Gestational diabetes mellitus (GDM) affects a significant percentage of pregnancies worldwide, which presents unique challenges for both expectant parents and healthcare providers. 

The primary goal in GDM management is to maintain maternal blood glucose within target ranges to reduce risks for both mother and baby. Traditionally, self-monitoring of blood glucose (SMBG) through finger-stick testing has been the cornerstone of care. 

However, there have always been questions around accuracy with this kind of testing. Is the blood tested at the right time? Are patients consistent with testing, or do the blockers of daily life (work, childcare) get in the way? Are values fudged, or misremembered? Do patients always even bring their logs?

Below, we explore recent studies that show the current challenges with SMBG, as well as the potential feasibility of CGM to improve data collection and, potentially, outcomes as well. 

The Problem with Compliance in SMBG and Paper Logs

Compliance with blood glucose monitoring is critical in gestational diabetes (GDM). Poor adherence to monitoring regimens can result in undetected hyperglycemia, leading to complications such as large-for-gestational-age infants, increased rates of cesarean section, neonatal hypoglycemia, and longer NICU stays.

Traditional self-monitoring of blood glucose (SMBG) requires frequent finger-sticks, typically four to seven times per day, which can be uncomfortable, time-consuming, and disruptive. Patients also need to log results manually, often on paper, which can lead to incomplete records and lost data.

Not surprisingly, compliance with SMBG is a well-documented challenge. Reviews have consistently noted that adherence rates for finger-stick testing are lower than recommended, with barriers including pain, inconvenience, and the burden of logging data consistently. But the challenges go beyond simply missing tests, with studies showing that paper logbooks themselves are often inaccurate or unreliable.

When patient logs are compared against CGM, discrepancies can be striking. In one study of pregnant women with diabetes, over 80% of participants added “phantom” glucose values not present in their meter, and nearly 70% omitted actual results. Overall, more than one in five logged values were inaccurate. 

Another study of women with GDM found that only 61.5% met the recommended frequency of testing during the first two weeks of care, and that nearly a quarter had fewer than 90% of their diary entries match meter records. Delayed testing (particularly postprandial checks taken too late) was also common, reducing the clinical value of the readings.

This problem is not limited to pregnancy. Across broader diabetes populations, studies have shown 30–50% of logbooks contain errors ranging from omissions and missing entries to fabricated values.

For providers, the result is a double challenge: not only are paper logs often incomplete or inaccurate, but they also may not reliably make it to appointments at all. Even when patients bring them, almost half of diaries in one adult study were found to be misleading or missing critical data. Meanwhile, a review by Song et al. (2023) found that compliance rates in CGM groups were as high as 90%, significantly higher than in SMBG groups

Taken together, these findings highlight a significant flaw in the traditional SMBG + paper log approach. Inaccurate or missing data can obscure true glycemic patterns, delay treatment adjustments, and ultimately undermine outcomes. 

For gestational diabetes in particular, where the monitoring window is short and the stakes are high, the limitations of paper-based monitoring can present a serious barrier to care. Not only this, but because physicians do not have the data before an appointment, they often must take valuable clinic time to review and make recommendations based on the data they do have. 

Can CGMs Solve the Problem?

Continuous glucose monitors offer an alternative by providing real-time or near-continuous glucose readings with less burden on the patient. With CGM, compliance is less about remembering to test and more about wearing the sensor consistently. Early studies suggest that this shift may result in higher adherence and better data capture.

Quah et al. (2024) conducted a pilot randomized controlled trial that demonstrated CGM use is both feasible and acceptable for pregnant women. Women generally reported willingness to use CGM throughout pregnancy, showing that device wear is realistic for this population.

Liang et al. (2023), in a prospective cohort study, found that CGM-derived metrics such as time above range (TAR) and mean nocturnal glucose correlated strongly with adverse pregnancy outcomes. Since CGM provides significantly more data about time in range, it may be able to predict risk and guide intervention more effectively than SMBG.

Systematic reviews, including Chai et al. (2025), highlight similar themes: CGM provides richer data, higher compliance, and improved metrics, but larger randomized controlled trials are still needed to determine whether these benefits consistently translate into improved maternal and neonatal outcomes.

Ongoing trials are being specifically designed to test whether real-time CGM can reduce complications compared to usual care. 

Key Takeaways

1. Compliance is a critical challenge in gestational diabetes when using SMBG and paper logs, due to pain, inconvenience, and manual data tracking.
2. CGM has potential to solve this compliance challenge: CGM has compliance rates around 90% and positive patient experiences, and provides more detailed data to a care team ahead of appointments.
3. More research is needed. While ACOG guidelines still recommend fasting/postprandial, the next steps are to conduct large, well-powered randomized controlled trials to define the role of CGM in standard care.

Conclusion

SMBG testing, as a cornerstone of gestational diabetes care, comes with a lot of risk. Patients dislike pricking their fingers, compliance is a constant challenge, and physicians and their teams end up working with poorer data.

Continuous glucose monitoring holds significant promise for transforming the management of gestational diabetes. It addresses compliance challenges inherent in SMBG, is feasible and acceptable for most patients, and delivers richer glucose data that can inform care. 

CGM can solve compliance, but the right targets for pregnancy are still being studied. In the meantime, platforms that convert CGM to fasting/postprandials can give the best of both worlds

References:

• Song Y, et al. Progress and indication for use of continuous glucose monitoring in pregnancy. [PMCID: PMC10482265]
• Liang X, et al. CGM-derived glycemic metrics and adverse pregnancy outcomes among women with GDM. Lancet Regional Health – Western Pacific, 2023. DOI: 10.1016/j.lanwpc.2023.100414.
• Quah PL, et al. Pilot RCT of CGM in pregnancy. [PMCID: PMC11156501]
• Burk J, et al. Evidence for improved glucose metrics and perinatal outcomes with CGM in GDM. AJOG, 2025. DOI: 10.1016/j.ajog.2025.02.170.
• Chai TY, et al. Continuous glucose monitoring in gestational diabetes: Review. Diabetes Research and Clinical Practice, 2025. DOI: 10.1016/j.diabres.2025.110054.
• Balaji V, et al. The use of continuous glucose monitoring in comparison with SMBG in GDM. [PMCID: PMC12286989]
• ClinicalTrials.gov. NCT04803357. Study on the use of real-time CGM in gestational diabetes.

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