Accuracy of clinical characteristics biochemical and ultrasound markers in predicting pre-eclampsia: External validation and development of prediction models using an Individual Participant Data (IPD) meta-analysis

John Allotey, Kym Snell, Melanie Smuk, Richard Hooper, Claire Chan, Asif Ahmed, Lucy C Chappell, Peter Von Dadelszen, Julie Dodds, Louise C Kenny, Asma Khalil, Khalid S Khan, Ben W J Mol, Jenny Myers, Lucilla Poston, Basky Thilaganathan, Anne C. Staff, Gordon C.S. Smith, Wessel Ganzevoort, Hannele LaivuoriAnthony O. Odibo, Javier A. Ramírez, John Kingdom, Marcus Green, George Daskalakis, Diane Farrar, Ahmet 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 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 G M Moons, Richard D Riley, Shakila Thangaratinam

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
JournalHealth Technology Assessment
Publication statusAccepted/In press - 24 Mar 2020

Keywords

  • Prediction model
  • Prognostic model
  • Validation
  • Pre-eclampsia
  • Individual Participant Data
  • IPD

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