Chromosomal Abnormality, fetal/neonatal Death and Socioeconomic Status: A Prospective Cohort Study

Choe, Seung‐Ah; Lee, Seung Mi; Han, You Jung; Kim, Min Hyoung; Shim, Jae-Yoon; Lee, Mi-Young; Oh, Soo‐Young; Lee, Woo Jung; Kim, Soo Hyun; Hyun, Dong Choon; Cho, Geum Joon; Kwon, Han Sung; Kim, Byoung Jae; Park, Mi Hye; Cho, Hee Young; Ko, Hyun Sun; Lim, Ji Hyae; Ryu, Hyun Mee

doi:10.1007/s10995-022-03542-y

Cited by 3 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thirdly, there were missing values, especially in model 3, including PAPP-A, which might have affected its performance. However, as non-invasive prenatal testing (NIPT) with high sensitivity and low false positive rate for the detection of Down syndrome was indicated mainly in high-risk pregnant women including women aged 35 years or more [ 31 ], NIPT has been widely used as an initial fetal aneuploidy screening test rather than a maternal serum screening including PAPP-A [ 32 ] in those women. Therefore, uterine artery Doppler and biochemical markers of PAPP-A and placental growth factor (PLGF) suggested by the FMF prediction model for gestational hypertension might require another cost for application of the FMF model in high-risk pregnant women [ 10 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study

Kim

Choi

et al. 2023

Life

Self Cite

View full text Add to dashboard Cite

This study aimed to develop an early pregnancy risk scoring model for pregnancy-associated hypertension (PAH) based on maternal pre-pregnancy characteristics, such as mean arterial pressure (MAP), pregnancy-associated plasma protein-A (PAPP-A) or neither. The perinatal databases of seven hospitals from January 2009 to December 2020 were randomly divided into a training set and a test set at a ratio of 70:30. The data of a total pregnant restricted population (women not taking aspirin during pregnancy) were analyzed separately. Three models (model 1, pre-pregnancy factors only; model 2, adding MAP; model 3, adding MAP and PAPP-A) and the American College of Obstetricians and Gynecologists (ACOG) risk factors model were compared. A total of 2840 (8.11%) and 1550 (3.3%) women subsequently developed PAH and preterm PAH, respectively. Performances of models 2 and 3 with areas under the curve (AUC) over 0.82 in both total population and restricted population were superior to those of model 1 (with AUCs of 0.75 and 0.748, respectively) and the ACOG risk model (with AUCs of 0.66 and 0.66) for predicting PAH and preterm PAH. The final scoring system with model 2 for predicting PAH and preterm PAH showed moderate to good performance (AUCs of 0.78 and 0.79, respectively) in the test set. “A risk scoring model for PAH and preterm PAH with pre-pregnancy factors and MAP showed moderate to high performances. Further prospective studies for validating this scoring model with biomarkers and uterine artery Doppler or without them might be required”.

show abstract

Section: Discussionmentioning

confidence: 99%