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Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment

BACKGROUND: Women who conceived with in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) are more likely to experience adverse pregnancy outcomes than women who conceived naturally. Cervical insufficiency (CI) is one of the important causes of miscarriage and premature birth, how...

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Autores principales: Wu, Yaoqiu, Liang, Xiaoyan, Cai, Meihong, Gao, Linzhi, Lan, Jie, Yang, Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789534/
https://www.ncbi.nlm.nih.gov/pubmed/33413472
http://dx.doi.org/10.1186/s12958-020-00693-x
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author Wu, Yaoqiu
Liang, Xiaoyan
Cai, Meihong
Gao, Linzhi
Lan, Jie
Yang, Xing
author_facet Wu, Yaoqiu
Liang, Xiaoyan
Cai, Meihong
Gao, Linzhi
Lan, Jie
Yang, Xing
author_sort Wu, Yaoqiu
collection PubMed
description BACKGROUND: Women who conceived with in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) are more likely to experience adverse pregnancy outcomes than women who conceived naturally. Cervical insufficiency (CI) is one of the important causes of miscarriage and premature birth, however there is no published data available focusing on the potential risk factors predicting CI occurrence in women who received IVF/ICSI treatment. This study aimed to identify the risk factors that could be integrated into a predictive model for CI, which could provide further personalized and clinically specific information related to the incidence of CI after IVF/ICSI treatment. PATIENTS AND METHODS: This retrospective study included 4710 patients who conceived after IVF/ICSI treatment from Jan 2011 to Dec 2018 at a public university hospital. The patients were randomly divided into development (n = 3108) and validation (n = 1602) samples for the building and testing of the nomogram, respectively. Multivariate logistic regression was developed on the basis of pre-pregnancy clinical covariates assessed for their association with CI occurrence. RESULTS: A total of 109 patients (2.31%) experienced CI among all the enrolled patients. Body mass index (BMI), basal serum testosterone (T), gravidity and uterine length were associated with CI occurrence. The statistical nomogram was built based on BMI, serum T, gravidity and uterine length, with an area under the curve (AUC) of 0.84 (95% confidence interval: 0.76–0.90) for the developing cohort. The AUC for the validation cohort was 0.71 (95% confidence interval: 0.69–0.83), showing a satisfactory goodness-of-fit and discrimination ability in this nomogram. CONCLUSION: The user-friendly nomogram which graphically represents the risk factors and a pre-pregnancy predicted tool for the incidence of CI in patients undergoing IVF/ICSI treatment, provides a useful guide for medical staff on individualized decisions making, where preventive measures could be carried out during the IVF/ICSI procedure and subsequent pregnancy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12958-020-00693-x.
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spelling pubmed-77895342021-01-07 Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment Wu, Yaoqiu Liang, Xiaoyan Cai, Meihong Gao, Linzhi Lan, Jie Yang, Xing Reprod Biol Endocrinol Research BACKGROUND: Women who conceived with in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) are more likely to experience adverse pregnancy outcomes than women who conceived naturally. Cervical insufficiency (CI) is one of the important causes of miscarriage and premature birth, however there is no published data available focusing on the potential risk factors predicting CI occurrence in women who received IVF/ICSI treatment. This study aimed to identify the risk factors that could be integrated into a predictive model for CI, which could provide further personalized and clinically specific information related to the incidence of CI after IVF/ICSI treatment. PATIENTS AND METHODS: This retrospective study included 4710 patients who conceived after IVF/ICSI treatment from Jan 2011 to Dec 2018 at a public university hospital. The patients were randomly divided into development (n = 3108) and validation (n = 1602) samples for the building and testing of the nomogram, respectively. Multivariate logistic regression was developed on the basis of pre-pregnancy clinical covariates assessed for their association with CI occurrence. RESULTS: A total of 109 patients (2.31%) experienced CI among all the enrolled patients. Body mass index (BMI), basal serum testosterone (T), gravidity and uterine length were associated with CI occurrence. The statistical nomogram was built based on BMI, serum T, gravidity and uterine length, with an area under the curve (AUC) of 0.84 (95% confidence interval: 0.76–0.90) for the developing cohort. The AUC for the validation cohort was 0.71 (95% confidence interval: 0.69–0.83), showing a satisfactory goodness-of-fit and discrimination ability in this nomogram. CONCLUSION: The user-friendly nomogram which graphically represents the risk factors and a pre-pregnancy predicted tool for the incidence of CI in patients undergoing IVF/ICSI treatment, provides a useful guide for medical staff on individualized decisions making, where preventive measures could be carried out during the IVF/ICSI procedure and subsequent pregnancy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12958-020-00693-x. BioMed Central 2021-01-07 /pmc/articles/PMC7789534/ /pubmed/33413472 http://dx.doi.org/10.1186/s12958-020-00693-x Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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
Wu, Yaoqiu
Liang, Xiaoyan
Cai, Meihong
Gao, Linzhi
Lan, Jie
Yang, Xing
Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title_full Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title_fullStr Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title_full_unstemmed Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title_short Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment
title_sort development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing ivf/icsi treatment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789534/
https://www.ncbi.nlm.nih.gov/pubmed/33413472
http://dx.doi.org/10.1186/s12958-020-00693-x
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