Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia
<p style="text-align:justify;"> 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: Wo...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
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Wiley
2015
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| _version_ | 1797078246502694912 |
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| author | Palomaki, GE Haddow, JE Haddow, HRM Salahuddin, S Geahchan, C Cerdeira, AS Verlohren, S Perschel, FH Horowitz, G Thadhani, R Karumanchi, SA Rana, S |
| author_facet | Palomaki, GE Haddow, JE Haddow, HRM Salahuddin, S Geahchan, C Cerdeira, AS Verlohren, S Perschel, FH Horowitz, G Thadhani, R Karumanchi, SA Rana, S |
| author_sort | Palomaki, GE |
| collection | OXFORD |
| description | <p style="text-align:justify;"> 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. </p> |
| first_indexed | 2024-03-07T00:29:21Z |
| format | Journal article |
| id | oxford-uuid:7f39b292-5075-4b49-b321-d9c56b59e976 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T00:29:21Z |
| publishDate | 2015 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:7f39b292-5075-4b49-b321-d9c56b59e9762022-03-26T21:15:30ZModeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsiaJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7f39b292-5075-4b49-b321-d9c56b59e976EnglishSymplectic Elements at OxfordWiley2015Palomaki, GEHaddow, JEHaddow, HRMSalahuddin, SGeahchan, CCerdeira, ASVerlohren, SPerschel, FHHorowitz, GThadhani, RKarumanchi, SARana, S <p style="text-align:justify;"> 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. </p> |
| spellingShingle | Palomaki, GE Haddow, JE Haddow, HRM Salahuddin, S Geahchan, C Cerdeira, AS Verlohren, S Perschel, FH Horowitz, G Thadhani, R Karumanchi, SA Rana, S 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 |
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