Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Thong, Eleanor P.; Ghelani, Drishti; Manoleehakul, Pamada; Yesmin, Anika; Slater, Kaylee; Taylor, Robert D.; Collins, Claire; Hutchesson, Melinda J.; Lim, Siew; Teede, Helena; Harrison, Cheryce L.; Moran, Lisa J.; Enticott, Joanne

doi:10.3390/jcdd9020055

Cited by 14 publications

(10 citation statements)

References 96 publications

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“…Accurately predicting GDM incidence based on early pregnancy markers could allow development and implementation of interventions to prevent GDM and its complications. However, most predictive models that rely on established clinical risk factors perform poorly 42 , 43 , and thus, there has been a search for reliable and replicable biomarkers. We found that low levels of circulating IGFBP1 in early pregnancy predict later diagnosis of GDM in a large population-based cohort (Gen3G), with external replication and consistent effect sizes in a separate cohort (MOMS).…”

Section: Discussionmentioning

confidence: 99%

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes

Hivert,

White,

Allard

et al. 2023

Preprint

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Reduced insulin sensitivity (or greater insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM) pathophysiology. We conducted transcriptomic profiling of 434 human placentas and identified a strong positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~ 26 weeks’ gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which together with high placental gene expression levels, suggests a placental source. Higher circulating IGFBP1 levels were strongly associated with greater insulin sensitivity (lesser insulin resistance) at ~ 26 weeks’ gestation in the same cohort and two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

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Section: Discussionmentioning

confidence: 99%

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes

Hivert,

White,

Allard

et al. 2023

Preprint

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“…In addition, a Google Scholar gray literature search was conducted as per Enticott et al 16 . Furthermore, we explored the reference list of all included studies and a recent narrative review 17 . The search strategies were developed following search filters for prognostic and diagnostic studies 18 and by consulting librarians at Monash University, Melbourne, VIC, Australia.…”

Section: Review Question and Search Strategymentioning

confidence: 99%

Externally validated prediction models for pre‐eclampsia: systematic review and meta‐analysis

Tiruneh,

Vu,

Moran

et al. 2024

Ultrasound in Obstet & Gyne

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ObjectiveThis systematic review and meta‐analysis aimed to evaluate the performance of existing externally validated prediction models for pre‐eclampsia (specifically for any‐ early‐ late‐onset and preterm pre‐eclampsia).MethodsA systematic search was conducted in five databases (MEDLINE, Embase, Emcare, CINAHL, and Maternity and Infant Care Database) to identify studies based on Population, Index model, Comparator, Outcome, Timing, and Setting (PICOTS) approach until May 20, 2023. We extracted data using the CHARMS checklist and appraised risk of bias using PROBAST tool. Discrimination and calibration performance were meta‐analysed when appropriate.ResultsTwenty‐three publications reported 52 externally validated prediction models on pre‐eclampsia (twenty any‐onset, seventeen early‐onset, fourteen late‐onset, and one preterm pre‐eclampsia). No model had the same set of predictors. Fifteen, two, and three any‐onset pre‐eclampsia models were externally validated once, twice, and thrice, respectively, and the Fetal Medicine Foundation (FMF) preterm model was widely validated in sixteen different settings. The most common predictors were maternal characteristics (pre‐pregnancy BMI, prior pre‐eclampsia, family history of pre‐eclampsia, chronic medical conditions, and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy‐associated plasma protein‐A). The model for preterm pre‐eclampsia (triple test FMF) had the best performances with a pooled area under the receiver operating characteristics curve (AUROC) of 0.90 (95% prediction interval (PI) 0.76 – 0.96) and was well‐calibrated. The other models generally had poor to fair discrimination performance (AUROC median 0.66, range 0.53 to 0.77) and were overfitted in calibration after external validation. Apart from the FMF model, only the two most validated models in any‐onset pre‐eclampsia using isolated maternal characteristics, produced reasonable pooled AUROCs of 0.71 (95% PI 0.66 – 0.76) and 0.73 (0.55 – 0.86).ConclusionExisting externally validated prediction models for any‐, early‐, and late‐onset pre‐eclampsia have limited discrimination and calibration performance with inconsistent input variables. The triple test FMF model had excellent discrimination performance in predicting preterm pre‐eclampsia in numerous settings, but the inclusion of specialised biomarkers may limit feasibility and implementation outside of high‐resource settings.This article is protected by copyright. All rights reserved.

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“…Developing certain complications of pregnancy increases the risk of cardiovascular disease later in life for women. 23,24 The interrelatedness of hyperglycemia, hypertension, hyperlipidemia, and obesity commonly contributes to metabolic syndrome 25 and, ultimately, multisystem pathophysiology that compounds the risk for severe cardiovascular disease and stroke. 26 Often co-occurring with cardiometabolicrelated conditions, preterm birth, GDM, birthing an small-for-gestational-age baby, and hypertensive disorders of pregnancy, including gestational hypertension and preeclampsia, are now recognized as risk enhancers for future cardiovascular disease in women.…”

Section: Cardiometabolic Risk Factors In Pregnancymentioning

confidence: 99%

Effects of Mindfulness-Based Interventions on Cardiometabolic-Related Adverse Pregnancy Outcomes

Root,

Crossley,

Heck

et al. 2023

J Cardiovasc Nurs

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Background Growing evidence suggests maternal stress contributes to the development of adverse pregnancy outcomes that are associated with cardiovascular and cardiometabolic risk in birthing persons. Mindfulness-based interventions may positively affect psychological stress in pregnancy and, in turn, reduce stress. However, few study authors have examined the effects of mindfulness-based interventions on adverse pregnancy outcomes that heighten cardiovascular risk. Objective The aim of this study was to appraise available literature examining the effects of mindfulness-based interventions delivered during pregnancy on adverse pregnancy outcomes associated with future cardiovascular and cardiometabolic disease risk. Methods In this systematic review, multiple electronic databases were searched using major keywords, including “mindfulness-based intervention,” “pregnancy,” “preterm delivery,” “gestational diabetes,” “small for gestational age,” “preeclampsia,” and “hypertension in pregnancy” during February 2023. Results Six studies using mindfulness-based interventions during pregnancy were included. The review indicated that these interventions were largely effective at reducing prenatal stress; however, the overall effects of interventions were mixed concerning their impact on pregnancy complications. Study authors examining the effects on gestational diabetes–related outcomes reported significant improvements in blood glucose levels, hemoglobin A1c, and oral glucose tolerance. Outcomes were mixed or inconclusive related to the effects of interventions on the incidence of preterm birth, birth of a small-for-gestational-age newborn, and preeclampsia. Conclusions Mitigating cardiovascular and cardiometabolic risk-associated adverse pregnancy outcomes through mindfulness-based approaches may represent an emerging field of study. The few studies and limited, mixed findings synthesized in this review indicate that high-validity studies are warranted to examine the effects of mindfulness-based interventions on pregnancy complications that contribute to cardiovascular-related maternal morbidity and suboptimal life course health for diverse birthing persons.

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Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Cited by 14 publications

References 96 publications

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes

Externally validated prediction models for pre‐eclampsia: systematic review and meta‐analysis

Effects of Mindfulness-Based Interventions on Cardiometabolic-Related Adverse Pregnancy Outcomes

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