Prediction models in obstetrics: understanding the treatment paradox and potential solutions to the threat it poses

Research output: Contribution to journalArticlepeer-review


  • F Cheong-See
  • N Marlin
  • B W Mol
  • E Schuit
  • G Ter Riet
  • R D Riley
  • Kgm Moons
  • K S Khan
  • S Thangaratinam

Colleges, School and Institutes

External organisations

  • Queen Mary University of London
  • The University of Adelaide
  • Department of Medical Microbiology, University Medical Centre Utrecht, Utrecht, Netherlands.
  • Amsterdam University Medical Centers/University of Amsterdam
  • Keele University


Original languageEnglish
Pages (from-to)1060-4
Number of pages5
JournalBJOG: An International Journal of Obstetrics & Gynaecology
Issue number7
Publication statusPublished - Jun 2016


  • Bias, Female, Humans, Models, Statistical, Obstetrics/statistics & numerical data, Pre-Eclampsia/therapy, Predictive Value of Tests, Pregnancy, Pregnancy Outcome, Pregnancy, High-Risk, Prenatal Care/statistics & numerical data, Propensity Score