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Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran

OBJECTIVE: To determine the maternal risk factors associated with preterm delivery in Iran. METHODS: A population-based case-control study was conducted including 48 women having preterm delivery (case group) and 100 women having term delivery (control group) between March 2007 and March 2012 in the...

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Autores principales: Valipour, Mehrdad, Ayubi, Erfan, Shiravand, Narges, Moradi, Yousef, Abbaszadeh, Abolfazl, Amrai, Firooz, Mokhtari, Shahin, Bahmanpour, Kaveh, Mansori, Kamyar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Obstetrics and Gynecology; Korean Society of Contraception and Reproductive Health; Korean Society of Gynecologic Endocrinology; Korean Society of Gynecologic Endoscopy and Minimal Invasive Surgery; Korean Society of Maternal Fetal Medicine; Korean Society of Ultrasound in Obstetrics and Gynecology; Korean Urogynecologic Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073365/
https://www.ncbi.nlm.nih.gov/pubmed/32206650
http://dx.doi.org/10.5468/ogs.2020.63.2.117
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author Valipour, Mehrdad
Ayubi, Erfan
Shiravand, Narges
Moradi, Yousef
Abbaszadeh, Abolfazl
Amrai, Firooz
Mokhtari, Shahin
Bahmanpour, Kaveh
Mansori, Kamyar
author_facet Valipour, Mehrdad
Ayubi, Erfan
Shiravand, Narges
Moradi, Yousef
Abbaszadeh, Abolfazl
Amrai, Firooz
Mokhtari, Shahin
Bahmanpour, Kaveh
Mansori, Kamyar
author_sort Valipour, Mehrdad
collection PubMed
description OBJECTIVE: To determine the maternal risk factors associated with preterm delivery in Iran. METHODS: A population-based case-control study was conducted including 48 women having preterm delivery (case group) and 100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals of the Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structured interview and reviewing the medical records. The maternal risk factors associated with preterm delivery were identified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The area under the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of the statistical models. RESULTS: Multivariable analysis demonstrated that multiparty (odds ratio [OR], 14.23; 95% confidence interval [CI], 1.60–127.05), history of gestational diabetes (OR, 0.10; 95% CI, 0.01–0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78–1,637.80), urinary tract infection (OR, 16.60; 95% CI, 3.20–85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03–0.50) had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curve for the aforementioned maternal risk factors was 0.86 (95% CI, 0.80–0.92). CONCLUSION: Our study provides evidence for the associations between multiparty, history of gestational diabetes, thyroid dysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery.
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spelling pubmed-70733652020-03-23 Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran Valipour, Mehrdad Ayubi, Erfan Shiravand, Narges Moradi, Yousef Abbaszadeh, Abolfazl Amrai, Firooz Mokhtari, Shahin Bahmanpour, Kaveh Mansori, Kamyar Obstet Gynecol Sci Original Article OBJECTIVE: To determine the maternal risk factors associated with preterm delivery in Iran. METHODS: A population-based case-control study was conducted including 48 women having preterm delivery (case group) and 100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals of the Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structured interview and reviewing the medical records. The maternal risk factors associated with preterm delivery were identified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The area under the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of the statistical models. RESULTS: Multivariable analysis demonstrated that multiparty (odds ratio [OR], 14.23; 95% confidence interval [CI], 1.60–127.05), history of gestational diabetes (OR, 0.10; 95% CI, 0.01–0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78–1,637.80), urinary tract infection (OR, 16.60; 95% CI, 3.20–85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03–0.50) had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curve for the aforementioned maternal risk factors was 0.86 (95% CI, 0.80–0.92). CONCLUSION: Our study provides evidence for the associations between multiparty, history of gestational diabetes, thyroid dysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery. Korean Society of Obstetrics and Gynecology; Korean Society of Contraception and Reproductive Health; Korean Society of Gynecologic Endocrinology; Korean Society of Gynecologic Endoscopy and Minimal Invasive Surgery; Korean Society of Maternal Fetal Medicine; Korean Society of Ultrasound in Obstetrics and Gynecology; Korean Urogynecologic Society 2020-03 2020-02-11 /pmc/articles/PMC7073365/ /pubmed/32206650 http://dx.doi.org/10.5468/ogs.2020.63.2.117 Text en Copyright © 2020 Korean Society of Obstetrics and Gynecology http://creativecommons.org/licenses/by-nc/3.0/ Articles published in Obstet Gynecol Sci are open-access, distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Valipour, Mehrdad
Ayubi, Erfan
Shiravand, Narges
Moradi, Yousef
Abbaszadeh, Abolfazl
Amrai, Firooz
Mokhtari, Shahin
Bahmanpour, Kaveh
Mansori, Kamyar
Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title_full Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title_fullStr Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title_full_unstemmed Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title_short Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran
title_sort determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in iran
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073365/
https://www.ncbi.nlm.nih.gov/pubmed/32206650
http://dx.doi.org/10.5468/ogs.2020.63.2.117
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