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Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach
INTRODUCTION: Preeclampsia is a major cause of maternal and prenatal mortality and morbidity worldwide. There are some risk factors that are of great value for prediction of preeclampsia by which the practitioners can counsel women regarding this disease. The aim of this study was to analyze the rol...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Termedia Publishing House
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776178/ https://www.ncbi.nlm.nih.gov/pubmed/24049529 http://dx.doi.org/10.5114/aoms.2013.36900 |
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author | Direkvand-Moghadam, Ashraf Khosravi, Afra Sayehmiri, Kourosh |
author_facet | Direkvand-Moghadam, Ashraf Khosravi, Afra Sayehmiri, Kourosh |
author_sort | Direkvand-Moghadam, Ashraf |
collection | PubMed |
description | INTRODUCTION: Preeclampsia is a major cause of maternal and prenatal mortality and morbidity worldwide. There are some risk factors that are of great value for prediction of preeclampsia by which the practitioners can counsel women regarding this disease. The aim of this study was to analyze the role of such risk factors as the predictors associated with preeclampsia among Iranian women using logistic regression. MATERIAL AND METHODS: The role of some risk factors such as demographic, anthropometric, medical and obstetrics variables in preeclampsia among 610 women attending the obstetric ward of Mustafa hospital in Ilam in the west of Iran was analyzed from May to September 2010. All the pregnant women referred to this hospital participated in the study except those cases that had abortion. Unvaried and Multiple logistic regression analyses were used to find the predictive factors behind preeclampsia. Standard errors of area compute using nonparametric methods. A p-value of 0.05 was considered statistically significant. RESULTS: Prevalence of preeclampsia was 9.5% (95% CI 7.4–11.6%). Predictive model build using history of preeclampsia, history of hypertension, and history of infertility. Area Under the Receiver Operation Character (AUROC) was estimated 0.67 (95% CI 0.59–0.67, p < 0.01) that showed that using the model is much better than having a guess. CONCLUSIONS: The odd of preeclampsia increased in women with a history of preeclampsia, hypertension and infertility. Recognition of these predictor factors would improve the ability to diagnose and monitor women likely to develop preeclampsia before the onset of disease for timely interventions. |
format | Online Article Text |
id | pubmed-3776178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Termedia Publishing House |
record_format | MEDLINE/PubMed |
spelling | pubmed-37761782013-09-18 Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach Direkvand-Moghadam, Ashraf Khosravi, Afra Sayehmiri, Kourosh Arch Med Sci Clinical Research INTRODUCTION: Preeclampsia is a major cause of maternal and prenatal mortality and morbidity worldwide. There are some risk factors that are of great value for prediction of preeclampsia by which the practitioners can counsel women regarding this disease. The aim of this study was to analyze the role of such risk factors as the predictors associated with preeclampsia among Iranian women using logistic regression. MATERIAL AND METHODS: The role of some risk factors such as demographic, anthropometric, medical and obstetrics variables in preeclampsia among 610 women attending the obstetric ward of Mustafa hospital in Ilam in the west of Iran was analyzed from May to September 2010. All the pregnant women referred to this hospital participated in the study except those cases that had abortion. Unvaried and Multiple logistic regression analyses were used to find the predictive factors behind preeclampsia. Standard errors of area compute using nonparametric methods. A p-value of 0.05 was considered statistically significant. RESULTS: Prevalence of preeclampsia was 9.5% (95% CI 7.4–11.6%). Predictive model build using history of preeclampsia, history of hypertension, and history of infertility. Area Under the Receiver Operation Character (AUROC) was estimated 0.67 (95% CI 0.59–0.67, p < 0.01) that showed that using the model is much better than having a guess. CONCLUSIONS: The odd of preeclampsia increased in women with a history of preeclampsia, hypertension and infertility. Recognition of these predictor factors would improve the ability to diagnose and monitor women likely to develop preeclampsia before the onset of disease for timely interventions. Termedia Publishing House 2013-08-08 2013-08-30 /pmc/articles/PMC3776178/ /pubmed/24049529 http://dx.doi.org/10.5114/aoms.2013.36900 Text en Copyright © 2013 Termedia & Banach http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Research Direkvand-Moghadam, Ashraf Khosravi, Afra Sayehmiri, Kourosh Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title | Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title_full | Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title_fullStr | Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title_full_unstemmed | Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title_short | Predictive factors for preeclampsia in pregnant women: a Receiver Operation Character approach |
title_sort | predictive factors for preeclampsia in pregnant women: a receiver operation character approach |
topic | Clinical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3776178/ https://www.ncbi.nlm.nih.gov/pubmed/24049529 http://dx.doi.org/10.5114/aoms.2013.36900 |
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