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Updated: Jun 13, 2025

The 4-vessel Sampling Approach to Integrative Studies of Human Placental Physiology In Vivo
Published on: August 2, 2017
Rule-in and rule-out of pre-eclampsia using a novel point-of-care placental growth factor test
James Rogers1, Alice Hurrell1, Gaayen Ravii Sahgal1
1Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK.
Objective:
To evaluate test performance of the point-of-care Lepzi® Quanti placental growth factor (PlGF) test to rule-in and rule-out pre-eclampsia at various time points, in women presenting with suspected preeclampsia.
Study Design:
242 frozen plasma samples from women with suspected pre-eclampsia were analysed from a prospective cohort study. Participants were recruited from two obstetric tertiary referral centres in London.
Main Outcome Measures:
PlGF concentration was quantified using the Lepzi® Quanti PlGF test, which is a point-of-care PlGF test. Test performance for diagnosis of pre-eclampsia was evaluated at various thresholds, and at different gestations. The area under the receiver operator curve (AUROC) was determined for the Lepzi® Quanti PlGF test and compared to that of the nationally recommended Delfia® Xpress PlGF1-2-3 test, in the same cohort of participants.
Results:
The LEPZI® Quanti PlGF test showed high test performance for rule-out of pre-eclampsia within seven and 28 days. A threshold of ≥ 129 pg/ml (in plasma) had high negative predictive value (NPV) for rule out of preeclampsia within seven days of sampling: NPV 96.9 % at < 34 weeks' gestation (95 % confidence interval (CI) 91.2-99.4), NPV 97.0 %; at 34 - 37 weeks' gestation (95 % CI 84.2-99.9), NPV 80.0 % at ≥ 37 weeks gestation (95 % CI 44.4-97.5).
Conclusion:
The LEPZI® Quanti PlGF test demonstrates high test performance for diagnosis of pre-eclampsia, comparable to test performance for validated, nationally recommended PlGF tests. The LEPZI® Quanti PlGF test is a whole blood, point-of-care option to optimise risk stratification, enhanced surveillance, and appropriate management strategies; this would be suitable for low- and middle-income settings, as well as high-income settings.

