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Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women
OBJECTIVE: Preeclampsia, the main cause of maternal and perinatal deaths, is associated with several maternal complications and adverse perinatal outcomes. Some prediction models are uesd to evaluate adverse pregnancy outcomes. However, some of the current prediction models are mainly carried out in...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210655/ https://www.ncbi.nlm.nih.gov/pubmed/35725446 http://dx.doi.org/10.1186/s12884-022-04820-x |
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author | Zheng, Jiangyuan Zhang, Li Zhou, Yang Xu, Lin Zhang, Zuyue Luo, Yaling |
author_facet | Zheng, Jiangyuan Zhang, Li Zhou, Yang Xu, Lin Zhang, Zuyue Luo, Yaling |
author_sort | Zheng, Jiangyuan |
collection | PubMed |
description | OBJECTIVE: Preeclampsia, the main cause of maternal and perinatal deaths, is associated with several maternal complications and adverse perinatal outcomes. Some prediction models are uesd to evaluate adverse pregnancy outcomes. However, some of the current prediction models are mainly carried out in developed countries, and many problems are still exist. We, thus, developed and validated a nomogram to predict the risk of adverse pregnancy outcomes of preeclampsia in Chinese pregnant women. METHODS: The clinical data of 720 pregnant women with preeclampsia in seven medical institutions in Chongqing from January 1, 2010, to December 31, 2020, were analyzed retrospectively. The patients were divided into two groups: 180 cases (25%) with adverse outcomes and 540 cases (75%) without adverse outcomes. The indicators were identified via univariate analysis. Logistic regression analysis was used to establish the prediction model, which was displayed by a nomogram. The performance of the nomogram was evaluated in terms of the area under the receiver operating characteristic (ROC) curve, calibration, and clinical utility. RESULTS: Univariate analysis showed that 24 indicators were significantly different (P < 0.05). Logistic regression analysis showed that gestational age, 24 h urine protein qualitative, and TT were significantly different (P < 0.05). The area under the ROC curve was 0.781 (95% CI 0.737–0.825) in training set and 0.777 (95% CI 0.689–0.865) in test set. The calibration curve of the nomogram showed good agreement between prediction and observation. The analysis of the clinical decision curve showed that the nomogram is of practical significance. CONCLUSION: Our study identified gestational age, 24 h urine protein qualitative, and TT as risk factors for adverse outcomes of preeclampsia in pregnant women, and constructed a nomogram that can easily predict and evaluate the risk of adverse pregnancy outcomes in women with preeclampsia. |
format | Online Article Text |
id | pubmed-9210655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92106552022-06-22 Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women Zheng, Jiangyuan Zhang, Li Zhou, Yang Xu, Lin Zhang, Zuyue Luo, Yaling BMC Pregnancy Childbirth Research OBJECTIVE: Preeclampsia, the main cause of maternal and perinatal deaths, is associated with several maternal complications and adverse perinatal outcomes. Some prediction models are uesd to evaluate adverse pregnancy outcomes. However, some of the current prediction models are mainly carried out in developed countries, and many problems are still exist. We, thus, developed and validated a nomogram to predict the risk of adverse pregnancy outcomes of preeclampsia in Chinese pregnant women. METHODS: The clinical data of 720 pregnant women with preeclampsia in seven medical institutions in Chongqing from January 1, 2010, to December 31, 2020, were analyzed retrospectively. The patients were divided into two groups: 180 cases (25%) with adverse outcomes and 540 cases (75%) without adverse outcomes. The indicators were identified via univariate analysis. Logistic regression analysis was used to establish the prediction model, which was displayed by a nomogram. The performance of the nomogram was evaluated in terms of the area under the receiver operating characteristic (ROC) curve, calibration, and clinical utility. RESULTS: Univariate analysis showed that 24 indicators were significantly different (P < 0.05). Logistic regression analysis showed that gestational age, 24 h urine protein qualitative, and TT were significantly different (P < 0.05). The area under the ROC curve was 0.781 (95% CI 0.737–0.825) in training set and 0.777 (95% CI 0.689–0.865) in test set. The calibration curve of the nomogram showed good agreement between prediction and observation. The analysis of the clinical decision curve showed that the nomogram is of practical significance. CONCLUSION: Our study identified gestational age, 24 h urine protein qualitative, and TT as risk factors for adverse outcomes of preeclampsia in pregnant women, and constructed a nomogram that can easily predict and evaluate the risk of adverse pregnancy outcomes in women with preeclampsia. BioMed Central 2022-06-20 /pmc/articles/PMC9210655/ /pubmed/35725446 http://dx.doi.org/10.1186/s12884-022-04820-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zheng, Jiangyuan Zhang, Li Zhou, Yang Xu, Lin Zhang, Zuyue Luo, Yaling Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title | Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title_full | Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title_fullStr | Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title_full_unstemmed | Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title_short | Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women |
title_sort | development and evaluation of a nomogram for adverse outcomes of preeclampsia in chinese pregnant women |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210655/ https://www.ncbi.nlm.nih.gov/pubmed/35725446 http://dx.doi.org/10.1186/s12884-022-04820-x |
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