Pre-analytical diagnostic differences despite high adherence to guidelines for gestational diabetes mellitus.

Regional variations in the prevalence of gestational diabetes mellitus (GDM) have been found across Denmark. The objectives of this exploratory survey were to evaluate adherence to the national guideline for screening and diagnosing GDM and to identify variations in pre-analytical or analytical factors, which could potentially contribute to variations in GDM prevalence across regions. In a national interview-based survey, obstetric departments and laboratories throughout Denmark handling GDM screening or diagnostic testing were invited to participate. Survey questionnaires were completed through personal interviews. In total, 21 of 22 identified obstetric departments and 44 of 45 identified laboratories participated. Adherence to guideline among obstetric departments ranged 67-100% and uniformity in laboratory procedures was high. However, the gestational age at the time of late diagnostic testing with oral glucose tolerance test (OGTT) varied considerably, with 48% (10/21) of departments testing outside the recommended 24-28 weeks' gestation. Procedural heterogeneity was most pronounced for the parts not described in current guidelines, with choice of laboratory equipment being the most diverse factor ranging 3-39% nationally. In conclusion, the overall adherence to the national guidelines was high across regions, and obstetric departments and laboratories had high uniformity in the procedures for screening and diagnosing GDM. Uniformity was generally high for procedures included in the guideline and low if not included. However, a high proportion of GDM testing was performed outside the recommended gestational window in late pregnancy, which may be a pre-analytical contributor to regional differences in GDM prevalence.

Design automation of microfluidic single and double emulsion droplets with machine learning.

Droplet microfluidics enables kHz screening of picoliter samples at a fraction of the cost of other high-throughput approaches. However, generating stable droplets with desired characteristics typically requires labor-intensive empirical optimization of device designs and flow conditions that limit adoption to specialist labs. Here, we compile a comprehensive droplet dataset and use it to train machine learning models capable of accurately predicting device geometries and flow conditions required to generate stable aqueous-in-oil and oil-in-aqueous single and double emulsions from 15 to 250 µm at rates up to 12000 Hz for different fluids commonly used in life sciences. Blind predictions by our models for as-yet-unseen fluids, geometries, and device materials yield accurate results, establishing their generalizability. Finally, we generate an easy-to-use design automation tool that yield droplets within 3 µm (<8%) of the desired diameter, facilitating tailored droplet-based platforms and accelerating their utility in life sciences.

Versatility and stability optimization of flow-focusing droplet generators via quality metric-driven design automation.

Droplet generation is a fundamental component of droplet microfluidics, compartmentalizing biological or chemical systems within a water-in-oil emulsion. As adoption of droplet microfluidics expands beyond expert labs or integrated devices, quality metrics are needed to contextualize the performance capabilities, improving the reproducibility and efficiency of operation. Here, we present two quality metrics for droplet generation: performance versatility, the operating range of a single device, and stability, the distance of a single operating point from a regime change. Both metrics were characterized in silico and validated experimentally using machine learning and rapid prototyping. These metrics were integrated into a design automation workflow, DAFD 2.0, which provides users with droplet generators of a desired performance that are versatile or flow stable. Versatile droplet generators with stable operating points accelerate the development of sophisticated devices by facilitating integration of other microfluidic components and improving the accuracy of design automation tools.

Gestational diabetes mellitus screening and diagnosis criteria before and during the COVID-19 pandemic: a retrospective pre-post study.

OBJECTIVE: To determine whether perinatal outcomes after excluding gestational diabetes mellitus (GDM) on the basis of fasting venous plasma glucose (FVPG) assessment during the coronavirus disease 2019 (COVID-19) pandemic in 2020 were similar to those during the preceding year after excluding GDM using the standard oral glucose tolerance test (OGTT) procedure. DESIGN: Retrospective pre-post study. SETTING, PARTICIPANTS: All women who gave birth in Queensland during 1 July - 31 December 2019 and 1 July - 31 December 2020. MAIN OUTCOME MEASURES: Perinatal (maternal and neonatal) outcomes for pregnant women assessed for GDM, by assessment method (2019: OGTT/glycated haemoglobin [HbA1c ] assessment; 2020: GDM could be excluded by an FVPG value below 4.7 mmol/L). RESULTS: 3968 of 29 113 pregnant women in Queensland during 1 July - 31 December 2019 (13.6%) were diagnosed with GDM, and 4029 of 28 778 during 1 July - 31 December 2020 (14.0%). In 2020, FVPG assessments established GDM in 216 women (1.1%) and excluded it in 1660 (5.8%). The frequencies of most perinatal outcomes were similar for women without GDM in 2019 and those for whom it was excluded in 2020 on the basis of FVPG values; the exception was caesarean delivery, for which the estimated probability increase in 2020 was 3.9 percentage points (95% credibility interval, 2.2-5.6 percentage points), corresponding to an extra 6.5 caesarean deliveries per 1000 births. The probabilities of several outcomes - respiratory distress, neonatal intensive care or special nursery admission, large for gestational age babies - were about one percentage point higher for women without GDM in 2020 (excluding those diagnosed on the basis of FVPG assessment alone) than for women without GDM in 2019. CONCLUSIONS: Identifying women at low absolute risk of gestational diabetes-related pregnancy complications on the basis of FVPG assessment as an initial step in GDM screening could reduce the burden for pregnant women and save the health system substantial costs.

Feasibility of the McIntyre audit tool for haemodialysis nurses.

BACKGROUND: Nurse-sensitive indicators (NSI) assess the quality of nursing care provided to patients. These indicators assess the structures (supportive measures), processes (nursing actions) and outcomes of care. The McIntyre Audit Tool (MAT) was developed to measure haemodialysis NSIs. OBJECTIVES: The objective of this study is to evaluate the feasibility and utility of the MAT in measuring haemodialysis NSIs in clinical practice. DESIGN: Multisite nonrandomized feasibility study. PARTICIPANTS: A convenience sample of nurses (n = 30) were recruited from two haemodialysis units in Australia. MEASUREMENTS: Participants completed the MAT once daily for 1 week, to measure the extent the clinical indicators were being met. Feasibility data including utility and acceptability of the tool was collected once from each participant. Data were analysed descriptively. RESULTS: Participants completed a total of 97 audits. Results revealed the majority of structural (75%) and process indicators (73%) were being achieved although some variation between sites was observed. Results for the outcome indicators showed more variation (5.9%-94.1). Feasibility results found most nurses (79%) took <5 min to complete the MAT and found the tool easy to use (91.7%). Most participants (83.3%) reported audits could be completed during a shift and auditing was easily implemented (79.2%). CONCLUSION: Use of the MAT in clinical practice is a feasible and acceptable way of auditing the quality of haemodialysis nursing practice. The tool could be used to establish minimum standards and improve the quality of nursing care in haemodialysis units, also enabling benchmarking between services.

The pre-pregnancy fasting blood glucose, glycated hemoglobin and lipid profiles as blood biomarkers for gestational diabetes mellitus: evidence from a multigenerational cohort study.

BACKGROUND: Early prevention of gestational diabetes mellitus (GDM) is important to reduce the risk of adverse pregnancy outcomes and post-pregnancy cardiometabolic risk in women and offspring over the life course. This study aimed to investigate some blood biomarkers before pregnancy as GDM predictors. METHODS: We investigated the prospective association of blood biomarkers before pregnancy and GDM risk among women from the Mater-University of Queensland Study of Pregnancy (MUSP) cohort. A multiple logistic regression model was applied to estimate the odds of experiencing GDM by blood biomarkers. RESULTS: Out of 525 women included in this study, the prevalence of GDM was 7.43%. There was an increased risk of experiencing GDM among women who experienced obesity (Odds ratio = OR 2.4; 95% confidence interval = CI 1.6-3.7), had high fasting blood glucose (OR = 2.2; 95% CI = 1.3-3.8), high insulin (OR = 1.1; 95% CI = 1.0-1.2), high insulin resistance (OR = 1.2; 95% CI = 1.0-1.3) and low high-density lipoprotein (OR = 0.2; 95% CI = 0.1-0.7) before pregnancy. Adjustment for potential confounders, such as age, marital status, and BMI did not attenuate these associations substantially. CONCLUSION: The pre-pregnancy fasting blood glucose, insulin, and insulin resistance were independent predictors of GDM. They may be used as early markers for predicting the incidence of GDM.

Validation of the McIntyre Audit Tool to measure haemodialysis nurse sensitive indicators.

BACKGROUND: Nurse sensitive indicators measure the quality of nursing care. Although there are some haemodialysis nurse sensitive indicators, there are currently no validated audit tools available to measure the indicators. OBJECTIVES: To test the validity of the McIntyre Audit Tool. DESIGN: This study used a descriptive observation design conducted over two phases to assess face and content validity. PARTICIPANTS: An expert panel of haemodialysis nurses (n = 13). METHODS: Face validity (phase 1) involved 13 nurses in two focus groups who reviewed the audit tool with qualitative data generated analysed to identify common themes. Phase 2 used a modified version of the audit tool to test for content validity for each item and then scale level content validity was calculated by combining all item scores. MEASUREMENTS: Ten nurses rated 26 indicators in the audit tool using a 4-point Likert scale to assess each item for clarity, relevance, appropriateness, and ambiguity. RESULTS: All 26-haemodialysis nurse sensitive indicators achieved item content validity indices ranging from 0.825 to 1.00 with a scale content validity index average of 0.910. However, based on feedback from phase 2, 6 outcome indicators were removed from the audit tool to reduce staff burden and assist with ease of use. The final audit tool had an excellent average scale content validity index of 0.924. CONCLUSIONS: The McIntyre Audit Tool to measure 20 haemodialysis nurse sensitive indicators has been validated. It now requires feasibility and reliability testing before auditing the quality of haemodialysis nursing care.

Prevalence of multiple non-communicable diseases risk factors among adolescents in 140 countries: A population-based study.

Background: Modifiable non-communicable disease (NCD) risk factors are becoming increasingly common among adolescents, with clustering of these risk factors in individuals of particular concern. The aim of this study was to assess global status of clustering of common modifiable NCD risk factors among adolescents. Methods: We used latest available data from nationally representative survey for 140 countries, namely the Global School-based Student Health Survey, the Health Behaviour in School-Aged Children and the longitudinal study of Australian Children. Weighted mean estimates of prevalence with corresponding 95% confidence intervals of nine NCD risk factors - physical inactivity, sedentary behaviour, insufficient fruits and vegetable consumption, carbonated soft drink consumption, fast food consumption, tobacco use, alcohol consumption and overweight/obesity - were calculated by country, region and sex. Findings: Over 487,565 adolescents, aged 11-17 years, were included in this study. According to trend analysis, prevalence of four or more NCD risk factors increased gradually over time. Prevalence of four or more NCD risk factors was 14.8% in 2003-2007 and increased to 44% in 2013-2017, an approximately three-fold increase (44.0%). Similar trends were also observed for three and two risk factors. Large variation between countries in the prevalence of adolescents with four or more risk factors was found in all regions. The country level range was higher in the South-East Asia Region (minimum Sri Lanka = 8%, maximum Myanmar = 84%) than Western Pacific Region (minimum China = 3%, maximum Niue = 72%), European Region (minimum Sweden = 13.9%, maximum Ireland = 66.0%), African Region (minimum Senegal = 0.8%, maximum Uganda = 82.1%) and Eastern Mediterranean Region (minimum Libya = 0.2%, maximum Lebanon = 80.2%). Insufficient vegetable consumption, insufficient fruit consumption and physically inactivity were three of the four most prevalent risk factors in all regions. Interpretation: Our results suggest a high prevalence of four or more NCD risk factors in adolescents globally, although variation was found between countries. Results from our study indicate that efforts to reduce adolescent NCD risk factors and the associated health burden need to be improved. These findings can assist policy makers to target the rollout of country- specific interventions. Funding: None.

Searching for Visual Singletons Without A Feature to Guide Attention.

RT studies have provided evidence for a singleton-detection strategy that is used to search for salient targets when there is no additional featural knowledge that would help guide attention. Despite this behavioral evidence, there have been few ERP studies of singleton detection mode because it was reported early on that the ERP signature of attentional selection (the N2pc) is absent without feature guidance. Recently, however, it was discovered that a small and relatively late N2pc occurs in singleton detection mode along with a previously unreported component called the singleton detection positivity (SDP). Here, we show that both components are influenced by the number of items in the display, as one might expect in a salience-based search mode. Specifically, the N2pc and SDP were larger when the set size was increased to make the singleton "pop out" more easily, when participants responded more quickly regardless of set size, and when RT search slopes were negative (Experiment 1). The latency of the SDP also depended on set size. In Experiment 2, EEG was recorded with a higher density electrode array to better characterize the scalp topography of the components and to estimate their neural sources. Regional sources near the ventral surface of extrastriate cortex in the occipital lobe explained over 96% of N2pc and SDP activities. These results indicate that searching in singleton detection mode selectively modulates processing within perceptual regions of visual cortex.

Machine learning for microfluidic design and control.

Microfluidics has developed into a mature field with applications across science and engineering, having particular commercial success in molecular diagnostics, next-generation sequencing, and bench-top analysis. Despite its ubiquity, the complexity of designing and controlling custom microfluidic devices present major barriers to adoption, requiring intuitive knowledge gained from years of experience. If these barriers were overcome, microfluidics could miniaturize biological and chemical research for non-experts through fully-automated platform development and operation. The intuition of microfluidic experts can be captured through machine learning, where complex statistical models are trained for pattern recognition and subsequently used for event prediction. Integration of machine learning with microfluidics could significantly expand its adoption and impact. Here, we present the current state of machine learning for the design and control of microfluidic devices, its possible applications, and current limitations.

Buildout and integration of an automated high-throughput CLIA laboratory for SARS-CoV-2 testing on a large urban campus.

In 2019, the first cases of SARS-CoV-2 were detected in Wuhan, China, and by early 2020 the first cases were identified in the United States. SARS-CoV-2 infections increased in the US causing many states to implement stay-at-home orders and additional safety precautions to mitigate potential outbreaks. As policies changed throughout the pandemic and restrictions lifted, there was an increase in demand for COVID-19 testing which was costly, difficult to obtain, or had long turn-around times. Some academic institutions, including Boston University (BU), created an on-campus COVID-19 screening protocol as part of a plan for the safe return of students, faculty, and staff to campus with the option for in-person classes. At BU, we put together an automated high-throughput clinical testing laboratory with the capacity to run 45,000 individual tests weekly by Fall of 2020, with a purpose-built clinical testing laboratory, a multiplexed reverse transcription PCR (RT-qPCR) test, robotic instrumentation, and trained staff. There were many challenges including supply chain issues for personal protective equipment and testing materials in addition to equipment that were in high demand. The BU Clinical Testing Laboratory (CTL) was operational at the start of Fall 2020 and performed over 1 million SARS-CoV-2 PCR tests during the 2020-2021 academic year.

Intrahepatic cholestasis of pregnancy: Association with glycaemic control in gestational diabetes.

AIMS: The aim of this study was to determine whether the metabolic glucose profile, based on glycaemic control and insulin requirements, was different in women with gestational diabetes mellitus (GDM) and intrahepatic cholestasis of pregnancy (ICP) compared to women with only GDM. METHODS: This retrospective cohort study comprised women with GDM and ICP matched with women with only GDM was undertaken at Aarhus University hospital, Denmark, from 2012 to 2019. A total of 46 cases and 184 controls were compared in relation to glycaemic control during pregnancy. Women with GDM and ICP were further divided into subgroups according to the severity of ICP: mild ICP (fasting bile salts 10-39 µmol/L) and moderate/severe ICP (bile salts ≥40 µmol/L). RESULTS: No statistically significant differences were observed in baseline 2-h oral glucose tolerance test values, second and third trimester HbA1c values, or maximum insulin requirements during pregnancy between women with GDM with and without ICP. Significantly more women with ICP developed preeclampsia during pregnancy: 23.9% (11/46) versus 7.6% (14/184); p = 0.003. CONCLUSIONS: This study is the first to address the course of pregnancy in women with GDM with and without ICP in a clinical setting. Under the current treatment guidelines, ICP is not associated with clinically significant changes in glycaemic control in GDM. Significantly more women with both GDM and ICP developed preeclampsia.

Machine learning enables design automation of microfluidic flow-focusing droplet generation.

Droplet-based microfluidic devices hold immense potential in becoming inexpensive alternatives to existing screening platforms across life science applications, such as enzyme discovery and early cancer detection. However, the lack of a predictive understanding of droplet generation makes engineering a droplet-based platform an iterative and resource-intensive process. We present a web-based tool, DAFD, that predicts the performance and enables design automation of flow-focusing droplet generators. We capitalize on machine learning algorithms to predict the droplet diameter and rate with a mean absolute error of less than 10 µm and 20 Hz. This tool delivers a user-specified performance within 4.2% and 11.5% of the desired diameter and rate. We demonstrate that DAFD can be extended by the community to support additional fluid combinations, without requiring extensive machine learning knowledge or large-scale data-sets. This tool will reduce the need for microfluidic expertise and design iterations and facilitate adoption of microfluidics in life sciences.

Monitoring for intradialytic hypotension: An audit of nursing practice.

BACKGROUND: Intradialytic hypotension (IDH) is one of the most common complications associated with haemodialysis (HD), yet the frequency of patient assessment by nurses varies in practice. We sought to measure the frequency of nursing assessments before, during and after HD and to identify any predictors of IDH. OBJECTIVES: To audit the frequency, nursing management and contributing factors of IDH. DESIGN: A prospective clinical audit was undertaken over 4 weeks. PARTICIPANTS: Nurses completed audit sheets on 132 patients at three chronic HD units. MEASUREMENTS: The audit tool consisted of 34 questions related to demographics, HD prescription, frequency of monitoring and nursing interventions. RESULTS: A total of 1584 sessions were performed with 876 (55.3%) audits returned, of which 452 were useable. There were 74 actual episodes of IDH, and a further 72 potential episodes may have been prevented due to nursing intervention. Most nurses reported assessing patients before starting HD and as required before an actual or potential IDH event (n = 85; 63%); few hourly assessments were performed. Predictors of IDH were systolic blood pressure ≤140 mmHg, having more than four comorbidities, dialysate temperature > 36°C, calcium < 1.3 mmol/L and a shorter dialysis session (3.0-4.5 h). These predictors explained 14.1% of the variance in hypotensive episodes during HD. CONCLUSION: This clinical audit highlighted the importance of assessing blood pressure trends during HD to preemptively intervene before IDH developing. The audit has resulted in a practice change to hourly assessments. Follow-up audits of practice should occur.

Dietary Fiber Intake Alters Gut Microbiota Composition but Does Not Improve Gut Wall Barrier Function in Women with Future Hypertensive Disorders of Pregnancy.

Pregnancy alters the inflammatory state, metabolic hormones, and gut microbiota composition. It is unclear if the lower abundance of dietary fiber-fermenting, short-chain fatty acid-producing bacteria observed in hypertension also occurs in hypertensive disorders of pregnancy (HDP). This study investigated the relationship between dietary fiber intake and the gut microbiota profile at 28 weeks gestation in women who developed HDP in late pregnancy (n = 22) or remained normotensive (n = 152) from the Study of PRobiotics IN Gestational diabetes (SPRING). Dietary fiber intake was classified as above or below the median of 18.2 g/day. Gut microbiota composition was examined using 16S rRNA gene amplicon sequencing. The gut permeability marker zonulin was measured in a subset of 46 samples. In women with future HPD, higher dietary fiber intake was specifically associated with increased abundance of Veillonella, lower abundance of Adlercreutzia, Anaerotruncus and Uncl. Mogibacteriaceae and higher zonulin levels than normotensive women. Fiber intake and zonulin levels were negatively correlated in women with normotensive pregnancies but not in pregnancies with future HDP. In women with normotensive pregnancies, dietary fiber intake may improve gut barrier function. In contrast, in women who develop HDP, gut wall barrier function is impaired and not related to dietary fiber intake.

Rapid and inexpensive microfluidic electrode integration with conductive ink.

Electrode integration significantly increases the versatility of droplet microfluidics, enabling label-free sensing and manipulation at a single-droplet (single-cell) resolution. However, common fabrication techniques for integrating electronics into microfluidics are expensive, time-consuming, and can require cleanroom facilities. Here, we present a simple and cost-effective method for integrating electrodes into thermoplastic microfluidic chips using an off-the-shelf conductive ink. The developed conductive ink electrodes cost less than $10 for an entire chip, have been shown here in channel geometries as small as 75 µm by 50 µm, and can go from fabrication to testing within a day without a cleanroom. The geometric fabrication limits of this technique were explored over time, and proof-of-concept microfluidic devices for capacitance sensing, droplet merging, and droplet sorting were developed. This novel method complements existing rapid prototyping systems for microfluidics such as micromilling, laser cutting, and 3D printing, enabling their wider use and application.

Poverty over the early life course and young adult cardio-metabolic risk.

OBJECTIVES: There is little known about whether exposure to family poverty at specific periods of the early life course independently contributes to coronary heart disease risk beyond the contribution of concurrent poverty. METHODS: Children were recruited in early pregnancy and additional survey data obtained during the pregnancy and at the 5-, 14- and 30-year follow-ups. Fasting blood samples were also obtained at the 30-year follow-up. Analyses are multinominal logistic regressions stratified by gender and with adjustments for confounding. RESULTS: For male offspring, family poverty at different stages of the early life course was not associated with measures of cardio-metabolic risk. For females early life course, poverty predicted obesity, homeostatic model assessment of insulin resistance (HOMA-IR) and total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C), as well as concurrent family poverty associated with obesity, HOMA-IR, TC/HDL-C, HDL-C and increased systolic and diastolic blood pressure. CONCLUSIONS: Family poverty in the early life course independently predicts increased levels of cardio-metabolic risk of females. The primary finding, however, is that concurrent poverty is independently and strongly associated with increased cardio-metabolic risk levels in young adulthood.

Antenatal models of care for women with gestational diabetes mellitus: Vignettes from an international meeting.

BACKGROUND: Gestational diabetes (GDM) is one of the commonest pregnancy complications and is placing an increasing burden on diabetes and obstetric resources. AIMS: To describe different antenatal models of care that have developed to address the increasing proportion of pregnancies complicated by GDM. MATERIALS AND METHODS: Narrative review with thematic analysis from 15 volunteer antenatal diabetes in pregnancy services from Australia and New Zealand identified through a national diabetes organisation. Main outcomes were approaches to patient education, medical nutrition therapy (MNT), ongoing management and escalation of therapy for women with GDM. RESULTS: All clinics provided at least one group education and one MNT session within 1-2 weeks of GDM diagnosis. Women from culturally and linguistically diverse communities usually required 1:1 education. Ongoing management of women with GDM was through either all women being seen in the GDM clinic, a step-up approach (ongoing management by the primary antenatal team with diabetes team referral if self-blood glucose monitoring (SBGM) or insulin therapy dosage criteria are reached) or step-down approach (ongoing management by the diabetes team with step-down to the primary antenatal team if SBGM criteria are reached). Telehealth was used to reduce the burden of clinic attendance, particularly in rural areas. CONCLUSIONS: Increasing numbers, earlier diagnoses, the need to provide care to women in rural, remote areas, and cultural/language differences, have generated a range of different antenatal models of care, allowed better workload accommodation and probably reduced costs. Randomised controlled trials of different models of care, with associated health economic analyses, are urgently needed.

OLA-Simple: A software-guided HIV-1 drug resistance test for low-resource laboratories.

BACKGROUND: HIV drug resistance (HIVDR) testing can assist clinicians in selecting treatments. However, high complexity and cost of genotyping assays limit routine testing in settings where HIVDR prevalence has reached high levels. METHODS: The oligonucleotide ligation assay (OLA)-Simple kit was developed for detection of HIVDR against first-line non-nucleoside/nucleoside reverse transcriptase inhibitors and validated on 672 codons (168 specimens) from subtypes A, B, C, D, and AE. The kit uses dry reagents to facilitate assay setup, lateral flow devices for visual HIVDR detections, and in-house software with an interface for guiding users and analyzing results. FINDINGS: HIVDR analysis of specimens by OLA-Simple compared to Sanger sequencing revealed 99.6 ±â€¯0.3% specificity and 98.2 ±â€¯0.9% sensitivity, and compared to high-sensitivity assays, 99.6 ±â€¯0.6% specificity and 86.2 ±â€¯2.5% sensitivity, with 2.6 ±â€¯0.9% indeterminate results. OLA-Simple was performed more rapidly compared to Sanger sequencing (<4 h vs. 35-72 h). Forty-one untrained volunteers blindly tested two specimens each with 96.8 ±â€¯0.8% accuracy. INTERPRETATION: OLA-Simple compares favorably with HIVDR genotyping by Sanger and sensitive comparators. Instructional software enabled inexperienced, first-time users to perform the assay with high accuracy. The reduced complexity, cost, and training requirements of OLA-Simple could improve access to HIVDR testing in low-resource settings and potentially allow same-day selection of appropriate antiretroviral therapy. FUND: USA National Institutes of Health R01; the Clinical and Retrovirology Research Core and the Molecular Profiling and Computational Biology Core of the UW CFAR; Seattle Children's Research Institute; UW Holloman Innovation Challenge Award; Pilcher Faculty Fellowship.

FIGO analysis of research priorities in hyperglycemia in pregnancy.

Hyperglycemia in pregnancy (HIP) is recognized as a major underlying cause of pregnancy complications and a contributing cause to health risks throughout the subsequent life of both mothers and babies, with amplification of the global epidemic of non-communicable diseases. Although some aspects of these associations are well described, detailed understanding of basic pathophysiologic mechanisms is lacking. Improved fundamental scientific knowledge must be developed to allow logical strategies for prevention and treatment. During pregnancy, much work is required to replace current empirical approaches to diagnosis and treatment of HIP with evidence based protocols, pragmatically adapted to differing health care and health economic contexts. Further, a life cycle approach to HIP, the risk of immediate pregnancy complications and later health risks to mother and baby must be developed and implemented across a wide range of health care environments. This document aims to outline key focus areas for further basic, epidemiologic, clinical and implementation research in this important area.