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Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics

OBJECTIVE: To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. STUDY DESIGN: Included were 400 women with singleton deliveries in California in 2009–2010 (200 PTB and 200 term) divided into training and testing sampl...

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Autores principales: Jelliffe-Pawlowski, Laura L., Rand, Larry, Bedell, Bruce, Baer, Rebecca J., Oltman, Scott P., Norton, Mary E., Shaw, Gary M., Stevenson, David K., Murray, Jeffrey C., Ryckman, Kelli K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089890/
https://www.ncbi.nlm.nih.gov/pubmed/29795450
http://dx.doi.org/10.1038/s41372-018-0112-0
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author Jelliffe-Pawlowski, Laura L.
Rand, Larry
Bedell, Bruce
Baer, Rebecca J.
Oltman, Scott P.
Norton, Mary E.
Shaw, Gary M.
Stevenson, David K.
Murray, Jeffrey C.
Ryckman, Kelli K.
author_facet Jelliffe-Pawlowski, Laura L.
Rand, Larry
Bedell, Bruce
Baer, Rebecca J.
Oltman, Scott P.
Norton, Mary E.
Shaw, Gary M.
Stevenson, David K.
Murray, Jeffrey C.
Ryckman, Kelli K.
author_sort Jelliffe-Pawlowski, Laura L.
collection PubMed
description OBJECTIVE: To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. STUDY DESIGN: Included were 400 women with singleton deliveries in California in 2009–2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15–20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC). RESULTS: Twenty-five serum biomarkers along with maternal age <34 years and poverty status identified >80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822–0.959) training; 0.883 (0.804–0.963) testing). CONCLUSION: Together with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia.
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spelling pubmed-60898902018-08-15 Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics Jelliffe-Pawlowski, Laura L. Rand, Larry Bedell, Bruce Baer, Rebecca J. Oltman, Scott P. Norton, Mary E. Shaw, Gary M. Stevenson, David K. Murray, Jeffrey C. Ryckman, Kelli K. J Perinatol Article OBJECTIVE: To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. STUDY DESIGN: Included were 400 women with singleton deliveries in California in 2009–2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15–20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC). RESULTS: Twenty-five serum biomarkers along with maternal age <34 years and poverty status identified >80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822–0.959) training; 0.883 (0.804–0.963) testing). CONCLUSION: Together with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia. Nature Publishing Group US 2018-05-24 2018 /pmc/articles/PMC6089890/ /pubmed/29795450 http://dx.doi.org/10.1038/s41372-018-0112-0 Text en © The Author(s) 2018 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jelliffe-Pawlowski, Laura L.
Rand, Larry
Bedell, Bruce
Baer, Rebecca J.
Oltman, Scott P.
Norton, Mary E.
Shaw, Gary M.
Stevenson, David K.
Murray, Jeffrey C.
Ryckman, Kelli K.
Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title_full Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title_fullStr Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title_full_unstemmed Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title_short Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
title_sort prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089890/
https://www.ncbi.nlm.nih.gov/pubmed/29795450
http://dx.doi.org/10.1038/s41372-018-0112-0
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