With randomised trial data confirming that continuous glucose monitoring (CGM) is associated with improvements in maternal glucose control and neonatal health outcomes, CGM is increasingly used in ...antenatal care. Across pregnancy, the ambition is to increase the CGM time in range (TIR), while reducing time above range (TAR), time below range (TBR) and glycaemic variability measures. Pregnant women with type 1 diabetes currently spend, on average, 50% (12 h), 55% (13 h) and 60% (14 h) in the target range of 3.5–7.8 mmol/l (63–140 mg/dl) during the first, second and third trimesters, respectively. Hyperglycaemia, as measured by TAR, reduces from 40% (10 h) to 33% (8 h) during the first to third trimester. A TIR of >70% (16 h, 48 min) and a TAR of <25% (6 h) is achieved only in the final weeks of pregnancy. CGM TBR data are particularly sensor dependent, but regardless of the threshold used for individual patients, spending ≥4% of time (1 h) below 3.5 mmol/l or ≥1% of time (15 min) below 3.0 mmol/l is not recommended. While maternal hyperglycaemia is a well-established risk factor for obstetric and neonatal complications, CGM-based risk factors are emerging. A 5% lower TIR and 5% higher TAR during the second and third trimesters is associated with increased risk of large for gestational age infants, neonatal hypoglycaemia and neonatal intensive care unit admissions. For optimal neonatal outcomes, women and clinicians should aim for a TIR of >70% (16 h, 48 min) and a TAR of <25% (6 h), from as early as possible during pregnancy.
Gestational diabetes mellitus (GDM) traditionally refers to abnormal glucose tolerance with onset or first recognition during pregnancy. GDM has long been associated with obstetric and neonatal ...complications primarily relating to higher infant birthweight and is increasingly recognized as a risk factor for future maternal and offspring cardiometabolic disease. The prevalence of GDM continues to rise internationally due to epidemiological factors including the increase in background rates of obesity in women of reproductive age and rising maternal age and the implementation of the revised International Association of the Diabetes and Pregnancy Study Groups' criteria and diagnostic procedures for GDM. The current lack of international consensus for the diagnosis of GDM reflects its complex historical evolution and pragmatic antenatal resource considerations given GDM is now 1 of the most common complications of pregnancy. Regardless, the contemporary clinical approach to GDM should be informed not only by its short-term complications but also by its longer term prognosis. Recent data demonstrate the effect of early in utero exposure to maternal hyperglycemia, with evidence for fetal overgrowth present prior to the traditional diagnosis of GDM from 24 weeks' gestation, as well as the durable adverse impact of maternal hyperglycemia on child and adolescent metabolism. The major contribution of GDM to the global epidemic of intergenerational cardiometabolic disease highlights the importance of identifying GDM as an early risk factor for type 2 diabetes and cardiovascular disease, broadening the prevailing clinical approach to address longer term maternal and offspring complications following a diagnosis of GDM.
Norbert Freinkel emphasized the need for "more aggressive therapy with exogenous insulin" during type 1 diabetes (T1D) pregnancy. Recent advances in diabetes technology, continuous glucose monitoring ...(CGM), and hybrid closed-loop (HCL) insulin delivery systems allow us to revisit Freinkel's observations from a contemporary perspective. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) led to international recommendations that CGM be offered to all pregnant women with T1D to help them meet their pregnancy glucose targets and improve neonatal outcomes. However, despite CGM use, only 35% of trial participants reached the pregnancy glucose targets by 35 weeks' gestation, which is too late for optimal obstetric and neonatal outcomes. The constant vigilance to CGM data and insulin dose adjustment, with perpetual worry about the impact of hyperglycemia on the developing fetal structures, leave many pregnant women feeling overwhelmed. HCL systems that can adapt to marked gestational changes in insulin sensitivity and pharmacokinetics may help to bridge the gap between the nonpregnant time in range glycemic targets (70-180 mg/dL) and the substantially more stringent pregnancy-specific targets (TIRp) (63-140 mg/dL) required for optimal obstetric and neonatal outcomes. Use of HCL (CamAPS FX system) was associated with a 10.5% higher TIRp, 10.2% less hyperglycemia, and 12.3% higher overnight TIRp. Clinical benefits were accompanied by 3.7 kg (8 lb) less gestational weight gain and consistently achieved across a representative patient population of insulin pump or injection users, across trial sites, and across maternal HbA1c categories. Working collaboratively, women, HCL technology, and health care teams achieved improved glycemia with less worry, less work, and more positive pregnancy experiences.
Pregnant women with diabetes are identified as being more vulnerable to the severe effects of COVID-19 and advised to stringently follow social distancing measures. Here, we review the management of ...diabetes in pregnancy before and during the lockdown.
Majority of antenatal diabetes and obstetric visits are provided remotely, with pregnant women attending hospital clinics only for essential ultrasound scans and labor and delivery. Online resources for supporting women planning pregnancy and for self-management of pregnant women with type 1 diabetes (T1D) using intermittent or continuous glucose monitoring are provided. Retinal screening procedures, intrapartum care, and the varying impact of lockdown on maternal glycemic control are considered. Alternative screening procedures for diagnosing hyperglycemia during pregnancy and gestational diabetes mellitus (GDM) are discussed. Case histories describe the remote initiation of insulin pump therapy and automated insulin delivery in T1D pregnancy.
Initial feedback suggests that video consultations are well received and that the patient experiences for women requiring face-to-face visits are greatly improved. As the pandemic eases, formal evaluation of remote models of diabetes education and technology implementation, including women's views, will be important.
Research and audit activities will resume and we will find new ways for supporting pregnant women with diabetes to choose their preferred glucose monitoring and insulin delivery.
In December 2020, the National Institute for Health and Care Excellence (NICE) reviewed the evidence and updated their recommendations on intermittently scanned (commonly known as Flash) and ...Continuous Glucose Monitoring (CGM) during pregnancy for women with type 1 diabetes.1 The NICE guidelines now recommend offering CGM to all pregnant women with type 1 diabetes to help them meet their pregnancy glucose targets and improve neonatal outcomes. Their evidence review, based on the CONCEPTT randomised trial2 and a Swedish observational study3 found that, compared to capillary glucose monitoring, CGM resulted in more women achieving their blood glucose targets, fewer caesarean sections and fewer neonatal intensive care admissions. Health economic modelling found that while Flash was the cheapest option (compared to CGM and capillary glucose monitoring) the quality of the evidence for Flash was very low, with concerns about clinical benefit, accuracy in the low glucose range and the number of daily capillary glucose tests required to use Flash safely. They concluded that there was high quality evidence that CGM was associated with better clinical outcomes and a 94% chance of CGM being cheaper than capillary glucose testing.
Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization ...of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Aims/hypothesis
The aim of this prospective nationwide study was to examine antenatal pregnancy care and pregnancy outcomes in women with type 1 and type 2 diabetes, and to describe changes since ...2002/2003.
Methods
This national population-based cohort included 3036 pregnant women with diabetes from 155 maternity clinics in England and Wales who delivered during 2015. The main outcome measures were maternal glycaemic control, preterm delivery (before 37 weeks), infant large for gestational age (LGA), and rates of congenital anomaly, stillbirth and neonatal death.
Results
Of 3036 women, 1563 (51%) had type 1, 1386 (46%) had type 2 and 87 (3%) had other types of diabetes. The percentage of women achieving HbA
1c
< 6.5% (48 mmol/mol) in early pregnancy varied greatly between clinics (median interquartile range 14.3% 7.7–22.2 for type 1, 37.0% 27.3–46.2 for type 2). The number of infants born preterm (21.7% vs 39.7%) and LGA (23.9% vs 46.4%) were lower for women with type 2 compared with type 1 diabetes (both
p
< 0.001). The prevalence rates for congenital anomaly (46.2/1000 births for type 1, 34.6/1000 births for type 2) and neonatal death (8.1/1000 births for type 1, 11.4/1000 births for type 2) were unchanged since 2002/2003. Stillbirth rates are almost 2.5 times lower than in 2002/2003 (10.7 vs 25.8/1000 births for type 1,
p
= 0.0012; 10.5 vs 29.2/1000 births for type 2,
p
= 0.0091).
Conclusions/interpretation
Stillbirth rates among women with type 1 and type 2 diabetes have decreased since 2002/2003. Rates of preterm delivery and LGA infants are lower in women with type 2 compared with type 1 diabetes. In women with type 1 diabetes, suboptimal glucose control and high rates of perinatal morbidity persist with substantial variations between clinics.
Data availability
Further details of the data collection methodology, individual clinic data and the full audit reports for healthcare professionals and service users are available from
http://content.digital.nhs.uk/npid
.
Cyclospora cayetanensis
is a protozoan parasite that causes foodborne and waterborne outbreaks of diarrheal illness worldwide. These foodborne outbreaks associated with the consumption of fresh ...produce and agricultural water could play a role in the contamination process. In this study, a method to detect
C. cayetanensis
in agricultural water by combining a robust filtration system with sensitive and specific molecular detection was developed and validated by the FDA. The results showed that this approach could consistently detect low levels of
C. cayetanensis
contamination in 10 liters of agricultural water, corresponding to the levels that may be found in naturally occurring environmental water sources. The method was also able to detect
C. cayetanensis
in surface water samples from a specific location in the Mid-Atlantic region. Our data demonstrate the robustness of the method to detect
C. cayetanensis
in agricultural water samples, which could be very useful to identify environmental sources of contamination.
ABSTRACT
Cyclospora cayetanensis
is a protozoan parasite that causes foodborne and waterborne diarrheal illness outbreaks worldwide. Most of these outbreaks are associated with the consumption of fresh produce. Sensitive and specific methods to detect
C. cayetanensis
in agricultural water are needed to identify the parasite in agricultural water used to irrigate crops that have been implicated in outbreaks. In this study, a method to detect
C. cayetanensis
in water by combining dead-end ultrafiltration (DEUF) with sensitive and specific molecular detection was developed and evaluated. Triplicates of 10-liter agricultural water samples were seeded with 200, 100, 25, 12, and 6
C. cayetanensis
oocysts. Surface water samples were also collected in the Mid-Atlantic region. All water samples were processed by DEUF and backflushed from the ultrafilters. DNA was extracted from concentrated samples and analyzed by quantitative PCR (qPCR) targeting the
C. cayetanensis
18S rRNA gene. All water samples seeded with 12, 25, 100, and 200 oocysts were positive, and all unseeded samples were negative. Samples seeded with 6 oocysts had a detection rate of 66.6% (8/12). The method was also able to detect
C. cayetanensis
isolates in surface water samples from different locations of the Chesapeake and Ohio Canal (C&O Canal) in Maryland. This approach could consistently detect
C. cayetanensis
DNA in 10-liter agricultural water samples contaminated with low levels of oocysts, equivalent to the levels that may be found in naturally incurred environmental water sources. Our data demonstrate the robustness of the method as a useful tool to detect
C. cayetanensis
from environmental sources.
IMPORTANCE
Cyclospora cayetanensis
is a protozoan parasite that causes foodborne and waterborne outbreaks of diarrheal illness worldwide. These foodborne outbreaks associated with the consumption of fresh produce and agricultural water could play a role in the contamination process. In this study, a method to detect
C. cayetanensis
in agricultural water by combining a robust filtration system with sensitive and specific molecular detection was developed and validated by the FDA. The results showed that this approach could consistently detect low levels of
C. cayetanensis
contamination in 10 liters of agricultural water, corresponding to the levels that may be found in naturally occurring environmental water sources. The method was also able to detect
C. cayetanensis
in surface water samples from a specific location in the Mid-Atlantic region. Our data demonstrate the robustness of the method to detect
C. cayetanensis
in agricultural water samples, which could be very useful to identify environmental sources of contamination.