ENDOCRINOLOGY IN THE TIME OF COVID-19: Diagnosis and management of gestational diabetes mellitus

Comparing the screening methods for gestational diabetes mellitus before and during the COVID-19 pandemic: A systematic review

BACKGROUND

The oral glucose tolerance test (OGTT) is the gold standard for detecting gestational diabetes mellitus (GDM). However, during the COVID-19 pandemic, screening practices were reevaluated due to the risk of infection associated with the prolonged hospital visit required for the OGTT. Some countries have published novel screening protocols for GDM, suggesting the utilization of hemoglobin A1c (HbA1c), random plasma glucose (RPG), or fasting plasma glucose (FPG) in favor of OGTTs during the pandemic. Therefore, differences in screening methods before and after the epidemic need to be examined.

METHODS

A systematic search was carried out across five electronic databases (Cinahl, Medline, Embase, Pubmed, and Web of Science) between 2016 and 2023. The Critical Appraisal Skills Programme (CASP) checklist for cohort studies was used to evaluate the quality of included papers.

RESULTS

A total of 13 eligible studies were included. Prior to the COVID-19 pandemic, the OGTT was the recommended measure to screen GDM, internationally based on various official guidelines. During the pandemic, it was recommended that HbA1c or FPG, or RPG be used as a substitute for OGTTs. However, the new methods have low sensitivity, may not reflect accurately the prevalence of GDM, and may lead to many false-negative results in women and to adverse pregnancy and neonatal outcomes.

CONCLUSION

The new screening methods for GDM have poor accuracy and a high risk of adverse pregnancy outcomes. Comparatively, targeted screening tests to detect GDM according to the risk level are more effective in an emergency. In the future, the alternatives to OGTTs still need to be further explored in more depth.

Effectiveness of remote monitoring for glycemic control on maternal-fetal outcomes in women with gestational diabetes mellitus: A meta-analysis

BACKGROUND

The current pandemic and future public health emergencies highlight the importance of evaluating a telehealth care model. Previous studies have reached mixed conclusions about the effectiveness of remote monitoring on glycemic control and maternal and infant outcomes in women with gestational diabetes mellitus (GDM).

OBJECTIVES

This meta-analysis aimed to evaluate the effectiveness of remote blood glucose monitoring for women with gestational diabetes mellitus and to provide evidence-based guidance on the management of women with gestational diabetes mellitus for policymakers and healthcare providers during situations such as pandemics or natural disasters.

METHODS

The Cochrane Library, PubMed, Web of Science, EBSCO, Embase, Medline, CINAHL databases, and ClinicalTrials.gov were systematically searched from their inception to July 10, 2021. Randomized controlled trials (RCTs) published in English with respect to remote blood glucose monitoring in women with GDM were included in the meta-analysis. Two independent reviewers performed data extraction and assessed the quality of the studies. Risk ratios, mean differences, 95% confidence intervals, and heterogeneity were calculated.

RESULTS

A total of 1265 participants were included in the 11 RCTs. There were no significant differences in glycemic control and maternal-fetal outcomes between the remote monitoring group and a standard care group, which included glycosylated hemoglobin (HbA1c), fasting blood glucose, mean 2-h postprandial blood glucose, caesarean birth, gestational weight gain, shoulder dystocia, neonatal hypoglycemia, and other outcomes.

CONCLUSION

This meta-analysis reveals that it is unclear if remote glucose monitoring is preferable to standard of care glucose monitoring. To improve glycemic control and maternal-fetal outcomes during the current epidemic or other natural disasters, the implementation of double-blind RCTs in the context of simulating similar disasters remains to be studied in the future.

Effects of the COVID-19 pandemic on gestational diabetes in Castilla-La Mancha (Spain)

SUBJECT-MATTER

To assess the effect of the 2019 coronavirus (COVID-19) pandemic on gestational diabetes (GDM).

MATERIAL AND METHODS

In this retrospective, multicentre, non-interventional study carried out in Castilla-La Mancha, Spain, we compared 663 women with GDM exposed to the pandemic (pandemic group), with 622 women with GDM seen one year earlier (pre-pandemic group). The primary endpoint was a Large for Gestational Age (LGA) newborn as an indicator of poor GDM control. Secondary endpoints included obstetric and neonatal complications.

RESULTS

During the pandemic, the gestational week at diagnosis (24.2 ± 7.4 vs 22.9 ± 7.7, p = 0.0016) and first visit to Endocrinology (26.6 ± 7.2 vs 25.3 ± 7.6, p = 0.0014) were earlier. Face-to-face consultations were maintained in most cases (80.3%). The new diagnostic criteria for GDM were used in only 3% of cases. However, in the pandemic group, the final HbA1c was higher (5.2 ± 0.48 vs 5.29 ± 0.44%, p = 0.047) and there were more LGA newborns (8.5% vs 12.8%, p = 0.015). There were no differences in perinatal complications.

CONCLUSIONS

Care for GDM in our Public Health System did not significantly deteriorate during the COVID-19 pandemic. However, this did not prevent a higher number of LGA newborns.

Temporal validation and updating of a prediction model for the diagnosis of gestational diabetes mellitus

OBJECTIVE

The original Monash gestational diabetes mellitus (GDM) risk prediction in early pregnancy model is internationally externally validated and clinically implemented. We temporally validate and update this model in a contemporary population with a universal screening context and revised diagnostic criteria and ethnicity categories, thereby improving model performance and generalizability.

STUDY DESIGN AND SETTING

The updating dataset comprised of routinely collected health data for singleton pregnancies delivered in Melbourne, Australia from 2016 to 2018. Model predictors included age, body mass index, ethnicity, diabetes family history, GDM history, and poor obstetric outcome history. Model updating methods were recalibration-in-the-large (Model A), intercept and slope re-estimation (Model B), and coefficient revision using logistic regression (Model C1, original ethnicity categories; Model C2, revised ethnicity categories). Analysis included 10-fold cross-validation, assessment of performance measures (c-statistic, calibration-in-the-large, calibration slope, and expected-observed ratio), and a closed-loop testing procedure to compare models' log-likelihood and akaike information criterion scores.

RESULTS

In 26,474 singleton pregnancies (4,756, 18% with GDM), the original model demonstrated reasonable temporal validation (c-statistic = 0.698) but suboptimal calibration (expected-observed ratio = 0.485). Updated model C2 was preferred, with a high c-statistic (0.732) and significantly better performance in closed testing.

CONCLUSION

We demonstrated updating methods to sustain predictive performance in a contemporary population, highlighting the value and versatility of prediction models for guiding risk-stratified GDM care.

Attitudes of women with gestational diabetes toward diet and exercise: a qualitative study

OBJECTIVE

Gestational diabetes (GDM) refers to glucose intolerance of varying severity first occurring in pregnancy. Following a diagnosis of GDM, exercise and dietary modification has a positive effect on improving glycemic control. Lifestyle changes affected in pregnancies affected by GDM have beneficial effects on long-term health if continued following birth. In addition, the psychological impact of a diagnosis of GDM should not be overlooked. Reports of maternal stress, anxiety, and fear are commonly reported issues in the literature. Support, both socially and from health care professionals, is also linked with higher rates of success in GDM management. Research to date had focused on women's reaction to a diagnosis of GDM, their mood and quality of life following a diagnosis, and their knowledge or opinions on the management of GDM. This qualitative study explored the attitudes of women with GDM toward these lifestyle changes, specifically diet and exercise. Women were also asked to identify advice that would be useful for other women newly diagnosed with GDM.

METHODS

With ethical approval a qualitative study was conducted using semi-structured interviews which were examined using Thematic Analysis. Patients were invited to participate and gave written consent after a discussion with a study researcher. The question plan for semi-structured interviews was designed with the advice of patient advocates. Recurrent themes were developed until the saturation of data.

RESULTS

Thirty-two women took part in the study. Time, convenience, and lack of educational awareness were common barriers to healthy eating and physical activity plans. Enablers for change included meal planning and organization. Women regarded their diets pre-diagnosis as healthy, with small "tweaks" (such as portion control) required to comply with recommendations. Another significant facilitator to change was support from the woman's partner. This also set a benchmark for plans of diet maintenance within the family structure after pregnancy. Unlike dietary changes, a consistent theme was that exercise was considered a "chore" in managing GDM and was unlikely to be continued in the long term. Practical advice offered by participants for other women with GDM included organization, realistic approaches, and lack of self-blame.

CONCLUSION

Women reported that changes in diet would be more achievable in the long term than changes in exercise patterns. Partners and the clinical team were significant sources of support. Women's views are crucial to providing clinicians with a comprehensive and holistic understanding of disease management. Involving women in self-care decisions and empowering women to manage their own health are key contributors to long-term behavior change as well as service provision and policy implementation.

Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning model

BACKGROUND

Early identification of pregnant women at high risk of developing gestational diabetes (GDM) is desirable as effective lifestyle interventions are available to prevent GDM and to reduce associated adverse outcomes. Personalised probability of developing GDM during pregnancy can be determined using a risk prediction model. These models extend from traditional statistics to machine learning methods; however, accuracy remains sub-optimal.

OBJECTIVE

We aimed to compare multiple machine learning algorithms to develop GDM risk prediction models, then to determine the optimal model for predicting GDM.

METHODS

A supervised machine learning predictive analysis was performed on data from routine antenatal care at a large health service network from January 2016 to June 2021. Predictor set 1 were sourced from the existing, internationally validated Monash GDM model: GDM history, body mass index, ethnicity, age, family history of diabetes, and past poor obstetric history. New models with different predictors were developed, considering statistical principles with inclusion of more robust continuous and derivative variables. A randomly selected 80% dataset was used for model development, with 20% for validation. Performance measures, including calibration and discrimination metrics, were assessed. Decision curve analysis was performed.

RESULTS

Upon internal validation, the machine learning and logistic regression model's area under the curve (AUC) ranged from 71% to 93% across the different algorithms, with the best being the CatBoost Classifier (CBC). Based on the default cut-off point of 0.32, the performance of CBC on predictor set 4 was: Accuracy (85%), Precision (90%), Recall (78%), F1-score (84%), Sensitivity (81%), Specificity (90%), positive predictive value (92%), negative predictive value (78%), and Brier Score (0.39).

CONCLUSIONS

In this study, machine learning approaches achieved the best predictive performance over traditional statistical methods, increasing from 75 to 93%. The CatBoost classifier method achieved the best with the model including continuous variables.

Maternal and Perinatal Outcomes During the COVID-19 Epidemic in Pregnancies Complicated by Gestational Diabetes

Introduction

Gestational diabetes (GDM) is one of the most common complications in pregnancy, with a prevalence that continues to rise. At the time of the COVID-19 epidemic, immediate reorganisation and adjustment of the system was needed. Telemedicine support was offered in order to provide high-quality treatment to pregnant women. However, the success of the treatment is unknown. We therefore aimed to evaluate COVID-19 epidemic effects on pregnancy outcomes in GDM.

Methods

The maternal outcomes (insulin treatment, gestational weight gain, caesarean section, hypertensive disorders) and perinatal outcomes (rates of large and small for gestational age, preterm birth and a composite child outcome) of women visiting a university hospital diabetes clinic from March to December 2020 were compared with those treated in the same period in 2019.

Results

Women diagnosed with GDM during the COVID-19 epidemic (n=417), were diagnosed earlier (23.9 [11.7-26.0] vs. 25.1 [21.8-26.7] gestational week), had higher fasting glucose (5.2 [5.0-5.4] vs. 5.1 [4.8-5.3] mmol/l) and earlier pharmacological therapy initiation, and had achieved lower HbA1c by the end of followup (5.1% (32.2 mmol/mol) [4.9% (30.1 mmol/mol)-5.4% (35.0 mmol/mol)] vs. 5.2% (33.3 mmol/mol) [5.0% (31.1 mmol/mol) - 5.4%·(35.5 mmol/mol)], p<0.001) compared to a year before (n=430). No significant differences in perinatal outcomes were found.

Conclusions

Although GDM was diagnosed at an earlier gestational age and higher fasting glucose concentration was present at the time of diagnosis, the COVID-19 epidemic did not result in worse glucose control during pregnancy or worse pregnancy outcomes in Slovenia.

Double jeopardy-pregnancy and birth during a catastrophic bushfire event followed by a pandemic lockdown, a natural experiment

BACKGROUND

From November 2019 to January 2020, eastern Australia experienced the worst bushfires in recorded history. Two months later, Sydney and surrounds were placed into lockdown for six weeks due to the COVID-19 pandemic, followed by ongoing restrictions. Many pregnant women at this time were exposed to both the bushfires and COVID-19 restrictions.

OBJECTIVE

To assess the impact of exposure to bushfires and pandemic restrictions on perinatal outcomes.

METHODS

The study included 60 054 pregnant women who gave birth between November 2017 and December 2020 in South Sydney. Exposure cohorts were based on conception and birthing dates: 1) bushfire late pregnancy, born before lockdown; 2) bushfires in early-mid pregnancy, born during lockdown or soon after; 3) conceived during bushfires, lockdown in second trimester; 4) conceived after bushfires, pregnancy during restrictions. Exposure cohorts were compared with pregnancies in the matching periods in the two years prior. Associations between exposure cohorts and gestational diabetes, preeclampsia, hypertension, stillbirth, mode of birth, birthweight, preterm birth and small for gestational age were assessed using generalised estimating equations, adjusting for covariates.

RESULTS

A decrease in low birth weight was observed for cohort 1 (aOR 0.81, 95%CI 0.69, 0.95). Conversely, cohort 2 showed an increase in low birth weight, and increases in prelabour rupture of membranes, and caesarean sections (aOR 1.18, 95%CI 1.03, 1.37; aOR 1.21, 95%CI 1.07, 1.37; aOR 1.10 (1.02, 1.18) respectively). Cohort 3 showed an increase in unplanned caesarean sections and high birth weight babies (aOR 1.15, 95%CI 1.04, 1.27 and aOR 1.16, 95%CI 1.02, 1.31 respectively), and a decrease in gestational diabetes mellitus was observed for both cohorts 3 and 4.

CONCLUSION

Pregnancies exposed to both severe climate events and pandemic disruptions appear to have increased risk of adverse perinatal outcomes beyond only experiencing one event, but further research is needed.

Development, validation and clinical utility of a risk prediction model for adverse pregnancy outcomes in women with gestational diabetes: The PeRSonal GDM model

BACKGROUND

The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with gestational diabetes mellitus (GDM) would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. We aimed to develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM.

METHODS

A prediction model development and validation study was conducted on data from a observational cohort. Participants included all women with GDM from three metropolitan tertiary teaching hospitals in Melbourne, Australia. The development cohort comprised those who delivered between 1 July 2017 to 30 June 2018 and the validation cohort those who delivered between 1 July 2018 to 31 December 2018. The main outcome was a composite of critically important maternal and perinatal complications (hypertensive disorders of pregnancy, large-for-gestational age neonate, neonatal hypoglycaemia requiring intravenous therapy, shoulder dystocia, perinatal death, neonatal bone fracture and nerve palsy). Model performance was measured in terms of discrimination and calibration and clinical utility evaluated using decision curve analysis.

FINDINGS

The final PeRSonal (Prediction for Risk Stratified care for women with GDM) model included body mass index, maternal age, fasting and 1-hour glucose values (75-g oral glucose tolerance test), gestational age at GDM diagnosis, Southern and Central Asian ethnicity, East Asian ethnicity, nulliparity, past delivery of an large-for-gestational age neonate, past pre-eclampsia, GWG until GDM diagnosis, and family history of diabetes. The composite adverse pregnancy outcome occurred in 27% (476/1747) of women in the development (1747 women) and in 26% (244/955) in the validation (955 women) cohorts. The model showed excellent calibration with slope of 0.99 (95% CI 0.75 to 1.23) and acceptable discrimination (c-statistic 0.68; 95% CI 0.64 to 0.72) when temporally validated. Decision curve analysis demonstrated that the model was useful across a range of predicted probability thresholds between 0.15 and 0.85 for adverse pregnancy outcomes compared to the alternatives of managing all women with GDM as if they will or will not have an adverse pregnancy outcome.

INTERPRETATION

The PeRSonal GDM model comprising of routinely available clinical data shows compelling performance, is transportable across time, and has clinical utility across a range of predicted probabilities. Further external validation of the model to a more disparate population is now needed to assess the generalisability to different centres, community based care and low resource settings, other healthcare systems and to different GDM diagnostic criteria.

FUNDING

This work is supported by the Mothers and Gestational Diabetes in Australia 2 NHMRC funded project #1170847.

Fasting Glucose for the Diagnosis of Gestational Diabetes Mellitus (GDM) during the COVID-19 Pandemic

Background: During the COVID-19 pandemic, different non-validated tests were proposed to simplify the diagnosis of gestational diabetes (GDM). Aim: To analyse the effects of replacing the two-step approach for Early-GDM and GDM diagnosis, with a fasting plasma glucose test. Material and Methods: This is a cohort study consisting of 3200 pregnant women: 400 with Early-GDM, 800 with GDM and 2000 with Non-GDM diagnosed using the two-step approach. Using fasting plasma glucose for Early-GDM and GDM diagnosis, according to the recommendations of Spain, Australia, Italy and the UK during the pandemic, the rates of missed and new Early-GDM and GDM were calculated and perinatal outcomes were analysed. Results: Using fasting plasma glucose in the first trimester >100 mg/dL for Early-GDM diagnosis, the rates of post-COVID missed and new Early-GDM were 79.5% and 3.2%, respectively. Using fasting plasma glucose at 24−28 weeks <84 or >92, 95 or 100 mg/dL for GDM diagnosis, the rates of missed GDM were 50.4%, 78%, 82.6% and 92.4%, respectively, and 8.6%, 5.6% and 2.3% women with Non-GDM were diagnosed with new GDM. Conclusion: Fasting plasma glucose is not a good test for the diagnosis of GDM either in the first trimester or at 24−28 weeks.

Serum hepatic biomarkers in women with obstetric cholestasis and a concurrent SARS-CoV-2 infection

Aim

The aim of the study was to evaluate the association between SARS‐CoV‐2 infection and serum hepatic biomarker levels among women with obstetric cholestasis.

Methods

In this prospective study, we recruited all pregnant women admitted in our hospital with obstetric cholestasis. Among those with a concurrent SARS‐CoV‐2 infection, we evaluated the following serum hepatic biomarkers: aspartate aminotransferase (AST), alanine aminotransferase (ALT), and biliar acids (BA).

Results

Among the 88 women enrolled in the study, 20 presented with a SARS‐CoV‐2 infection while 68 were negative. SARS‐CoV‐2 infected women were younger (mean age 30.5 ± 5.7 vs. 34.3 ± 5.4; p < 0.01) and in a greater percentage of non‐Caucasian ethnicity when compared to noninfected women (60.0% vs. 17.6%; p < 0.01). Regarding levels of hepatic biomarkers, they showed higher levels of AST (111.5 ± 134.1 vs. 37.3 ± 43.4 UI/L; p = 0.02), ALT (132.2 ± 115.7 vs. 50.5 ± 73.173.1 UI/L; p < 0.01), and BA (41.4 ± 46.8 vs. 18.4 ± 13.4 μmol/L; p = 0.04) compared to noninfected patients. No significant differences in maternal or fetal outcomes were found between infected and noninfected women.

Conclusion

SARS‐CoV‐2 infection was associated with higher levels of liver enzymes in patients with obstetric cholestasis. This could be the result of a possible hepatic involvement in patients with SARS‐CoV‐2 infection.

Cardiometabolic and Mental Health in Women With Early Gestational Diabetes Mellitus: A Prospective Cohort Study

CONTEXT

Early diagnosis and treatment of gestational diabetes (GDM) may reduce adverse obstetric and neonatal outcomes, especially in high-risk women. However, there is a lack of data for other outcomes.

OBJECTIVE

We compared cardiometabolic and mental health outcomes in women with early (eGDM) and classical (cGDM) GDM.

METHODS

This prospective cohort included 1185 All women with cGDM and 76 women with eGDM. The eGDM group had GDM risk factors (BMI >30 kg/m2, family history of diabetes, history of GDM, ethnicity), were tested at <20 weeks gestational age, and diagnosed using American Diabetes Association prediabetes criteria. All women underwent lifestyle adaptations. Obstetric, neonatal, mental, and cardiometabolic outcomes were assessed during pregnancy and postpartum.

RESULTS

The eGDM group had lower gestational weight gain than cGDM (10.7 ± 6.2 vs 12.6 ± 6.4; P = 0.03) but needed more medical treatment (66% vs 42%; P < 0.001). They had similar rates of adverse maternal and neonatal outcomes, except for increased large-for-gestational-age infants (25% vs 15%; P = 0.02). Mental health during pregnancy and postpartum did not differ between groups. eGDM had more atherogenic postpartum lipid profile than cGDM (P ≤ 0.001). In eGDM, the postpartum prevalence of the metabolic syndrome (MetS) was 1.8-fold, prediabetes was 3.1-fold, and diabetes was 7.4-fold higher than cGDM (waist circumference-based MetS: 62% vs 34%/BMI-based MetS: 46% vs 24%; prediabetes: 47.5% vs 15.3%; diabetes: 11.9% vs 1.6%, all P < 0.001). These differences remained unchanged after adjusting for GDM risk factors.

CONCLUSION

Compared with cGDM, eGDM was not associated with differences in mental health, but with increased adverse cardiometabolic outcomes, independent of GDM risk factors and gestational weight gain. This hints to a preexisting risk profile in eGDM.

Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Cardiovascular disease, especially coronary heart disease and cerebrovascular disease, is a leading cause of mortality and morbidity in women globally. The development of cardiometabolic conditions in pregnancy, such as gestational diabetes mellitus and hypertensive disorders of pregnancy, portend an increased risk of future cardiovascular disease in women. Pregnancy therefore represents a unique opportunity to detect and manage risk factors, prior to the development of cardiovascular sequelae. Risk prediction models for gestational diabetes mellitus and hypertensive disorders of pregnancy can help identify at-risk women in early pregnancy, allowing timely intervention to mitigate both short- and long-term adverse outcomes. In this narrative review, we outline the shared pathophysiological pathways for gestational diabetes mellitus and hypertensive disorders of pregnancy, summarise contemporary risk prediction models and candidate predictors for these conditions, and discuss the utility of these models in clinical application.

Association of COVID-19 Lockdown With Gestational Diabetes Mellitus

IMPORTANCE

The ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear.

AIM

To investigate the association between COVID-19 lockdown and GDM.

SUBJECTS AND METHODS

Medical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM.

RESULTS

The rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with < 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM.

CONCLUSIONS

The COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Impact of the Gestational Diabetes Diagnostic Criteria during the Pandemic: An Observational Study

OBJECTIVE

To analyze the effect of applying alternative diagnostic criteria for gestational diabetes mellitus (GDM) during the COVID-19 pandemic on GDM prevalence and obstetrical and perinatal outcomes, in comparison to usual diagnostic approaches.

METHODS

Data from women referred to GDM diagnosis from 1 September to 30 November 2019 were retrospectively collected (2019-group). The same data from the same period in 2020 were prospectively collected (2020-group). In both cases, a two-step diagnostic approach was used, the first step being a screening test (1 h 50 goral glucose tolerance test, OGTT). In 2019 it was followed by a 100 gr OGTT for diagnosis. In 2020, this was replaced by a blood test for the measurement of plasma glucose and HbA1c, according to alternative GDM diagnostic criteria during the COVID-19 pandemic.

RESULTS

From 237 women in the 2019 group, 40 (16.9%) were diagnosed with GDM, while from 255 women in the 2020 group, 37 (14.5%) had GDM (p = 0.470). More women in the 2020 group, in comparison to the 2019 group, were nulligravid (41.9% vs. 47.2%, p = 0.013), had a personal history of GDM (11.4% vs. 4.6%, p = 0.013) and had macrosomia in previous pregnancies (10.2% vs. 2.1%, p = 0.001). Obstetrical and perinatal outcomes were similar when comparing women with GDM to non-GDM women in the 2019 and 2020 groups and between GDM women and non-GDM women.

CONCLUSION

In a Spanish population, GDM prevalence during the COVID-19 pandemic using the alternative diagnostic criteria was similar to that found in 2019 using the usual diagnostic criteria. Despite women referred for GDM diagnosis during the pandemic having more GDM risk factors, obstetrical and perinatal outcomes were comparable to those observed before the pandemic.

COVID-19 and pregnancy: A scoping review on pregnancy characteristics and outcomes

AIM

The study aim was to map clinical characteristics and the evolution of pregnancies in pregnant women with confirmed diagnosis of SARS-CoV-2 infection.

METHODS

Searching four databases, studies were investigated that described the evolution of pregnancies in women diagnosed with SARS-CoV-2 infection through laboratory tests. A scoping review was undertaken, including 35 articles published in English. Two pairs of independent researchers synthesized the data.

RESULTS

Most studies were case studies or case series and had a low risk of bias. A predominance of cases was found in women over the age of 30 years who got infected in the third term of pregnancy and who had comorbidities. The prematurity index varied with the heterogeneity of the samples, and the cases of abortion occurred in combination with severe forms of infection. Caesarean section deliveries predominated, indicated mainly by respiratory decompensation caused by infection. Most women were discharged.

CONCLUSION

Based on the reviewed studies, the profile and evolution of pregnant women infected with COVID-19 could be evaluated.

COVID-19-related thyroiditis: A novel disease entity?

The literature on COVID-19-related thyroid complications has accumulated over the past year or so as the pandemic has accelerated throughout the world. In particular, several recent case reports have been published describing a possible correlation between COVID-19 disease and subacute thyroiditis (SAT). In this review, we briefly present one of our own patients and review the current published literature in this area up to January 2021, including analyses of major series of thyroid function tests in patients with significant COVID-19 infection. We conclude that while the great majority of patients with severe COVID-19 infection may show manifestations of the sick euthyroid syndrome, clinicians should be aware of the possibility of SAT, especially in the early weeks and months following even mild COVID-19 infection.

A Review of Prenatal Care Delivery to Inform the Michigan Plan for Appropriate Tailored Health Care in Pregnancy Panel

OBJECTIVE

To perform a literature review of key aspects of prenatal care delivery to inform new guidelines.

DATA SOURCES

A comprehensive review of Ovid MEDLINE, Elsevier's Scopus, Google Scholar, and ClinicalTrials.gov.

METHODS OF STUDY SELECTION

We included studies addressing components of prenatal care delivery (visit frequency, routine pregnancy assessments, and telemedicine) that assessed maternal and neonatal health outcomes, patient experience, or care utilization in pregnant individuals with and without medical conditions. Quality was assessed using the RAND/UCLA Appropriateness Methodology approach. Articles were independently reviewed by at least two members of the study team for inclusion and data abstraction.

TABULATION, INTEGRATION, AND RESULTS

Of the 4,105 published abstracts identified, 53 studies met inclusion criteria, totaling 140,150 participants. There were no differences in maternal and neonatal outcomes among patients without medical conditions with reduced visit frequency schedules. For patients at risk of preterm birth, increased visit frequency with enhanced prenatal services was inconsistently associated with improved outcomes. Home monitoring of blood pressure and weight was feasible, but home monitoring of fetal heart tones and fundal height were not assessed. More frequent weight measurement did not lower rates of excessive weight gain. Home monitoring of blood pressure for individuals with medical conditions was feasible, accurate, and associated with lower clinic utilization. There were no differences in health outcomes for patients without medical conditions who received telemedicine visits for routine prenatal care, and patients had decreased care utilization. Telemedicine was a successful strategy for consultations among individuals with medical conditions; resulted in improved outcomes for patients with depression, diabetes, and hypertension; and had inconsistent results for patients with obesity and those at risk of preterm birth.

CONCLUSION

Existing evidence for many components of prenatal care delivery, including visit frequency, routine pregnancy assessments, and telemedicine, is limited.

An Update on Screening Strategies for Gestational Diabetes Mellitus: A Narrative Review

Gestational diabetes mellitus (GDM) is a frequent medical complication during pregnancy. Screening and diagnostic practices for GDM are inconsistent across the world. This narrative review includes data from 87 observational studies and randomized controlled trials (RCTs), and aims to give an overview of the current evidence on screening strategies and diagnostic criteria for GDM. Screening in early pregnancy remains controversial and studies show conflicting results on the benefit of screening and treatment of GDM in early pregnancy. Implementing the one-step "International Association of Diabetes and Pregnancy Study Groups" (IADPSG) screening strategy at 24-28 weeks often leads to a substantial increase in the prevalence of GDM, without conclusive evidence regarding the benefits on pregnancy outcomes compared to a two-step screening strategy with a glucose challenge test (GCT). In addition, RCTs are needed to investigate the impact of treatment of GDM diagnosed with IADPSG criteria on long-term maternal and childhood outcomes. Selective screening using a risk-factor-based approach could be helpful in simplifying the screening algorithm but carries the risk of missing significant proportions of GDM cases. A two-step screening method with a 50g GCT and subsequently a 75g oral glucose tolerance test (OGTT) with IADPSG could be an alternative to reduce the need for an OGTT. However, to have an acceptable sensitivity to screen for GDM with the IADPSG criteria, the threshold of the GCT should be lowered from 7.8 to 7.2 mmol/L. A pragmatic approach to screen for GDM can be implemented during the COVID-19 pandemic, using fasting plasma glucose (FPG), HbA1c or even random plasma glucose (RPG) to reduce the number of OGTTs needed. However, usual guidelines and care should be resumed as soon as the COVID pandemic is controlled.

Reorganisation of obstetric services during the COVID pandemic - Experience from National Maternity Hospital Dublin Ireland

The 2020 SARS-CoV-2 pandemic posed significant challenges to the health service. Many services cancelled all routine appointments and surgery, which allowed them to redirect care towards large numbers of infected patients requiring respiratory and other support. Maternity services are relatively unique in that most of the care is time sensitive and cannot be rescheduled. Assessment such as routine bloods need to be taken in early pregnancy, anatomic surveys are best conducted at 20-22 weeks' gestation, and births continue regardless of a pandemic. In this paper we describe how National Maternity Hospital Dublin, with an annual delivery rate of 8000 births, reorganised services to continue to care for our mothers and babies. This included the development of a 'hospital within a hospital' approach, and separate physical and care pathways for positive cases. The delivery of virtual outpatient appointments and a comprehensive online patient education portal have proved successful.

Screening for Gestational Diabetes Mellitus in Early Pregnancy: What Is the Evidence?

The incidence of gestational diabetes mellitus (GDM) is increasing worldwide. This has a significant effect on the health of the mother and offspring. There is no doubt that screening for GDM between 24 and 28 weeks is important to reduce the risk of adverse pregnancy outcomes. However, there is no consensus about diagnosis and treatment of GDM in early pregnancy. In this narrative review on the current evidence on screening for GDM in early pregnancy, we included 37 cohort studies and eight randomized controlled trials (RCTs). Observational studies have shown that a high proportion (15–70%) of women with GDM can be detected early in pregnancy depending on the setting, criteria used and screening strategy. Data from observational studies on the potential benefit of screening and treatment of GDM in early pregnancy show conflicting results. In addition, there is substantial heterogeneity in age and BMI across the different study populations. Smaller RCTs could not show benefit but several large RCTs are ongoing. RCTs are also necessary to determine the appropriate cut-off for HbA1c in pregnancy as there is limited evidence showing that an HbA1c ≥6.5% has a low sensitivity to detect overt diabetes in early pregnancy.

Maternal medicine in the COVID era

The coronavirus disease-19 (COVID-19) pandemic has directly and indirectly impacted pregnant women with co-morbidities or antenatal medical complications, through vulnerability to the severe effects of COVID-19 and service reconfiguration. Women with diabetes or hypertension in pregnancy are at higher risk of admission to intensive care, need for invasive ventilation and death from COVID-19. Suggested service modifications specific to maternal medicine services include home measurement of blood glucose or blood pressure, the use of risk calculators, adaptations to screening criteria for gestational diabetes and monitoring of obstetric cholestasis. Neither the added risk of COVID-19 on pregnant women with medical comorbidities nor the impact of maternal medicine service modifications has yet been established.

Utility of Screening Fasting Plasma Glucose and Glycated Hemoglobin to Circumvent the Need for Oral Glucose Tolerance Test in Women with Prior Gestational Diabetes

INTRODUCTION

Our aim is to propose an evidence-based strategy for screening postpartum dysglycemia.

METHODS

This study included adult non-pregnant women who were diagnosed with gestational diabetes (GDM) using International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria during their index pregnancy (2012-2019). Eligible participants underwent a concurrent oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) test. A detailed questionnaire documenting relevant personal and medical history was filled, and the relevant anthropometric parameters were recorded.

RESULTS

We evaluated data from 377 women at a mean (± SD) age of 32.1 ± 4.6 years and at a median duration of 15 (10-33) months following childbirth. Diabetes was diagnosed in 42 (11.1%) women. Use of a combination cutoff [fasting plasma glucose (FPG) ≥ 6.1 mmol/L or glycated hemoglobin (HbA1c) ≥ 6.0% (42 mmol/mol)] avoided OGTT in 80.9% of the study cohort, without missing the diagnosis of diabetes in any study subject. The diagnosis was missed in 2.4% of women with diabetes (and 0.3% of whole cohort) using only the FPG criterion (≥ 5.6 mmol/L) or HbA1c criterion [HbA1c ≥ 5.7% (39 mmol/mol)] alone. These tests avoided the need for an OGTT in 75.3% and 65.5% of women, respectively.

CONCLUSIONS

The proposed strategies are likely to be both patient- and physician-friendly and have the potential to address several barriers for postpartum screening among women with prior GDM.

Adherence to Antidiabetic Medications among Women with Gestational Diabetes

BACKGROUND

Optimal adherence to prescribed medications in women with gestational diabetes is relevant for perinatal outcomes.

OBJECTIVE

To summarize available information on the prevalence and factors contributing to medication adherence in women with gestational diabetes from the biological and psychosocial perspectives.

METHODS

A literature search on adherence in gestational diabetes was conducted in PubMed/MEDLINE, CINAHL, Scopus, and the Directory of Open Access Journals for studies published on the topic. The Arksey and O'Malley framework for scoping reviews was used to explore and summarize the evidence.

RESULTS

A total of 2395 studies were retrieved of which 13 fully met the eligibility criteria. The studies were reported in Zimbabwe (n = 5), Iran (n = 1), Mexico (n = 1), South India (n = 1), the United States of America (n = 4), and one multinational study covering Australia, Europe, North and South America. The main types of antidiabetic medications used were insulin (n = 6), metformin (n = 4), and glyburide (n = 2). The prevalence of adherence ranged from 35.6% to 97%, with the assessment tool being self-report measures (n = 8). The main factors associated with nonadherence included worsening pregnancy symptoms, side effects of medications, perceived risks, mental health symptoms, poor social support, and socioeconomic status. Recommendations that evolved from the studies to improve adherence included education, counselling, improved support networks, and social interventions, while the main reported interventional study employed continuous education on the impact of adherence on perinatal outcomes.

CONCLUSION

Medication nonadherence in gestational diabetes seems to be influenced by multiple factors with some educational interventions positively impacting adherence behaviours. Thus, future research in women with gestational diabetes could consider interventions from a multifactorial perspective to improve therapeutic outcomes.

Management of gestational diabetes in women with a concurrent severe acute respiratory syndrome coronavirus 2 infection, experience of a single center in Northern Italy

Objective

In this study we describe the management of women with gestational diabetes (GD) and an ongoing severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. The aim of the study is to evaluate whether coronavirus disease 2019 (COVID‐19) can further complicate pregnancies, and if the protocol we usually use for GD pregnancies is also applicable to patients who have contracted a SARS‐CoV‐2 infection.

Methods

This is a retrospective study analyzing all pregnant women with GD and concomitant COVID‐19 admitted to our institution for antenatal care between March 1 and April 30, 2020.

Results

Among pregnant women with GD and a concomitant SARS‐CoV‐2 infection, the mean age was 32.9 (SD 5.6) years. Two patients (33%) were of white racial origin and four (67%) were of non‐white racial origin. All patients were diagnosed with COVID‐19 during the third trimester of pregnancy. Two women were asymptomatic and four were symptomatic. Only two (33.3%) women received treatment with insulin. None of the patients required intensive care or mechanical ventilation. No complications were found among the neonates.

Conclusion

COVID‐19 was not found to worsen the prognosis of patients with GD or of their offspring. Glycemic monitoring, diet therapy, and insulin, when needed, are sufficient for good metabolic control and favorable maternal and fetal outcomes.

The Oral Glucose Tolerance Test-Is It Time for a Change?-A Literature Review with an Emphasis on Pregnancy

Globally, gestational diabetes (GDM) is increasing at an alarming rate. This increase is linked to the rise in obesity rates among women of reproductive age. GDM poses a major global health problem due to the related micro- and macro-vascular complications of subsequent Type 2 diabetes and the impact on the future health of generations through the long-term impact of GDM on both mothers and their infants. Therefore, correctly identifying subjects as having GDM is of utmost importance. The oral glucose tolerance test (OGTT) has been the mainstay for diagnosing gestational diabetes for decades. However, this test is deeply flawed. In this review, we explore a history of the OGTT, its reproducibility and the many factors that can impact its results with an emphasis on pregnancy.

[Screening for gestational diabetes due to of the COVID-19 pandemic]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that causes coronavirus disease in 2019 (COVID-19). Currently, there is no evidence that pregnant women are more vulnerable to COVID-19. All concerns and anticipated risks are related to the potential impact of COVID-19 on perinatal outcomes, so pregnant women require special attention in relation to the preventive measures, diagnosis and treatment of a new coronavirus disease. Women with gestational diabetes mellitus (GDM) belong to the group of high perinatal risk and need timely medical assistance. During the COVID-19 pandemic, there is a necessity in temporary changes of approaches to diagnosing GSD and pregnancy care before and after delivery in women with GSD. The purpose of our review is to present and analyze all available GSD screening recommendations, updated and published in various countries in response to the coronavirus pandemic, at the time of publication of this article. It seems that there is no single universal strategy to achieve a reasonable balance. In this regard, it is necessary to develop new national algorithms for GSD screening, taking into account both demographic factors and the features and capabilities of our health system. We believe that the knowledge and experience achieved as a result of these changes will lead to the revision and improvement of national and international recommendations.

Testing for gestational diabetes during the COVID-19 pandemic. An evaluation of proposed protocols for the United Kingdom, Canada and Australia

AIMS

We assessed how altered diagnostic processes and criteria for gestational diabetes mellitus (GDM) recommended by the United Kingdom (UK), Canada and Australia for use during the COVID-19 pandemic would affect both GDM frequency and related adverse outcomes.

METHODS

Secondary analysis of 5974 HAPO study women with singleton pregnancies who underwent 75 g OGTTs and HbA1c assays between 24 and 32 weeks' gestation and who received no treatment for GDM.

RESULTS

All post COVID-19 modified pathways reduced GDM frequency - UK (81%), Canada (82%) and Australia (25%). Canadian women whose GDM would remain undetected post COVID-19 (missed GDMs) displayed similar rates of pregnancy complications to those with post COVID-19 GDM. Using UK modifications, the missed GDM group were at slightly lower risk whilst the women missed using the Australian modifications were at substantially lower risk.

CONCLUSIONS

The modifications in GDM diagnosis proposed for the UK, Canada and Australia result in differing reductions of GDM frequency. Each has both potential benefits in terms of reduction in potential exposure to COVID-19 and costs in terms of missed opportunities to influence pregnancy and postpartum outcomes. These factors should be considered when deciding which protocol is most appropriate for a particular context.