Emerging technologies for the management of Type 1 diabetes in pregnancy

Purpose of Review: The purpose of the study is to discuss emerging technologies available in the management of type 1 diabetes in pregnancy. Recent Findings: The latest evidence suggests that continuous glucose monitoring (CGM) should be offered to all women on intensive insulin therapy in early pregnancy. Studies have additionally demonstrated the ability of CGM to help gain insight into specific glucose profiles as they relate to glycaemic targets and pregnancy outcomes. Despite new studies comparing insulin pump therapy to multiple daily injections, its effectiveness in improving glucose and pregnancy outcomes remains unclear. Sensor-integrated insulin delivery (also called artificial pancreas or closed-loop insulin delivery) in pregnancy has been demonstrated to improve time in target and performs well despite the changing insulin demands of pregnancy. Summary: Emerging technologies show promise in the management of type 1 diabetes in pregnancy; however, research must continue to keep up as technology advances. Further research is needed to clarify the role technology can play in optimising glucose control before and during pregnancy as well as to understand which women are candidates for sensor-integrated insulin delivery

Seasonal variations in incidence and maternal-fetal outcomes of gestational diabetes.

AIMS: To determine whether the neonatal and delivery outcomes of gestational diabetes vary seasonally in the context of a relatively cool temperate climate. METHODS: A retrospect cohort of 23 735 women consecutively delivering singleton, live-born term infants in a single tertiary obstetrics centre in the UK (2004-2008) was identified. A total of 985 (4.1%) met the diagnostic criteria for gestational diabetes. Additive dynamic regression models, adjusted for maternal age, BMI, parity and ethnicity, were used to compare gestational diabetes incidence and outcomes over annual cycles. Outcomes included: random plasma glucose at booking; gestational diabetes diagnosis; birth weight centile; and delivery mode. RESULTS: The incidence of gestational diabetes varied by 30% from peak incidence (October births) to lowest incidence (March births; P=0.031). Ambient temperature at time of testing (28 weeks) was strongly positively associated with diagnosis (P<0.001). Significant seasonal variation was evident in birth weight in gestational diabetes-affected pregnancies (average 54th centile June to September; average 60th centile December to March; P=0.027). Emergency Caesarean rates also showed significant seasonal variation of up to 50% (P=0.038), which was closely temporally correlated with increased birth weights. CONCLUSIONS: There is substantial seasonal variation in gestational diabetes incidence and maternal-fetal outcomes, even in a relatively cool temperate climate. The highest average birth weight and greatest risk of emergency Caesarean delivery occurs in women delivering during the spring months. Recognizing seasonal variation in neonatal and delivery outcomes provides new opportunity for individualizing approaches to managing gestational diabetes.Catherine Aiken is supported by an Isaac Newton Trust/Wellcome Trust ISSF/ University of Cambridge Joint Research Grant. Claire Meek receives salary funding from the Diabetes UK Harry Keen Intermediate Clinical Fellowship (17/0005712). The funders have had no role in study design, data collection, data analysis, manuscript preparation and/or publication decisions

Managing hyperglycaemia during antenatal steroid administration, labour and birth in pregnant women with diabetes

Optimal glycaemic control before and during pregnancy improves both maternal and fetal outcomes. This article summarizes the recently published guidelines on the management of glycaemic control in pregnant women with diabetes on obstetric wards and delivery units produced by the Joint British Diabetes Societies for Inpatient Care and available in full at www.diabetes.org.uk/joint-british-diabetes-society and https://abcd.care/joint-british-diabetes-societies-jbds-inpatient-care-group. Hyperglycaemia following steroid administration can be managed by variable rate intravenous insulin infusion (VRIII) or continuous subcutaneous insulin infusion (CSII) in women who are willing and able to safely self‐manage insulin dose adjustment. All women with diabetes should have capillary blood glucose (CBG) measured hourly once they are in established labour. Those who are found to be higher than 7 mmol/l on two consecutive occasions should be started on VRIII. If general anaesthesia is used, CBG should be monitored every 30 min in the theatre. Both the VRIII and CSII rate should be reduced by at least 50% once the placenta is delivered. The insulin dose needed after delivery in insulin‐treated Type 2 and Type 1 diabetes is usually 25% less than the doses needed at the end of first trimester. Additional snacks may be needed after delivery especially if breastfeeding. Stop all anti‐diabetes medications after delivery in gestational diabetes. Continue to monitor CBG before and 1 h after meals for up to 24 h after delivery to pick up any pre‐existing diabetes or new‐onset diabetes in pregnancy. Women with Type 2 diabetes on oral treatment can continue to take metformin after birth

Improved pregnancy outcomes in women with type 1 and type 2 diabetes but substantial clinic-to-clinic variations: a prospective nationwide study

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 HbA1c < 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

Evaluating the informatics for integrating biology and the bedside system for clinical research

<p>Abstract</p> <p>Background</p> <p>Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.</p> <p>Methods</p> <p>Our evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.</p> <p>Results</p> <p>We found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.</p> <p>Conclusion</p> <p>The i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.</p

Differential effects of tactile high- and low-frequency stimulation on tactile discrimination in human subjects

<p>Abstract</p> <p>Background</p> <p>Long-term potentiation (LTP) and long-term depression (LTD) play important roles in mediating activity-dependent changes in synaptic transmission and are believed to be crucial mechanisms underlying learning and cortical plasticity. In human subjects, however, the lack of adequate input stimuli for the induction of LTP and LTD makes it difficult to study directly the impact of such protocols on behavior.</p> <p>Results</p> <p>Using tactile high- and low-frequency stimulation protocols in humans, we explored the potential of such protocols for the induction of perceptual changes. We delivered tactile high-frequency and low-frequency stimuli (t-HFS, t-LFS) to skin sites of approximately 50 mm²on the tip of the index finger. As assessed by 2-point discrimination, we demonstrate that 20 minutes of t-HFS improved tactile discrimination, while t-LFS impaired performance. T-HFS-effects were stable for at least 24 hours whereas t-LFS-induced changes recovered faster. While t-HFS changes were spatially very specific with no changes on the neighboring fingers, impaired tactile performance after t-LFS was also observed on the right middle-finger. A central finding was that for both t-LFS and t-HFS perceptual changes were dependent on the size of the stimulated skin area. No changes were observed when the stimulated area was very small (< 1 mm²) indicating special requirements for spatial summation.</p> <p>Conclusion</p> <p>Our results demonstrate differential effects of such protocols in a frequency specific manner that might be related to LTP- and LTD-like changes in human subjects.</p

Translating HbA1c measurements into estimated average glucose values in pregnant women with diabetes

Aims/hypothesis This study aimed to examine the relationship between average glucose levels, assessed by continuous glucose monitoring (CGM), and HbA1c levels in pregnant women with diabetes to determine whether calculations of standard estimated average glucose (eAG) levels from HbA1c measurements are applicable to pregnant women with diabetes. Methods CGM data from 117 pregnant women (89 women with type 1 diabetes; 28 women with type 2 diabetes) were analysed. Average glucose levels were calculated from 5–7 day CGM profiles (mean 1275 glucose values per profile) and paired with a corresponding (±1 week) HbA1c measure. In total, 688 average glucose–HbA1c pairs were obtained across pregnancy (mean six pairs per participant). Average glucose level was used as the dependent variable in a regression model. Covariates were gestational week, study centre and HbA1c. Results There was a strong association between HbA1c and average glucose values in pregnancy (coefficient 0.67 [95% CI 0.57, 0.78]), i.e. a 1% (11 mmol/mol) difference in HbA1c corresponded to a 0.67 mmol/l difference in average glucose. The random effects model that included gestational week as a curvilinear (quadratic) covariate fitted best, allowing calculation of a pregnancy-specific eAG (PeAG). This showed that an HbA1c of 8.0% (64 mmol/mol) gave a PeAG of 7.4–7.7 mmol/l (depending on gestational week), compared with a standard eAG of 10.2 mmol/l. The PeAG associated with maintaining an HbA1c level of 6.0% (42 mmol/mol) during pregnancy was between 6.4 and 6.7 mmol/l, depending on gestational week. Conclusions/interpretation The HbA1c–average glucose relationship is altered by pregnancy. Routinely generated standard eAG values do not account for this difference between pregnant and non-pregnant individuals and, thus, should not be used during pregnancy. Instead, the PeAG values deduced in the current study are recommended for antenatal clinical care

Stochastic population growth in spatially heterogeneous environments

Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study the following model for population abundances in $n$ patches: the conditional law of $X_{t+dt}$ given $X_t=x$ is such that when $dt$ is small the conditional mean of $X_{t+dt}^i-X_t^i$ is approximately $[x^i\mu_i+\sum_j(x^j D_{ji}-x^i D_{ij})]dt$, where $X_t^i$ and $\mu_i$ are the abundance and per capita growth rate in the $i$-th patch respectivly, and $D_{ij}$ is the dispersal rate from the $i$-th to the $j$-th patch, and the conditional covariance of $X_{t+dt}^i-X_t^i$ and $X_{t+dt}^j-X_t^j$ is approximately $x^i x^j \sigma_{ij}dt$. We show for such a spatially extended population that if $S_t=(X_t^1+...+X_t^n)$ is the total population abundance, then $Y_t=X_t/S_t$, the vector of patch proportions, converges in law to a random vector $Y_\infty$ as $t\to\infty$, and the stochastic growth rate $\lim_{t\to\infty}t^{-1}\log S_t$ equals the space-time average per-capita growth rate \sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i Y_\infty^j] experienced by the population. We derive analytic results for the law of $Y_\infty$, find which choice of the dispersal mechanism $D$ produces an optimal stochastic growth rate for a freely dispersing population, and investigate the effect on the stochastic growth rate of constraints on dispersal rates. Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure