Diabetes & Women’s Health (DWH) Study: an observational study of long-term health consequences of gestational diabetes, their determinants and underlying mechanisms in the USA and Denmark

PurposeWomen who experience gestational diabetes mellitus (GDM) are at exceptionally high-risk of developing type 2 diabetes (T2DM) later in life. However, limited information is available about genetic and environmental factors that are implicated in the progression from GDM to T2DM.ParticipantsThe Diabetes & Women’s Health (DWH) Study applied a hybrid design, which combined new prospective data collection with existing data in two prospective cohorts, the Danish National Birth Cohort (DNBC) and the Nurses’ Health Study II (NHS II). In total, the DWH Study identified 7759 women with a GDM diagnosis from both cohorts; 4457 women participated in the DWH Study data collection, which included two cycles of follow-up from 2012 to 2014 and 2014 to 2016.Findings to dateProgression from GDM to T2DM was high. In the NHS II group, by 2013, 23.1% (n=846/3667) developed T2DM. In the DNBC group, at cycle 1 (2012–2014), the progression rate was even higher: 27.2% (n=215/790) had developed T2DM. Furthermore, we have shown that women who had GDM experienced a significantly greater risk of hypertension and cardiovascular diseases, as well as early stages of glomerular hyperfiltration and renal damage. Moreover, the DWH Study findings have shown that healthful diet and lifestyle factors and weight control were related to a lower risk of T2DM, hypertension and cardiovascular diseases.Future plansPrimary data collection for the DWH Study is complete and investigators are currently investigating interactions of the abovementioned modifiable factors with T2DM genetic susceptibility in determining the risk of progression from GDM to T2DM. Findings from ongoing work will provide further insights for identifying more precise prevention strategies for T2DM and comorbidities in this high-risk population. Future work will examine novel biomarkers of health and disease in this cohort.

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Twenty Years of Data Linkage in The Australian Longitudinal Study on Women’s Health

International Journal for Population Data Science ◽

10.23889/ijpds.v5i5.1500 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Colleen Loos ◽

Gita Mishra ◽

Annette Dobson ◽

Leigh Tooth

Keyword(s):

Longitudinal Study ◽

Data Collection ◽

Women’S Health ◽

Women's Health ◽

Linked Data ◽

Data Linkage ◽

Data Access ◽

National Study ◽

Australian Longitudinal Study ◽

Data Collections

IntroductionLinked health record collections, when combined with large longitudinal surveys, are a rich research resource to inform policy development and clinical practice across multiple sectors. Objectives and ApproachThe Australian Longitudinal Study on Women’s Health (ALSWH) is a national study of over 57,000 women in four cohorts. Survey data collection commenced in 1996. Over the past 20 years, ALSWH has also established an extensive data linkage program. The aim of this poster is to provide an overview of ALSWH’s program of regularly up-dated linked data collections for use in parallel with on-going surveys, and to demonstrate how data are made widely available to research collaborators. ResultsALSWH surveys collect information on health conditions, ageing, reproductive characteristics, access to health services, lifestyle, and socio-demographic factors. Regularly updated linked national and state administrative data collections add information on health events, health outcomes, diagnoses, treatments, and patterns of service use. ALSWH’s national linked data collections, include Medicare Benefits Schedule, Pharmaceutical Benefits Scheme, the National Death Index, the Australian Cancer Database, and the National Aged Care Data Collection. State and Territory hospital collections include Admitted Patients, Emergency Department and Perinatal Data. There are also substudies, such as the Mothers and their Children’s Health Study (MatCH), which involves linkage to children’s educational records. ALSWH has an internal Data Access Committee along with systems and protocols to facilitate collaborative multi-sectoral research using de-identified linked data. Conclusion / ImplicationsAs a large scale Australian longitudinal multi-jurisdictional data linkage and sharing program, ALSWH is a useful model for anyone planning similar research.

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273: Gestational diabetes screening: do neonatal outcomes differ based on one-step or two-step methods in a high risk population?

American Journal of Obstetrics and Gynecology ◽

10.1016/j.ajog.2012.10.438 ◽

2013 ◽

Vol 208 (1) ◽

pp. S124-S125

Author(s):

Kisti Fuller ◽

Adam Borgida

Keyword(s):

High Risk ◽

Gestational Diabetes ◽

Neonatal Outcomes ◽

High Risk Population ◽

Diabetes Screening ◽

Risk Population ◽

One Step

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First Trimester Biomarkers in the Prediction of Later Pregnancy Complications

BioMed Research International ◽

10.1155/2014/807196 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 15

Author(s):

Stefan C. Kane ◽

Fabricio da Silva Costa ◽

Shaun Brennecke

Keyword(s):

Risk Factors ◽

Clinical Trials ◽

Clinical Practice ◽

Preterm Birth ◽

High Risk ◽

Gestational Diabetes ◽

First Trimester ◽

Obstetric Outcomes ◽

High Risk Population ◽

Maternal History

Adverse obstetric outcomes, such as preeclampsia, preterm birth, gestational diabetes, and fetal growth restriction, are poorly predicted by maternal history and risk factors alone, especially in nulliparae. The ability to predict these outcomes from the first trimester would allow for the early initiation of prophylactic therapies, institution of an appropriate model and location of care, and recruitment of a truly “high risk” population to clinical trials of interventions to prevent or ameliorate these conditions. To this end, development of adequately sensitive and specific predictive tests for these outcomes has become a significant focus of perinatal research. This paper reviews the biomarkers involved in these multiparametric tests and also outlines the performance of these tests and issues regarding their introduction into clinical practice.

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Gestational diabetes screening of a multiethnic, high-risk population using glycated proteins

Diabetes Research and Clinical Practice ◽

10.1016/s0168-8227(00)00206-0 ◽

2001 ◽

Vol 51 (1) ◽

pp. 67-73 ◽

Cited By ~ 35

Author(s):

M.M Agarwal ◽

P.F Hughes ◽

John Punnose ◽

M Ezimokhai ◽

L Thomas

Keyword(s):

High Risk ◽

Gestational Diabetes ◽

High Risk Population ◽

Diabetes Screening ◽

Risk Population ◽

Glycated Proteins

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Does gestational diabetes affect women's health-related quality of life after delivery?

European Journal of Obstetrics & Gynecology and Reproductive Biology ◽

10.1016/j.ejogrb.2009.09.025 ◽

2010 ◽

Vol 148 (1) ◽

pp. 40-43 ◽

Cited By ~ 10

Author(s):

Arja Halkoaho ◽

Marja Kavilo ◽

Anna-Maija Pietilä ◽

Hanna Huopio ◽

Harri Sintonen ◽

...

Keyword(s):

Quality Of Life ◽

Gestational Diabetes ◽

Women’S Health ◽

Women's Health ◽

Health Related Quality ◽

Related Quality ◽

Health Related

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Gestational diabetes in a high-risk population: using the fasting plasma glucose to simplify the diagnostic algorithm

European Journal of Obstetrics & Gynecology and Reproductive Biology ◽

10.1016/j.ejogrb.2004.07.034 ◽

2005 ◽

Vol 120 (1) ◽

pp. 39-44 ◽

Cited By ~ 18

Author(s):

Mukesh M. Agarwal ◽

Gurdeep S. Dhatt ◽

John Punnose ◽

Gertrude Koster

Keyword(s):

High Risk ◽

Gestational Diabetes ◽

Plasma Glucose ◽

Fasting Plasma Glucose ◽

Diagnostic Algorithm ◽

High Risk Population ◽

Risk Population ◽

Fasting Plasma

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Collecting Data from a Vulnerable Population during the COVID-19 Pandemic

10.31235/osf.io/af2sr ◽

2021 ◽

Author(s):

Sela R. Harcey ◽

G. Robin Gauthier ◽

Kelly Markowski ◽

Jeffrey A. Smith

Keyword(s):

High Risk ◽

Data Collection ◽

Research Design ◽

Site Selection ◽

Field Research ◽

Vulnerable Population ◽

Ethical Review ◽

High Risk Population ◽

Ethical Considerations ◽

Data Collection Effort

Conducting field research with a vulnerable population is difficult under the most auspicious conditions, and these difficulties only increase during a pandemic. Here, we describe the practical challenges and ethical considerations surrounding a recent data collection effort with a high-risk population during the COVID-19 pandemic. We detail our strategies related to research design, site selection, and ethical review.

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MP33: Predictors of delirium in older patient at the emergency department: a prospective multicentre derivation study

CJEM ◽

10.1017/cem.2019.168 ◽

2019 ◽

Vol 21 (S1) ◽

pp. S54

Author(s):

E. Béland ◽

A. Nadeau ◽

V. Boucher ◽

P. Carmichael ◽

P. Voyer ◽

...

Keyword(s):

Emergency Department ◽

High Risk ◽

Length Of Stay ◽

Risk Model ◽

Classification Tree ◽

Cognitive Status ◽

Hospital Length Of Stay ◽

Classification Error ◽

High Risk Population ◽

Modifiable Factors

Introduction: Delirium is a frequent pathology in the elderly presenting to the emergency department (ED) and is seldom recognised. This condition is associated with many medical complications and has been shown to increase the hospital length-of-stay. The objective of this study was to identify the predictor factors of developing delirium in this high-risk population. Methods: Design: This study was part of the multicenter prospective cohort INDEED study. Participants: Patients aged 65 and older, initially free of delirium and with an ED stay of 8h or longer, were followed up to 24h after ward admission. Measures: Clinical and demographic variables were collected by interview and chart review. A research professional assessed their delirium status twice daily using the Confusion Assessment Method (CAM). Analyses: A classification tree was used to select predictors and cut-points that minimized classification error of patients with incident delirium. After literature review, nineteen predictors were considered for inclusion in the model (eight non-modifiable and eleven modifiable factors). Results: Among the 605 patients included in this study, incident delirium was detected by the CAM in 69 patients (11.4%). In total, fourteen variables were included in a preliminary model, of which six were intrinsic to the patient and eight were modifiable in the ED. Variables with the greatest impact in the prediction of delirium includes age, cognitive status, ED length of stay, autonomy in daily activities, fragility and mobility during their hospital stay. The diagnostic performance of the model applied to the study sample gave a sensitivity of 78.3% (95% CI: 66.7 to 87.3), a specificity of 100.0% (95% CI: 99.3 to 100.0), a PPV of 100.0% (95% CI: 93.4 to 100.0) and a NPV of 97.3% (95% CI: 95.6 to 98.5). Conclusion: The delirium risk model developed in this study shows promising results with elevated sensitivity and specificity values. Considering the limited ability to predict and detect delirium among physicians, the potential increase in sensitivity provided by this tool could be beneficial to patients. This model will ultimately serve to identify high-risk patients with the goal of developing strategies to alter modifiable risk factors and subsequently decrease the incidence of delirium in this population.

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Screening pregnant women in a high-risk population with WHO-2013 or NICE diagnostic criteria does not affect the prevalence of gestational diabetes

Scientific Reports ◽

10.1038/s41598-021-84918-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mohammed Bashir ◽

Ibrahim Ibrahim ◽

Fatin Eltaher ◽

Stephen Beer ◽

Khaled Baagar ◽

...

Keyword(s):

High Risk ◽

Gestational Diabetes ◽

Pregnant Women ◽

Diagnostic Criteria ◽

High Risk Population ◽

Pregnancy Induced Hypertension ◽

Risk Population ◽

Increased Risk ◽

Induced Hypertension ◽

The Uk

AbstractThere are currently several diagnostic criteria for gestational diabetes (GDM). Both the WHO -2013 and NICE diagnose GDM based on a single step 75 g OGT; however; each uses different glucose thresholds. Previous studies have shown that the prevalence of GDM using the NICE criteria (GDM-N) is lower than that using the WHO-2013 criteria (GDM-W). Qatar has national diabetes in pregnancy program in which all pregnant women undergo OGTT screening using the WHO-2013 criteria. This study aims to define the prevalence of GDM using both criteria in a high-risk population. This retrospective study included 2000 women who underwent a 75 g (OGTT) between Jan 2016 and Apr 2016 and excluded patients with known pre-conception diabetes, multiple pregnancy, and those who did not complete the OGTT. We then classified the women into GDM-W positive, GDM-N positive but GDM-W negative, and normal glucose tolerance (NGT) population. A total of 1481 women (74%) had NGT using the NICE or the WHO-2013 criteria. The number of patients who met both criteria was 279 subjects (14%) with a good agreement (Kappa coefficient 0.67, p < 0.001). The NICE and the WHO-2013 criteria were discordant in 240 subjects (12% of the cohort); 6.7% met the WHO -2013 criteria only and only 5.3% met the NICE criteria. The frequency of pre-eclampsia, pre-term delivery, Caesarean-section, LGA and neonatal ICU admissions were significantly increased in the GDM-W group. However, the GDM-N positive but GDM-W negative had no increased risk of maternal or fetal complications apart from pregnancy-induced hypertension. The WHO-2013 and the NICE criteria classified a similar proportion of pregnant women, 21.5% and 20.1%, respectively, as having GDM; however, they were concordant in only 14% of the cases. Women who are GDM-N positive but GDM-W negative are not at increased risk of maternal and fetal pregnancy complications, except for pregnancy-induced hypertension. As the NICE criteria are more specific to the UK population, we would recommend the use of the WHO-2013 criteria to diagnose GDM in the MENA region and possibly other regions that do not have the same set-up as the UK.

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