Continuous Glucose Monitoring Metrics and Birth Weight: Informing Management of Type 1 Diabetes Throughout Pregnancy

Despite advances in antenatal diabetes care, 60% of liveborn infants of mothers with type 1 diabetes (T1D) are born with a birth weight that is large for gestational age (LGA), which is unchanged from the first reports of so-called giant babies in 1941 (1–5). LGA birth weight > 90th percentile is associated with increased rates of obstetric and neonatal complications (e.g., preterm and operative delivery, neonatal hypoglycemia, and neonatal intensive care admission) (2,6). In severe cases, additional maneuvers are required to release the shoulders (shoulder dystocia), which can result in nerve injury, fractures, and hypoxic brain injury. This is the third most litigated obstetric-related complication in the U.K., incurring escalating National Health Service costs (7). Furthermore, LGA birth weight predisposes the infant to developing obesity, type 2 diabetes, and cardiovascular disease, persisting into adulthood (8,9). Optimal glucose control to prevent these outcomes is the major focus of antenatal care (10,11).

Continuous glucose monitoring (CGM) is revolutionizing diabetes care (12,13). Compared with HbA_1c or self-monitored capillary glucose, CGM provides up to 288 glucose measures per day, depending on the device used, providing detailed information about glucose changes across the 24-h day (12,13). It demonstrates complete 24-h glucose profiles with percentage of time spent in the target glucose range (time in range [TIR]) and high and low glucose excursions, which inform therapy decisions, thereby informing diabetes self-management (12,13). In T1D pregnancies, CGM improves maternal glucose, reducing LGA and associated neonatal complications (4). However, despite this technology becoming standard care (10,11), LGA prevalence remains high (2,4,5).

Pregnancy is a dynamic state of continuous metabolic adaptation, with changes in insulin sensitivity and glucose tolerance throughout (14). Pregnant women with T1D are reviewed frequently, and therapeutic decisions are made based on the previous week’s mean CGM glucose data (a combination of glucose summary metrics and 24-h glucose profiles); however, the weekly CGM glucose metrics and 24-h profiles associated with a normal birth weight baby are unknown. Therefore, despite widespread CGM use, international diabetes guidelines do not include gestationally appropriate CGM glucose targets (10–13). This analysis was designed to inform clinical care by determining gestational changes in CGM glucose metrics and 24-h profiles weekly during pregnancy and the relationship of these to birth weight outcomes.

The CGM data from two existing studies were combined (4,5). Full details of the CONCEPTT international clinical trial were previously published (4). Pregnant women aged 18–40 years, with HbA_1c between 6.5 and 10% (48 and 86 mmol/mol) using a pump or multiple daily insulin injections and a singleton fetus, were randomly assigned to the continuous real-time CGM (Guardian REAL-Time or MiniMed Minilink system; Medtronic, Northridge, CA) or control group, where they performed self-monitored blood glucose measurements at least seven times per day. CGM data were downloaded monthly in the real-time CGM group and at baseline and 24 and 34 weeks of gestation in the control group.

Full details of the Swedish observational study have also been published (5). It included women aged ≥ 18 years with a singleton pregnancy, who were using a Freestyle Libre or Dexcom G4 CGM device compatible with the internet-based Diasend system (Glooko, Gothenburg, Sweden) at two tertiary clinics in Sweden (Skåne University Hospital and Östra/Sahlgrenska University Hospital).

Women in both studies received specialist antenatal care, with clinic visits every 2 to 4 weeks. This analysis combines all the available raw downloaded continuous glucose data from 200 women in CONCEPTT and 186 women from the Swedish study, with complete birth weight records. Each participant had only one singleton pregnancy; 26% (102 of 386) of participants were using CGM prior to pregnancy. The number of participants contributing at least 4 days of CGM data for each gestational week is detailed in Supplementary Table 1.

The CONCEPTT study was approved by the Health Research Authority, East of England Research Ethics Committee, Essex, England, (12/EE/0310) for all U.K. sites and by each individual center for all other sites. The Swedish study was approved by the Ethics Committee of Lund University (2017/322), Lund, Sweden, and was conducted in accordance with the Swedish Act on Ethics Review of Research Involving Humans and the Swedish Act on Personal Data. All women gave written informed consent.

Electronic antenatal and perinatal records provided data on maternal age, parity, BMI, insulin regimen, birth weight, gestational age at birth, and sex of infant. LGA was defined as birth weight ≥90th percentile using Gestation Related Optimal Weight software, which adjusts for infant sex and gestational age, maternal height, weight, parity, and ethnicity (15).

For each participant and for each gestational week, the mean of each 5-min time interval was taken from the ≥4 days of temporal CGM data obtained at each time point across the 24-h day. A standard range of summary CGM metrics was calculated for each week’s gestation from the raw downloaded glucose data (12). These included mean CGM glucose concentration, percentage of time spent within the pregnancy target glucose range of 3.5–7.8 mmol/L (63–140 mg/dL) (TIR), and time spent above 7.8 mmol/L (>140 mg/dL) (TAR) and below 3.5 mmol/L (<63 mg/dL) target range (TBR). Measures of glycemic variability included coefficient of variation of mean CGM glucose and mean amplitude of glucose excursions (12). Weekly summary metrics were plotted for women with and without LGA birth weight infants. These were fitted using Epanechnikov kernel–weighted local polynomial smoothing, with 95% CIs to assess the significance of the relationship.

We performed functional data analysis as previously described to establish the population-level 24-h glucose profiles each week across gestation (16–20). For each participant and for each gestational week, the mean of each 5-min time interval was taken from the ≥4 days of temporal CGM data obtained at each time point across the 24-h day. In this way, there were no missing data for applying the functional data analysis. Changes in glucose over time were therefore assumed to be progressive, occurring in a trend or sequence that could be considered smooth (in a mathematic sense), without step changes from one measurement to the next. Sequential glucose concentrations from each measurement episode were modeled as trajectories by calculating continuous mathematic functions of CGM-derived glucose values (20).

The CGM glucose trajectories were modeled using the technique of fitting B-splines to the repeated measures (20). This generated a polynomial function that describes the curve (or spline) used to model changes in glucose levels over time for each participant, with splines required to pass though measured glucose values at discrete time points (called knots) during each 24-h period. At each of these knots, the spline function was required to be continuous (i.e., with no breaks or step changes) so that the function remained mathematically smooth. Knots were placed at 30-min intervals over each 24-h measurement period, with data from measurements recorded during the 4 h either side of midnight (i.e., from 2000 to 0400), repeated at the beginning and end to eliminate artifactual edge effects.

Multivariable regression analysis was used for the functional data analysis–generated glucose function to establish the relationship between weekly maternal glucose levels in women with and without LGA birth weight infants. To assess the significance of the relationship, 95% CIs were used. All statistical analyses were conducted in Stata (21) and R (22) software.

Data are available on request from the authors.

Baseline characteristics of the 386 participants are shown in Table 1. Swedish participants delivered slightly later, with higher birth weight and fewer preterm births and caesarean deliveries but remarkably similar customized birth weight percentiles (83%) and LGA rates (60%).

CGM metrics, weekly across gestation with 95% CIs, are shown in Fig. 1. Mean glucose fell steeply in the first 10 weeks of gestation in both normal and LGA birth weight mothers. By 10 weeks of gestation, a significant divergence in mean glucose emerged between women who went on to have a normal-sized versus LGA birth weight infant (7.1 vs. 7.6 mmol/L [128 vs. 137 mg/dL]). This between-group divergence persisted during 10–20 weeks and increased further during 20–30 weeks of gestation, after which glucose fell by ∼1 mmol/L (∼18 mg/dL) in both groups, reaching a nadir after 36 weeks of gestation.

CGM percentage of TIR started at 40% (9.6 h/day) in early pregnancy, with significant between-group differences from ∼6 to 8 weeks of gestation. Women who went on to have a normal-sized versus LGA birth weight infant reached 57 versus 50% TIR by ∼10 weeks of gestation. Similar to mean glucose, the divergence between groups in CGM TIR persisted during 10–20 weeks, increased further during 20–30 weeks, and remained significantly lower (by 8–10%) in the LGA birth weight group until 34 weeks of gestation. There were no between-group differences after 36 weeks, with both groups only achieving the recommended international consensus target of ≥70% TIR (16 h 48 min) late in the third trimester.

As expected from the changes in mean CGM glucose and percentage of TIR, both groups achieved striking early pregnancy reductions in hyperglycemia. CGM percentage of TAR (>7.8 mmol/L [140 mg/dL]) decreased from 60 to 40% by 10 weeks of gestation. From 10 weeks onward, a significant 5% TAR difference persisted between women with a normal-sized versus LGA birth weight infant (40 vs. 35%). This between-group divergence also increased, with increasing hyperglycemia in the LGA birth weight group during 18–28 weeks of gestation. CGM percentage of TAR then fell by ∼15% in both groups, with mothers of normal-sized infants only reaching the recommended international consensus target of ≤25% (6 h/day) late in the third trimester.

Maternal hypoglycemia, as measured by CGM percentage of TBR varied more than other glucose metrics, peaking at ∼10% (2.4 h/day) at 10 weeks. There were no between-group differences until ∼14 weeks of gestation, at which point TBR progressively decreased in the LGA birth weight group, reaching 6% by 30 weeks. CGM percentage of TBR remained above the recommended international consensus target of ≤4% (1 h/day), never falling below 8% in women with normal-sized babies. CGM percentage of TBR increased by 1.5% in both groups after 30 weeks of gestation.

Like hypoglycemia, glucose variability peaked in early pregnancy (coefficient of variation 38–40% at ∼10 weeks of gestation). This was followed by a sustained reduction in glucose variability measures throughout pregnancy, with less glycemic variability in mothers of LGA birth weight infants between 24 and 30 weeks of gestation. Mean amplitude glucose excursions also started high, with sustained gestational improvements, and remained slightly higher in mothers of LGA birth weight infants throughout 10–36 weeks of gestation.

Functional data analysis (Fig. 2 and Supplementary Video 1) showed week-by-week changes in the mean CGM glucose profile across the 24-h day. Women entered pregnancy (weeks 0–4) with CGM glucose levels that were predominantly above the upper target range limit of 7.8 mmol/L (140 mg/dL). Mean CGM glucose fell progressively until 10 weeks and plateaued between 10 and 30 weeks of gestation, until a further fall occurred from ∼30 weeks. The initial CGM glucose trajectory demonstrated a high overnight glucose pattern followed by a morning (0800–1200 h) dip. Thereafter, diurnal glucose levels increased with each meal as the day progressed, leading to high nocturnal glucose levels. From 7 weeks of gestation onward, women consistently demonstrated a nocturnal glucose dip, with higher daytime glucose levels and clear daytime peaks (at ∼1000 and 2200 h), which persisted until the end of pregnancy.

Multivariable regression of the functional data analysis (Fig. 3 and Supplementary Video 2) demonstrated the relationship of mean CGM glucose profiles across the 24-h day in women who went on to have LGA infants compared with those with normal birth weight infants. At 11 weeks, there was a significantly higher daytime glucose pattern in mothers of LGA infants, and from 12 weeks onward, this higher CGM glucose profile was evident for most of the 24-h day, with daytime peaks persisting until 35 weeks of gestation.

Internationally, many women with T1D are using CGM to optimize their glucose levels during pregnancy. Our analysis shows in detail how CGM glucose metrics change across pregnancy and identify the CGM glucose levels that are associated with having a normal birth weight baby. In doing so, it provides pregnant women and their clinical teams with the weekly CGM targets to aim for across pregnancy. Despite widespread CGM use, glycemic control targets are currently based on HbA_1c, which has well-documented gestational limitations (10,11,23). These data will inform international clinical guidelines and support patients and clinicians to use CGM more effectively, which will, it is hoped, help to improve glycemia and reduce LGA.

In clinical practice, the most recent week’s CGM metrics are reviewed, while the 24-h profiles are used to spot patterns of glucose excursions across the 24-h day when optimizing glucose management can achieve more TIR. We have analyzed our data to reproduce this clinical situation at a population level, providing weekly CGM metrics and 24-h profiles. This extensive temporal information demonstrates the central role of maternal glucose in the pathogenesis of LGA from early gestation. Importantly, we show a sustained difference of 0.5 mmol/L (9 mg/dL) in mean CGM glucose concentration across the 24-h day, every week, from 10 weeks of gestation onward in women who had an LGA infant. This small but clinically relevant (24) difference persisted for the rest of pregnancy, with increasing glycemic divergence until 30 weeks of gestation. By 12 weeks of gestation, the fetal pancreas can respond to maternal glucose by increasing endogenous insulin production (25). This leads to the incremental accrual of adipose tissue, fetal growth acceleration, and LGA birth weight in more than two-thirds of T1D pregnancies (25).

Our data show that achieving tight CGM glucose targets from early pregnancy (10–12 weeks of gestation) is associated with normal birth weight outcomes. Irrespective of baseline maternal glycemia, first trimester mean glucose levels decreased rapidly, without initial differences between women who went on to have a normal-sized or LGA birth weight infant. However, from 10 weeks of gestation, achieving a mean glucose of ≤7 mmol/L (≤126 mg/dL) was associated with having a normal-sized infant. Irrespective of baseline maternal glucose level, early intervention to optimize glycemia (specifically mean CGM glucose, CGM TIR, and CGM TAR) within the first 10 gestational weeks may help to reduce fetal growth acceleration and complications associated with LGA birth weight that are traditionally associated with glycemia in late pregnancy.

The recommended glucose target range for pregnancy is 3.5–7.8 mmol/L (63–140 mg/dL) (10–13). By examining the weekly 24-h profiles, we show that, before 10 weeks of gestation, most maternal glucose levels remained above target across the 24-h day. Thereafter, the 24-h CGM glucose profiles show that maternal glucose levels exceeded the recommended target, particularly at 1000 and 2200 h, which is consistent with postprandial rises following breakfast and evening meals. This was more pronounced in those women who had LGA infants. For optimal antenatal glycaemia and to achieve more TIR, targeting maternal dietary intake, along with the timing and accuracy of carbohydrate counting and prandial insulin doses for the morning and evening mealtimes, is required (26). This may require more emphasis on education and support prepregnancy and in early pregnancy. Future research should examine whether tighter overnight glucose targets (e.g., 3.5–5.5 mmol/L) are applicable or safely achievable.

Free from the increasingly recognized gestational limitations of HbA_1c, which fails to detect midtrimester plateauing or deteriorating glycemia (23), CGM TIR has become a key metric for monitoring antenatal glucose levels (27). An international consensus guideline has proposed that a CGM TIR target of >70% be recommended in pregnancy (13). This target is currently challenging to achieve, with the majority of women using CGM in addition to intensive insulin therapy (insulin pumps or multiple daily injections) only reaching this after 34 weeks of gestation (4,5). Our current analysis suggests that aiming for a CGM TIR of ≥55 to 60% by 10 weeks of gestation may be sufficient for normal fetal growth, aiming to achieve 70% thereafter. Additional dietary attention, psychoeducational support, and technologic interventions, such as closed-loop insulin delivery, may be required for women who do not achieve their pregnancy CGM glucose targets by 10 weeks (19).

Our study demonstrates that, in addition to CGM TIR, mean glucose and TAR are also clinically relevant CGM metrics in relation to birth weight. Achieving a mean glucose of ≤7.0 mmol/L (≤126 mg/dL) and spending no more than 35% TAR by 10 weeks were associated with normal fetal growth.

The first trimester fall in mean glucose concentration, which plateaued until 28 weeks of gestation, followed by a smaller third trimester reduction was remarkably consistent in women whose babies did and did not develop LGA. This supports previous work and suggests a large physiologic component to the glycemic changes, which mirror gestational changes in maternal insulin sensitivity, increasing in early gestation and decreasing during the second trimester, before increasing late in the third trimester (14,28). There is considerable clinician anxiety around a fall in maternal insulin requirements in the last trimester, suggesting placental insufficiency (29). Our data indicate that a fall in mean glucose, accompanied by a fall in CGM TAR and rise in TIR, is not unexpected in late pregnancy.

This is the largest cohort of CGM data from pregnant women with T1D. It included women using pumps and multiple daily injections, reflecting contemporary antenatal diabetes management. Combining two data sets makes it widely representative of women with T1D internationally and provides statistical power to assess glycemic differences across gestation. A potential limitation is that one data set was obtained from a randomized controlled trial, whereas the other was from an observational study. In doing so, we obtained data from several different CGM devices, of varying accuracy. However, while TIR may vary slightly between some devices, mean glucose has been shown to be consistent (30). Despite having 386 participants, data in any given week were available from fewer women, such that we had fewer CGM data at the start and end of pregnancy, as women presented for antenatal care and delivered their babies at different gestational ages (mean 37 weeks), which is likely to have contributed to the wider 95% CIs at these times. We did not have data available for all participants on the gestational week of their first antenatal clinic visit or when in relation to this CGM was started. While we used all eligible CGM raw data, we did not have the level of detail available on each participant to know if they chose not to wear the sensor or if the sensor malfunctioned or came off early, which may have contributed to loss of data. We acknowledge that sensor compliance was likely to be lower than that seen with the newer-generation CGM systems.

In summary, our results provide unprecedented insight into glucose physiology across gestation and the relationship between CGM glucose levels and birth weight in pregnant women with T1D. We have shown that normal birth weight is associated with achieving a significantly lower mean CGM glucose concentration (sustained across the 24-h day), higher CGM TIR, and lower CGM TAR from before the end of the first trimester, emphasizing the need for a paradigm shift in clinical management, with increased focus on using weekly CGM glucose targets to optimize maternal glycemia from early pregnancy.

Acknowledgments. The authors thank all the women with T1D who participated. They also acknowledge the invaluable support from the 31 clinical care teams and the CONCEPTT Steering Committee (Denice S. Feig, Helen R. Murphy, Elisabeth Asztalos, Jon F.R. Barrett, Rosa Corcoy, Alberto de Leiva, Lois E. Donovan, J. Moshe Hod, Lois Jovanovic, Erin Keely, Craig Kollman, Ruth McManus, Kellie E. Murphy, Katrina Ruedy, and George Tomlinson), the antenatal diabetes clinical team at Skåne University Hospital and Östra/Sahlgrenska University Hospital in Sweden (in particular Anastasia Katsarou, Nael Shaat, Annika Dotevall, Verena Sengpiel, Anders Elfvin, and Ulrika Sandgren), and the CGM data management team at the Parker Institute, Copenhagen, Denmark.

Funding. The CONCEPTT trial was funded by Juvenile Diabetes Research Foundation (JDRF) International grant 17-2011-533 and grants under the JDRF Canadian Clinical Trial Network, a public-private partnership including JDRF and FedDev Ontario and supported by JDRF Canada grant 80-2010-585. Medtronic supplied the CGM sensors and CGM systems at reduced cost. G.R.L., E.M.S., and H.R.M. were partially funded by Higher Education Funding Council for England and Medical Research Council grant MR/T001828/1. E.M.S. and H.R.M. were partially funded by National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation Programme grant EME 16/35/01, and H.R.M., was partially funded by NIHR Health Services and Delivery Research Programme grant CDF-2013-06-035. The Swedish study was funded by a research grant from Region Skåne, Sweden, and the Oak Foundation.

The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, National Institute for Health Research, or U.K. Department of Health.

Duality of Interest. E.M.S. has received honoraria for speaking from Abbott Diabetes Care and Eli Lilly. H.R.M. serves on the Medtronic European Scientific Advisory Board. D.S.F. has received funds from Novo Nordisk for serving on an expert panel. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. E.M.S. and H.R.M. designed this study. E.M.S., H.R.M., and G.R.L. wrote the manuscript, which all authors critically reviewed. H.R.M. and D.S.F. were responsible for CONCEPTT study design and data collection. K.H.K., K.K., L.E.-Ö., and K.E.B. were responsible for the Swedish study design and data collection. D.S.F., K.K., and K.E.B. discussed preliminary results. E.M.S. and G.R.L. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of this data analysis.