Date of Award

January 2020

Document Type

Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

Leah Ferrucci

Abstract

Pregnant women with type 1 diabetes (T1D) experience increased glycemic variability as a result of changing insulin sensitivity and resistance throughout gestation. Therefore, strategies that help pregnant women with T1D manage their glycemic control are of great interest. We examined whether remote monitoring of Continuous Glucose Monitor (CGM) data by friends and family affects glycemic variability during pregnancy compared to CGM use alone in a pilot non-randomized trial (n = 28). During preconception or the first trimester, women with T1D were placed in one of two groups based on device compatibility: (1) CGM Alone (n = 13): women without iPhone, iPad or iPod Touch; or (2) CGM Share (n = 15): women with iPhone, iPad, or iPod Touch and followers with devices compatible for data viewing. Linear mixed models and t-tests we used to compare indices of glycemic control and glycemic variability over time between groups and during each trimester. Mean sensor glucose was lower in the CGM Share group than the CGM Alone group (p = 0.003). Estimated hemoglobin A1c from CGM data decreased in both groups as pregnancy progressed and was significantly lower over time in women using CGM Share compared to CGM Alone (p = 0.028). Glucose management index was also lower among women in the CGM Share group (p = 0.041, Table 2). Average number of excursions above 200 mg/dL was higher in the CGM Alone group (p = 0.021). In this small pilot study, use of CGM with remote monitoring was associated with a lower risk of hyperglycemia, lower standard deviation, and lower area under the curve. However, other measures of glycemic variability including mean amplitude of glucose excursions, and coefficient of variation, were similar between groups. A larger, randomized study is warranted to confirm if CGM Share use helps pregnant women with T1D achieve tighter glucose control across multiple clinical measures.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 05/27/2022

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