Hypertension and the pregnancy complicated by diabetes

Leguizamón, Gustavo; Zeff, Natalia P.; Fernández, Alberto

doi:10.1007/s11892-006-0064-1

Cited by 14 publications

(6 citation statements)

References 52 publications

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“…We also showed an increased risk of PIH in obese versus nonobese GDM mothers while those women managed by diet-only were more likely to have gestational hypertension. Previous researchers have consistently shown similar findings [16,[25][26][27][28][29][30][31][32]. Similar findings apply to increased prevalence of C-section in obese versus non-obese GDM mothers (50.6% vs.37.5%).…”

Section: Discussionsupporting

confidence: 75%

See 1 more Smart Citation

Maternal Obesity, Maternal Gestational Diabetes Mellitus, and Maternal and Neonatal Outcomes

AT¹

2016

J Obes Weight Loss Ther

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We aimed to investigate the co-morbid effects of maternal obesity, Gestational Diabetes Mellitus (GDM), and GDM treatment options on maternal and neonatal outcomes in an inner-city population. This is a retrospective chart review study of singleton mothers with new diagnosis of GDM and their infants during a 3-year period. During the study period, 356 women ages 13-48 years with GDM gave birth to 180 males and 175 females. Majority of mothers were African American (50.8%) and had Medicaid insurance (75.8%). Obese mothers constituted 48.3% of the study population, had a higher prevalence of pregnancy induced hypertension/preeclampsia, more commonly were managed with medication and delivered by C-section than non-obese mothers. Infants of obese GDM mothers had significantly higher mean birth weight, lower mean blood glucose, and were less at risk for Small for Gestational Age (SGA). In obese mothers, heaviest mothers had infants with higher bilirubin levels than less heavy mothers. We also observed a high rate of feeding difficulty in infants of GDM mothers (12.4%). Our study emphasizes the burden of maternal obesity as a major risk factor for both maternal and neonatal poor outcomes in the context of GDM and calls for further prospective and interventional research.

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Section: Discussionsupporting

confidence: 75%

“…Although, the pathophysiology of hypertension in GDM is not clear but glucose intolerance and insulin resistance may be responsible [28][29][30]. We also showed an increased risk of PIH in obese versus nonobese GDM mothers while those women managed by diet-only were more likely to have gestational hypertension.…”

Section: Discussionmentioning

confidence: 59%

Maternal Obesity, Maternal Gestational Diabetes Mellitus, and Maternal and Neonatal Outcomes

AT¹

2016

J Obes Weight Loss Ther

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“…There are biological underpinnings to these correlations; for instance, prior studies found that TGF-β is a common biological factor between preeclampsia and diabetes ( 38 , 39 ). Diabetes was moderately correlated with hypertension and superimposed preeclampsia ( 40 ), and significantly correlated with every other APORF. Similarly, BMI prior to pregnancy was also significantly correlated with all outcomes ( 41 ).…”

Section: Resultsmentioning

confidence: 96%

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

et al. 2022

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Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.ObjectivesThe primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and MethodsIn a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).ResultsJointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.ConclusionsElucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

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“…48,57,58 Children of ladies with GDM have an augmented risk for childhood and adult obesity and an augmented risk of glucose intolerance and type 2 DM later in life. 59 This risk is linked to higher values of maternal glucose. 51 It is now not clear how much genetic and environmental variables each contribute to this risk, and if treatment of GDM can influence this outcome.…”

Section: Prognosismentioning

confidence: 99%

“…51 It is now not clear how much genetic and environmental variables each contribute to this risk, and if treatment of GDM can influence this outcome. 59…”

Section: Prognosismentioning

confidence: 99%

Gestational Diabetes Mellitus

Chowdhury

Hasan²,

Islam³

et al. 2018

KYAMC j.

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White 6 had pioneered research on the effect of high blood glucose levels on pre-natal, perinatal and post-natal outcomes. The most commonly used White classification was proposed after his name. It is extensively used to evaluate and assess maternal and fetal risks. AbstractDiabetes mellitus during pregnancy (i.e., Gestational Diabetes Mellitus or GDM) has definite impact on maternal & fetal health. A woman is diagnosed with gestational diabetes specially when glucose intolerance continues beyond 24-28 weeks of gestation GDM needs to be specially considered, because it may often remain undiagnosed leading to abortion, miscarriage, fetal obesity, intra-uterine growth retardation (IUGR), intrauterine death (IUD) of fetus in addition to maternal morbidities & mortalities. Here we have reviewed in brief about the causes, pathophysiology, complications, risks, diagnosis, management, prevention etc. of GDM. Date of acceptance: 03. 04. 2018 KYAMC Journal.2018;9(2):81-86.

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Hypertension and the pregnancy complicated by diabetes

Cited by 14 publications

References 52 publications

Maternal Obesity, Maternal Gestational Diabetes Mellitus, and Maternal and Neonatal Outcomes

Maternal Obesity, Maternal Gestational Diabetes Mellitus, and Maternal and Neonatal Outcomes

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Gestational Diabetes Mellitus

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