Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis

Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis

Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objectives: To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia u...

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Main Authors: John Allotey, Kym IE Snell, Melanie Smuk, Richard Hooper, Claire L Chan, Asif Ahmed, Lucy C Chappell, Peter von Dadelszen, Julie Dodds, Marcus Green, Louise Kenny, Asma Khalil, Khalid S Khan, Ben W Mol, Jenny Myers, Lucilla Poston, Basky Thilaganathan, Anne C Staff, Gordon CS Smith, Wessel Ganzevoort, Hannele Laivuori, Anthony O Odibo, Javier A Ramírez, John Kingdom, George Daskalakis, Diane Farrar, Ahmet A Baschat, Paul T Seed, Federico Prefumo, Fabricio da Silva Costa, Henk Groen, Francois Audibert, Jacques Masse, Ragnhild B Skråstad, Kjell Å Salvesen, Camilla Haavaldsen, Chie Nagata, Alice R Rumbold, Seppo Heinonen, Lisa M Askie, Luc JM Smits, Christina A Vinter, Per M Magnus, Kajantie Eero, Pia M Villa, Anne K Jenum, Louise B Andersen, Jane E Norman, Akihide Ohkuchi, Anne Eskild, Sohinee Bhattacharya, Fionnuala M McAuliffe, Alberto Galindo, Ignacio Herraiz, Lionel Carbillon, Kerstin Klipstein-Grobusch, SeonAe Yeo, Helena J Teede, Joyce L Browne, Karel GM Moons, Richard D Riley, Shakila Thangaratinam
Format: Article
Language:English
Published: NIHR Journals Library 2020-12-01
Series:Health Technology Assessment
Subjects:
prediction model
prognostic model
validation
pre-eclampsia
individual participant data
ipd
Online Access:https://doi.org/10.3310/hta24720

Internet

https://doi.org/10.3310/hta24720

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