Intermittent Blood Glucose Monitoring Research Articles

SAT134 CGM Use During Pregnancy Complicated By CF-Induced Diabetes

Abstract Disclosure: A.Y. Mazori: None. E.S. Markovic: None. C.J. Levy: Advisory Board Member; Self; Dexcom, Eli Lilly & Company. Research Investigator; Self; Abbott Laboratories, Insulet Corporation, Tandem Diabetes Care, Dexcom. Introduction: Glycemic control remains challenging in pregnancies complicated by diabetes mellitus. Strict glycemic targets are required to optimize maternal and neonatal outcomes, but euglycemia is hindered by fluctuating insulin sensitivity and the need for frequent blood-glucose monitoring (BGM). Consensus guidelines recommend therapeutic continuous glucose monitoring (CGM) for pregnant and nonpregnant individuals with type 1 and type 2 diabetes, but current data support therapeutic CGM use in cystic fibrosis (CF)-related diabetes (CFRD) only outside of pregnancy. We report the case of a patient with CFRD who achieved recommended glycemic targets with a therapeutic CGM during a singleton pregnancy. Methods: A case report and literature review are presented. Results: A 32-year-old nulliparous woman with CF became pregnant via frozen-embryo transfer. Prior CF complications included CFRD, pancreatic insufficiency, and recurrent pancreatitis. A therapeutic Dexcom G6 CGM and intermittent BGM were used to monitor glycemic control before and during pregnancy; sensor use exceeded 96%. Pressure-induced sensor attenuations yielded sporadic hypoglycemic values discordant with simultaneous BGM. CGM analysis for the 90 days preceding conception revealed: time in range of 63-140 mg/dL (TIR) was 90.8%, time above range (TAR) 6.3%, and time below range (TBR) 2.9%. Throughout pregnancy, TIR was 92.9%, TAR 3.4%, and TBR 3.6%; no severe hypoglycemia occurred. Daytime (6AM to midnight) and nighttime hypoglycemia were 4.6% and 2.2%, respectively. In the first trimester, TIR was 90.8%, TAR 3.7%, and TBR 5.5%. During the second trimester, the patient achieved TIR 94.2%, TAR 2.6%, and TBR 3.2%. In the third trimester, TIR was 95.7%, TAR 0.9%, and TBR 3.4%. The pregestational CFRD regimen consisted of insulin glargine 12 units and lispro 3-8 units. The basal-insulin dose was 10 units at 13 weeks’ gestation, 9 units at 27 weeks’ gestation, and 8 units at 38 weeks’ gestation. The prandial-insulin doses varied between 1.5-5 units at 13 weeks’ gestation, 0-7 units at 27 weeks’ gestation, and 0-5 units at 38 weeks’ gestation. After an uncomplicated vaginal delivery at 38 weeks and six days’ gestation, maternal fasting hypoglycemia occurred after one dose of glargine 3 units. Euglycemia was obtained without basal, prandial, or correctional insulin. The neonate experienced mild hypoglycemia that resolved with oral glucose gel and feeding. The neonate was neither macrosomic nor large for gestational age (birth weight, 3.54 kg, 71st percentile) and did not require intensive-care unit management. Both the patient and neonate were discharged on postpartum day two. Conclusion: Therapeutic CGM use in a pregnancy complicated by CFRD was effective for maternal and neonatal outcomes. Further study is warranted to examine CGM use and efficacy in this population. Presentation: Saturday, June 17, 2023

The role of technology in the care of diabetes mellitus in pregnancy: an expert review

Diabetes mellitus is one of the most commonly encountered pregnancy complications and is associated with multiple adverse perinatal outcomes. Technology has progressed to address the unique challenges patients face in managing diabetes mellitus in pregnancy. Technology has bolstered diabetes mellitus education with smartphone applications focused on nutrition counseling and carbohydrate intake advice. Continuous glucose monitors and insulin infusion systems have shown benefit by simplifying glycemic monitoring and insulin administration. Improvements in glycemic control and perinatal outcomes have been seen with continuous glucose monitor use when compared with intermittent blood glucose monitoring, and more pregnant people are using insulin pumps instead of multiple daily insulin injections. Hybrid closed-loop systems are emerging and are able to integrate continuous glucose monitoring and insulin pump technologies while maximizing automated features in the nonpregnant population, but these have not been endorsed for use in pregnancy yet. Applying telehealth practices has been associated with high patient satisfaction among those with diabetes mellitus in pregnancy, and leveraging remote patient monitoring through telehealth platforms and short-range wireless technologies can reduce the burden of patient visits. As technology becomes more integrated into routine management of diabetes mellitus in pregnancy, practitioners should emphasize individualized counseling and device selection to ensure patient autonomy and safety.

Comparison of venous, capillary and interstitial blood glucose data measured during hyperbaric oxygen treatment from patients with diabetes mellitus.

Patients undergoing hyperbaric oxygen treatments (HBOT) have been shown to experience a reduction in blood glucose (BG) levels during a treatment. This necessitates frequent assessment of BG levels. Continuous glucose monitoring (CGM) may represent an alternative to the current finger prick monitoring method in-chamber, however, continuous sensor glucose (SG) data has not been validated in situ. The aim was to determine the validity of continuous SG and intermittent BG monitoring with serum BG levels in diabetic patients during HBOT. Measurements were obtained (finger prick [capillary sample], CGM [interstitial fluid], and serum [venous sample]) at baseline, and at 30, 60, 90 and 120 minutes during the hyperbaric treatment. Data were analysed by calculating intraclass correlation coefficients (ICC) and using mixed effects linear regression. The ICC results (n = 10 patients) between the three methods indicated very high and statistically significant absolute agreement at baseline (pre-dive) (ICC = 0.90, 95% CI 0.74-0.97), at 30 minutes (ICC = 0.85, 95% CI 0.61-0.96), 60 minutes (ICC = 0.86, 95% CI 0.58-0.96), 90 minutes (ICC = 0.87, 96% CI 0.63-0.96) and 120 minutes (ICC = 0.90, 95% CI 0.70-0.97). Capillary glucose and CGM SG readings were each within 1 mmol·L-1 on average of the serum glucose reading, with multi-level linear regression finding the average difference between the CGM SG and capillary glucose methods of BG sampling was not statistically significant (P = 0.81). The CGM SG data were comparable with glucose readings from capillary monitoring. Both CGM and capillary data were consistent with serum values.

Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

Continuous Glucose Monitoring in Critically Ill Patients With COVID-19: Results of an Emergent Pilot Study.

Amidst the coronavirus disease 2019 (COVID-19) pandemic, continuous glucose monitoring (CGM) has emerged as an alternative for inpatient point-of-care blood glucose (POC-BG) monitoring. We performed a feasibility pilot study using CGM in critically ill patients with COVID-19 in the intensive care unit (ICU). Single-center, retrospective study of glucose monitoring in critically ill patients with COVID-19 on insulin therapy using Medtronic Guardian Connect and Dexcom G6 CGM systems. Primary outcomes were feasibility and accuracy for trending POC-BG. Secondary outcomes included reliability and nurse acceptance. Sensor glucose (SG) was used for trends between POC-BG with nursing guidance to reduce POC-BG frequency from one to two hours to four hours when the SG was in the target range. Mean absolute relative difference (MARD), Clarke error grids analysis (EGA), and Bland-Altman (B&A) plots were calculated for accuracy of paired SG and POC-BG measurements. CGM devices were placed on 11 patients: Medtronic (n = 6) and Dexcom G6 (n = 5). Both systems were feasible and reliable with good nurse acceptance. To determine accuracy, 437 paired SG and POC-BG readings were analyzed. For Medtronic, the MARD was 13.1% with 100% of readings in zones A and B on Clarke EGA. For Dexcom, MARD was 11.1% with 98% of readings in zones A and B. B&A plots had a mean bias of -17.76 mg/dL (Medtronic) and -1.94 mg/dL (Dexcom), with wide 95% limits of agreement. During the COVID-19 pandemic, CGM is feasible in critically ill patients and has acceptable accuracy to identify trends and guide intermittent blood glucose monitoring with insulin therapy.

898-P: Benefit of Continuous Glucose Monitoring (CGM) in Reducing Hemoglobin A1c Is Sustained through 12 Months of Use among Adolescents and Young Adults with Type 1 Diabetes (T1D)

The CGM Intervention in Teens and Young Adults (CITY) trial demonstrated reductions in hemoglobin A1c (HbA1c) and hypoglycemia using CGM compared with intermittent blood glucose monitoring over a 6-month period. To determine if this improvement would be sustained, we evaluated outcomes in participants who continued CGM use through 12 months. The study was completed by 70 of 74 (95%) in the CGM group (43% female, median age 17 yrs, 67% non-Hispanic white, and 47% insulin pump users). Central-lab measured HbA1c and CGM measured glycemic outcomes at 12 months were compared with baseline (CGM at baseline was masked). HbA1c decreased from 8.9% at baseline to 8.3% at 12 months (p<0.001) (Table). Time spent in range 70-180 mg/dL was 38% at baseline and 41% at 12 months (P=0.3). Median percent time <70 mg/dL was reduced from 3.4% (49 min/day) at baseline to 1.1% (16 min/day) at 12 months (p<0.001). Similar improvements were observed for time <54 mg/dL with a decrease from a median of 1.0% (14 minutes/day) at baseline to 0.1% (<2 minutes/day) at 12 months. Glycemic variability measured by coefficient of variation was reduced from 42% at baseline to 37% at 12 months (p<0.001). These results demonstrate improvements in outcomes for teens and young adults with CGM use over a 12-month period with substantial improvements in HbA1c and reductions in hypoglycemia. Disclosure K. Miller: None. L. Kanapka: None. C. Bauza: None. L.M. Laffel: Advisory Panel; Self; Roche Diabetes Care. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Insulogic LLC, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk Inc., Sanofi US. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Dexcom, Inc.

How does continuous compare with intermittent blood glucose monitoring during pregnancy for women with pre-existing diabetes?

How does continuous compare with intermittent blood glucose monitoring during pregnancy for women with pre-existing diabetes?

Wearable Microsystem for Minimally Invasive, Pseudo-Continuous Blood Glucose Monitoring: The e-Mosquito

This paper presents a wearable microsystem for minimally invasive, autonomous, and pseudo-continuous blood glucose monitoring, addressing a growing demand for replacing tedious fingerpricking tests for diabetic patients. Unlike prevalent solutions which estimate blood glucose levels from interstitial fluids or tears, our design extracts a whole blood sample from a small lanced skin wound using a novel shape memory alloy (SMA)-based microactuator and directly measures the blood glucose level from the sample. In vitro characterization determined that the SMA microactuator produced penetration force of 225 gf, penetration depth of 3.55 mm, and consumed approximately 5.56 mW·h for triggering. The microactuation mechanism was also evaluated by extracting blood samples from the wrist of four human volunteers. A total of 19 out of 23 actuations successfully reached capillary vessels below the wrists producing blood droplets on the surface of the skin. The integrated potentiostat-based glucose sensing circuit of our e-Mosquito device also showed a good linear correlation (R2 = 0.9733) with measurements using standard blood glucose monitoring technology. These proof-of-concept studies demonstrate the feasibility of the e-Mosquito microsystem for autonomous intermittent blood glucose monitoring.

Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements.

Despite the risk associated with nocturnal hypoglycemia (NH) there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data. One of the first methods that potentially can be used for NH prediction is based on the low blood glucose index (LBGI) and suggested, for example, in Accu-Chek® Connect as a hypoglycemia risk indicator. On the other hand, nowadays there are other glucose control indices (GCI), which could be used for NH prediction in the same spirit as LBGI. In the present study we propose a general approach of combining NH predictors constructed from different GCI. The approach is based on a recently developed strategy for aggregating ranking algorithms in machine learning. NH predictors have been calibrated and tested on data extracted from clinical trials, performed in EU FP7-funded project DIAdvisor. Then, to show a portability of the method we have tested it on another dataset that was received from EU Horizon 2020-funded project AMMODIT. We exemplify the proposed approach by aggregating NH predictors that have been constructed based on 4 GCI associated with hypoglycemia. Even though these predictors have been preliminary optimized to exhibit better performance on the considered dataset, our aggregation approach allows a further performance improvement. On the dataset, where a portability of the proposed approach has been demonstrated, the aggregating predictor has exhibited the following performance: sensitivity 77%, specificity 83.4%, positive predictive value 80.2%, negative predictive value 80.6%, which is higher than conventionally considered as acceptable. The proposed approach shows potential to be used in telemedicine systems for NH prediction.

Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application

Background and ObjectiveNocturnal hypoglycemia (NH) is common in patients with insulin-treated diabetes. Despite the risk associated with NH, there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data and none has been validated for clinical use. Here we propose a method of combining several predictors into a new one that will perform at the level of the best involved one, or even outperform all individual candidates. MethodsThe idea of the method is to use a recently developed strategy for aggregating ranking algorithms. The method has been calibrated and tested on data extracted from clinical trials, performed in the European FP7-funded project DIAdvisor. Then we have tested the proposed approach on other datasets to show the portability of the method. This feature of the method allows its simple implementation in the form of a diabetic smartphone app. ResultsOn the considered datasets the proposed approach exhibits good performance in terms of sensitivity, specificity and predictive values. Moreover, the resulting predictor automatically performs at the level of the best involved method or even outperforms it. ConclusionWe propose a strategy for a combination of NH predictors that leads to a method exhibiting a reliable performance and the potential for everyday use by any patient who performs self-monitoring of blood glucose.

The effect of real time continuous blood glucose monitoring system versus intermittent blood glucose monitoring in critically ill patients under the intensive insulin therapy: a Meta-analysis

Objective To evaluate the value of real time continuous blood glucose monitoring system (RT-CGMS) versus intermittent blood glucose monitoring (IGM) in the critically ill patients under intensive insulin therapy (IIT) . Methods A systematic searching randomized and controlled trials (RCT) in databases was performed for meta-analysis by Review Manager 5.2 software. Outcomes were hypoglycemia episode, alteration of mean blood glucose level, the percentage of time at a blood glucose level within optimal target range, and the early mortalities. Results Six studies, totally 531 patients, were included in this meta-analysis. The pooled SMD of mean blood glucose level was =-0.21 (95% SMD: -0.43 - 0.01, P =0.07) . The pooled SMD of percentage of time at a blood glucose level within optimal target range was 0.20 (95% SMD: -0.09 -0.49, P =0.18) . The pooled OR of hypoglycemia episode frequency was 0.20 (95% CI: 0.09 -0.43, P <0.01) . The pooled OR of early mortalities was 0.35 (95% CI: 0.14 -0.89, P =0.03) . Conclusions In critically ill patients under the intensive insulin therapy, RT-CGMS had obvious beneficial effect on reducing hypoglycemic events. RT-CGMS had no obvious beneficial effect on keeping blood glucose level within optimal target range. Key words: Critically ill patients; Real time continuous glucose monitoring system; Intensive insulin therapy; Meta-analysis

Continuous glucose monitoring for treatment adjustment in diabetic pregnancies--a pilot study.

To examine the efficacy of a continuous glucose monitoring (CGM) system for treatment adjustment in patients with diabetic pregnancy treated with insulin. The study sample consisted of eight women with diabetic pregnancy, six with pre-pregnancy Type 1 diabetes mellitus and two with gestational diabetes (GDM), all being treated with multiple daily insulin injections. Gestational age ranged from 24 to 32 weeks. Data derived from the Continuous Glucose Monitoring System (MiniMed) for 72 h were compared with fingerstick glucose measurements (six to eight times a day), and treatment was adjusted on the basis of the findings. Two to four weeks later, the patients were re-evaluated with CGM. In the first part of the study, an average of 744+/-33 glucose measurements was recorded for each patient with CGM. The mean total time of hyperglycaemia (glucose level >7.7 mmol/l) undetected by the fingerstick method was 152+/-33 min/day. Nocturnal hypoglycaemic events (glucose level <2.7 mmol/l) were recorded in seven patients. Based on the additional information obtained by continuous monitoring, the insulin regimen was changed in all patients. CGM re-evaluation after treatment adjustment showed a reduction in undetected hyperglycaemia to 89+/-17 min/day and in nocturnal hypoglycaemic events, which were recorded in only one patient. Continuous glucose monitoring may diagnose high blood glucose levels and nocturnal hypoglycaemic events that are unrecognized by intermittent blood glucose monitoring and could serve as a useful tool for the long-term management of diabetic pregnancies. A large prospective study is needed to determine the clinical implications of this new monitoring technique.

Continuous glucose monitoring for the evaluation of gravid women with type 1 diabetes mellitus

Objective To compare the daily glycemic profile reflected by continuous and intermittent blood glucose monitoring in pregnant women with type 1 diabetes and to compare the treatment protocols based on the two monitoring methods. Methods The study sample consisted of 34 gravid patients at gestational weeks 16–32, with type 1 diabetes being treated by multiple insulin injections. Data derived from the continuous glucose monitoring system for 72 hours were compared with fingerstick glucose measurements performed 6–8 times per day. During the study period, patients documented the time of food intake, insulin injections, and hypoglycemic events. Data on demographics, gravidity, parity, body mass index, hemoglobin A1c, and fructosamine levels were collected for each patient. Results An average (± standard deviation) of 780 ± 54 glucose measurements was recorded for each patient with continuous glucose monitoring. The mean total time of hyperglycemia (glucose level greater than 140 mg/dL) undetected by the fingerstick method was 192 ± 28 minutes per day. Nocturnal hypoglycemic events (glucose level less than 50 mg/dL) were recorded in 26 patients; in all cases, there was an interval of 1–4 hours before clinical manifestations appeared or the event was revealed by random blood glucose examination. Based on the additional information obtained by continuous monitoring, the insulin therapeutic regimen was adjusted in 24 patients (70%). Conclusion Continuous glucose monitoring can diagnose high postprandial blood glucose levels and nocturnal hypoglycemic events that are unrecognized by intermittent blood glucose monitoring and may serve as a basis for determining treatment regimens. A large, prospective study on maternal and neonatal outcome is needed to evaluate the clinical implications of this new monitoring technique.

Continuous Glucose Monitoring for the Evaluation of Gravid Women With Type 1 Diabetes Mellitus

In Brief OBJECTIVE To compare the daily glycemic profile reflected by continuous and intermittent blood glucose monitoring in pregnant women with type 1 diabetes and to compare the treatment protocols based on the two monitoring methods. METHODS The study sample consisted of 34 gravid patients at gestational weeks 16–32, with type 1 diabetes being treated by multiple insulin injections. Data derived from the continuous glucose monitoring system for 72 hours were compared with fingerstick glucose measurements performed 6–8 times per day. During the study period, patients documented the time of food intake, insulin injections, and hypoglycemic events. Data on demographics, gravidity, parity, body mass index, hemoglobin A1c, and fructosamine levels were collected for each patient. RESULTS An average (± standard deviation) of 780 ± 54 glucose measurements was recorded for each patient with continuous glucose monitoring. The mean total time of hyperglycemia (glucose level greater than 140 mg/dL) undetected by the fingerstick method was 192 ± 28 minutes per day. Nocturnal hypoglycemic events (glucose level less than 50 mg/dL) were recorded in 26 patients; in all cases, there was an interval of 1–4 hours before clinical manifestations appeared or the event was revealed by random blood glucose examination. Based on the additional information obtained by continuous monitoring, the insulin therapeutic regimen was adjusted in 24 patients (70%). CONCLUSION Continuous glucose monitoring can diagnose high postprandial blood glucose levels and nocturnal hypoglycemic events that are unrecognized by intermittent blood glucose monitoring and may serve as a basis for determining treatment regimens. A large, prospective study on maternal and neonatal outcome is needed to evaluate the clinical implications of this new monitoring technique. Continuous glucose monitoring may be a method for adjusting treatment in gravid women with type 1 diabetes mellitus.

Continuous glucose monitoring for the evaluation and improved control of gestational diabetes mellitus

Objectives: To compare the daily glycemic profile reflected by continuous versus self-monitoring of blood glucose in women with gestational diabetes mellitus (GDM), and to evaluate possible differencesin treatment strategy based on the two monitoring methods.Materials and methods: The study sample consisted of 57 women with gestational diabetes, 47 in Israel and ten in California. Gestationalage ranged from 24 to 32 weeks in the Israeli women, and 32 to 36 weeks in the American women. Data derived from the Continuous Glucose Monitoring (CGM) System (MiniMed) for 72 h were compared to fingerstickglucose measurements (6-8 times a day). During continuous monitoring, patients documented the timing of food intake, insulin injections and hypoglycemic events.Results: In the Israeli group,23 women were treated by diet alone, and 24 by diet plus insulin. An average of 763 ± 62 glucose measurements was recorded for each patient with continuous glucose monitoring. The mean total timeof hyperglycemia (glucose level > 140 mg/dl) undetected by the fingerstick method was 132 ± 31 min/day in the insulin-treated group and 94 ± 23 min/day in the diet-treated group. Nocturnalhypoglycemic events (glucose levels < 50 mg/dl) were recorded in 14 patients, all insulin-treated. On the basis of the additional information provided by continuous monitoring, the therapeutic regimen(insulin therapy, diet adjustment, or both) was changed in 36 of the 47 patients. All ten American women were treated with insulin. The mean time of undetected hyperglycemia for a total group monitoringtime of 30 days was 78 ± 13 min/day. Eight women had nocturnal hypoglycemia on at least one of the three nights of monitoring for a total of 12 nights. A change in insulin dosage was made in allwomen on the basis of the data provided by continuous glucose monitoring.Conclusion: Continuous glucose monitoring is helpful for monitoring women with GDM and for adjusting diabetes therapy.It can accurately detect high postprandial blood glucose levels and nocturnal hypoglycemic events that may go unrecognized by intermittent blood glucose monitoring. A large prospective study on maternaland neonatal outcome is needed to determine the clinical implications of this new monitoring technique.

Continuous glucose monitoring during pregnancy complicated by gestational diabetes mellitus.

Postprandial glucose has been reported to be the best predictor of neonatal macrosomia. Therefore, self-blood glucose monitoring (SBGM) protocols for diabetic pregnant women stress the importance of measuring blood glucose after meals. However, there is controversy in the literature. Traditionally, glucose monitoring has been prescribed at 2 hours after eating to coincide with the times a patient is at increased risk of hypoglycemia. Human regular insulin peaks at 2 to 3 hours after injection; thus, checking blood glucose at the 2-hour point is a relic of strategies to prevent hypoglycemia. In pregnancy, the emphasis has been on measuring during times when blood glucose levels are highest. One hour after the start of the meal has been shown to be the time of peak postprandial response in 90% of pregnant woman. Because glucose excursions may reach their maximum at varying times, based on the size and number of meals ingested, SBGM alone may not capture the full extent of total daily postprandial hyperglycemia. Because intermittent blood glucose monitoring underestimates the number of hyperglycemic events, a more accurate determination of postprandial glucose levels is necessary to decrease the risk of macrosomia in gestational diabetes mellitus. Continuous glucose monitoring may facilitate the detection of all postprandial peaks, including those due to unscheduled meals, and may provide an opportunity for better intervention by providing the complete glucose profile.