External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis

External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis

Abstract Background Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external da...

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Main Authors: Kym I. E. Snell, John Allotey, Melanie Smuk, Richard Hooper, Claire Chan, Asif Ahmed, Lucy C. Chappell, Peter Von Dadelszen, Marcus Green, Louise Kenny, Asma Khalil, Khalid S. Khan, Ben W. Mol, Jenny Myers, Lucilla Poston, Basky Thilaganathan, Anne C. Staff, Gordon C. S. Smith, Wessel Ganzevoort, Hannele Laivuori, Anthony O. Odibo, Javier Arenas 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 J. M. Smits, Christina A. Vinter, Per 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, Seon Ae Yeo, Joyce L. Browne, Karel G. M. Moons, Richard D. Riley, Shakila Thangaratinam, for the IPPIC Collaborative Network
Format: Article
Language:English
Published: BMC 2020-11-01
Series:BMC Medicine
Subjects:
Pre-eclampsia
External validation
Prediction model
Individual participant data
Online Access:http://link.springer.com/article/10.1186/s12916-020-01766-9

Internet

http://link.springer.com/article/10.1186/s12916-020-01766-9

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