The first trimester: Prediction and prevention of the great obstetrical syndromes

Sweeting, Arianne; Park, Felicity; Hyett, Jon

doi:10.1016/j.bpobgyn.2014.09.006

Cited by 27 publications

(24 citation statements)

References 111 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Therefore, the early placenta should not be expected to release diagnostically different quantities of microRNAs into plasma until after intervillous blood flow is fully established. Attention should, therefore, be drawn to the first trimester placental bed for the purposes of risk assessment [24, 25]. However, acquiring biomarkers from the placental bed in the first trimester is invasive.…”

Section: Discussionmentioning

confidence: 99%

Early first trimester peripheral blood cell microRNA predicts risk of preterm delivery in pregnant women: Proof of concept

Winger¹,

Reed²,

2017

PLoS ONE

View full text Add to dashboard Cite

ObjectiveWe investigated the capacity of first trimester peripheral blood mononuclear cell (PBMC) microRNA to determine risk of spontaneous preterm birth among pregnant women.Study designThe study included 39 pregnant women with the following delivery outcomes: 25 with a full term delivery (38–42 weeks gestation) 14 with spontaneous preterm birth (<38 weeks gestation). Of the 14 women experiencing spontaneous preterm birth, 7 delivered at 34-<38 weeks gestation (late preterm) and 7 delivered at <34 weeks gestation (early preterm). Samples were collected at a mean of 7.9±3.0 weeks gestation. Quantitative rtPCR was performed on 30 selected microRNAs. MicroRNA Risk Scores were calculated and Area-Under the Curve-Receiver-Operational-Characteristic (AUC-ROC) curves derived.ResultsThe AUC-ROC for the group delivering preterm (<38 weeks) was 0.95 (p>0.0001). The AUC-ROC for early preterm group (<34 weeks) was 0.98 (p<0.0001) and the AUC-ROC for the late preterm group (34-<38 weeks) was 0.92 (p<0.0001).ConclusionQuantification of first trimester peripheral blood PBMC MicroRNA may provide sensitive and specific prediction of spontaneous preterm birth in pregnant women. Larger studies are needed for confirmation.

show abstract

Section: Discussionmentioning

confidence: 99%

Early first trimester peripheral blood cell microRNA predicts risk of preterm delivery in pregnant women: Proof of concept

Winger¹,

Reed²,

2017

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Therefore, promising prediction models that also use more invasive measurements may have been missed. Leaving aside that studies on the added value of biomarkers to noninvasive models are scarce, the biomarkers that have been studied for the prediction of GDM show that their predictive performance is limited and contradictory results have been published [32,[37][38][39]. For future studies, we recommend to assess the added value of biomarkers only for prediction models that have been proven to perform well in external validation studies.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Prediction models for the risk of gestational diabetes: a systematic review

et al. 2017

View full text Add to dashboard Cite

Background: Numerous prediction models for gestational diabetes mellitus (GDM) have been developed, but their methodological quality is unknown. The objective is to systematically review all studies describing first-trimester prediction models for GDM and to assess their methodological quality. Methods: MEDLINE and EMBASE were searched until December 2014. Key words for GDM, first trimester of pregnancy, and prediction modeling studies were combined. Prediction models for GDM performed up to 14 weeks of gestation that only include routinely measured predictors were eligible. Data was extracted by the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). Data on risk predictors and performance measures were also extracted. Each study was scored for risk of bias. Results: Our search yielded 7761 articles, of which 17 were eligible for review (14 development studies and 3 external validation studies). The definition and prevalence of GDM varied widely across studies. Maternal age and body mass index were the most common predictors. Discrimination was acceptable for all studies. Calibration was reported for four studies. Risk of bias for participant selection, predictor assessment, and outcome assessment was low in general. Moderate to high risk of bias was seen for the number of events, attrition, and analysis. Conclusions: Most studies showed moderate to low methodological quality, and few prediction models for GDM have been externally validated. External validation is recommended to enhance generalizability and assess their true value in clinical practice.

show abstract

“…This recommendation equates GDM to the pre-diabetic state of the non-obstetric population. Subsequently, many researchers have proposed HbA1c testing in the first trimester (HbA1c-FT) as a predictor of GDM development in the third trimester [19,20], thus opening a window of opportunity for GDM prevention [21,22].…”

Section: Introductionmentioning

confidence: 99%

Glycated haemoglobin in the first trimester: A predictor of gestational diabetes mellitus in pregnant Asian Indian women

Punnose

Malhotra

Sukhija

et al. 2020

Diabetes Research and Clinical Practice

View full text Add to dashboard Cite

The first trimester: Prediction and prevention of the great obstetrical syndromes

Cited by 27 publications

References 111 publications

Early first trimester peripheral blood cell microRNA predicts risk of preterm delivery in pregnant women: Proof of concept

Early first trimester peripheral blood cell microRNA predicts risk of preterm delivery in pregnant women: Proof of concept

Prediction models for the risk of gestational diabetes: a systematic review

Glycated haemoglobin in the first trimester: A predictor of gestational diabetes mellitus in pregnant Asian Indian women

Contact Info

Product

Resources

About