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.