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...
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0dcc6959279147e19b2fae8d5e9574cb |
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| Sumario: | 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. |
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