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Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births
BACKGROUND: There is a higher risk of preterm delivery (PTD) in singleton live births conceived after in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) compared with spontaneously conceived pregnancies. The objective of our study was to build a predictive nomogram model to suggest...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233110/ https://www.ncbi.nlm.nih.gov/pubmed/37274330 http://dx.doi.org/10.3389/fendo.2023.1065291 |
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author | Liao, Zhiqi Cai, Lei Liu, Chang Li, Jie Hu, Xinyao Lai, Youhua Shen, Lin Sui, Cong Zhang, Hanwang Qian, Kun |
author_facet | Liao, Zhiqi Cai, Lei Liu, Chang Li, Jie Hu, Xinyao Lai, Youhua Shen, Lin Sui, Cong Zhang, Hanwang Qian, Kun |
author_sort | Liao, Zhiqi |
collection | PubMed |
description | BACKGROUND: There is a higher risk of preterm delivery (PTD) in singleton live births conceived after in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) compared with spontaneously conceived pregnancies. The objective of our study was to build a predictive nomogram model to suggest the possibility of PTD in singleton pregnancies after IVF/ICSI treatment. METHOD: 11513 IVF/ICSI cycles with singleton live births were enrolled retrospectively. These cycles were randomly allocated into a training group (80%) and a validation group (20%). We used the multivariate logistics regression analysis to determine prognostic factors for PTD in the training group. A nomogram based on the above factors was further established for predicting PTD. Receiver operating characteristic curves (ROC), areas under the ROC curves (AUC), concordance index (C-index), and calibration plots were analyzed for assessing the performance of this nomogram in the training and validation group. RESULTS: There were fourteen risk factors significantly related to PTD in IVF/ICSI singleton live births, including maternal body mass index (BMI) > 24 kg/m(2), smoking, uterine factors, cervical factors, ovulatory factors, double embryo transferred (DET), blastocyst transfer, FET, vanishing twin syndrome (VTS), obstetric complications (placenta previa, placenta abruption, hypertensive of pregnancies, and premature rupture of membrane), and a male fetus. These factors were further incorporated to construct a nomogram prediction model. The AUC, C-index, and calibration curves indicated that this nomogram exhibited fair performance and good calibration. CONCLUSIONS: We found that the occurrence of PTD increased when women with obesity, smoking, uterine factors, cervical factors, ovulatory factors, DET, VTS, and obstetric complications, and a male fetus. Furthermore, a nomogram was constructed based on the above factors and it might have great value for clinic use. |
format | Online Article Text |
id | pubmed-10233110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102331102023-06-02 Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births Liao, Zhiqi Cai, Lei Liu, Chang Li, Jie Hu, Xinyao Lai, Youhua Shen, Lin Sui, Cong Zhang, Hanwang Qian, Kun Front Endocrinol (Lausanne) Endocrinology BACKGROUND: There is a higher risk of preterm delivery (PTD) in singleton live births conceived after in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) compared with spontaneously conceived pregnancies. The objective of our study was to build a predictive nomogram model to suggest the possibility of PTD in singleton pregnancies after IVF/ICSI treatment. METHOD: 11513 IVF/ICSI cycles with singleton live births were enrolled retrospectively. These cycles were randomly allocated into a training group (80%) and a validation group (20%). We used the multivariate logistics regression analysis to determine prognostic factors for PTD in the training group. A nomogram based on the above factors was further established for predicting PTD. Receiver operating characteristic curves (ROC), areas under the ROC curves (AUC), concordance index (C-index), and calibration plots were analyzed for assessing the performance of this nomogram in the training and validation group. RESULTS: There were fourteen risk factors significantly related to PTD in IVF/ICSI singleton live births, including maternal body mass index (BMI) > 24 kg/m(2), smoking, uterine factors, cervical factors, ovulatory factors, double embryo transferred (DET), blastocyst transfer, FET, vanishing twin syndrome (VTS), obstetric complications (placenta previa, placenta abruption, hypertensive of pregnancies, and premature rupture of membrane), and a male fetus. These factors were further incorporated to construct a nomogram prediction model. The AUC, C-index, and calibration curves indicated that this nomogram exhibited fair performance and good calibration. CONCLUSIONS: We found that the occurrence of PTD increased when women with obesity, smoking, uterine factors, cervical factors, ovulatory factors, DET, VTS, and obstetric complications, and a male fetus. Furthermore, a nomogram was constructed based on the above factors and it might have great value for clinic use. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10233110/ /pubmed/37274330 http://dx.doi.org/10.3389/fendo.2023.1065291 Text en Copyright © 2023 Liao, Cai, Liu, Li, Hu, Lai, Shen, Sui, Zhang and Qian 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 | Endocrinology Liao, Zhiqi Cai, Lei Liu, Chang Li, Jie Hu, Xinyao Lai, Youhua Shen, Lin Sui, Cong Zhang, Hanwang Qian, Kun Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title | Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title_full | Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title_fullStr | Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title_full_unstemmed | Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title_short | Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births |
title_sort | nomogram for predicting the risk of preterm delivery after ivf/icsi treatment: an analysis of 11513 singleton births |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233110/ https://www.ncbi.nlm.nih.gov/pubmed/37274330 http://dx.doi.org/10.3389/fendo.2023.1065291 |
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