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

      Snell, Kym I.E.; Allotey, John; Smuk, Melanie; Hooper, Richard; Chan, Claire; Ahmed, Asif; Chappell, Lucy C.; Von Dadelszen, Peter; Green, Marcus; Kenny, Louise; Khalil, Asma; Khan, Khalid; Mol, Ben W.; Myers, Jenny; Poston, Lucilla; Thilaganathan, Basky; Staff, Anne Cathrine; Smith, Gordon C.S.; Ganzevoort, Wessel; Laivuori, Hannele; Odibo, Anthony; Arenas Ramírez, Javier; Kingdom, John; Daskalakis, George; Farrar, Diane; Baschat, Ahmet A.; Seed, Paul T.; Prefumo, Federico; da Silva Costa, Fabricio; Groen, Henk; Audibert, Francois; Masse, Jacques; Skråstad, Ragnhild Bergene; Salvesen, Kjell Å; Haavaldsen, Camilla; Nagata, Chie; Rumbold, Alice R.; Heinonen, Seppo; Askie, Lisa; Smits, Luc; Vinter, Christina; Magnus, Per; Eero, Kajantie; Villa, Pia M.; Jenum, Anne Karen; Andersen, Louise B.; Norman, Jane E.; Ohkuchi, Akihide; Eskild, Anne; Bhattacharya, Sohinee; McAuliffe, Fionnuala; Galindo, Alberto; Herraiz, Ignacio; Carbillon, Lionel; Klipstein-Grobusch, Kerstin; Yeo, SeonAe; Browne, Joyce L.; Moons, Karel G.M.; Riley, Richard D.; Thangaratinam, Shakila (Peer reviewed; Journal article, 2020)
      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 ...