Development of an Advisory System for Glycemic Control During the Menstrual Cycle in Patient With Type 1 Diabetes
This overall research goal will be to develop a mobile-based module to improve glycemic control during the menstrual cycle in women with Type 1 diabetes mellitus (T1DM). This module will run on an Android Operating System (OS) and will be available as: (i) a stand-alone application and (ii) an important additional component to a larger system, the Diabetes Assistant (DiAs) - a mobile-based medical platform for diabetes applications. This proposal aims to build one such application or module targeting the improvement of diabetes control in younger women who experience glucose variation related to their menstrual cycle.
Type 1 Diabetes Mellitus
|Study Design:||Observational Model: Case-Only
Time Perspective: Prospective
|Official Title:||Development of an Advisory System for Glycemic Control During the Menstrual Cycle in Patient With Type 1 Diabetes|
- Luteal Phase Hyperglycemic Risk [ Time Frame: 28 days ] [ Designated as safety issue: No ]Our primary outcome measure is hyperglycemia risk during the luteal phase of the menstrual cycle. The primary hypothesis is there is an increased hyperglycemia risk during the luteal phase when compared to the follicular phase. Subjects will be compared to themselves across the three menstrual cycles captured. Hyperglycemia will be primarily assessed by high blood glucose index.
- Glycemic Changes during Luteal Phase [ Time Frame: 28 days ] [ Designated as safety issue: No ]Changes in estrogen and progesterone will be primary drivers of hyperglycemia risk during the luteal phase. These data will be analyzed as continuous variables.
- Insulin Requirement during Menstrual Cycle [ Time Frame: 28 days ] [ Designated as safety issue: No ]Insulin requirements will increase during the luteal phase compared to the follicular phase.
- Follicular Phase Hypoglycemia Risk [ Time Frame: 28 days ] [ Designated as safety issue: Yes ]There is an increased hypoglycemia risk during the early follicular phase of the menstrual cycle. Variables assessed will include low blood glucose index (LBGI) and average daily risk ratio (ADRR).
Biospecimen Retention: Samples Without DNA
At each follow-up visit #3-13, blood will be taken to sample estradiol, progesterone, luteinizing hormone (LH), follicle-stimulating hormone (FSH), total testosterone and sex-hormone binding globulin (SHBG). At the end of study visit #14, a hemoglobin A1c will be measured.
|Study Start Date:||August 2012|
|Estimated Study Completion Date:||July 2013|
|Estimated Primary Completion Date:||July 2013 (Final data collection date for primary outcome measure)|
The purpose of this particular protocol is to study the underlying glycemic variability across the menstrual cycle in women with T1DM. A subset of premenopausal women with T1DM experience loss of glucose control during the latter half of the cycle (the luteal phase). Clinical trials are sparse and tools are limited to focus on this aspect of diabetes care which is highly relevant in affected individuals. To obtain data to initialize this mobile-based module, we will enroll premenopausal women for approximately three-month outpatient study designed to characterize at least three complete menstrual cycles. These subjects will wear continuous glucose monitors (CGMs), record self-monitored blood glucoses (SMBGs) and utilize an insulin pump to capture insulin dosing. In-home ovulation kits will be used to determine relevant days for sex-steroid blood measurements to define menstrual cycle phases. Finally, structured at-home meals will be provided during different phases of the menstrual cycle for insulin action parameters assessments.
The software module will be developed in parallel with the data collection from study subjects. The software module will not be used with the patients in this study as it is not in existence as would be developed in parallel. The goal of the module functionality will be to 1) assist patients and providers in the identification and management of glycemic variability surrounding the menstrual cycle and 2) add value to and become an integral module within the artificial pancreas.
|Contact: Molly K. McElwee, RNemail@example.com|
|Contact: Mary C. Oliveri, CCRPfirstname.lastname@example.org|
|United States, Virginia|
|University of Virginia Center for Diabetes Technology||Recruiting|
|Charlottesville, Virginia, United States, 22904|
|Sub-Investigator: Boris P. Kovatchev, PhD|
|Sub-Investigator: Marc D. Breton, PhD|
|Sub-Investigator: Patrick Keith-Hynes, PhD|
|Sub-Investigator: Colleen Hughes-Karvetski, PhD|
|Sub-Investigator: Stacey M. Anderson, MD|
|Sub-Investigator: Susan M Demartini, MD|
|Principal Investigator:||Sue M. Brown, MD||University of Virginia|