#xD;
&#xD;
          -  Severe hypoglycemia resulting in seizure or loss of consciousness in the 12 months&#xD;
             prior to enrollment.&#xD;
&#xD;
          -  History of a seizure disorder (except hypoglycemic seizure), unless written clearance&#xD;
             is received from a neurologist and not currently on a seizure medication.&#xD;
&#xD;
          -  Pregnancy, breast-feeding, or intention of becoming pregnant over time of study&#xD;
             procedures.&#xD;
&#xD;
          -  If female and sexually active, must agree to use a form of contraception to prevent&#xD;
             pregnancy while a participant in the study. A negative urine pregnancy test will be&#xD;
             required for all premenopausal women who are not surgically sterile. Subjects who&#xD;
             become pregnant will be discontinued from the study.&#xD;
&#xD;
          -  A known medical condition that in the judgment of the investigator might interfere&#xD;
             with the completion of the study.*&#xD;
&#xD;
          -  Abuse of alcohol or recreational drugs.&#xD;
&#xD;
          -  Infectious process not anticipated to resolve prior to study procedures (e.g.&#xD;
             meningitis, pneumonia, osteomyelitis, etc).&#xD;
&#xD;
          -  Uncontrolled arterial hypertension (resting diastolic blood pressure &gt;90 mmHg and/or&#xD;
             systolic blood pressure &gt;160 mmHg).&#xD;
&#xD;
          -  A recent injury to body or limb, muscular disorder, use of any medication, any&#xD;
             carcinogenic disease, or other significant medical disorder if that injury, medication&#xD;
             or disease in the judgment of the investigator will affect the completion of the&#xD;
             protocol.&#xD;
&#xD;
          -  Current use of the following drugs and supplements:&#xD;
&#xD;
               -  Any drug other than insulin to treat diabetes.&#xD;
&#xD;
               -  Any other medication that according to the investigator's criteria is a&#xD;
                  contraindication for the subject's participation.&#xD;
&#xD;
                    -  Note: The software implementation, in the current development status, is&#xD;
                       designed to interact with subjects with T1D that only use insulin for&#xD;
                       diabetes treatment and do not present any comorbidity related to diabetes.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>21 Years</minimum_age>
    <maximum_age>65 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Patricio Colmegna, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Virginia, Center for Diabetes Technology</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Virginia - Center for Diabetes Technology</name>
      <address>
        <city>Charlottesville</city>
        <state>Virginia</state>
        <zip>22903</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>March 2021</verification_date>
  <study_first_submitted>June 14, 2020</study_first_submitted>
  <study_first_submitted_qc>June 17, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 19, 2020</study_first_posted>
  <last_update_submitted>March 10, 2021</last_update_submitted>
  <last_update_submitted_qc>March 10, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">March 12, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Virginia</investigator_affiliation>
    <investigator_full_name>Patricio Colmegna, PhD</investigator_full_name>
    <investigator_title>Research Associate</investigator_title>
  </responsible_party>
  <keyword>Web-based Simulation Tool (WST)</keyword>
  <keyword>Continuous Glucose Monitoring (CGM)</keyword>
  <keyword>Glucose Metabolism Model</keyword>
  <keyword>Insulin Pump</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>
    <ipd_description>No plan to share IPD.</ipd_description>
  </patient_data>
  <pending_results>
    <submitted>February 21, 2022</submitted>
    <returned>May 9, 2022</returned>
    <submitted>May 25, 2022</submitted>
    <returned>February 28, 2023</returned>
    <submitted>February 28, 2023</submitted>
  </pending_results>
  <!-- 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/NCT04439903
org study id: 200157
nct id: NCT04439903
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
This project focuses on embedding the participants' own diabetes data into state-of-the-art
      technology platforms to constitute a novel educational simulation interface for
      decision-support in Type 1 Diabetes (T1D) - the Web-based Simulation Tool (WST).
The Web-based Simulation Tool (WST) allows patients with Type 1 Diabetes (T1D) to not only
      visualize their data, but also to explore changes to their meals and insulin parameters, and
      easily estimate their potential clinical impact. WST is an educational tool, and as such, it
      does not have prescriptive power. This platform collects glucose, insulin and meal data from
      the participants' insulin pump, and generates personalized models of their glucose
      metabolism. Both data collection and model personalization are backend processes, that is,
      without user intervention.

      Participants can interact with WST through a user interface (UI) that is equipped with a
      dashboard page, where they can:

      (i) select a particular date range using a calendar to visualize their historical glucose
      control, such as glucose traces, and time in range;

      (ii) control the amount of information on the screen - users can show/hide more details, such
      as glucose variability;

      (iii) select different insulin therapy parameters: basal rate, insulin sensitivity factor,
      and carbohydrate ratio;

      (iv) change their values by moving a slider;

      (v) select informed meals within the selected date range, and modify their time and size by
      moving a slider;

      (vi) run a simulation with the modified insulin therapy parameters and meals by tapping a
      button;

      (vii) save the insulin and meal settings of the simulations to compare multiple
      configurations; and

      (viii) generate a report from the selected simulation, comparing both original and simulated
      or replay data.
allocation: N/A
intervention model: Single Group Assignment
intervention model description: Single-arm, single center, non-randomized, uncontrolled pilot clinical trial
primary purpose: Other
masking: None (Open Label)
measure: Technology Expectation and Technology Acceptance Questionnaires
time frame: 5 weeks
description: Technology Expectation (TE) and Technology Acceptance (TA) questionnaires are based on the Bionic Pancreas User Opinion Survey. They were tailored on WST and are made of 27 items scored on a 5-point Likert scale. The items in each questionnaire are almost identical; however, TE questions are in the future tense while TA questions are in the past tense. Participants will be asked to provide their expectation and evaluation regarding ease of use, trustworthy and usefulness of the system. The items in each questionnaire yield to two scores (burdens and benefits), each one is computed as the mean item score converted into a percentage. The TA questionnaire also includes four items that are not part of the standard questionnaire, but will investigate the participants' interaction with WST from a time perspective and assess if they modified their insulin therapy using WST as a source of information.
measure: Diabetes Distress Scale
time frame: 5 weeks
description: The Diabetes Distress Scale (DDS) is a 17-item scale that yields a total diabetes distress score plus 4 subscale scores: Emotional burden, regimen distress, interpersonal distress and physician distress. To score, the participants' responses to the appropriate items are summed and divided by the number of items in that scale. A mean item score <2.0 is considered little or no distress, 2.0 - 2.9 is considered moderate distress, and >3.0 is considered high distress.
measure: Potential Correlation Between System Use and Changes in Treatment Satisfaction and Glucose Control
time frame: 5 weeks
description: Weekly glucose metrics from continuous glucose monitoring (CGM) data will be computed as per current consensus guidelines, and used along with the scores of the questionnaires in regression analysis to infer the impact of the duration and frequency of participants' interaction with the application (predictor variables) on variations in metabolic control and treatment satisfaction (response variables).
arm group label: Web-based Simulation Tool (WST)
arm group type: Experimental
intervention type: Other
intervention name: Web-based Simulation Tool
description: Glucose, insulin and meal data from the participants' insulin pump will be collected and entered into the WST, which will generate personalized models of the participants' glucose metabolism to enable replay simulations.
arm group label: Web-based Simulation Tool (WST)
criteria: 
gender: All
minimum age: 21 Years
maximum age: 65 Years
healthy volunteers: No
last name: Patricio Colmegna, PhD
role: Principal Investigator
affiliation: University of Virginia, Center for Diabetes Technology
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Virginia
investigator full name: Patricio Colmegna, PhD
investigator title: Research Associate
mesh term: Diabetes Mellitus
mesh term: Diabetes Mellitus, Type 1
sharing ipd: No
ipd description: No plan to share IPD.
submitted: February 21, 2022
returned: May 9, 2022
submitted: May 25, 2022
returned: February 28, 2023
submitted: February 28, 2023