Effect of a CGMS and SMBG on Maternal and Neonatal Outcomes in Gestational Diabetes Mellitus: a Randomized Controlled Trial

American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Echouffo-Tcheugui JB, Ekhlaspour L, Garg R, Khunti K, Lal R, Lingvay I, Matfin G, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Bannuru RR. 7. Diabetes Technology: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Practical Considerations for Using Continuous Glucose Monitoring in Patients with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is the most prevalent metabolic complication during pregnancy. GDM is associated with adverse perinatal, neonatal, and long-term health consequences. Studies have demonstrated that the use of continuous glucose monitoring (CGM) reduces the incidence of maternal and neonatal complications in pregnant women with type 1 diabetes. Although the use of CGM in GDM has not been well studied, a growing body of evidence is showing potential benefits in the GDM population. This article discusses the advantages and challenges of CGM and provides practical guidelines for using this technology in the GDM population.

Use of continuous glucose monitoring and hybrid closed-loop therapy in pregnancy

Continuous glucose monitoring (CGM) has led to a paradigm shift in the management of pregnant women with type 1 diabetes (T1D), with improved glycaemic control, less hypoglycaemia and fewer pregnancy complications. Data on CGM use in pregnant women with type 2 diabetes (T2D) are limited. A large randomized controlled trial (RCT) on CGM use in people with T2D in pregnancy is ongoing. Small studies on CGM use in women with gestational diabetes (GDM) have suggested improved glycaemic control and better qualification when insulin is needed. However, none of these studies was powered to evaluate pregnancy outcomes. Several large RCTs are ongoing in women with GDM. In addition to CGM, other technologies, such as advanced hybrid closed-loop (AHCL) systems have further improved glycaemic management in people with T1D. AHCL therapy adapts insulin delivery via a predictive algorithm integrated with CGM and an insulin pump. A large RCT with the AHCL CamAPS® FX demonstrated a 10% increase in time in range compared to standard insulin therapy in a pregnant population with T1D. Recently, an RCT of an AHCL system not approved for use in pregnancy (780G MiniMed) has also demonstrated additional benefits of AHCL therapy compared to standard insulin therapy, with improved time in range overnight, less hypoglycaemia and improved treatment satisfaction. More evidence is needed on the impact of AHCL therapy on maternal and neonatal outcomes and on which glycaemic targets with CGM should be used in pregnant women with T2D and GDM. We review the current evidence on the use of CGM and AHCL therapy in pregnancy.

All Children Deserve to Be Safe, Mothers Too: Evidence and Rationale Supporting Continuous Glucose Monitoring Use in Gestational Diabetes Within the Medicaid Population

Gestational diabetes mellitus (GDM) is a common metabolic disease of pregnancy that threatens the health of several million women and their offspring. The highest prevalence of GDM is seen in women of low socioeconomic status. Women with GDM are at increased risk of adverse maternal outcomes, including increased rates of Cesarean section delivery, preeclampsia, perineal tears, and postpartum hemorrhage. However, of even greater concern is the increased risk to the fetus and long-term health of the child due to elevated glycemia during pregnancy. Although the use of continuous glucose monitoring (CGM) has been shown to reduce the incidence of maternal and fetal complications in pregnant women with type 1 diabetes and type 2 diabetes, most state Medicaid programs do not cover CGM for women with GDM. This article reviews current statistics relevant to the incidence and costs of GDM among Medicaid beneficiaries, summarizes key findings from pregnancy studies using CGM, and presents a rationale for expanding and standardizing CGM coverage for GDM within state Medicaid populations.

Continuous glucose monitoring metrics in pregnancy with type 1 diabetes mellitus

Managing diabetes during pregnancy is challenging, given the significant risk it poses for both maternal and foetal health outcomes. While traditional methods involve capillary self-monitoring of blood glucose level monitoring and periodic HbA1c tests, the advent of continuous glucose monitoring (CGM) systems has revolutionized the approach. These devices offer a safe and reliable means of tracking glucose levels in real-time, benefiting both women with diabetes during pregnancy and the healthcare providers. Moreover, CGM systems have shown a low rate of side effects and high feasibility when used in pregnancies complicated by diabetes, especially when paired with continuous subcutaneous insulin infusion pump as hybrid closed loop device. Such a combined approach has been demonstrated to improve overall blood sugar control, lessen the occurrence of preeclampsia and neonatal hypoglycaemia, and minimize the duration of neonatal intensive care unit stays. This paper aims to offer a comprehensive evaluation of CGM metrics specifically tailored for pregnancies impacted by type 1 diabetes mellitus.

American Diabetes Association Professional Practice Committee, ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 7. Diabetes Technology: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Flash glucose monitoring system in gestational diabetes: a study of accuracy and usability

PURPOSE

Studies of flash glucose monitoring systems (FGMSs) in pregnancy are insufficient, especially in gestational diabetes (GD). Our aim was to evaluate Freestyle Libre's usability and accuracy (compared to self-monitoring of blood glucose [SMBG]) for GD patients in real-life conditions.

METHODS

This is a prospective study with pregnant women diagnosed with GD (n = 24 for the usability analysis; n = 19 for the accuracy analysis). The study duration was up to 28 days (lifetime of two sensors). Participants executed a minimum of four daily FGMS readings obtained immediately after capillary SMBG. Analytical accuracy was assessed with mean absolute relative difference (MARD) and mean absolute difference (MAD); clinical accuracy was assessed with Surveillance Error Grid (SEG). Usability was evaluated with a user acceptability questionnaire.

RESULTS

The mean pregestational BMI was 25.21 ± 5.15 kg/m2 (mean ± SD), the mean gestational age was 30.31 ± 2.02 weeks, and the mean glucose values were 76.63 ± 7.49 mg/dL. A total of 1339 SMBG-FGMS pairs of values were obtained. Analytical accuracy was good with an overall MARD of 14.07% and an in-target MARD of 13.79%. The number of SMBG-FMGS pairs for above-target values was low (122 of 1339) with an associated MARD of 17.95%. Clinical accuracy of the FGMS was demonstrated, with 94.4% of values in the no-risk or slight, lower risk zones of the SEG. FGMS accuracy was unaffected by pregestational BMI or gestational age. The user acceptability questionnaire showed high levels of satisfaction, with 95.8-100% preferring FGMS to SMBG. No unexpected or severe adverse effects occurred.

CONCLUSION

FGMS showed good performance in GD regarding accuracy and usability. Larger studies are needed to corroborate our results, verify the analytical accuracy of above-target values as this glucose range might lead to initiation or adjustment of pharmacological therapy, and ultimately establish definitive recommendations regarding prescription of FGMS for GD patients.

Supporting the Management of Gestational Diabetes Mellitus With Comprehensive Self-Tracking: Mixed Methods Study of Wearable Sensors

BACKGROUND

Gestational diabetes mellitus (GDM) is an increasing health risk for pregnant women as well as their children. Telehealth interventions targeted at the management of GDM have been shown to be effective, but they still require health care professionals for providing guidance and feedback. Feedback from wearable sensors has been suggested to support the self-management of GDM, but it is unknown how self-tracking should be designed in clinical care.

OBJECTIVE

This study aimed to investigate how to support the self-management of GDM with self-tracking of continuous blood glucose and lifestyle factors without help from health care personnel. We examined comprehensive self-tracking from self-discovery (ie, learning associations between glucose levels and lifestyle) and user experience perspectives.

METHODS

We conducted a mixed methods study where women with GDM (N=10) used a continuous glucose monitor (CGM; Medtronic Guardian) and 3 physical activity sensors: activity bracelet (Garmin Vivosmart 3), hip-worn sensor (UKK Exsed), and electrocardiography sensor (Firstbeat 2) for a week. We collected data from the sensors, and after use, participants took part in semistructured interviews about the wearable sensors. Acceptability of the wearable sensors was evaluated with the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire. Moreover, maternal nutrition data were collected with a 3-day food diary, and self-reported physical activity data were collected with a logbook.

RESULTS

We found that the CGM was the most useful sensor for the self-discovery process, especially when learning associations between glucose and nutrition intake. We identified new challenges for using data from the CGM and physical activity sensors in supporting self-discovery in GDM. These challenges included (1) dispersion of glucose and physical activity data in separate applications, (2) absence of important trackable features like amount of light physical activity and physical activities other than walking, (3) discrepancy in the data between different wearable physical activity sensors and between CGMs and capillary glucose meters, and (4) discrepancy in perceived and measured quantification of physical activity. We found the body placement of sensors to be a key factor in measurement quality and preference, and ultimately a challenge for collecting data. For example, a wrist-worn sensor was used for longer compared with a hip-worn sensor. In general, there was a high acceptance for wearable sensors.

CONCLUSIONS

A mobile app that combines glucose, nutrition, and physical activity data in a single view is needed to support self-discovery. The design should support tracking features that are important for women with GDM (such as light physical activity), and data for each feature should originate from a single sensor to avoid discrepancy and redundancy. Future work with a larger sample should involve evaluation of the effects of such a mobile app on clinical outcomes.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03941652; https://clinicaltrials.gov/study/NCT03941652.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Flash glucose monitoring in gestational diabetes mellitus (FLAMINGO): a randomised controlled trial

AIMS

Gestational diabetes mellitus (GDM) is the most common type of hyperglycaemia in pregnancy. GDM is a risk factor of adverse perinatal outcomes, with the incidence rate increasing proportionally to the level of maternal dysglycaemia. Therefore, glycaemic control plays an important role in management of GDM. The aim of this study was to assess the efficacy of flash glucose monitoring (FGM) in GDM.

MATERIALS AND METHODS

This was a non-blinded, randomised controlled trial, that recruited 100 pregnant women diagnosed with GDM between 24 and 28 weeks of gestation at the 1st Department of Obstetrics and Gynaecology, Medical University of Warsaw. After meeting the inclusion criteria patients were randomly allocated to the study group (FGM, n = 50) or control group (self-monitoring of blood glucose-SMBG, n = 50). Clinical and laboratory results were assessed at four follow-up visits. The primary outcome was mean fasting and postprandial glycaemia. The secondary outcomes were perinatal outcomes.

RESULTS

There was no significant difference in mean glycaemia between the groups (p = 0.437) Compared to the control group, the study group significantly reduced their fasting (p = 0.027) and postprandial glycaemia (p = 0.034) during the first 4 weeks following GDM diagnosis, with no significant difference in progression to insulin therapy (OR 1.09, 95% CI 0.47-2.57). Incidence of fetal macrosomia was significantly higher in SMBG as compared to FGM group (OR 5.63, 95% CI 1.16-27.22).

CONCLUSIONS

Study results indicate that FGM has an impact on glycaemic control, dietary habits and incidence of fetal macrosomia in patients with GDM. Trial registration clinicaltrials.gov ID: NCT04422821.

Expert Recommendations for Using Time-in-Range and Other Continuous Glucose Monitoring Metrics to Achieve Patient-Centered Glycemic Control in People With Diabetes

New metrics for assessing glycemic control beyond HbA1c have recently emerged due to the increasing use of continuous glucose monitoring (CGM) in diabetes clinical practice. Among them, time in range (TIR) has appeared as a simple and intuitive metric that correlates inversely with HbA1c and has also been newly linked to the risk of long-term diabetes complications. The International Consensus on Time in Range established a series of target glucose ranges (TIR, time below range and time above range) and recommendations for time spent within these ranges for different diabetes populations. These parameters should be evaluated together with the ambulatory glucose profile (AGP). Using standardized visual reporting may help people with diabetes and healthcare professionals in the evaluation of glucose control in frequent clinical situations. The objective of the present review is to provide practical insights to quick interpretation of patient-centered metrics based on flash glucose monitoring data, as well as showing some visual examples of common clinical situations and giving practical recommendations for their management.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

7. Diabetes Technology: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Effect of continuous glucose monitoring compared with self-monitoring of blood glucose in gestational diabetes patients with HbA1c<6%: a randomized controlled trial

Objective

This study evaluated the effect of continuous glucose monitoring (CGM) versus self-monitored blood glucose (SMGB) in gestational diabetes mellitus (GDM) with hemoglobin A1c (HbA1c) <6%.

Methods

From January 2019 to February 2021, 154 GDM patients with HbA1c<6% at 24-28 gestational weeks were recruited and assigned randomly to either SMBG only or CGM in addition to SMBG, with 77 participants in each group. CGM was used in combination with fingertip blood glucose monitoring every four weeks until antepartum in the CGM group, while in the SMBG group, fingertip blood glucose monitoring was applied. The CGM metrics were evaluated after 8 weeks, HbA1c levels before delivery, gestational weight gain (GWG), adverse pregnancy outcomes and CGM medical costs were compared between the two groups.

Results

Compared with patients in the SMBG group, the CGM group patients had similar times in range (TIRs) after 8 weeks (100.00% (93.75-100.00%) versus 99.14% (90.97-100.00%), p=0.183) and HbA1c levels before delivery (5.31 ± 0.06% versus 5.35 ± 0.06%, p=0.599). The proportion with GWG within recommendations was higher in the CGM group (59.7% versus 40.3%, p=0.046), and the newborn birth weight was lower (3123.79 ± 369.58 g versus 3291.56 ± 386.59 g, p=0.015). There were no significant differences in prenatal or obstetric outcomes, e.g., cesarean delivery rate, hypertensive disorders, preterm births, macrosomia, hyperbilirubinemia, neonatal hypoglycemia, respiratory distress, and neonatal intensive care unit admission >24 h, between the two groups. Considering glucose monitoring, SMBG group patients showed a lower cost than CGM group patients.

Conclusions

For GDM patients with HbA1c<6%, regular SMBG is a more economical blood glucose monitoring method and can achieve a similar performance in glycemic control as CGM, while CGM is beneficial for ideal GWG.

[Insulin pump therapy and continuous glucose monitoring]

This Guideline represents the recommendations of the Austrian Diabetes Association (ÖDG) on the use of diabetes technology (insulin pump therapy; continuous glucose monitoring, CGM; hybrid closed-loop systems, HCL; diabetes apps) and access to these technological innovations for people with diabetes mellitus based on current scientific evidence.

Efficacy of Continuous Glucose Monitoring on Glycaemic Control in Pregnant Women with Gestational Diabetes Mellitus-A Systematic Review

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy, affecting up to 14% of pregnant women. The population of patients with risk factors of GDM is increasing; thus, it is essential to improve management of this condition. One of the key factors affecting perinatal outcomes in GDM is glycaemic control. Until recently, glucose monitoring was only available with self-monitoring of blood glucose (SMBG). However, nowadays, there is a new method, continuous glucose monitoring (CGM), which has been shown to be safe in pregnancy. Since proper glycaemia assessment has been shown to affect perinatal outcomes, we decided to perform a systematic review to analyse the role of CGM in glycaemic control in GDM. We conducted a web search of the MEDLINE, EMBASE, Cochrane Library, Scopus, and Web of Science databases according to the PRISMA guidelines. The web search was performed by two independent researchers and resulted in 14 articles included in the systematic review. The study protocol was registered in the PROSPERO database with registration number CRD42021289883. The main outcome of the systematic review was determining that, when compared, CGM played an important role in better glycaemic control than SMBG. Furthermore, glycaemic control with CGM improved qualification for insulin therapy. However, most of the articles did not reveal CGM’s role in improving neonatal outcomes. Therefore, more studies are needed to analyse the role of CGM in affecting perinatal outcomes in GDM.

Glycaemia dynamics in gestational diabetes mellitus

Pregnant women may develop gestational diabetes mellitus (GDM), a disease of pregnancy characterised by maternal and fetal hyperglycaemia with hazardous consequences to the mother, the fetus, and the newborn. Maternal hyperglycaemia in GDM results in fetoplacental endothelial dysfunction. GDM-harmful effects result from chronic and short periods of hyperglycaemia. Thus, it is determinant to keep glycaemia within physiological ranges avoiding short but repetitive periods of hyper or hypoglycaemia. The variation of glycaemia over time is defined as 'glycaemia dynamics'. The latter concept regards with a variety of mechanisms and environmental conditions leading to blood glucose handling. In this review we summarized the different metrics for glycaemia dynamics derived from quantitative, plane distribution, amplitude, score values, variability estimation, and time series analysis. The potential application of the derived metrics from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in the potential alterations of pregnancy outcome in GDM are discussed.

Effects of continuous glucose monitoring on maternal and neonatal outcomes in perinatal women with diabetes: A systematic review and meta-analysis of randomized controlled trials

AIMS

This systematic review aims to assess the effects of continuous glucose monitoring (CGM) on maternal and neonatal outcomes in perinatal women with diabetes.

METHODS

A three-step comprehensive search was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guideline. Randomized controlled trials (RCTs) were retrieved from international databases of PubMed, Embase, Cochrane Library, CINAHL, PsycINFO and Scopus from their respective inception dates until 5th January 2021. Comprehensive Meta-Analysis Software Version 3 was used. The overall effect was determined using Hedges' g. Cochrane collaboration's tool version 1 and grading of recommendations, assessment, development and evaluation criteria were used for quality assessment.

RESULTS

A total of 1215 records were identified and 10 RCTs involving a total of 1358 perinatal women were selected. The meta-analysis revealed that CGM significantly improved HbA1c levels (g = -0.43, 95% CI: -0.63, -0.22), lowered cesarean section rate (g = -0.17, 95% CI: -0.33, -0.02) and neonatal birth weight (g = -0.16, 95% CI: -0.27, -0.04) when compared to the comparator. The majority (86.67%) has a low risk of biases and certainty of evidence ranged from very low to moderate.

CONCLUSION

CGM improves maternal and neonatal outcomes. Future studies should use well-designed large-scale trials.

American Diabetes Association Professional Practice Committee. 7. Diabetes Technology: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Efficacy of continuous glucose monitoring on maternal and neonatal outcomes in gestational diabetes mellitus: a systematic review and meta-analysis of randomized clinical trials

AIMS

This systematic review aims to evaluate the effect of continuous glucose monitoring (CGM) on maternal and neonatal outcomes in gestational diabetes mellitus (GDM).

METHODS

Two authors conducted a systematic search using PubMed, Embase, CENTRAL, CINAHL, Scopus, Web of Science, ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform. The inclusion criteria for the systematic review were randomized clinical trials that compared the effects of CGM and blood glucose monitoring (BGM) in women with GDM. A restricted maximum likelihood random-effects model was used for the meta-analysis. The measures of effect were risk ratios for categorical data and mean differences for continuous data.

RESULTS

Of the 457 studies reviewed, six randomized clinical trials met the inclusion criteria. A total of 482 patients were included in the meta-analysis. The use of CGM was associated with lower HbA1c levels at the end of pregnancy (mean difference: -0.22; 95%CI -0.42 to -0.03) compared to BGM. Women using CGM also had less gestational weight gain (mean difference: -1.17, 95%CI -2.15 to -0.19), and their children had lower birth weight (mean difference: -116.26, 95%CI -224.70 to -7.81). No differences were observed in the other outcomes evaluated.

CONCLUSION

Women with GDM using CGM may achieve lower average blood glucose levels, lower maternal weight gain and infant birth weight than women using BGM. Nevertheless, current evidence is limited by the low number of studies and the small sample sizes of these studies. Larger clinical trials are needed to better understand the effects of CGM in GDM.

REGISTRATION

PROSPERO registration ID CRD42021225651.

Congenital Heart Disease in Non-Diabetic Large-for-Gestational-Age (LGA) Neonates

BACKGROUND

Congenital heart diseases are the most prevalent congenital abnormalities in the neonates, caused by environmental and genetic factors and contributing to the leading cause of death. This study aims to evaluate the relationship between neonates with large for gestational age and increased risk of congenital heart diseases among non-diabetic mothers.

METHODS

In this study, 179 neonates with large gestational age in Khorramabad were enrolled where heart abnormalities were evaluated using echocardiography.

RESULTS

87 neonates had more than 4000 g of birth weight with no heart abnormalities and 92 (51%) macrosomic neonates had congenital heart diseases. Statistical analysis revealed a significant relationship between birth weight and increased risk of acquiring congenital heart disease between the two groups. There was no significant relationship between birth weight, maternal age, gender, labor type and blood group between the two groups. The highest incidence of congenital heart anomalies was related to 38% of arterial septal defect (ASD) and 15.2% of ASD and VSD, respectively.

CONCLUSION

The most prevalent abnormality was arterial septal ASD. None of these abnormalities were associated with maternal age, birth weight and neonate gender. Future studies for congenital heart disease and neonatal birth weight are, therefore, recommended.

Continuous glucose monitoring in obese pregnant women with no hyperglycemia on glucose tolerance test

Objective

The objective of the present study was to compare 24-hour glycemic levels between obese pregnant women with normal glucose tolerance and non-obese pregnant women.

Methods

In the present observational, longitudinal study, continuous glucose monitoring was performed in obese pregnant women with normal oral glucose tolerance test with 75 g of glucose between the 24^th and the 28^th gestational weeks. The control group (CG) consisted of pregnant women with normal weight who were selected by matching the maternal age and parity with the same characteristics of the obese group (OG). Glucose measurements were obtained during 72 hours.

Results

Both the groups were balanced in terms of baseline characteristics (age: 33.5 [28.7–36.0] vs. 32.0 [26.0–34.5] years, p = 0.5 and length of pregnancy: 25.0 [24.0–25.0] vs. 25.5 [24.0–28.0] weeks, p = 0.6 in the CG and in the OG, respectively). Pre-breakfast glycemic levels were 77.77 ± 10.55 mg/dL in the CG and 82.02 ± 11.06 mg/dL in the OG (p<0.01). Glycemic levels at 2 hours after breakfast were 87.31 ± 13.10 mg/dL in the CG and 93.48 ± 18.74 mg/dL in the OG (p<0.001). Daytime blood glucose levels were 87.6 ± 15.4 vs. 93.1 ± 18.3 mg/dL (p<0.001) and nighttime blood glucose levels were 79.3 ± 15.8 vs. 84.7 ± 16.3 mg/dL (p<0.001) in the CG and in the OG, respectively. The 24-hour, daytime, and nighttime values of the area under the curve were higher in the OG when compared with the CG (85.1 ± 0.16 vs. 87.9 ± 0.12, 65.6 ± 0.14 vs. 67.5 ± 0.10, 19.5 ± 0.07 vs. 20.4 ± 0.05, respectively; p<0.001).

Conclusion

The results of the present study showed that obesity in pregnancy was associated with higher glycemic levels even in the presence of normal findings on glucose tolerance test.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

Time in Range in Pregnancy: Is There a Role?

Continuous glucose monitoring (CGM) is being used with increasing frequency as an adjunct to self-monitoring of blood glucose in pregnancy, and novel targets based on CGM data are becoming standardized. This adoption of CGM is the result of its improving accuracy, patient preference, and evolving data demonstrating associations of novel targets such as time in range (TIR) with pregnancy and neonatal outcomes. A greater understanding of the relationship of various CGM metrics to outcomes in pregnancy complicated by diabetes is needed. It is clear that TIR parameters need to be uniquely lower for pregnant women than for nonpregnant individuals. CGM technology is also an integral part of hybrid closed-loop insulin delivery systems. These insulin delivery systems will be a significant advance in the management of diabetes during pregnancy if they can achieve the pre- and postprandial targets required for pregnancy and optimize TIR.

Clinical Effectiveness of Different Technologies for Diabetes in Pregnancy: Systematic Literature Review

BACKGROUND

Hyperglycemia in pregnancy occurs worldwide and is closely associated with health issues in women and their offspring, such as pregnancy and birth complications, respectively, as well as comorbidities, such as metabolic and cardiovascular diseases. To optimize the management of diabetic pregnancies, sustainable strategies are urgently needed. Investigation of constantly evolving technologies for diabetes that help to manage pregnancy and health is required.

OBJECTIVE

We aimed to conduct a systematic review to assess the clinical effectiveness of technologies for diabetes in pregnancy.

METHODS

Relevant databases including MEDLINE (PubMed), Cochrane Library, Embase, CINAHL, and Web of Science Core Collection were searched in September 2020 for clinical studies (2008-2020). Findings were organized by type of diabetes, type of technology, and outcomes (glycemic control, pregnancy- and birth-related outcomes, and neonatal outcomes). Study quality was assessed using Effective Public Health Practice Project criteria.

RESULTS

We identified 15 randomized controlled trials, 3 randomized crossover trials, 2 cohort studies, and 2 controlled clinical trials. Overall, 9 studies focused on type 1 diabetes, 0 studies focused on gestational diabetes, and 3 studies focused on both type 1 diabetes and type 2 diabetes. We found that 9 studies were strong quality, 11 were moderate quality, and 2 were weak quality. Technologies for diabetes seemed to have particularly positive effects on glycemic control in all types of diabetes, shown by some strong and moderate quality studies. Positive trends in pregnancy-related, birth-related, and neonatal outcomes were observed.

CONCLUSIONS

Technologies have the potential to effectively improve the management of diabetes during pregnancy. Further research on the clinical effectiveness of these technologies is needed, especially in pregnant women with type 2 diabetes.

A novel classification of glucose profile in pregnancy based on continuous glucose monitoring data

AIM

To investigate the glucose profile of women with and without gestational diabetes mellitus (GDM) by simultaneously analyzing several factors of continuous glucose monitoring (CGM) data.

METHODS

CGM was conducted for 2 weeks in the second trimester of pregnant women whose random blood glucose level was ≥100 mg/dl. A 75-g oral glucose tolerance test was performed around day 7, and the index of hyperglycemia, relative hypoglycemia, and indices of glucose variability were extracted from CGM data. Unsupervised hierarchical clustering was performed to categorize glucose profiles of the participants.

RESULTS

CGM data were obtained from 29 women. Glucose profiles were categorized into three clusters: low glucose levels with less glucose variability group (L group, n = 7); moderate glucose levels with moderate-to-high glucose variability group (M group, n = 18); and high glucose levels with high glucose variability group (H group, n = 4). The waveforms of the glucose profiles were very different among the three groups. Women with GDM tended to be more frequent in the H group than in the M and L groups (75.0%, 16.7%, and 14.3%, respectively; p = 0.053). Maternal age was significantly higher and the proportion of multiparous women was significantly larger in the H group compared to L group (p = 0.002 and 0.015, respectively).

CONCLUSIONS

A comprehensive analysis of CGM data could help us extract a subgroup of women with characteristics of GDM.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Effectiveness of real-time continuous glucose monitoring to improve glycaemic control and pregnancy outcome in patients with gestational diabetes mellitus: a study protocol for a randomised controlled trial

INTRODUCTION

Real-time continuous glucose monitoring (rt-CGM) informs users about current interstitial glucose levels and allows early detection of glycaemic excursions and timely adaptation by behavioural change or pharmacological intervention. Randomised controlled studies adequately powered to evaluate the impact of long-term application of rt-CGM systems on the reduction of adverse obstetric outcomes in women with gestational diabetes (GDM) are missing. We aim to assess differences in the proportion of large for gestational age newborns in women using rt-CGM as compared with women with self-monitored blood glucose (primary outcome). Rates of neonatal hypoglycaemia, caesarean section and shoulder dystocia are secondary outcomes. A comparison of glucose metabolism and quality of life during and after pregnancy completes the scope of this study.

METHODS AND ANALYSIS

Open-label multicentre randomised controlled trial with two parallel groups including 372 female patients with a recent diagnosis of GDM (between 24+0 until 31+6 weeks of gestation): 186 with rt-CGM (Dexcom G6) and 186 with self-monitored blood glucose (SMBG). Women with GDM will be consecutively recruited and randomised to rt-CGM or control (SMBG) group after a run-in period of 6-8 days. The third visit will be scheduled 8-10 days later and then every 2 weeks. At every visit, glucose measurements will be evaluated and all patients will be treated according to the standard care. The control group will receive a blinded CGM for 10 days between the second and third visit and between week 36+0 and 38+6. Cord blood will be sampled immediately after delivery. 48 hours after delivery neonatal biometry and maternal glycosylated haemoglobin A1c (HbA1c) will be assessed, and between weeks 8 and 16 after delivery all patients receive a re-examination of glucose metabolism including blinded CGM for 8-10 days.

ETHICS AND DISSEMINATION

This study received ethical approval from the main ethic committee in Vienna. Data will be presented at international conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT03981328; Pre-results.

Glycemic Status Assessment by the Latest Glucose Monitoring Technologies

The advanced and performing technologies of glucose monitoring systems provide a large amount of glucose data that needs to be properly read and interpreted by the diabetology team in order to make therapeutic decisions as close as possible to the patient's metabolic needs. For this purpose, new parameters have been developed, to allow a more integrated reading and interpretation of data by clinical professionals. The new challenge for the diabetes community consists of promoting an integrated and homogeneous reading, as well as interpretation of glucose monitoring data also by the patient himself. The purpose of this review is to offer an overview of the glycemic status assessment, opened by the current data management provided by latest glucose monitoring technologies. Furthermore, the applicability and personalization of the different glycemic monitoring devices used in specific insulin-treated diabetes mellitus patient populations will be evaluated.

Lessons from Use of Continuous Glucose Monitoring Systems in Digital Healthcare

We live in a digital world where a variety of wearable medical devices are available. These technologies enable us to measure our health in our daily lives. It is increasingly possible to manage our own health directly through data gathered from these wearable devices. Likewise, healthcare professionals have also been able to indirectly monitor patients' health. Healthcare professionals have accepted that digital technologies will play an increasingly important role in healthcare. Wearable technologies allow better collection of personal medical data, which healthcare professionals can use to improve the quality of healthcare provided to the public. The use of continuous glucose monitoring systems (CGMS) is the most representative and desirable case in the adoption of digital technology in healthcare. Using the case of CGMS and examining its use from the perspective of healthcare professionals, this paper discusses the necessary adjustments required in clinical practices. There is a need for various stakeholders, such as medical staff, patients, industry partners, and policy-makers, to utilize and harness the potential of digital technology.

A Review of Research Progress on Glycemic Variability and Gestational Diabetes

Gestational diabetes mellitus (GDM) is associated with many adverse obstetric outcomes and neonatal outcomes, including preeclampsia, Cesarean section, and macrosomia. Active screening and early diabetes control can reduce the occurrence of adverse outcomes. Glycosylated hemoglobin (HbA1c) only reflects average blood glucose levels, but not glycemic variability (GV). Studies have shown that GV can cause a series of adverse reactions, and good control of GV can reduce the incidence of adverse pregnancy outcomes in patients with GDM. In order to provide clinicians with a better basis for diagnosis and treatment, this study reviewed the measurement, evaluation, and control of GV, the importance of GV for patients with GDM, and correlations between GV and maternal and neonatal outcomes.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2020

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc20-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Gestational Diabetes Mellitus

Although it has been accepted for decades that women with gestational diabetes mellitus (GDM) are at high risk for future development of type 2 diabetes, vigorous debate regarding the value of detecting and treating GDM has persisted into the twenty-first century. Although results from 2 randomized trials provide strong evidence that treating GDM reduces adverse perinatal outcomes, it remains to be determined whether treatment impacts long-term offspring outcomes. Insulin is the first-line pharmacologic treatment and is added when glycemic goals are not met with nutritional modifications. Oral agent use is controversial, as data on long-term offspring outcomes are lacking.

Chinese clinical guidelines for continuous glucose monitoring (2018 edition)

Blood glucose monitoring is an important part of diabetes management. Continuous glucose monitoring (CGM) technology has become an effective complement to conventional blood glucose monitoring methods and has been widely applied in clinical practice. The indications for its use, the accuracy of the generated data, the interpretation of the CGM results, and the application of the results must be standardized. In December 2009, the Chinese Diabetes Society (CDS) drafted and published the first Chinese Clinical Guideline for Continuous Glucose Monitoring (2009 edition), providing a basis for the standardization of CGM in clinical application. Based on the updates of international guidelines and the increasing evidence of domestic studies, it is necessary to revise the latest CGM guidelines in China so that the recent clinical evidence can be effectively translated into clinical benefit for diabetic patients. To this end, the CDS revised the Chinese Clinical Guideline for Continuous Glucose Monitoring (2012 Edition) based on the most recent evidence from international and domestic studies.

Application and Utility of Continuous Glucose Monitoring in Pregnancy: A Systematic Review

Background: In the past decade, continuous glucose monitoring (CGM) has been proven to have similar accuracy to self-monitoring of blood glucose (SMBG) and yet provides better therapy optimization and detects trends in glucose values due to higher frequency of testing. Even though the feasibility and utility of CGM has been proven successfully in Type 1 and 2 diabetes, there is a lack of knowledge of its application and effectiveness in pregnancy, especially in gestational diabetes mellitus (GDM). In this review, we aimed to summarize and evaluate the updated scientific evidence on the application of CGM in pregnancies complicated with GDM. Methods: A search using keywords related to CGM and GDM on PubMed was conducted and articles were filtered based on full text, year of publication (Jan 1998-Dec 2018), human subject studies, and written in English. Reviews and duplicate articles were removed. A final total of 29 articles were included in this review. Results: In terms of maternal and fetal outcomes, inconsistent evidence was reported. Among GDM patients using CGM and SMBG, two randomized controlled trials (RCTs) found no significant differences in macrosomia, birth weight (BW), and gestational age (GA) at delivery between these two groups, while one prospective cohort found a lower incidence of cesarean section and macrosomia in CGM use subjects. Furthermore, CGM use was consistently found to have increased detection in dysglycemia and glycemic variability compared to SMBG. In terms of clinical utility, CGM use led to more treatment adjustments and lower gestational weight gain (GWG). Lastly, CGM use showed higher postprandial glucose levels in GDM-complicated pregnancies than in normal pregnancies. Conclusion: Current updated evidence suggests that CGM is superior to SMBG among GDM pregnancies in terms of detecting hypoglycemic and hyperglycemic episodes, which might result in an improvement of maternal and fetal outcomes. In addition, CGM detects a wider glycemic variability in GDM mothers than non-GDM controls. Further research with larger sample sizes and complete pregnancy coverage is needed to explore the clinical utility such as screening and predictive values of CGM for GDM.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2019

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Perspective on the Accuracy of Blood Glucose Meters During Pregnancy

Blood glucose monitoring is fundamental for hyperglycemia management during pregnancy, but are the devices up to the job? Studies assessing the accuracy of 10 commercially available glucose meters during pregnancy showed that although >98-99% of the meter values were in the acceptable zones of the error grid for the majority of the meters, the meter performance varied, with the majority showing positive bias and a few showing minimal negative bias. The mean difference between meter and laboratory plasma values varied between -0.33 and 0.73 mmol/L. Three meters showed deviations from laboratory results with a change in maternal hematocrit levels. No meters had a total analytical error <5%, and no studies evaluated meters using recent International Organization for Standardization 15197:2013 criteria. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) recently showed that an antenatal continuous glucose monitoring system (CGMS), as an adjunct to capillary monitoring, was associated with a lower incidence of large-for-gestational-age babies, fewer neonatal intensive care unit admissions (>24 h), and a lower incidence of neonatal hypoglycemia. The flash glucose monitoring system shows good accuracy in pregnant women but has not been marketed widely in the U.S. We suggest that meters cannot be assumed to be sufficiently accurate during pregnancy and that manufacturers should ensure a total error <5%, with bias and imprecision <2% during pregnancy. Large studies are needed to evaluate the usefulness of CGMS among pregnant women with type 2 diabetes and gestational diabetes mellitus.

Comparison of Glycemic Variability in Chinese T2DM Patients Treated with Exenatide or Insulin Glargine: A Randomized Controlled Trial

INTRODUCTION

Increasing the frequency of blood glucose monitoring aids the evaluation of glycemic variability and blood glucose control by antidiabetic drugs. It remains unclear, however, whether GLP-1 receptor agonists or basal insulin has a better effect on glycemic variability in type 2 diabetes mellitus (T2DM) patients who are inadequately controlled by metformin. We used a continuous glucose monitoring system (CGMS) to compare patients on a GLP-1 receptor agonist with patients on basal insulin in terms of glycemic variability.

METHODS

This prospective randomized study assigned T2DM patients treated with metformin (N = 39) to either exenatide treatment or insulin glargine treatment for 16 weeks. Glycemic variability was assessed using a CGMS; hemoglobin A1c (HbA1c), β-cell function, weight, body mass index (BMI), and waist circumference were also evaluated.

RESULTS

Mean blood glucose level, continuous overlapping net glycemic action, mean amplitude of glycemic excursions, percentage of the time that the blood glucose value was > 10.0 mmol/L, and highest blood glucose level (P  < 0.01-0.05) significantly decreased in both groups. Standard deviation of the mean glucose value, largest amplitude of glycemic excursions, and waist circumference significantly decreased for those treated with exenatide (P  < 0.05), while no changes were observed with insulin glargine treatment. Percentage of the time that the blood glucose value was > 7.8 mmol/L decreased after insulin glargine use (P  < 0.05) but not with the exenatide intervention. Similar decreases in fasting blood glucose and HbA1c and increases in the 1/homeostasis model assessment of insulin resistance, disposition index 30, and disposition index 120 were observed in both groups (P  < 0.01-0.05). Reductions in weight and BMI were greater with exenatide than with insulin glargine treatment (P  < 0.05).

CONCLUSIONS

In overweight and obese patients with T2DM inadequately controlled by metformin, exenatide and insulin glargine have similar efficacies in terms of glycemic variability, HbA1c alleviation, and β-cell function, but exenatide has a greater effect on body weight and BMI.

Correlation Between Third Trimester Glycemic Variability in Non-Insulin-Dependent Gestational Diabetes Mellitus and Adverse Pregnancy and Fetal Outcomes

BACKGROUND

Gestational diabetes mellitus (GDM) is a pregnancy-related metabolic complication. Despite optimal glycemic control from self-monitoring blood glucose (SMBG) in non-insulin-dependent GDM, variations in pregnancy outcomes persist. Glycemic variability is believed to be a factor that causes adverse pregnancy outcomes. Continuous glucose monitoring system (CGMS) detects interstitial glucose values every 5 minutes, and glycemic variability data from CGMS during the third trimester may be a predictor of fetal birth weight and pregnancy outcomes. The aim of this study was to investigate correlation between third trimester glycemic variability in non-insulin-dependent GDM and fetal birth weight.

METHOD

This prospective study was conducted in 55 pregnant volunteers with non-insulin-dependent GDM that were recruited at 28 to 32 weeks' gestation from the outpatient clinic of the Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital during the study period of August 1 to December 31, 2016. Patients had CGMS installed for at least 72 hours and glycemic variability data were analyzed.

RESULTS

Of 55 enrolled volunteers, the data from 47 women were included in the analysis. Mean CGMS duration was 85.5 ± 12.83 hours. No statistically significant correlation was identified between glycemic variability in third trimester and birth weight percentiles, or between third trimester CGMS parameters and pregnancy outcomes in the study.

CONCLUSION

Based on these findings, third trimester glycemic variability data from CGMS are not a predictor of fetal birth weight percentile, and no significant association was found between CGMS parameters and adverse pregnancy outcomes; thus, CGMS is not necessary in non-insulin-dependent GDM.

Parâmetros utilizados na avaliação de bem-estar do bebê no nascimento

Objectivo: identificar parâmetros que se utilizan para evaluar el bienestar del recién nacido.Síntesis del contenido: revisión integrativa de la literatura, realizada en las bases PubMed y Biblioteca Virtual de Salud (bvs), que utilizó los descriptores “apgar score”, “neonatal outcomes”, “fetal vitality” y “health services evaluation”. El recorte temporal fue de enero del 2011 a diciembre del 2016. Se importaron los resúmenes para el software Endnote Web®, para la remoción de duplicados y los remanentes exportados para el software Covidence®, lo que permitió la selección de la muestra final por dos investigadoras, de forma independiente. La muestra final incluyó 17 estudios. Los parámetros más utilizados fueron admisión del neonato en Unidad de Cuidados Intensivos en las primeras 24 a 48 horas de vida y el índice de Apgar, pero hubo variaciones en la mensuración de esos parámetros entre los estudios. Otros parámetros fueron: peso al nacer, temperatura corporal, natimortalidad y mortalidad neonatal. El Apgar, a pesar de utilizado mundialmente, posibilita subjetividad en la evaluación de algunas variables; este puede evaluar la respuesta del bebé a las maniobras empleadas en el atendimiento en sala de parto, pero no debe ser un parámetro decisorio para instituir o no maniobras de reanimación.Conclusión: algunos parámetros fueron comunes entre los estudios, sin embargo pueden agregarse otros parâmetros al abordar patologías específicas. Se considera importante entrenar enfermeiros en la medición del Apgar, pues son professionales responsables por el cuidado de la madre y el bebé 24 horas del día y, en muchos servicios, por la primera atención del recién nacido.

Maternal glycoregulation in pregnancies complicated by diabetes mellitus in the prediction of fetal echography findings and perinatal outcomes

AIM

We aimed to determine maternal hemoglobin A1c (HbA1c) levels and pregestational body mass index (BMI) as the predictors of glycemic control and its importance for fetal echography findings and perinatal outcomes in pregnancies complicated by diabetes mellitus (DM).

METHODS

Our intention was to evaluate how BMI and HbA1c levels might be used to predict fetal interventricular septum (IVS) thickness, atrioventricular inflow early diastole (E)/ atrial systole (A) velocity ratio, and perinatal outcomes. Patients in the 38th gestational week were divided into three groups according to their insulin therapy: (i) patients with gestational diabetes mellitus (GDM) treated only with dietary changes (GDM group, n = 32); (ii) patients with GDM treated with insulin therapy (DM2 group, n = 27); and (iii) patients with type 1 DM (DM1 group, n = 22).

RESULTS

In the DM1 group, we found statistically significant correlations between BMI and IVS thickness (P = 0.036), HbA1c and IVS thickness, as well as the mitral E/A velocity ratio (P = 0.013 vs P = 0.007). In this group, HbA1c showed a statistically significant correlation to neonatal birth weight (P = 0.037) and BMI influenced on appearance respiratory distress syndrome in neonates in DM1 group (P = 0.027). The values of HbA1c predict neonatal respiratory distress syndrome in DM2 and GDM groups (P = 0.036).

CONCLUSION

As good predictors of maternal glycoregulation, BMI and HbA1c levels determine fetal echography findings as well as neonatal outcomes in pregnancies complicated by DM.

Different methods and settings for glucose monitoring for gestational diabetes during pregnancy

BACKGROUND

Incidence of gestational diabetes mellitus (GDM) is increasing worldwide. Blood glucose monitoring plays a crucial part in maintaining glycaemic control in women with GDM and is generally recommended by healthcare professionals. There are several different methods for monitoring blood glucose which can be carried out in different settings (e.g. at home versus in hospital).

OBJECTIVES

The objective of this review is to compare the effects of different methods and settings for glucose monitoring for women with GDM on maternal and fetal, neonatal, child and adult outcomes, and use and costs of health care.

SEARCH METHODS

We searched the Cochrane Pregnancy and Childbirth Group Trials Register (30 September 2016) and reference lists of retrieved studies.

SELECTION CRITERIA

Randomised controlled trials (RCTs) or quasi-randomised controlled trials (qRCTs) comparing different methods (such as timings and frequencies) or settings, or both, for blood glucose monitoring for women with GDM.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed study eligibility, risk of bias, and extracted data. Data were checked for accuracy.We assessed the quality of the evidence for the main comparisons using GRADE, for:- primary outcomes for mothers: that is, hypertensive disorders of pregnancy; caesarean section; type 2 diabetes; and- primary outcomes for children: that is, large-for-gestational age; perinatal mortality; death or serious morbidity composite; childhood/adulthood neurosensory disability;- secondary outcomes for mothers: that is, induction of labour; perineal trauma; postnatal depression; postnatal weight retention or return to pre-pregnancy weight; and- secondary outcomes for children: that is, neonatal hypoglycaemia; childhood/adulthood adiposity; childhood/adulthood type 2 diabetes.

MAIN RESULTS

We included 11 RCTs (10 RCTs; one qRCT) that randomised 1272 women with GDM in upper-middle or high-income countries; we considered these to be at a moderate to high risk of bias. We assessed the RCTs under five comparisons. For outcomes assessed using GRADE, we downgraded for study design limitations, imprecision and inconsistency. Three trials received some support from commercial partners who provided glucose meters or financial support, or both. Main comparisons Telemedicine versus standard care for glucose monitoring (five RCTs): we observed no clear differences between the telemedicine and standard care groups for the mother, for:- pre-eclampsia or pregnancy-induced hypertension (risk ratio (RR) 1.49, 95% confidence interval (CI) 0.69 to 3.20; 275 participants; four RCTs; very low quality evidence);- caesarean section (average RR 1.05, 95% CI 0.72 to 1.53; 478 participants; 5 RCTs; very low quality evidence); and- induction of labour (RR 1.06, 95% CI 0.63 to 1.77; 47 participants; 1 RCT; very low quality evidence);or for the child, for:- large-for-gestational age (RR 1.41, 95% CI 0.76 to 2.64; 228 participants; 3 RCTs; very low quality evidence);- death or serious morbidity composite (RR 1.06, 95% CI 0.68 to 1.66; 57 participants; 1 RCT; very low quality evidence); and- neonatal hypoglycaemia (RR 1.14, 95% CI 0.48 to 2.72; 198 participants; 3 RCTs; very low quality evidence).There were no perinatal deaths in two RCTs (131 participants; very low quality evidence). Self-monitoring versus periodic glucose monitoring (two RCTs): we observed no clear differences between the self-monitoring and periodic glucose monitoring groups for the mother, for:- pre-eclampsia (RR 0.17, 95% CI 0.01 to 3.49; 58 participants; 1 RCT; very low quality evidence); and- caesarean section (average RR 1.18, 95% CI 0.61 to 2.27; 400 participants; 2 RCTs; low quality evidence);or for the child, for:- perinatal mortality (RR 1.54, 95% CI 0.21 to 11.24; 400 participants; 2 RCTs; very low quality evidence);- large-for-gestational age (RR 0.82, 95% CI 0.50 to 1.37; 400 participants; 2 RCTs; low quality evidence); and- neonatal hypoglycaemia (RR 0.64, 95% CI 0.39 to 1.06; 391 participants; 2 RCTs; low quality evidence). Continuous glucose monitoring system (CGMS) versus self-monitoring of glucose (two RCTs): we observed no clear differences between the CGMS and self-monitoring groups for the mother, for:- caesarean section (RR 0.91, 95% CI 0.68 to 1.20; 179 participants; 2 RCTs; very low quality evidence);or for the child, for:- large-for-gestational age (RR 0.67, 95% CI 0.43 to 1.05; 106 participants; 1 RCT; very low quality evidence) and- neonatal hypoglycaemia (RR 0.79, 95% CI 0.35 to 1.78; 179 participants; 2 RCTs; very low quality evidence).There were no perinatal deaths in the two RCTs (179 participants; very low quality evidence). Other comparisons Modem versus telephone transmission for glucose monitoring (one RCT): none of the review's primary outcomes were reported in this trial Postprandial versus preprandial glucose monitoring (one RCT): we observed no clear differences between the postprandial and preprandial glucose monitoring groups for the mother, for:- pre-eclampsia (RR 1.00, 95% CI 0.15 to 6.68; 66 participants; 1 RCT);- caesarean section (RR 0.62, 95% CI 0.29 to 1.29; 66 participants; 1 RCT); and- perineal trauma (RR 0.38, 95% CI 0.11 to 1.29; 66 participants; 1 RCT);or for the child, for:- neonatal hypoglycaemia (RR 0.14, 95% CI 0.02 to 1.10; 66 participants; 1 RCT).There were fewer large-for-gestational-age infants born to mothers in the postprandial compared with the preprandial glucose monitoring group (RR 0.29, 95% CI 0.11 to 0.78; 66 participants; 1 RCT).

AUTHORS' CONCLUSIONS

Evidence from 11 RCTs assessing different methods or settings for glucose monitoring for GDM suggests no clear differences for the primary outcomes or other secondary outcomes assessed in this review.However, current evidence is limited by the small number of RCTs for the comparisons assessed, small sample sizes, and the variable methodological quality of the RCTs. More evidence is needed to assess the effects of different methods and settings for glucose monitoring for GDM on outcomes for mothers and their children, including use and costs of health care. Future RCTs may consider collecting and reporting on the standard outcomes suggested in this review.

Electronic-based lifestyle interventions in overweight or obese perinatal women: a systematic review and meta-analysis

Electronic-based (e-based) lifestyle interventions provide potential and cost-effective delivery of remote interventions for overweight and obese perinatal women. To date, no meta-analysis has reported the efficacy of maternal and neonatal outcomes. Seven electronic databases were searched from inception up to July 13, 2016, including the Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, EMBASE, ProQuest Dissertations and Theses, PsycINFO, PubMed and Scopus. Among the 1,145 studies retrieved, 14 randomized controlled trials were selected among 17 publications. The Cochrane risk of bias tool was used to appraise the quality assessment. The meta-analyses demonstrated a significant result for limiting gestational weight gain, losing postnatal weight in 1-2 months, increasing self-reported moderate and vigorous physical activity and reducing caloric intake using diet-related software. Our review shows that an e-based lifestyle intervention is an acceptable approach. The findings reveal the variability in intervention methods and provide limited conclusive evidence. Thus, future studies should examine the efficacy and essential components as well as the various approaches using optimal portions of in-person and phone sessions. Further evaluations comparing the effectiveness of different e-based lifestyle intervention approaches toward activity-related and diet-related outcomes are necessary.

Efficacy of Internet-Based Self-Monitoring Interventions on Maternal and Neonatal Outcomes in Perinatal Diabetic Women: A Systematic Review and Meta-Analysis

Background

Self-monitoring using the Internet offers new opportunities to engage perinatal diabetic women in self-management to reduce maternal and neonatal complications.

Objective

This review aims to synthesize the best available evidence to evaluate the efficacy of Internet-based self-monitoring interventions in improving maternal and neonatal outcomes among perinatal diabetic women.

Methods

The review was conducted using Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, PsyINFO, Scopus, and ProQuest Dissertations and Theses to search for English-language research studies without any year limitation. A risk of bias table was used to assess methodological quality. Meta-analysis was performed with RevMan software. Cochran Q and I² tests were used to assess heterogeneity. The overall effect was assessed using z tests at P<.05. Of the 438 studies identified through electronic searches and reference lists, nine experimental studies from 10 publications were selected.

Results

Half of the selected studies showed low risk of bias and comprised 852 perinatal diabetic women in six countries. The meta-analysis revealed that Internet-based self-monitoring interventions significantly decreased the level of maternal glycated hemoglobin A1c (z=2.23, P=.03) compared to usual care among perinatal diabetic women at postintervention. Moreover, Internet-based self-monitoring interventions significantly decreased the cesarean delivery rate (z=2.23, P=.03) compared to usual care among the mixed group at postintervention.

Conclusions

This review shows neonatal or other maternal outcomes are similar between Internet-based self-monitoring interventions and usual diabetes care among perinatal diabetic women. The long-term effects of the intervention must be confirmed in future studies using randomized controlled trials and follow-up data.