INTRODUCTION
Gestational diabetes mellitus (GDM) is an abnormal glucose metabolism
where blood glucose does not reach the level of overt diabetes, with
onset or first recognition during pregnancy 1.
Largescale randomized controlled trials (RCTs) have shown that although,
screening and treatment for GDM are associated with improved short-term
outcomes 2, it failed to reduce rates of long-term
outcomes such as childhood obesity 3. This points to
the need for earlier screening and detection, followed by appropriate
management strategies that can help to reduce the occurrence of these
adverse outcomes.
GDM is typically diagnosed using an oral glucose tolerance test (OGTT)
between 24 and 28 weeks of gestation. However, prospective studies have
observed higher fetal adiposity 4, and growth velocity5 as early as 20 weeks of gestational age, preceding
the clinical diagnosis of GDM at 24-28 weeks of gestation. This was
corroborated by Graca et al. 6 who reported
increased amniotic fluid glucose concentrations representing maternal
plasma glucose transported across the placenta as early as the second
trimester in women later diagnosed with GDM. In a retrospective cohort
study, “early GDM” diagnosis (at an average of 17 weeks’ gestation) in
pregnant women had better composite neonatal outcomes than their
later-diagnosed peers (> 24 weeks) despite arguably
representing a higher-risk cohort 7. These findings
indicate that the effects of hyperglycaemia of GDM mothers on the
offspring are apparent at earlier timepoints (early second trimester),
pointing to the potential advantages of an earlier diagnosis than the
current recommended guidelines.
Glycaemic variability (GV) is defined as a degree to which blood glucose
level fluctuates between high and low levels, and is emerging as an
important metric used to characterize and detect subtle abnormalities in
glucose metabolism under usual ambulatory conditions. With the advent of
continuous glucose monitoring (CGM), it now is feasible to analyze the
changes in GV indicators, and to assess glycaemic control (GC)
throughout the day 8. Furthermore, the clinical
utility of the CGM to analyze GV and GC has been well demonstrated in
diabetic patients (Type 1 and Type 2 diabetes) by predicting risks for
diabetic complications 9, 10. In GDM patients, GV
parameters had been reported to be significantly higher in patients with
GDM compared to healthy controls in several cross-sectional studies11-14. Contrary to those studies, there were reports
of no significant differences 15 , or only borderline
differences 16 in the GV parameters between the GDM
and NDP group. However, these existing studies are mainly
cross-sectional 12-15, 17, and conducted from the late
second trimester (24 week of gestational age) onwards. To the best of
our knowledge, studies assessing early indicators of GV prior to
diagnosis of GDM are scarce. Moreover, available studies were primarily
conducted in Western populations 11, 12, 15-17, and
were not aligned to the core CGM metrics for clinical practice according
to the international consensus group, which includes a CGM wear-time for
a recommended 14 days and the analysis of percentage time spent in
glucose target ranges 9.
To fill this gap in literature, we aimed to prospectively associate
CGM-derived GV parameters and “time in ranges” in the first and second
trimester of pregnancy with the subsequent development of GDM using
longitudinal data from participants in the Integrating the Use of
Calibration-Free Continuous Monitoring for Pregnancy Glucose Profiling
(I-PROFILE) study. While some of the existing studies have only used two
or three parameters to represent glycaemic variability (15, 18, 19), we
chose to include a range of GV and GC parameters that are clinically
relevant 18 and suitable for GDM pregnant women10 which include: mean amplitude of glycaemic
excursion (MAGE), standard deviation of blood glucose (SDBG) and mean of
daily continuous 24 h blood glucose (MBG) and coefficient of variation
(CV) used commonly in available studies as measures of GV10. J-Index and percentage of time spent-in-range
(%TIR), time-above-target range (%TAR) and time-below-target range
(%TBR) will be measured as GC parameters 9, 19.
During a pregnancy in women with Type I or II Diabetes and GDM, the
overall goal is to increase %TIR, while reducing %TAR, %TBR and GV9. In this study, we hypothesize that there will be
higher MBG, SDBG, %CV, %TAR and %TBR, and lower J-Index and %TIR in
the first and second trimester of pregnancy in participants who
developed GDM compared to those who did not.