Absolute Risk of Adverse Obstetric Outcomes Among Twin Pregnancies After In Vitro Fertilization by Maternal Age

Author(s): Yuanyuan Wang , PhD ¹ ^, ² ^, ³ ^, ⁴ , Huifeng Shi , PhD ² ^, ³ ^, ⁵ , Lian Chen , MD ² ^, ³ ^, ⁵ , Danni Zheng , PhD ¹ ^, ² ^, ³ ^, ⁴ , Xiaoyu Long , MD ¹ ^, ² ^, ³ ^, ⁴ , Yunjun Zhang , PhD ⁶ , Haibo Wang , PhD ⁷ ^, ⁸ , Ying Shi , MPH ⁹ , Yangyu Zhao , MD ² ^, ³ ^, ⁵ , Yuan Wei , MD ² ^, ³ ^, ⁵ ^, , Jie Qiao , MD, PhD ¹ ^, ² ^, ³ ^, ⁴ ^, ⁵ ^,

Publication date (Electronic): 10 September 2021

Journal: JAMA Network Open

Publisher: American Medical Association

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Key Points

Question

What is the absolute risk of adverse obstetric outcomes stratified by in vitro fertilization (IVF), twin or singleton pregnancy, and maternal age?

Findings

In this cohort study of 16 879 728 pregnant women, the twin pregnancy rate was 32.1% among those who conceived via IVF. Twin pregnancies conceived via IVF had higher absolute obstetric risks in each maternal age compared with IVF-conceived singleton pregnancies or non–IVF-conceived twin pregnancies.

Meaning

These findings suggest that twin pregnancy, IVF, and advanced maternal age are independently associated with adverse obstetric outcomes, and their coexistence may lead to the aggravation of obstetric risk.

Abstract

This cohort study estimates the absolute risk of maternal and neonatal complications among women who gave birth in China during a 6-year period stratified by in vitro fertilization, twin or singleton pregnancy, and maternal age.

Abstract

Importance

Twin pregnancy is a common occurrence in pregnancies conceived with in vitro fertilization (IVF), but the absolute risk of adverse obstetric outcomes stratified by IVF, twin or singleton pregnancy, and maternal age are unknown.

Objective

To estimate the absolute risk of adverse obstetric outcomes at each maternal age among twin pregnancies conceived with IVF.

Design, Setting, and Participants

This retrospective cohort study included pregnant women with infants born from January 1, 2013, to December 31, 2018, based on the Hospital Quality Monitoring System in China. Data were analyzed from September 1, 2020, to June 30, 2021.

Exposures

Twin pregnancy with IVF (IVF-T), singleton pregnancy with IVF (IVF-S), twin pregnancy with non-IVF (nIVF-T), and singleton pregnancy with non-IVF (nIVF-S).

Main Outcomes and Measures

Sixteen obstetric outcomes, including 10 maternal complications (gestational hypertension, eclampsia and preeclampsia, gestational diabetes, placenta previa, placental abruption, placenta accreta, preterm birth, dystocia, cesarean delivery, and postpartum hemorrhage) and 6 neonatal complications (fetal growth restriction, low birth weight, very low birth weight, macrosomia, malformation, and stillbirth).

Results

Among 16 879 728 pregnant women aged 20 to 49 years (mean [SD] age, 29.2 [4.7] years), the twin-pregnancy rates were 32.1% in the IVF group and 1.5% in the non-IVF group (relative risk, 20.8; 95% CI, 20.6-20.9). The most common adverse obstetric outcomes after pregnancy conceived with IVF were cesarean delivery (88.8%), low birth weight (43.8%), preterm birth (39.6%), gestational diabetes (20.5%), gestational hypertension and preeclampsia and eclampsia (17.5%), dystocia (16.8%), and postpartum hemorrhage (11.9%). The absolute risk of most adverse obstetric outcomes in each subgroup presented in 2 dominant patterns: Pattern A indicated the absolute risk ranging from IVF-T to nIVF-T to IVF-S to nIVF-S, and pattern B indicated the absolute risk ranging from IVF-T to IVF-S to nIVF-T to nIVF-S. Both patterns showed an elevated obstetric risk with increasing maternal age in each subgroup.

Conclusions and Relevance

In this cohort study, twin pregnancy, IVF, and advanced maternal age were independently associated with adverse obstetric outcomes. Given these findings, promotion of the elective single embryo transfer strategy is needed to reduce multiple pregnancies following IVF technologies. Unnecessary cesarean delivery shouldh be avoided in all pregnant women.

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Most cited references 38

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Global epidemiology of use of and disparities in caesarean sections

Ties Boerma, Carine Ronsmans, Dessalegn Y Melesse … (2018)

In this Series paper, we describe the frequency of, trends in, determinants of, and inequalities in caesarean section (CS) use, globally, regionally, and in selected countries. On the basis of data from 169 countries that include 98·4% of the world's births, we estimate that 29·7 million (21·1%, 95% uncertainty interval 19·9-22·4) births occurred through CS in 2015, which was almost double the number of births by this method in 2000 (16·0 million [12·1%, 10·9-13·3] births). CS use in 2015 was up to ten times more frequent in the Latin America and Caribbean region, where it was used in 44·3% (41·3-47·4) of births, than in the west and central Africa region, where it was used in 4·1% (3·6-4·6) of births. The global and regional increases in CS use were driven both by an increasing proportion of births occurring in health facilities (accounting for 66·5% of the global increase) and increases in CS use within health facilities (33·5%), with considerable variation between regions. Based on the most recent data available for each country, 15% of births in 106 (63%) of 169 countries were by CS, whereas 47 (28%) countries showed CS use in less than 10% of births. National CS use varied from 0·6% in South Sudan to 58·1% in the Dominican Republic. Within-country disparities in CS use were also very large: CS use was almost five times more frequent in births in the richest versus the poorest quintiles in low-income and middle-income countries; markedly high CS use was observed among low obstetric risk births, especially among more educated women in, for example, Brazil and China; and CS use was 1·6 times more frequent in private facilities than in public facilities.

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Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC).

Scott Vrieze (2012)

This article reviews the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in model selection and the appraisal of psychological theory. The focus is on latent variable models, given their growing use in theory testing and construction. Theoretical statistical results in regression are discussed, and more important issues are illustrated with novel simulations involving latent variable models including factor analysis, latent profile analysis, and factor mixture models. Asymptotically, the BIC is consistent, in that it will select the true model if, among other assumptions, the true model is among the candidate models considered. The AIC is not consistent under these circumstances. When the true model is not in the candidate model set the AIC is efficient, in that it will asymptotically choose whichever model minimizes the mean squared error of prediction/estimation. The BIC is not efficient under these circumstances. Unlike the BIC, the AIC also has a minimax property, in that it can minimize the maximum possible risk in finite sample sizes. In sum, the AIC and BIC have quite different properties that require different assumptions, and applied researchers and methodologists alike will benefit from improved understanding of the asymptotic and finite-sample behavior of these criteria. The ultimate decision to use the AIC or BIC depends on many factors, including the loss function employed, the study's methodological design, the substantive research question, and the notion of a true model and its applicability to the study at hand. (c) 2012 APA, all rights reserved

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Author and article information

Journal

Journal ID (nlm-ta): JAMA Netw Open

Journal ID (iso-abbrev): JAMA Netw Open

Journal ID (pmc): JAMA Netw Open

Title: JAMA Network Open

Publisher: American Medical Association

ISSN (Electronic): 2574-3805

Publication date (Electronic): 10 September 2021

Publication date Collection: September 2021

Publication date PMC-release: 10 September 2021

Volume: 4

Issue: 9

Electronic Location Identifier: e2123634

Affiliations

[1 ]Center for Reproductive Medicine, Peking University Third Hospital, Beijing, China

[2 ]Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

[3 ]National Clinical Research Center for Obstetrical and Gynecology, Peking University Third Hospital, Beijing, China

[4 ]Key Laboratory of Assisted Reproduction, Peking University, Ministry of Education, Beijing, China

[5 ]National Center for Healthcare Quality Management in Obstetrics, Beijing, China

[6 ]Department of Biostatistics, Peking University School of Public Health, Beijing, China

[7 ]Clinical Trial Unit, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

[8 ]Centre for Data Science in Health and Medicine, Peking University, Beijing, China

[9 ]China Standard Medical Information Research Center, Shenzhen, China

Author notes

Article Information

Accepted for Publication: June 25, 2021.

Published: September 10, 2021. doi:10.1001/jamanetworkopen.2021.23634

Corresponding Authors: Jie Qiao, MD, PhD, Center for Reproductive Medicine, Peking University Third Hospital, 49 N Garden Rd, Haidian District, Beijing 100191, China ( jie.qiao@ 123456263.net ), and Yuan Wei, MD ( weiyuanbysy@ 123456163.com ), Department of Obstetrics and Gynecology, Peking University Third Hospital, 49 N Garden Rd, Haidian District, Beijing 100191, China.

Author Contributions: Drs Y. Wang, H. Shi, and Chen contributed equally and are considered co–first authors. Drs Wei and Qiao contributed equally. Dr Qiao had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Y. Wang, Zhao, Wei, Qiao.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Y. Wang, H. Shi, Chen, Wei.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Y. Wang, H. Shi, Chen, Zheng, Long, H. Wang, Y. Shi, Zhao, Wei.

Obtained funding: Y. Wang, Zhao, Qiao.

Administrative, technical, or material support: H. Wang, Zhao, Qiao.

Supervision: Zhao, Wei, Qiao.

Conflict of Interest Disclosures: Dr Y. Wang reported receiving grants from Beijing Municipal Science & Technology Commission during the conduct of the study. Dr Zhao reported receiving grants from the National Key Research and Development Program during the conduct of the study. Dr Qiao reported receiving grants from the National Natural Science Foundation of China and grants from Chinese Academy of Engineering during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was supported by grant Z191100006619086 from Beijing Municipal Science & Technology Commission (Dr Y. Wang); grant 2016YFC1000400 from National Key Research and Development Program (Dr Y. Zhao); grant 81730038 from National Natural Science Foundation of China (Dr Qiao); and grant 2020-XZ-22 Chinese Academy of Engineering (Dr Qiao).

Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank China’s National Health Commission for approving retrieval of data from the database of Hospital Quality Monitoring System. We give special thanks to the thousands of health workers who contributed to the data collection and management, as well as the millions of pregnant women included in our study.

Additional Information: Additional data are available from Dr Qiao ( jie.qiao@ 123456263.net ).

Article

Publisher ID: zoi210694

DOI: 10.1001/jamanetworkopen.2021.23634

PMC ID: 8433605

PubMed ID: 34505887

SO-VID: 312210a8-8330-4d65-aab2-055e448dd43c

License:

This is an open access article distributed under the terms of the CC-BY License.

Absolute Risk of Adverse Obstetric Outcomes Among Twin Pregnancies After In Vitro Fertilization by Maternal Age

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Key Points

Question

Findings

Meaning

Abstract

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Related collections

Advocacy for Maternal and Women’s Health

Most cited references 38

Regression Modeling Strategies

Global epidemiology of use of and disparities in caesarean sections

Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC).

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