MEtabolic and Renal Effects of AutoMAted Insulin Delivery Systems in Youth With Type 1 Diabetes Mellitus (MERMAID-T1D)
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ClinicalTrials.gov Identifier: NCT03945747 |
Recruitment Status :
Recruiting
First Posted : May 10, 2019
Last Update Posted : October 27, 2020
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Condition or disease | Intervention/treatment |
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Type1 Diabetes Mellitus Diabetes Mellitus, Type 1 Autoimmune Diabetes Juvenile Diabetes Diabetes Mellitus Complication Diabetic Nephropathies Metabolic Disease Diabetic Kidney Disease | Diagnostic Test: Blood draw Diagnostic Test: Urine sample collection Diagnostic Test: DXA scan |
Background: Over 1.25 million Americans have type 1 diabetes mellitus (T1DM), significantly increasing the risk of early death from cardio-renal disease. Per the American Diabetes Association, only 14% of children with T1DM meet glycemic targets [Wood et al. Diabetes Care 2013; 36:2035-37]. This is a severe and pervasive problem, as a child diagnosed with T1DM today is expected to live up to 17 years less than non-diabetic peers. It is established that time outside of goal glycemic target range increases the likelihood of developing micro- and macro-vascular diabetic complications including diabetic kidney disease (DKD) and cardiovascular disease (CVD). However, metabolic risk factors beyond glycemic control including insulin resistance and obesity are also increasingly recognized to contribute to the increased risk of DKD and CVD. Automated insulin delivery (AID) systems such as the hybrid closed loop artificial pancreas (HCL AP) combine use of an insulin pump, continuous glucose monitor (CGM), and a control algorithm to adjust background insulin delivery to improve time in target range. AID systems such as the predictive low glucose suspend (PLGS) system pause insulin delivery to try to reduce hypoglycemia. AID systems are now seeing markedly increased commercial use; however, the long-term effects on insulin sensitivity, body mass index (BMI), cardio-metabolic markers, and kidney function have not yet been studied. Preliminary basic science research suggests that periods of rest from insulin exposure provided by AID systems may have positive effects on DKD and CVD risk. In this proposal we intend to investigate the gap in knowledge between glycemic changes seen with AID systems and the impact on markers of long-term complications.
Specific Aims and Hypotheses:
Specific Aim 1: To examine the effects of the AID systems on glycemic control and insulin sensitivity as compared to traditional insulin pumps and multiple daily injections in youth with T1DM Hypothesis 1.1: Treatment with the AID systems improves glycemic control in youth with T1DM Hypothesis 1.2: Treatment with the AID systems increases insulin sensitivity and decreases insulin requirement in youth with T1DM
Specific Aim 2: To examine the effects of the AID systems on kidney function and metabolic markers as compared to traditional insulin pumps and multiple daily injections in youth with T1DM Hypothesis 2.1: Treatment with the AID systems improves metabolic markers in youth with T1DM Hypothesis 2.2: Treatment with the AID systems improves kidney function in youth with T1DM
Design: This study is a pilot study aimed at recruiting youth ages 7 to 18 years from the following 3 groups with T1DM: control participants on either multiple daily injections or conventional pump therapy, youth being transitioned to a HCL AP system, and youth being transitioned to a PLGS system. Exclusion criteria include non-T1DM, non-insulin blood glucose altering medications, pregnancy, breastfeeding, or a ketogenic diet. We plan to complete a physical exam with pubertal staging, collect information on recent insulin usage and dosages, fasting serum and urine samples, and a DXA scan before the participant transitions to either a HCL AP or a PLGS system, if applicable. Following 3-6 months of treatment we will then collect the identical data as at baseline. Outcome measures include CGM data, total daily insulin dose, time suspended from insulin delivery, height, weight, BMI, waist circumference, hip circumference, blood pressure, HbA1c, c-peptide, total cholesterol, HDL, LDL, triglycerides, adiponectin, and DXA scan to evaluate cardio-metabolic markers and calculate insulin sensitivity, as well as serum creatinine, cystatin c, copeptin, and urine microalbumin to evaluate kidney health and calculate GFR by Zappitelli and FAS equations.
Study Type : | Observational |
Estimated Enrollment : | 50 participants |
Observational Model: | Case-Control |
Time Perspective: | Prospective |
Official Title: | MEtabolic and Renal Effects of AutoMAted Insulin Delivery Systems in Youth With Type 1 Diabetes Mellitus (MERMAID-T1D) |
Actual Study Start Date : | August 14, 2019 |
Estimated Primary Completion Date : | July 2021 |
Estimated Study Completion Date : | July 2021 |

Group/Cohort | Intervention/treatment |
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Control group
Individuals continue current treatment regimen with either standard insulin pump therapy or multiple daily insulin injections for the duration of the study.
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Diagnostic Test: Blood draw
Participants will undergo a blood collection for hemoglobin A1c, adiponectin, total cholesterol, LDL, HDL, triglycerides, and c-peptide at baseline and follow up in 3-6 months. Diagnostic Test: Urine sample collection Participants will undergo urine sample collection for urine microalbumin and urine creatinine at baseline and follow up in 3-6 months. Diagnostic Test: DXA scan Participants will undergo a DXA scan for lean and fat mass measurements at baseline and follow up in 3-6 months. |
Hybrid closed-loop artificial pancreas system group
Individuals transition from either standard insulin pump therapy or multiple daily injections to a hybrid closed-loop system at the beginning of the study after initial labs and imaging studies are completed.
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Diagnostic Test: Blood draw
Participants will undergo a blood collection for hemoglobin A1c, adiponectin, total cholesterol, LDL, HDL, triglycerides, and c-peptide at baseline and follow up in 3-6 months. Diagnostic Test: Urine sample collection Participants will undergo urine sample collection for urine microalbumin and urine creatinine at baseline and follow up in 3-6 months. Diagnostic Test: DXA scan Participants will undergo a DXA scan for lean and fat mass measurements at baseline and follow up in 3-6 months. |
Predictive low glucose suspend system group
Individuals transition from either standard insulin pump therapy or multiple daily injections to a predictive low glucose suspend system at the beginning of the study after initial labs and imaging studies are completed.
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Diagnostic Test: Blood draw
Participants will undergo a blood collection for hemoglobin A1c, adiponectin, total cholesterol, LDL, HDL, triglycerides, and c-peptide at baseline and follow up in 3-6 months. Diagnostic Test: Urine sample collection Participants will undergo urine sample collection for urine microalbumin and urine creatinine at baseline and follow up in 3-6 months. Diagnostic Test: DXA scan Participants will undergo a DXA scan for lean and fat mass measurements at baseline and follow up in 3-6 months. |
- Change in estimated insulin sensitivity [ Time Frame: 3-6 months ]Estimated by calculating the eIS, Pittsburgh eGDR, and SEARCH IS equations
- Change in estimated glomerular filtration rate (GFR) [ Time Frame: 3-6 months ]Estimated by calculating the Zappitelli (CysCrEq) and eGFR-FAS (using serum creatinine) equations
- Change in body mass index (BMI) [ Time Frame: 3-6 months ]Measured by evaluations of height and weight
- Change in lipid profile [ Time Frame: 3-6 months ]Measured by fasting blood draw for total cholesterol, LDL, HDL, and triglycerides
- Change in c-peptide [ Time Frame: 3-6 months ]Measured by fasting blood draw for c-peptide level
- Change in DXA scan [ Time Frame: 3-6 months ]Evaluation of lean and fat mass by DXA scan
Biospecimen Retention: Samples Without DNA

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Ages Eligible for Study: | 7 Years to 18 Years (Child, Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Sampling Method: | Non-Probability Sample |
Inclusion Criteria:
- Age 7-18 years
- Type 1 diabetes with at least two of the following criteria: diabetes-associated antibody-positivity, rapid conversion to insulin requirement after diagnosis, absent c-peptide, or DKA at diagnosis
- Currently receiving insulin therapy by multiple daily injections or standard insulin pump therapy
Exclusion Criteria:
- Non-type 1 diabetes mellitus
- Pregnant or breastfeeding
- Receiving treatment with non-insulin glucose-altering medications including oral anti-hyperglycemic medications, steroids, or antipsychotics
- Following a ketogenic diet

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03945747
Contact: Kalie L Tommerdahl, MD | 720-777-5898 | Kalie.Tommerdahl@childrenscolorado.org | |
Contact: Kristen J Nadeau, MD, MS | 720-777-2855 | Kristen.Nadeau@childrenscolorado.org |
United States, Colorado | |
Children's Hospital Colorado | Recruiting |
Aurora, Colorado, United States, 80045 | |
Contact: Kalie L Tommerdahl, MD 720-777-5898 Kalie.Tommerdahl@childrenscolorado.org | |
Contact: Kristen J Nadeau, MD, MS 720-777-2855 Kristen.Nadeau@childrenscolorado.org |
Responsible Party: | University of Colorado, Denver |
ClinicalTrials.gov Identifier: | NCT03945747 |
Other Study ID Numbers: |
18-1558 UL1TR002535 ( U.S. NIH Grant/Contract ) 5T32DK063687-15 ( U.S. NIH Grant/Contract ) |
First Posted: | May 10, 2019 Key Record Dates |
Last Update Posted: | October 27, 2020 |
Last Verified: | October 2020 |
Individual Participant Data (IPD) Sharing Statement: | |
Plan to Share IPD: | Undecided |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | No |
Automated insulin delivery systems Insulin sensitivity Cardiometabolic function Renal function |
Kidney Diseases Diabetic Nephropathies Diabetes Mellitus Diabetes Mellitus, Type 1 Metabolic Diseases Diabetes Complications |
Glucose Metabolism Disorders Endocrine System Diseases Urologic Diseases Autoimmune Diseases Immune System Diseases |