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MEtabolic and Renal Effects of AutoMAted Insulin Delivery Systems in Youth With Type 1 Diabetes Mellitus

MEtabolic and Renal Effects of AutoMAted Insulin Delivery Systems in Youth With Type 1 Diabetes Mellitus (MERMAID-T1D)

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03945747
Acronym
MERMAID-T1D
Enrollment
50
Registered
2019-05-10
Start date
2019-08-14
Completion date
2026-08-01
Last updated
2025-03-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type1 Diabetes Mellitus, Diabetes Mellitus, Type 1, Autoimmune Diabetes, Juvenile Diabetes, Diabetes Mellitus Complication, Diabetic Nephropathies, Metabolic Disease, Diabetic Kidney Disease

Keywords

Automated insulin delivery systems, Insulin sensitivity, Cardiometabolic function, Renal function

Brief summary

In type 1 diabetes (T1DM), automated insulin delivery (AID) systems such as the hybrid closed loop artificial pancreas (HCL AP) combine the use of an insulin pump, continuous blood sugar monitor, and control algorithm to adjust background insulin delivery to improve time in target blood sugar range. Systems such as the predictive low glucose suspend system (PLGS) pause insulin delivery to try and reduce low blood sugars. We aim to complete a pilot study involving recruitment of youth ages 7 to 18 years from the following groups with type 1 diabetes: control participants consisting of youth on either multiple daily insulin injections or conventional insulin pump therapy that plan to continue with their current treatment modality, youth being transitioned to the HCL AP system, and youth being transitioned to the PLGS system. Individuals will be recruited into each of the aforementioned study groups based on their own expressed desire to either continue on MDI/standard insulin pump therapy or transition to either the HCL AP or PLGS systems. The decision to either continue with current therapy or transition therapy will remain entirely up to the participant and their family and will be based on personal preference and insurance coverage for that individual. We will not be randomizing the participants to any given treatment group during this study but rather will be recruiting based on the participant's decision. We would like to complete a physical exam with pubertal staging, collect blood and urine samples to evaluate cardiometabolic and renal markers, and complete a DXA scan to evaluate total lean and fat mass. After 3-6 months of either continuation of current treatment with either multiple daily insulin injections or conventional insulin pump therapy or transitioning to the HCL AP or PLGS systems, we would like to repeat the previously described blood, urine, and imaging tests for comparison. We are interested in examining the impact of the HCL AP and PLGS systems on maintaining blood sugars in target range, insulin sensitivity, and markers of cardiometabolic and renal function. We hypothesize that pauses in insulin delivery, as seen in the setting of automated insulin delivery systems, will result in improvements in insulin sensitivity, cardiometabolic markers, and renal function markers.

Detailed description

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.

Interventions

DIAGNOSTIC_TESTBlood 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.

Participants will undergo urine sample collection for urine microalbumin and urine creatinine at baseline and follow up in 3-6 months.

DIAGNOSTIC_TESTDXA scan

Participants will undergo a DXA scan for lean and fat mass measurements at baseline and follow up in 3-6 months.

Sponsors

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
CollaboratorNIH
Colorado Clinical & Translational Sciences Institute
CollaboratorOTHER
National Center for Advancing Translational Sciences (NCATS)
CollaboratorNIH
University of Colorado, Denver
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
7 Years to 18 Years
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Change in estimated insulin sensitivity3-6 monthsEstimated by calculating the eIS, Pittsburgh eGDR, and SEARCH IS equations

Secondary

MeasureTime frameDescription
Change in estimated glomerular filtration rate (GFR)3-6 monthsEstimated by calculating the Zappitelli (CysCrEq) and eGFR-FAS (using serum creatinine) equations
Change in body mass index (BMI)3-6 monthsMeasured by evaluations of height and weight
Change in lipid profile3-6 monthsMeasured by fasting blood draw for total cholesterol, LDL, HDL, and triglycerides
Change in c-peptide3-6 monthsMeasured by fasting blood draw for c-peptide level
Change in DXA scan3-6 monthsEvaluation of lean and fat mass by DXA scan

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026