Screening for trisomy 18 using traditional combined screening vs. ultrasound-based protocol in tertiary center environment

Wiechec, M.; Knafel, Anna; Nocun, A.; Ludwin, Artur; Ludwin, I.; Maczka, M; Ziętek, Damian; Pasternok, Marcin; Moosburger, Dietmar; Zalewski, Sebastian; Rozmus-Warcholińska, Wioletta

doi:10.1080/14767058.2016.1224837

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…We thank the authors for addressing this important issue. Their findings may explain a trend that we have observed for several years in the Polish population [2][3][4][5] .…”

supporting

confidence: 75%

Re: Assay interference leading to erroneous pregnancy‐associated plasma protein‐A results

Matyszkiewicz,

Wiecheć,

Nocuń

2023

Ultrasound in Obstet & Gyne

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“…We thank the authors for addressing this important issue. Their findings may explain a trend that we have observed for several years in the Polish population [2][3][4][5] .…”

supporting

confidence: 75%

Re: Assay interference leading to erroneous pregnancy‐associated plasma protein‐A results

Matyszkiewicz,

Wiecheć,

Nocuń

2023

Ultrasound in Obstet & Gyne

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“…The same applies to Pappalysin-1 (PAPP-A), one of the top nine proteins whose concentration increased more than five-fold in this study. PAPP-A is mainly produced by the placenta, and its concentration is low in the first trimester of pregnancies complicated by either chromosomal abnormalities (Trisomies 21, 18 and 13, and monosomy X) (93, 97-100, [245][246][247][248] or a subset destined to develop placenta-mediated obstetrical syndromes such as SGA and preeclampsia (119, [249][250][251][252][253][254][255][256][257][258][259][260][261] and preterm birth (262). In this study, we also report the longitudinal changes in the plasma concentrations of PAPP-A as a function of gestational age.…”

Section: Meaning Of the Studymentioning

confidence: 99%

The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study

Romero

Erez

Maymon

et al. 2017

American Journal of Obstetrics and Gynecology

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Objective Pregnancy is accompanied by dramatic physiologic changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age, and determine biological processes that are perturbed in normal pregnancy. Materials and methods A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age (AGA) without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median=5,) were profiled to measure the abundance of 1,125 proteins using multiplex assays. Linear mixed effects models with polynomial splines were used to model protein abundance as a function of gestational age, and significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having: 1) more than 1.5 fold change between 8 and 40 weeks of gestation; and 2) a false discovery rate (FDR) adjusted p-value <0.1. Gene ontology enrichment analysis was employed to identify biological processes over-represented among the proteins that changed with advancing gestation. Results 1) Ten percent (112/1,125) of the profiled proteins changed in abundance as a function of gestational age; 2) of the 1,125 proteins analyzed Glypican-3, sialic acid-binding immunoglobulin-type lectins (Siglec)-6, placental growth factor (PlGF), C-C motif (CCL)-28, carbonic anhydrase 6, Prolactin (PRL), interleukin-1 receptor 4 (IL-1 R4), dual specificity mitogen-activated protein kinase 4 (MP2K4) and pregnancy-associated plasma protein-A (PAPP-A) had more than 5 fold change in abundance across gestation. These 9 proteins are known to be involved in a wide range of both physiologic and pathologic processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc.; and 3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis and leukocyte migration (FDR=10%). Conclusions The plasma proteome of normal pregnancy demonstrates dramatic changes in both magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy, development of biomarkers to differentiate normal vs. abnormal pregnancy, and determine the response to interventions.

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“…Congenital heart disease (CHD) is a birth defect that causes structural and functional abnormalities of the heart and blood vessels at birth, which is the most ubiquitous congenital disease that affects the health of infants [ 1 ]. According to the statistics of the World Health Organization (WHO), about 1.49 to 2.01 million infants are born with CHD every year [ 2 ]. CHD accounted for 1.2% of newborns in the United States [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

Han¹,

Jin²,

Zhang³

et al. 2022

Applied Bionics and Biomechanics

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This research was aimed at exploring the diagnostic and screening effect of composite echocardiography based on the artificial intelligence (AI) segmentation algorithm on fetal congenital heart disease (CHD) during pregnancy, so as to reduce the birth rate of newborns with CHD. A total of 204 fetuses with abnormal heart conditions were divided into group II, group C (optimized with the AI algorithm), and group W (not optimized with the AI algorithm). In addition, 9,453 fetuses with normal heart conditions were included in group I. The abnormal distribution of fetal heart and the difference of cardiac Z score between group II and group I were analyzed, and the diagnostic value of group C and group W for CHD was compared. The results showed that the segmentation details of the proposed algorithm were better than those of the convolutional neural network (CNN), and the Dice coefficient, precision, and recall values were higher than those of the CNN. In fetal CHD, the incidence of abnormal ultrasonic manifestations was ventricular septal defect (98/48.04%), abnormal right subclavian artery (29/14.22%), and persistent left superior vena cava (25/12.25%). The diagnostic sensitivity (75.0% vs. 51.5%), specificity (99.6% vs. 99.2%), accuracy (99.0% vs. 98.2%), negative predictive value (88.5% vs. 78.5%), and positive predictive value (99% vs. 57.7%) of echocardiography segmentation in group C were significantly higher than those in group W. To sum up, echocardiography segmented by the AI algorithm could obviously improve the diagnostic efficiency of fetal CHD during gestation. Cardiac ultrasound parameters of children with CHD changed greatly.

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Screening for trisomy 18 using traditional combined screening vs. ultrasound-based protocol in tertiary center environment

Abstract: Only, a multiparameter ultrasound-based screening method may be considered an effective alternative to combined screening for T18 screening. The technique exhibits high and stable DRs irrespective of MA.

Cited by 7 publications

References 23 publications

Re: Assay interference leading to erroneous pregnancy‐associated plasma protein‐A results

Re: Assay interference leading to erroneous pregnancy‐associated plasma protein‐A results

The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study

Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

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