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Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia

INTRODUCTION: Preeclampsia (PE) is a pregnancy-specific syndrome associated with adverse maternal and fetal outcomes. Patient-specific risks based on angiogenic factors might better categorize those who might have a severe adverse outcome. METHODS: Women evaluated for suspected PE at a tertiary hosp...

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Autores principales: Palomaki, Glenn E, Haddow, James E, Haddow, Hamish R M, Salahuddin, Saira, Geahchan, Carl, Cerdeira, Ana Sofia, Verlohren, Stefan, Perschel, Frank H, Horowitz, Gary, Thadhani, Ravi, Karumanchi, S Ananth, Rana, Sarosh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409832/
https://www.ncbi.nlm.nih.gov/pubmed/25641027
http://dx.doi.org/10.1002/pd.4554
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author Palomaki, Glenn E
Haddow, James E
Haddow, Hamish R M
Salahuddin, Saira
Geahchan, Carl
Cerdeira, Ana Sofia
Verlohren, Stefan
Perschel, Frank H
Horowitz, Gary
Thadhani, Ravi
Karumanchi, S Ananth
Rana, Sarosh
author_facet Palomaki, Glenn E
Haddow, James E
Haddow, Hamish R M
Salahuddin, Saira
Geahchan, Carl
Cerdeira, Ana Sofia
Verlohren, Stefan
Perschel, Frank H
Horowitz, Gary
Thadhani, Ravi
Karumanchi, S Ananth
Rana, Sarosh
author_sort Palomaki, Glenn E
collection PubMed
description INTRODUCTION: Preeclampsia (PE) is a pregnancy-specific syndrome associated with adverse maternal and fetal outcomes. Patient-specific risks based on angiogenic factors might better categorize those who might have a severe adverse outcome. METHODS: Women evaluated for suspected PE at a tertiary hospital (2009–2012) had pregnancy outcomes categorized as ‘referent’ or ‘severe’, based solely on maternal/fetal findings. Outcomes that may have been influenced by a PE diagnosis were considered ‘unclassified’. Soluble fms-like tyrosine kinase (sFlt1) and placental growth factor (PlGF) were subjected to bivariate discriminant modeling, allowing patient-specific risks to be assigned for severe outcomes. RESULTS: Three hundred twenty-eight singleton pregnancies presented at ≤34.0 weeks' gestation. sFlt1 and PlGF levels were adjusted for gestational age. Risks above 5 : 1 (10-fold over background) occurred in 77% of severe (95% CI 66 to 87%) and 0.7% of referent (95% CI <0.1 to 3.8%) outcomes. Positive likelihood ratios for the modeling and validation datasets were 19 (95% CI 6.2–58) and 15 (95% CI 5.8–40) fold, respectively. CONCLUSIONS: This validated model assigns patient-specific risks of any severe outcome among women attending PE triage. In practice, women with high risks would receive close surveillance with the added potential for reducing unnecessary preterm deliveries among remaining women. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd.
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spelling pubmed-44098322015-04-29 Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia Palomaki, Glenn E Haddow, James E Haddow, Hamish R M Salahuddin, Saira Geahchan, Carl Cerdeira, Ana Sofia Verlohren, Stefan Perschel, Frank H Horowitz, Gary Thadhani, Ravi Karumanchi, S Ananth Rana, Sarosh Prenat Diagn Original Articles INTRODUCTION: Preeclampsia (PE) is a pregnancy-specific syndrome associated with adverse maternal and fetal outcomes. Patient-specific risks based on angiogenic factors might better categorize those who might have a severe adverse outcome. METHODS: Women evaluated for suspected PE at a tertiary hospital (2009–2012) had pregnancy outcomes categorized as ‘referent’ or ‘severe’, based solely on maternal/fetal findings. Outcomes that may have been influenced by a PE diagnosis were considered ‘unclassified’. Soluble fms-like tyrosine kinase (sFlt1) and placental growth factor (PlGF) were subjected to bivariate discriminant modeling, allowing patient-specific risks to be assigned for severe outcomes. RESULTS: Three hundred twenty-eight singleton pregnancies presented at ≤34.0 weeks' gestation. sFlt1 and PlGF levels were adjusted for gestational age. Risks above 5 : 1 (10-fold over background) occurred in 77% of severe (95% CI 66 to 87%) and 0.7% of referent (95% CI <0.1 to 3.8%) outcomes. Positive likelihood ratios for the modeling and validation datasets were 19 (95% CI 6.2–58) and 15 (95% CI 5.8–40) fold, respectively. CONCLUSIONS: This validated model assigns patient-specific risks of any severe outcome among women attending PE triage. In practice, women with high risks would receive close surveillance with the added potential for reducing unnecessary preterm deliveries among remaining women. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd. Blackwell Publishing Ltd 2015-04 2015-02-04 /pmc/articles/PMC4409832/ /pubmed/25641027 http://dx.doi.org/10.1002/pd.4554 Text en © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Palomaki, Glenn E
Haddow, James E
Haddow, Hamish R M
Salahuddin, Saira
Geahchan, Carl
Cerdeira, Ana Sofia
Verlohren, Stefan
Perschel, Frank H
Horowitz, Gary
Thadhani, Ravi
Karumanchi, S Ananth
Rana, Sarosh
Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title_full Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title_fullStr Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title_full_unstemmed Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title_short Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
title_sort modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409832/
https://www.ncbi.nlm.nih.gov/pubmed/25641027
http://dx.doi.org/10.1002/pd.4554
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