<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/NCT03835208</url>
  </required_header>
  <id_info>
    <org_study_id>HMKvLMK</org_study_id>
    <nct_id>NCT03835208</nct_id>
  </id_info>
  <brief_title>Effect of Carbohydrate Distribution on Blood Glucose in Women With Gestational Diabetes Mellitus (GDM)</brief_title>
  <official_title>The Effect of High-morning-carbohydrate Intake Versus Low-morning-carbohydrate Intake on Glycemic Variability Measured by Continuous Glucose Monitoring in GDM Patients - a Randomized Crossover Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Aarhus</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>University of Copenhagen</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Aarhus</source>
  <oversight_info>
    <has_dmc>Yes</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 study aims to investigate whether high-morning carbohydrate intake (HMK) compared with&#xD;
      low-morning carbohydrate intake (LMK) affects glycemic variability in GDM patients based on&#xD;
      Continuous glucose monitoring (CGM).&#xD;
&#xD;
      High carbohydrate morning intake is expected to reduce hyperglycemic episodes and stabilize&#xD;
      blood glucose compared with low morning carbohydrate intake.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Background:&#xD;
&#xD;
      Women with GDM have an increased risk of macrosomia, cesarean section, birth defects and long&#xD;
      term complications such as an increased risk, in both mother and child, to develop type 2&#xD;
      diabetes.&#xD;
&#xD;
      According to Invitro and invivo studies of type 1 and 2 diabetes, great variations in blood&#xD;
      glucose levels caused more complications than constantly elevated glucose levels. This study,&#xD;
      therefore, intends to use Continuous glucose monitoring (CGM) for day-to-day monitoring of&#xD;
      glycemic variability, including frequency, duration, and magnitude of hyperglycaemic&#xD;
      fluctuations.&#xD;
&#xD;
      Carbohydrate is the macronutrient that has the greatest impact on postprandial blood glucose&#xD;
      response. Despite this, there is a current lack of evidence of how the carbohydrate intake&#xD;
      should be distributed throughout a day.&#xD;
&#xD;
      This study aims to investigate whether high-morning carbohydrate intake (HMK) compared to&#xD;
      low-morning carbohydrate intake (LMK) affects glycemic variability in GDM patients.&#xD;
&#xD;
      Design:&#xD;
&#xD;
      Randomized crossover intervention study comparing two intervention diets; high-morning&#xD;
      carbohydrate intake (HMK) versus low-morning carbohydrate intake (LMK) each of 3 days&#xD;
      duration with four-day washout.&#xD;
&#xD;
      Diet intervention: Both intervention diets have the same calorie content and contain the same&#xD;
      amounts of protein, carbohydrate and fat for the individual patient, but the distribution of&#xD;
      carbohydrate and energy differs throughout the day.&#xD;
&#xD;
      Dietary intake will be estimated through 24-hour recall interview by trained dietitians.&#xD;
      Estimation of actual intake is validated by photos of every main meal.&#xD;
&#xD;
      All data will be collected and stored in RedCap to secure data checks.&#xD;
&#xD;
      Statistics Analysis and sample size:&#xD;
&#xD;
      Power calculation on primary outcome MAGE- estimates 15 patients for inclusion with a power&#xD;
      of 80%, SD 0,6mmol/l, a significance level of 0,05 and a MIREDIF of 0,5 mmol/l. 15 persons&#xD;
      include an expected dropout rate at 20%.&#xD;
&#xD;
      Non-parametric tests will be used for the secondary and primary outcome.&#xD;
&#xD;
      Perspective:&#xD;
&#xD;
      A future perspective of this study is to improve the current treatment in regards to&#xD;
      nutritional recommendations. Thus, the study could potentially contribute with the knowledge&#xD;
      that would clarify the carbohydrate recommendations and improve the glycemic control of&#xD;
      patients with GDM and therefore be beneficial to patients' future treatment and prevent&#xD;
      complications and development of type 2 diabetes in the child.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Enrolling by invitation</last_known_status>
  <start_date type="Actual">February 25, 2019</start_date>
  <completion_date type="Anticipated">May 1, 2020</completion_date>
  <primary_completion_date type="Actual">September 27, 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Crossover Assignment</intervention_model>
    <intervention_model_description>Each patient will follow the HMK and LMK diet in a period of 2x3 days in randomized order with a four day washout between. The order of the two diets will be assigned randomly.</intervention_model_description>
    <primary_purpose>Treatment</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>mean amplitude of glucose excursions (MAGE)</measure>
    <time_frame>6 days</time_frame>
    <description>An index for glycemic variability assessment MAGE is the average variation in amplitude and is calculated as the mean of absolute value differences between adjacent glucose peaks and valleys, where the differences exceed 1 Standard Deviation (SD) from the mean.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Coefficient of variation</measure>
    <time_frame>6 days</time_frame>
    <description>Coefficient of variation</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>MBG</measure>
    <time_frame>6 days</time_frame>
    <description>The average blood glucose, calculated for each two intervention periods using CGM data.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Glucagon-like-peptide 1 (GLP1)</measure>
    <time_frame>1 hour *2</time_frame>
    <description>glucagon-like-peptide 1, difference in 1 hour postprandial response</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Gastric inhibitory polypeptide (GIP)</measure>
    <time_frame>1 hour*2</time_frame>
    <description>Gastric inhibitory polypeptide difference in 1 hour postprandial response</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>C-peptide</measure>
    <time_frame>11 days</time_frame>
    <description>Changes in C-peptide according to carbohydrate distribution</description>
  </secondary_outcome>
  <other_outcome>
    <measure>3-hydroxy-butyrate</measure>
    <time_frame>11 days</time_frame>
    <description>To assess ketonemia</description>
  </other_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">15</enrollment>
  <condition>Diabetes, Gestational</condition>
  <arm_group>
    <arm_group_label>Low-morning-carbohydrate</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Low morning intake and high evening intake of carbohydrates. This means a distribution of carbohydrate as follows:&#xD;
10% morning, 40% lunch, 50% dinner. The overall recommendations for macro- and micronutrient intake for GDM patients will be met.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>High-morning-carbohydrate</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>High morning intake and low evening intake of carbohydrates.&#xD;
This means a distribution of carbohydrate as follows:&#xD;
50% morning, 40% lunch, 10% dinner. The overall recommendations for macro- and micronutrient intake for GDM patients will be met.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>High/low carbohydrate distribution</intervention_name>
    <description>A total of 2x3 days, were the patient follow a detailed diet plan. For 3 days they follow a diet plan where the majority of the carbohydrates are located on either the first part of the day(HMK) or the last part of the day(LMK). 4 days of washout are placed between the two interventions. They will not receive food but will be guided by a trained dietitian and the use of a meal plan.</description>
    <arm_group_label>High-morning-carbohydrate</arm_group_label>
    <arm_group_label>Low-morning-carbohydrate</arm_group_label>
    <other_name>High-energy breakfasting compared with high-energy dinner</other_name>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Gestational diabetes mellitus diagnosed according to current WHO criteria for a 2-hour&#xD;
             oral glucose tolerance test (OGTT) &gt; 8.5 mmol/l&#xD;
&#xD;
          -  Non-insulin depending&#xD;
&#xD;
          -  Adult 18+ years&#xD;
&#xD;
          -  Gestational age weeks 30-36 at start of inclusion&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Diagnosed with celiac disease&#xD;
&#xD;
          -  Received bariatric surgery&#xD;
&#xD;
          -  Diagnosed eating disorder&#xD;
&#xD;
          -  Insulin-dependent diabetes at trial start&#xD;
&#xD;
          -  Known with type 2 diabetes before pregnancy&#xD;
&#xD;
          -  Children under 18 years&#xD;
&#xD;
          -  Starting up in insulin during the intervention period&#xD;
&#xD;
          -  Diagnosed with lactose intolerance&#xD;
&#xD;
          -  Goes into labor before the intervention is completed&#xD;
      </textblock>
    </criteria>
    <gender>Female</gender>
    <gender_based>Yes</gender_based>
    <gender_description>pregnant women</gender_description>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Per G Ovesen, Dr.Med</last_name>
    <role>Study Director</role>
    <affiliation>Women's diseases and births</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University hospital Aarhus</name>
      <address>
        <city>Skejby</city>
        <state>Aarhus N</state>
        <zip>8200</zip>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>University of Aarhus</name>
      <address>
        <city>Skejby</city>
        <state>Aarhus N</state>
        <zip>8200</zip>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Denmark</country>
  </location_countries>
  <verification_date>July 2019</verification_date>
  <study_first_submitted>February 7, 2019</study_first_submitted>
  <study_first_submitted_qc>February 7, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 8, 2019</study_first_posted>
  <last_update_submitted>September 27, 2019</last_update_submitted>
  <last_update_submitted_qc>September 27, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">September 30, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>gestational diabetes</keyword>
  <keyword>carbohydrate distribution</keyword>
  <keyword>high/low carbohydrate</keyword>
  <keyword>glycemic variability</keyword>
  <keyword>MAGE</keyword>
  <keyword>continuous glucose monitoring</keyword>
  <keyword>Pregnancy in Diabetics</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Diabetes, Gestational</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/NCT03835208
org study id: HMKvLMK
nct id: NCT03835208
lead sponsor: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
This study aims to investigate whether high-morning carbohydrate intake (HMK) compared with
      low-morning carbohydrate intake (LMK) affects glycemic variability in GDM patients based on
      Continuous glucose monitoring (CGM).

      High carbohydrate morning intake is expected to reduce hyperglycemic episodes and stabilize
      blood glucose compared with low morning carbohydrate intake.
Background:

      Women with GDM have an increased risk of macrosomia, cesarean section, birth defects and long
      term complications such as an increased risk, in both mother and child, to develop type 2
      diabetes.

      According to Invitro and invivo studies of type 1 and 2 diabetes, great variations in blood
      glucose levels caused more complications than constantly elevated glucose levels. This study,
      therefore, intends to use Continuous glucose monitoring (CGM) for day-to-day monitoring of
      glycemic variability, including frequency, duration, and magnitude of hyperglycaemic
      fluctuations.

      Carbohydrate is the macronutrient that has the greatest impact on postprandial blood glucose
      response. Despite this, there is a current lack of evidence of how the carbohydrate intake
      should be distributed throughout a day.

      This study aims to investigate whether high-morning carbohydrate intake (HMK) compared to
      low-morning carbohydrate intake (LMK) affects glycemic variability in GDM patients.

      Design:

      Randomized crossover intervention study comparing two intervention diets; high-morning
      carbohydrate intake (HMK) versus low-morning carbohydrate intake (LMK) each of 3 days
      duration with four-day washout.

      Diet intervention: Both intervention diets have the same calorie content and contain the same
      amounts of protein, carbohydrate and fat for the individual patient, but the distribution of
      carbohydrate and energy differs throughout the day.

      Dietary intake will be estimated through 24-hour recall interview by trained dietitians.
      Estimation of actual intake is validated by photos of every main meal.

      All data will be collected and stored in RedCap to secure data checks.

      Statistics Analysis and sample size:

      Power calculation on primary outcome MAGE- estimates 15 patients for inclusion with a power
      of 80%, SD 0,6mmol/l, a significance level of 0,05 and a MIREDIF of 0,5 mmol/l. 15 persons
      include an expected dropout rate at 20%.

      Non-parametric tests will be used for the secondary and primary outcome.

      Perspective:

      A future perspective of this study is to improve the current treatment in regards to
      nutritional recommendations. Thus, the study could potentially contribute with the knowledge
      that would clarify the carbohydrate recommendations and improve the glycemic control of
      patients with GDM and therefore be beneficial to patients' future treatment and prevent
      complications and development of type 2 diabetes in the child.
allocation: Randomized
intervention model: Crossover Assignment
intervention model description: Each patient will follow the HMK and LMK diet in a period of 2x3 days in randomized order with a four day washout between. The order of the two diets will be assigned randomly.
primary purpose: Treatment
masking: None (Open Label)
measure: mean amplitude of glucose excursions (MAGE)
time frame: 6 days
description: An index for glycemic variability assessment MAGE is the average variation in amplitude and is calculated as the mean of absolute value differences between adjacent glucose peaks and valleys, where the differences exceed 1 Standard Deviation (SD) from the mean.
measure: Coefficient of variation
time frame: 6 days
description: Coefficient of variation
measure: MBG
time frame: 6 days
description: The average blood glucose, calculated for each two intervention periods using CGM data.
measure: Glucagon-like-peptide 1 (GLP1)
time frame: 1 hour *2
description: glucagon-like-peptide 1, difference in 1 hour postprandial response
measure: Gastric inhibitory polypeptide (GIP)
time frame: 1 hour*2
description: Gastric inhibitory polypeptide difference in 1 hour postprandial response
measure: C-peptide
time frame: 11 days
description: Changes in C-peptide according to carbohydrate distribution
measure: 3-hydroxy-butyrate
time frame: 11 days
description: To assess ketonemia
arm group label: Low-morning-carbohydrate
arm group type: Experimental
description: Low morning intake and high evening intake of carbohydrates. This means a distribution of carbohydrate as follows:
10% morning, 40% lunch, 50% dinner. The overall recommendations for macro- and micronutrient intake for GDM patients will be met.
arm group label: High-morning-carbohydrate
arm group type: Experimental
description: High morning intake and low evening intake of carbohydrates.
This means a distribution of carbohydrate as follows:
50% morning, 40% lunch, 10% dinner. The overall recommendations for macro- and micronutrient intake for GDM patients will be met.
intervention type: Behavioral
intervention name: High/low carbohydrate distribution
description: A total of 2x3 days, were the patient follow a detailed diet plan. For 3 days they follow a diet plan where the majority of the carbohydrates are located on either the first part of the day(HMK) or the last part of the day(LMK). 4 days of washout are placed between the two interventions. They will not receive food but will be guided by a trained dietitian and the use of a meal plan.
arm group label: High-morning-carbohydrate
arm group label: Low-morning-carbohydrate
other name: High-energy breakfasting compared with high-energy dinner
criteria: 
gender: Female
gender based: Yes
gender description: pregnant women
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Per G Ovesen, Dr.Med
role: Study Director
affiliation: Women's diseases and births
facility: 
facility: 
country: Denmark
responsible party type: Sponsor
mesh term: Diabetes, Gestational
sharing ipd: No