Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach

Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fe...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Jonathan Yinhao Huang, Shirong Cai, Zhongwei Huang, Mya Thway Tint, Wen Lun Yuan, Izzuddin M. Aris, Keith M. Godfrey, Neerja Karnani, Yung Seng Lee, Jerry Kok Yen Chan, Yap Seng Chong, Johan Gunnar Eriksson, Shiao-Yng Chan
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Q
Acceso en línea:https://doaj.org/article/0dcc6959279147e19b2fae8d5e9574cb
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:0dcc6959279147e19b2fae8d5e9574cb
record_format dspace
spelling oai:doaj.org-article:0dcc6959279147e19b2fae8d5e9574cb2021-12-02T18:14:23ZAnalyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach10.1038/s41467-021-25899-42041-1723https://doaj.org/article/0dcc6959279147e19b2fae8d5e9574cb2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25899-4https://doaj.org/toc/2041-1723Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fetal DNA methylation. No strong differences in metabolic parameters were seen.Jonathan Yinhao HuangShirong CaiZhongwei HuangMya Thway TintWen Lun YuanIzzuddin M. ArisKeith M. GodfreyNeerja KarnaniYung Seng LeeJerry Kok Yen ChanYap Seng ChongJohan Gunnar ErikssonShiao-Yng ChanNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-16 (2021)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Jonathan Yinhao Huang
Shirong Cai
Zhongwei Huang
Mya Thway Tint
Wen Lun Yuan
Izzuddin M. Aris
Keith M. Godfrey
Neerja Karnani
Yung Seng Lee
Jerry Kok Yen Chan
Yap Seng Chong
Johan Gunnar Eriksson
Shiao-Yng Chan
Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
description Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fetal DNA methylation. No strong differences in metabolic parameters were seen.
format article
author Jonathan Yinhao Huang
Shirong Cai
Zhongwei Huang
Mya Thway Tint
Wen Lun Yuan
Izzuddin M. Aris
Keith M. Godfrey
Neerja Karnani
Yung Seng Lee
Jerry Kok Yen Chan
Yap Seng Chong
Johan Gunnar Eriksson
Shiao-Yng Chan
author_facet Jonathan Yinhao Huang
Shirong Cai
Zhongwei Huang
Mya Thway Tint
Wen Lun Yuan
Izzuddin M. Aris
Keith M. Godfrey
Neerja Karnani
Yung Seng Lee
Jerry Kok Yen Chan
Yap Seng Chong
Johan Gunnar Eriksson
Shiao-Yng Chan
author_sort Jonathan Yinhao Huang
title Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
title_short Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
title_full Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
title_fullStr Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
title_full_unstemmed Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
title_sort analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/0dcc6959279147e19b2fae8d5e9574cb
work_keys_str_mv AT jonathanyinhaohuang analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT shirongcai analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT zhongweihuang analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT myathwaytint analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT wenlunyuan analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT izzuddinmaris analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT keithmgodfrey analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT neerjakarnani analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT yungsenglee analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT jerrykokyenchan analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT yapsengchong analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT johangunnareriksson analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
AT shiaoyngchan analysesofchildcardiometabolicphenotypefollowingassistedreproductivetechnologiesusingapragmatictrialemulationapproach
_version_ 1718378375969505280