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A New Approach for Classifying Fetal Growth Restriction
Fetal growth restriction is commonly defined using small for gestational age (SGA) birth (birthweight < 10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478298/ https://www.ncbi.nlm.nih.gov/pubmed/34270495 http://dx.doi.org/10.1097/EDE.0000000000001399 |
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author | Hutcheon, Jennifer A. Riddell, Corinne A. Himes, Katherine P. |
author_facet | Hutcheon, Jennifer A. Riddell, Corinne A. Himes, Katherine P. |
author_sort | Hutcheon, Jennifer A. |
collection | PubMed |
description | Fetal growth restriction is commonly defined using small for gestational age (SGA) birth (birthweight < 10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying fetal growth restriction at birth that combines information on multiple, imperfect measures of fetal growth restriction in a probabilistic manner. METHODS: We combined information on birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia using latent profile analysis to classify fetal growth in births at the Royal Victoria Hospital in Montreal, Canada, 2001–2009. We examined the clinical characteristics and health outcomes of infants classified as growth-restricted and nongrowth-restricted by our model, and among the subgroup of growth-restricted infants who had a birthweight ≥10th percentile (i.e., would have been missed by the conventional SGA proxy). RESULTS: Among 26,077 births, 345 (1.3%) were classified as growth-restricted by our latent profile model. Growth-restricted infants were more likely than nongrowth-restricted infants to have an Apgar score <7 (10% vs. 2%), have hypoglycemia at birth (17% vs. 3%), require neonatal intensive care unit admission (59% vs. 6%), die in the perinatal period (3.8% vs. 0.2%), and require an emergency cesarean delivery (42% vs. 15%). Risks remained elevated in growth-restricted infants who were not SGA, suggesting our model identified at-risk infants not detected using the SGA proxy. CONCLUSIONS: Latent profile analysis is a promising strategy for classifying growth restriction at birth in fetal growth restriction research. |
format | Online Article Text |
id | pubmed-8478298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-84782982021-10-06 A New Approach for Classifying Fetal Growth Restriction Hutcheon, Jennifer A. Riddell, Corinne A. Himes, Katherine P. Epidemiology Perinatal Epidemiology Fetal growth restriction is commonly defined using small for gestational age (SGA) birth (birthweight < 10th percentile) as a proxy, but this approach is problematic because most SGA infants are small but healthy. In this proof-of-concept study, we sought to develop a new approach for identifying fetal growth restriction at birth that combines information on multiple, imperfect measures of fetal growth restriction in a probabilistic manner. METHODS: We combined information on birthweight, placental weight, placental malperfusion lesions, maternal disease, and fetal acidemia using latent profile analysis to classify fetal growth in births at the Royal Victoria Hospital in Montreal, Canada, 2001–2009. We examined the clinical characteristics and health outcomes of infants classified as growth-restricted and nongrowth-restricted by our model, and among the subgroup of growth-restricted infants who had a birthweight ≥10th percentile (i.e., would have been missed by the conventional SGA proxy). RESULTS: Among 26,077 births, 345 (1.3%) were classified as growth-restricted by our latent profile model. Growth-restricted infants were more likely than nongrowth-restricted infants to have an Apgar score <7 (10% vs. 2%), have hypoglycemia at birth (17% vs. 3%), require neonatal intensive care unit admission (59% vs. 6%), die in the perinatal period (3.8% vs. 0.2%), and require an emergency cesarean delivery (42% vs. 15%). Risks remained elevated in growth-restricted infants who were not SGA, suggesting our model identified at-risk infants not detected using the SGA proxy. CONCLUSIONS: Latent profile analysis is a promising strategy for classifying growth restriction at birth in fetal growth restriction research. Lippincott Williams & Wilkins 2021-07-09 2021-11 /pmc/articles/PMC8478298/ /pubmed/34270495 http://dx.doi.org/10.1097/EDE.0000000000001399 Text en Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Perinatal Epidemiology Hutcheon, Jennifer A. Riddell, Corinne A. Himes, Katherine P. A New Approach for Classifying Fetal Growth Restriction |
title | A New Approach for Classifying Fetal Growth Restriction |
title_full | A New Approach for Classifying Fetal Growth Restriction |
title_fullStr | A New Approach for Classifying Fetal Growth Restriction |
title_full_unstemmed | A New Approach for Classifying Fetal Growth Restriction |
title_short | A New Approach for Classifying Fetal Growth Restriction |
title_sort | new approach for classifying fetal growth restriction |
topic | Perinatal Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478298/ https://www.ncbi.nlm.nih.gov/pubmed/34270495 http://dx.doi.org/10.1097/EDE.0000000000001399 |
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