This article is part of the network’s archive of useful research information. This article is closed to new comments due to inactivity. We welcome new content which can be done by submitting an article for review or take part in discussions in an open topic or submit a blog post to take your discussions online.

 

Preeclampsia remains a major problem worldwide for mothers and babies. Despite intensive study, we have not been able to improve the management or early recognition of preeclampsia. At least part of this is because of failure to standardize the approach to studying this complex syndrome. It is possible that within the syndrome there may be different phenotypes with pathogenic pathways that differ between the subtypes. The capacity to recognize and to exploit different subtypes is of obvious importance for prediction, prevention, and treatment. We present a strategy for research to study preeclampsia, which will allow discrimination of such possible subtypes and also allow comparison and perhaps combinations of findings in different studies by standardized data and biosample collection. To make studies relevant to current clinical practice, the definition of preeclampsia can be that currently used and accepted. However, more importantly, sufficient data should be collected to allow other diagnostic criteria to be used and applied retrospectively. To that end, we present what we consider to be the minimum requirements for a data set in a study of preeclampsia that will facilitate comparisons. We also present a comprehensive or optimal data set for in-depth investigation of pathophysiology. As we approach the definition of phenotypes of preeclampsia by clinical and biochemical criteria, adherence to standardized protocols will hasten our  understanding of the causes of preeclampsia and development of targeted treatment strategies.

(Hypertension. 2014;63:1293-1301.)

Leslie Myatt, Christopher W. Redman, Anne Cathrine Staff, Stefan Hansson,
Melissa L. Wilson, Hannele Laivuori, Lucilla Poston, James M. Roberts;
for the Global Pregnancy CoLaboratory (CoLab)