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Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa
Background: Pernicious placenta previa (PPP) is one of the most dangerous complications in pregnancy after cesarean section, with high perinatal mortality. This study aimed to develop a nomogram to predict postpartum hemorrhage in patients with PPP. Methods: A total of 246 patients with confirmed PP...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441797/ https://www.ncbi.nlm.nih.gov/pubmed/36072853 http://dx.doi.org/10.3389/fphys.2022.982080 |
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author | Zhou, Yangzi Song, Zixuan Wang, Xiaoxue Zhang, Mingjie Chen, Xueting Zhang, Dandan |
author_facet | Zhou, Yangzi Song, Zixuan Wang, Xiaoxue Zhang, Mingjie Chen, Xueting Zhang, Dandan |
author_sort | Zhou, Yangzi |
collection | PubMed |
description | Background: Pernicious placenta previa (PPP) is one of the most dangerous complications in pregnancy after cesarean section, with high perinatal mortality. This study aimed to develop a nomogram to predict postpartum hemorrhage in patients with PPP. Methods: A total of 246 patients with confirmed PPP at Shengjing Hospital of China Medical University from January 2018 to December 2021 were included. Patients were divided into to two cohorts depending on a postpartum blood loss of > 1000 ml (n = 146) or ≤ 1000 ml (n = 100). Lasso regression analysis was performed on the risk factors screened by univariate analysis to screen out the final risk factors affecting postpartum hemorrhage. Based on the final risk factors, a Nomogram prediction model with excellent performance was constructed using Logistic regression. A nomogram was constructed with further screening of the selected risk factors of postpartum hemorrhage in PPP. A second nomogram based only on the total ultrasonic risk score was constructed. Decision curve analysis (DCA) was used to evaluate the clinical efficacy of the nomograms. Results: Older age, larger gestational age, larger neonatal birth weight, presence of gestational diabetes mellitus, larger amniotic fluid index, absence of gestational bleeding, and higher ultrasonic risk single score were selected to establish a nomogram for postpartum hemorrhage in PPP. The area under the curve of the nomogram constructed by Lasso regression analysis was higher than that of the ultrasonic total score alone (0.887 vs. 0.833). Additionally, DCA indicated better clinical efficacy in the former nomogram than in the later nomogram. Furthermore, internal verification of the nomogram constructed by Lasso regression analysis showed good agreement between predicted and actual values. Conclusion: A nomogram for postpartum hemorrhage in PPP was developed and validated to assist clinicians in evaluating postpartum hemorrhage. This nomogram was more accurate than using the ultrasonic score alone. |
format | Online Article Text |
id | pubmed-9441797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94417972022-09-06 Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa Zhou, Yangzi Song, Zixuan Wang, Xiaoxue Zhang, Mingjie Chen, Xueting Zhang, Dandan Front Physiol Physiology Background: Pernicious placenta previa (PPP) is one of the most dangerous complications in pregnancy after cesarean section, with high perinatal mortality. This study aimed to develop a nomogram to predict postpartum hemorrhage in patients with PPP. Methods: A total of 246 patients with confirmed PPP at Shengjing Hospital of China Medical University from January 2018 to December 2021 were included. Patients were divided into to two cohorts depending on a postpartum blood loss of > 1000 ml (n = 146) or ≤ 1000 ml (n = 100). Lasso regression analysis was performed on the risk factors screened by univariate analysis to screen out the final risk factors affecting postpartum hemorrhage. Based on the final risk factors, a Nomogram prediction model with excellent performance was constructed using Logistic regression. A nomogram was constructed with further screening of the selected risk factors of postpartum hemorrhage in PPP. A second nomogram based only on the total ultrasonic risk score was constructed. Decision curve analysis (DCA) was used to evaluate the clinical efficacy of the nomograms. Results: Older age, larger gestational age, larger neonatal birth weight, presence of gestational diabetes mellitus, larger amniotic fluid index, absence of gestational bleeding, and higher ultrasonic risk single score were selected to establish a nomogram for postpartum hemorrhage in PPP. The area under the curve of the nomogram constructed by Lasso regression analysis was higher than that of the ultrasonic total score alone (0.887 vs. 0.833). Additionally, DCA indicated better clinical efficacy in the former nomogram than in the later nomogram. Furthermore, internal verification of the nomogram constructed by Lasso regression analysis showed good agreement between predicted and actual values. Conclusion: A nomogram for postpartum hemorrhage in PPP was developed and validated to assist clinicians in evaluating postpartum hemorrhage. This nomogram was more accurate than using the ultrasonic score alone. Frontiers Media S.A. 2022-08-22 /pmc/articles/PMC9441797/ /pubmed/36072853 http://dx.doi.org/10.3389/fphys.2022.982080 Text en Copyright © 2022 Zhou, Song, Wang, Zhang, Chen and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Zhou, Yangzi Song, Zixuan Wang, Xiaoxue Zhang, Mingjie Chen, Xueting Zhang, Dandan Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title | Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title_full | Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title_fullStr | Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title_full_unstemmed | Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title_short | Ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
title_sort | ultrasound-based nomogram for postpartum hemorrhage prediction in pernicious placenta previa |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441797/ https://www.ncbi.nlm.nih.gov/pubmed/36072853 http://dx.doi.org/10.3389/fphys.2022.982080 |
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