<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/NCT03034759</url>
  </required_header>
  <id_info>
    <org_study_id>1611018615</org_study_id>
    <nct_id>NCT03034759</nct_id>
  </id_info>
  <brief_title>A New Wizard for Insulin Sensitivity Estimation From SAP: a Randomized Controlled Trial in Adolescents With T1D</brief_title>
  <official_title>A New Wizard for Insulin Sensitivity Estimation From SAP: a Randomized Controlled Trial in Adolescents With T1D</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Yale University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Yale University</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>
      We aim to test the efficacy of a new method for determining individual insulin sensitivity&#xD;
      (IS) based on sensor-augmented-insulin pump (SAP) data in order to customize the insulin to&#xD;
      carbohydrate ratio (CR) in adolescents with type 1 diabetes (T1D).&#xD;
&#xD;
      To date, the individual insulin sensitivity (IS) could only be investigated by intensive and&#xD;
      invasive research techniques that are not feasible to perform in an outpatient setting for&#xD;
      pediatric patients with diabetes.&#xD;
&#xD;
      Recently published studies have demonstrated the efficacy of an algorithm to calculate the&#xD;
      patient specific insulin sensitivity to customize the CR for adult patients with T1D. The&#xD;
      algorithm has been validated in adult patients, however not yet investigated in the pediatric&#xD;
      population with T1D.&#xD;
&#xD;
      The aims of our study are:&#xD;
&#xD;
        1. to customize the CR of pediatric subjects with T1D using the individualized insulin&#xD;
           sensitivity index (ISind) to improve post-prandial blood glucose control after a&#xD;
           standard meal.&#xD;
&#xD;
        2. to test, under free living condition (at home), the efficacy of the customized CR in&#xD;
           improving post-prandial glycemic control for pediatric subjects with T1D.&#xD;
&#xD;
      This approach would have at least two potential benefits for pediatric patients with T1D:&#xD;
&#xD;
        1. To provide a non-invasive tool for individualizing their home insulin therapy;&#xD;
&#xD;
        2. To offer a reliable instrument for adjusting the meal bolus of the current hybrid closed&#xD;
           loop (HCL) systems to account for the inter-subject variability in insulin action.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      A new method to assess insulin sensitivity (IS) has been proposed and investigated by the PI&#xD;
      and his group at the University of Padova. The new insulin sensitivity index, named &quot;SISP&quot; is&#xD;
      calculated from data derived from insulin pump and continuous glucose monitoring (CGM)&#xD;
      uploads. The efficiency of the SISP has been tested in-silico using the University of&#xD;
      Virginia/Padova T1D simulator by mimicking a single-meal scenario with patient-specific&#xD;
      optimized carbohydrate ratio (CR) (increased or decreased by 20%) and optimal CR. In all the&#xD;
      simulations the use of the optimal CR, calculated with the proposed method, has improved the&#xD;
      overall glycemic control. The simulator (S2013) used for this purpose has been valdated and&#xD;
      is approved by the FDA as a substitute for preclinical trials for insulin treatments,&#xD;
      including closed-loop algorithms. It is comprised of data from 100 in-silico patients that&#xD;
      represent the biological variability of a generic real diabetic population. Thus, an&#xD;
      algorithm that is tuned on the basis of in-silico analysis can be safely implemented in&#xD;
      real-life setting.&#xD;
&#xD;
      The method to estimate SISP and to optimize the CR from SAP data, could be easily applied to&#xD;
      the daily management of patients with T1D and in a closed-loop context since several&#xD;
      closed-loop algorithms, currently used in clinical trials, are based on the pre-programmed&#xD;
      open-loop insulin therapy.&#xD;
&#xD;
      Once the individualized SISP is calculated, it can be used to customize the CR using the&#xD;
      in-silico tested algorithm to determine an individualized CR (CRIND).&#xD;
&#xD;
      Consequently, the CRIND can be tested in outpatient setting safely, and adjusted in a&#xD;
      run-to-run framework, using a well described approach of self-learning, the latter allowing&#xD;
      titration of the insulin therapy based on CGM data using a self-learning algorithm as&#xD;
      previously described.&#xD;
&#xD;
        -  Phase 1: &quot;Control period&quot;. This phase represents the control frame-time, during which&#xD;
           patients, once enrolled, will use their SAP without any adjustment of the CR and&#xD;
           correction factors, according to the parameters recorded at the screening visit. This&#xD;
           phase is aimed to record the CGM data and will represent the control period of the&#xD;
           study. It lasts 3 weeks.&#xD;
&#xD;
        -  Phase 2: &quot;Build-up period&quot; This phase is aimed to obtain an adequate amount of data for&#xD;
           customizing the insulin pump parameters to the specific features of each subject&#xD;
           according to the proposed algorithms. It consists of three standardized meals (Figure 2)&#xD;
           and a run-in phase.&#xD;
&#xD;
      Subjects will be randomly assigned to two different pre-meal insulin CR groups in a 1:1 ratio&#xD;
      to determine parameters that will be used to adjust the IS algorithm for pediatric patients&#xD;
      with T1D. The post-prandial blood glucose pattern after a pre-meal bolus of CR, CR 20%&#xD;
      increased, CR 20% decreased are validated parameters necessary to customize the algorithm for&#xD;
      a specific patient population with T1D, therefore subjects will be challenged with two&#xD;
      different CRs, depending on the randomization, to collect sufficient data to fine tune the&#xD;
      algorithm.&#xD;
&#xD;
      Each subject will go through three meal studies;&#xD;
&#xD;
      Group 1. Meal 1: CR with 20% increase; Meal 2: CR home; Meal 3: CR individualized Group 2.&#xD;
      Meal 1: CR with 20% decrease; Meal 2: CR home; Meal 3:CR individualized&#xD;
&#xD;
        -  Before the 1st meal subjects will be randomly assigned to receive a modified premeal&#xD;
           bolus (increased or decreased of 20%, CR+/-20%) in a 1:1 ratio. This change of the home&#xD;
           CR (CRHOME) will allow us to estimate the accuracy and error of the CRHOME and to&#xD;
           calculate, according to the described algorithm ((21) and below), the optimized CR&#xD;
           (CRIND). This latter will be tested in both groups as third meal at home.&#xD;
&#xD;
        -  The three meals are followed by a 7 day- run-in period necessary to collect a minimum&#xD;
           amount of CGM data to run the algorithm calculations used in the intervention phase.&#xD;
           During this period subjects will adopt the CRIND obtained after the standard meals.&#xD;
&#xD;
        -  Phase 3: &quot;Intervention period&quot;. This phase is aimed to test the efficacy of the CRIND on&#xD;
           mitigating post-prandial hyperglycemia by a home-based study, using periodical&#xD;
           adjustment of CR and basal rate according to the &quot;run-to-run&quot; approach. It consists of a&#xD;
           self-learning algorithm method to adjust insulin regimen (the basal rate and the CRIND)&#xD;
           based on CGM post-meal blood glucose patterns and pre-meal insulin bolus.&#xD;
&#xD;
      Subjects will use the SAP tuned according to the individualized ISR2R and CRR2R obtained from&#xD;
      the run-in period, along with an individualized insulin basal rate (BasalR2R). During the&#xD;
      run-to-run period subjects will receive weekly revised parameters based on run-to-run&#xD;
      algorithm according to data analysis of the past seven days. It will last 3 weeks.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Withdrawn</overall_status>
  <why_stopped>
    Investigator has moved to another institution&#xD;
  </why_stopped>
  <start_date type="Anticipated">October 1, 2019</start_date>
  <completion_date type="Anticipated">December 1, 2022</completion_date>
  <primary_completion_date type="Anticipated">January 1, 2020</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>Treatment</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>overall time in target (70-180mg/dl)</measure>
    <time_frame>4 weeks</time_frame>
    <description>the percentage of time in target will be calculated &quot;(time in target/total time of records using continuous glucose monitoring)*100.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>median percentage of time spent in hypoglycemia (&lt;70mg/dl) during control period</measure>
    <time_frame>4 weeks</time_frame>
    <description>the percentage of time in target will be calculated &quot;(time in target/total time of records using continuous glucose monitoring)*100.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time spent in hypoglycemia (&lt;70mg/dl) post meal 1</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time spent in hypoglycemia (&lt;70mg/dl) post meal 2</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time spent in hypoglycemia (&lt;70mg/dl) post meal 3</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time spent in hypoglycemia (&lt;70mg/dl) during Intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>the percentage of time in target will be calculated &quot;(time in target/total time of records using continuous glucose monitoring)*100.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>overall time in target (70-180mg/dl) after meal 1</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>overall time in target (70-180mg/dl) after meal 2</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>overall time in target (70-180mg/dl) after meal 3</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>overall time in target (70-180mg/dl) during Intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>the percentage of time in target will be calculated &quot;(time in target/total time of records using continuous glucose monitoring)*100.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time in hyperglycemia (&gt;180mg/dl) during Control Phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>time in target/total time of records using continuous glucose monitoring)*100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time in hyperglycemia (&gt;180mg/dl) after meal 1</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time in hyperglycemia (&gt;180mg/dl) after meal 2</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time in hyperglycemia (&gt;180mg/dl)after meal 3</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time in hyperglycemia (&gt;180mg/dl) during intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>time in target/total time of records using continuous glucose monitoring)*100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time below 50mg/dl during control phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>time in target/total time of records using continuous glucose monitoring)*100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time below 50mg/dl after meal 1</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time below 50mg/dl after meal 2</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time below 50mg/dl after meal 3</measure>
    <time_frame>180 minutes post meal</time_frame>
    <description>time in target/180 mins * 100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>median percentage of time below 50mg/dl during intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>time in target/total time of records using continuous glucose monitoring)*100</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>severe hypoglycemic events during control phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>They will be measured as number of events per person during the weeks of Control Phase</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>severe hypoglycemic events after meal 1</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>They will be measured as number of events per person after meal 1 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>severe hypoglycemic events after meal 2</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>They will be measured as number of events per person after meal 2 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>severe hypoglycemic events after meal 3</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>They will be measured as number of events per person after meal 3 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>severe hypoglycemic events during intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>They will be measured as number of events per person during the weeks of Intervention Phase.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>active hypoglycemia correction (carbohydrate intake) during control phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>total number of active events per person during the weeks of Control Phase</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>active hypoglycemia correction (carbohydrate intake) after meal 1</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>total number of active events per person after meal 1 all day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>active hypoglycemia correction (carbohydrate intake) after meal 2</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>total number of active events per person after meal 2 all day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>active hypoglycemia correction (carbohydrate intake) after meal 3</measure>
    <time_frame>up to 23 hours</time_frame>
    <description>total number of active events per person after meal 3 all day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>active hypoglycemia correction (carbohydrate intake) during intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>total number of active events per person during the weeks of Intervention Phase</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>corrective bolus after meal during control phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>total number of active events per person during the weeks of Control Phase vs Intervention Phase</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>corrective bolus after meal 1</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>total number of active events per person after meal 1 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>corrective bolus after meal after meal 2</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>total number of active events per person after meal 2 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>corrective bolus after meal after meal 3</measure>
    <time_frame>up to 24 hours</time_frame>
    <description>total number of active events per person after meal 3 for the entire day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>corrective bolus after meal during intervention phase</measure>
    <time_frame>4 weeks</time_frame>
    <description>total number of active events per person during the weeks of Intervention Phase</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">0</enrollment>
  <condition>Diabetes Mellitus</condition>
  <arm_group>
    <arm_group_label>All participants</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>+Pediatric patients with T1D. All comparisons will be made within group pre and post intervention.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>individualized insulin sensitivity index (ISind)</intervention_name>
    <description>The new insulin sensitivity index, named &quot;SISP&quot; is calculated from data derived from insulin pump and glucose monitoring (CGM) uploads.</description>
    <arm_group_label>All participants</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Age 12-21 year old.&#xD;
&#xD;
          -  Clinical diagnosis of T1D ≥1 year&#xD;
&#xD;
          -  Treatment with sensor augmented pump therapy (insulin pump + glucose sensor) for at&#xD;
             least 1 month&#xD;
&#xD;
          -  HbA1c &lt;10%&#xD;
&#xD;
          -  Be able to comprehend written and spoken English&#xD;
&#xD;
        Exclusion Criteria&#xD;
&#xD;
          -  Pregnancy, breast feeding, or plans to get pregnant for the next 12 months&#xD;
&#xD;
          -  On medications that affect insulin sensitivity; has other medical conditions known to&#xD;
             affect insulin sensitivity;&#xD;
&#xD;
          -  Cognitive impairment&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>12 Years</minimum_age>
    <maximum_age>21 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Eda Cengiz, MD</last_name>
    <role>Study Chair</role>
    <affiliation>Yale University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Yale Pediatric Diabetes Research Program</name>
      <address>
        <city>New Haven</city>
        <state>Connecticut</state>
        <zip>06511</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>July 2019</verification_date>
  <study_first_submitted>January 24, 2017</study_first_submitted>
  <study_first_submitted_qc>January 26, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">January 27, 2017</study_first_posted>
  <last_update_submitted>July 10, 2019</last_update_submitted>
  <last_update_submitted_qc>July 10, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">July 11, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>continuous glucose monitoring</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Insulin Resistance</mesh_term>
  </condition_browse>
  <intervention_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Insulin</mesh_term>
  </intervention_browse>
  <!-- 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/NCT03034759
org study id: 1611018615
nct id: NCT03034759
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
We aim to test the efficacy of a new method for determining individual insulin sensitivity
      (IS) based on sensor-augmented-insulin pump (SAP) data in order to customize the insulin to
      carbohydrate ratio (CR) in adolescents with type 1 diabetes (T1D).

      To date, the individual insulin sensitivity (IS) could only be investigated by intensive and
      invasive research techniques that are not feasible to perform in an outpatient setting for
      pediatric patients with diabetes.

      Recently published studies have demonstrated the efficacy of an algorithm to calculate the
      patient specific insulin sensitivity to customize the CR for adult patients with T1D. The
      algorithm has been validated in adult patients, however not yet investigated in the pediatric
      population with T1D.

      The aims of our study are:

        1. to customize the CR of pediatric subjects with T1D using the individualized insulin
           sensitivity index (ISind) to improve post-prandial blood glucose control after a
           standard meal.

        2. to test, under free living condition (at home), the efficacy of the customized CR in
           improving post-prandial glycemic control for pediatric subjects with T1D.

      This approach would have at least two potential benefits for pediatric patients with T1D:

        1. To provide a non-invasive tool for individualizing their home insulin therapy;

        2. To offer a reliable instrument for adjusting the meal bolus of the current hybrid closed
           loop (HCL) systems to account for the inter-subject variability in insulin action.
A new method to assess insulin sensitivity (IS) has been proposed and investigated by the PI
      and his group at the University of Padova. The new insulin sensitivity index, named "SISP" is
      calculated from data derived from insulin pump and continuous glucose monitoring (CGM)
      uploads. The efficiency of the SISP has been tested in-silico using the University of
      Virginia/Padova T1D simulator by mimicking a single-meal scenario with patient-specific
      optimized carbohydrate ratio (CR) (increased or decreased by 20%) and optimal CR. In all the
      simulations the use of the optimal CR, calculated with the proposed method, has improved the
      overall glycemic control. The simulator (S2013) used for this purpose has been valdated and
      is approved by the FDA as a substitute for preclinical trials for insulin treatments,
      including closed-loop algorithms. It is comprised of data from 100 in-silico patients that
      represent the biological variability of a generic real diabetic population. Thus, an
      algorithm that is tuned on the basis of in-silico analysis can be safely implemented in
      real-life setting.

      The method to estimate SISP and to optimize the CR from SAP data, could be easily applied to
      the daily management of patients with T1D and in a closed-loop context since several
      closed-loop algorithms, currently used in clinical trials, are based on the pre-programmed
      open-loop insulin therapy.

      Once the individualized SISP is calculated, it can be used to customize the CR using the
      in-silico tested algorithm to determine an individualized CR (CRIND).

      Consequently, the CRIND can be tested in outpatient setting safely, and adjusted in a
      run-to-run framework, using a well described approach of self-learning, the latter allowing
      titration of the insulin therapy based on CGM data using a self-learning algorithm as
      previously described.

        -  Phase 1: "Control period". This phase represents the control frame-time, during which
           patients, once enrolled, will use their SAP without any adjustment of the CR and
           correction factors, according to the parameters recorded at the screening visit. This
           phase is aimed to record the CGM data and will represent the control period of the
           study. It lasts 3 weeks.

        -  Phase 2: "Build-up period" This phase is aimed to obtain an adequate amount of data for
           customizing the insulin pump parameters to the specific features of each subject
           according to the proposed algorithms. It consists of three standardized meals (Figure 2)
           and a run-in phase.

      Subjects will be randomly assigned to two different pre-meal insulin CR groups in a 1:1 ratio
      to determine parameters that will be used to adjust the IS algorithm for pediatric patients
      with T1D. The post-prandial blood glucose pattern after a pre-meal bolus of CR, CR 20%
      increased, CR 20% decreased are validated parameters necessary to customize the algorithm for
      a specific patient population with T1D, therefore subjects will be challenged with two
      different CRs, depending on the randomization, to collect sufficient data to fine tune the
      algorithm.

      Each subject will go through three meal studies;

      Group 1. Meal 1: CR with 20% increase; Meal 2: CR home; Meal 3: CR individualized Group 2.
      Meal 1: CR with 20% decrease; Meal 2: CR home; Meal 3:CR individualized

        -  Before the 1st meal subjects will be randomly assigned to receive a modified premeal
           bolus (increased or decreased of 20%, CR+/-20%) in a 1:1 ratio. This change of the home
           CR (CRHOME) will allow us to estimate the accuracy and error of the CRHOME and to
           calculate, according to the described algorithm ((21) and below), the optimized CR
           (CRIND). This latter will be tested in both groups as third meal at home.

        -  The three meals are followed by a 7 day- run-in period necessary to collect a minimum
           amount of CGM data to run the algorithm calculations used in the intervention phase.
           During this period subjects will adopt the CRIND obtained after the standard meals.

        -  Phase 3: "Intervention period". This phase is aimed to test the efficacy of the CRIND on
           mitigating post-prandial hyperglycemia by a home-based study, using periodical
           adjustment of CR and basal rate according to the "run-to-run" approach. It consists of a
           self-learning algorithm method to adjust insulin regimen (the basal rate and the CRIND)
           based on CGM post-meal blood glucose patterns and pre-meal insulin bolus.

      Subjects will use the SAP tuned according to the individualized ISR2R and CRR2R obtained from
      the run-in period, along with an individualized insulin basal rate (BasalR2R). During the
      run-to-run period subjects will receive weekly revised parameters based on run-to-run
      algorithm according to data analysis of the past seven days. It will last 3 weeks.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Treatment
masking: None (Open Label)
measure: overall time in target (70-180mg/dl)
time frame: 4 weeks
description: the percentage of time in target will be calculated "(time in target/total time of records using continuous glucose monitoring)*100.
measure: median percentage of time spent in hypoglycemia (<70mg/dl) during control period
time frame: 4 weeks
description: the percentage of time in target will be calculated "(time in target/total time of records using continuous glucose monitoring)*100.
measure: median percentage of time spent in hypoglycemia (<70mg/dl) post meal 1
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time spent in hypoglycemia (<70mg/dl) post meal 2
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time spent in hypoglycemia (<70mg/dl) post meal 3
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time spent in hypoglycemia (<70mg/dl) during Intervention phase
time frame: 4 weeks
description: the percentage of time in target will be calculated "(time in target/total time of records using continuous glucose monitoring)*100.
measure: overall time in target (70-180mg/dl) after meal 1
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: overall time in target (70-180mg/dl) after meal 2
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: overall time in target (70-180mg/dl) after meal 3
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: overall time in target (70-180mg/dl) during Intervention phase
time frame: 4 weeks
description: the percentage of time in target will be calculated "(time in target/total time of records using continuous glucose monitoring)*100.
measure: median percentage of time in hyperglycemia (>180mg/dl) during Control Phase
time frame: 4 weeks
description: time in target/total time of records using continuous glucose monitoring)*100
measure: median percentage of time in hyperglycemia (>180mg/dl) after meal 1
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time in hyperglycemia (>180mg/dl) after meal 2
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time in hyperglycemia (>180mg/dl)after meal 3
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time in hyperglycemia (>180mg/dl) during intervention phase
time frame: 4 weeks
description: time in target/total time of records using continuous glucose monitoring)*100
measure: median percentage of time below 50mg/dl during control phase
time frame: 4 weeks
description: time in target/total time of records using continuous glucose monitoring)*100
measure: median percentage of time below 50mg/dl after meal 1
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time below 50mg/dl after meal 2
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time below 50mg/dl after meal 3
time frame: 180 minutes post meal
description: time in target/180 mins * 100
measure: median percentage of time below 50mg/dl during intervention phase
time frame: 4 weeks
description: time in target/total time of records using continuous glucose monitoring)*100
measure: severe hypoglycemic events during control phase
time frame: 4 weeks
description: They will be measured as number of events per person during the weeks of Control Phase
measure: severe hypoglycemic events after meal 1
time frame: up to 24 hours
description: They will be measured as number of events per person after meal 1 for the entire day
measure: severe hypoglycemic events after meal 2
time frame: up to 24 hours
description: They will be measured as number of events per person after meal 2 for the entire day
measure: severe hypoglycemic events after meal 3
time frame: up to 24 hours
description: They will be measured as number of events per person after meal 3 for the entire day
measure: severe hypoglycemic events during intervention phase
time frame: 4 weeks
description: They will be measured as number of events per person during the weeks of Intervention Phase.
measure: active hypoglycemia correction (carbohydrate intake) during control phase
time frame: 4 weeks
description: total number of active events per person during the weeks of Control Phase
measure: active hypoglycemia correction (carbohydrate intake) after meal 1
time frame: up to 24 hours
description: total number of active events per person after meal 1 all day
measure: active hypoglycemia correction (carbohydrate intake) after meal 2
time frame: up to 24 hours
description: total number of active events per person after meal 2 all day
measure: active hypoglycemia correction (carbohydrate intake) after meal 3
time frame: up to 23 hours
description: total number of active events per person after meal 3 all day
measure: active hypoglycemia correction (carbohydrate intake) during intervention phase
time frame: 4 weeks
description: total number of active events per person during the weeks of Intervention Phase
measure: corrective bolus after meal during control phase
time frame: 4 weeks
description: total number of active events per person during the weeks of Control Phase vs Intervention Phase
measure: corrective bolus after meal 1
time frame: up to 24 hours
description: total number of active events per person after meal 1 for the entire day
measure: corrective bolus after meal after meal 2
time frame: up to 24 hours
description: total number of active events per person after meal 2 for the entire day
measure: corrective bolus after meal after meal 3
time frame: up to 24 hours
description: total number of active events per person after meal 3 for the entire day
measure: corrective bolus after meal during intervention phase
time frame: 4 weeks
description: total number of active events per person during the weeks of Intervention Phase
arm group label: All participants
arm group type: Experimental
description: +Pediatric patients with T1D. All comparisons will be made within group pre and post intervention.
intervention type: Other
intervention name: individualized insulin sensitivity index (ISind)
description: The new insulin sensitivity index, named "SISP" is calculated from data derived from insulin pump and glucose monitoring (CGM) uploads.
arm group label: All participants
criteria: 
gender: All
minimum age: 12 Years
maximum age: 21 Years
healthy volunteers: No
last name: Eda Cengiz, MD
role: Study Chair
affiliation: Yale University
facility: 
country: United States
responsible party type: Sponsor
mesh term: Insulin Resistance
mesh term: Insulin