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Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study
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 f...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302265/ https://www.ncbi.nlm.nih.gov/pubmed/37374113 http://dx.doi.org/10.3390/life13061330 |
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author | Jo, Yun Sung Kim, Woo Jeng Choi, Sae Kyung Kim, Su Mi Shin, Jae Eun Kil, Ki Cheol Kim, Yeon Hee Wie, Jeong Ha Kim, Han Wool Hong, Subeen Ko, Hyun Sun |
author_facet | Jo, Yun Sung Kim, Woo Jeng Choi, Sae Kyung Kim, Su Mi Shin, Jae Eun Kil, Ki Cheol Kim, Yeon Hee Wie, Jeong Ha Kim, Han Wool Hong, Subeen Ko, Hyun Sun |
author_sort | Jo, Yun Sung |
collection | PubMed |
description | 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”. |
format | Online Article Text |
id | pubmed-10302265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103022652023-06-29 Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study Jo, Yun Sung Kim, Woo Jeng Choi, Sae Kyung Kim, Su Mi Shin, Jae Eun Kil, Ki Cheol Kim, Yeon Hee Wie, Jeong Ha Kim, Han Wool Hong, Subeen Ko, Hyun Sun Life (Basel) Article 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”. MDPI 2023-06-06 /pmc/articles/PMC10302265/ /pubmed/37374113 http://dx.doi.org/10.3390/life13061330 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jo, Yun Sung Kim, Woo Jeng Choi, Sae Kyung Kim, Su Mi Shin, Jae Eun Kil, Ki Cheol Kim, Yeon Hee Wie, Jeong Ha Kim, Han Wool Hong, Subeen Ko, Hyun Sun Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title | Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title_full | Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title_fullStr | Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title_full_unstemmed | Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title_short | Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study |
title_sort | prediction of pregnancy-associated hypertension using a scoring system: a multicenter cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302265/ https://www.ncbi.nlm.nih.gov/pubmed/37374113 http://dx.doi.org/10.3390/life13061330 |
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