Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mitral Valve Prolapse III: Nursing Management01:19

Mitral Valve Prolapse III: Nursing Management

214
The nursing management of Mitral Valve Prolapse, or MVP, centers around patient education, symptom monitoring, and lifestyle modifications.Patient Education on MVP Diagnosis and Heredity: Nurses should provide comprehensive education about MVP, a condition where the mitral valve does not close appropriately during heartbeats. This education often includes the condition's pathophysiology, symptoms, and potential complications, like arrhythmias or mitral regurgitation. Though not fully...
214

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

EMBRACE COMPASS: protocol for a multi-country cross-sectional comparative analysis of pregnancy and postnatal care architecture.

BMC pregnancy and childbirth·2026
Same author

Multi-Omics Reveals Early Pregnancy Placental Dysfunction Associated With Preterm and Term Preeclampsia.

MedComm·2026
Same author

Prognostic value of cervical length for spontaneous preterm birth in asymptomatic women with singleton pregnancy: An individual participant data meta-analysis.

PLoS medicine·2026
Same author

Comments on: Low adherence to aspirin and calcium carbonate for preeclampsia prevention in pregnant women with chronic hypertension in a Brazilian hospital.

Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia·2026
Same author

First-trimester prediction and prevention of preterm pre-eclampsia in women with chronic hypertension.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology·2026
Same author

The Routine 36-Week Scan-Is It Time for a Change in Policy and Practice? The Arguments for a Routine Third Trimester Ultrasound in Australian Healthcare.

The Australian & New Zealand journal of obstetrics & gynaecology·2026

Related Experiment Video

Updated: Dec 27, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.5K

Prediction of preterm pre-eclampsia at midpregnancy using a multivariable screening algorithm.

Carin Black1,2, Daniel Lorber Rolnik3,4, Ahmed Al-Amin5,6

  • 1Pregnancy Research Centre, Department of Maternal-Fetal Medicine, Royal Women's Hospital, Melbourne, Victoria, Australia.

The Australian & New Zealand Journal of Obstetrics & Gynaecology
|March 4, 2020
PubMed
Summary

This study shows the Fetal Medicine Foundation (FMF) algorithm effectively screens for preterm pre-eclampsia using maternal factors, mean arterial pressure (MAP), uterine artery pulsatility index (UtAPI), and placental growth factor (PlGF) in multiples of the median (MoM). The algorithm achieved high detection rates with acceptable false-positive rates in mid-pregnancy screening.

Keywords:
multivariable algorithmplacental growth factor (PlGF)pre-eclampsiapredictionsecond trimester

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.8K
Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles
05:31

Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles

Published on: January 26, 2024

1.2K

Related Experiment Videos

Last Updated: Dec 27, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.8K
Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles
05:31

Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles

Published on: January 26, 2024

1.2K

Area of Science:

  • Maternal-fetal medicine
  • Obstetrics
  • Reproductive health

Background:

  • Competing risk models are used for mid-pregnancy prediction of preterm pre-eclampsia.
  • Previous models showed 85% detection rates (DR) at a 10% false-positive rate (FPR).
  • The Fetal Medicine Foundation (FMF) algorithm incorporates maternal factors, mean arterial pressure (MAP), uterine artery pulsatility index (UtAPI), placental growth factor (PlGF) in multiples of the median (MoM), and soluble Fms-like tyrosine kinase-1 (sFlt-1) MoM.

Purpose of the Study:

  • To assess the performance of the FMF algorithm for screening preterm pre-eclampsia (<37 weeks) at mid-pregnancy.
  • To evaluate the algorithm's predictive accuracy for preterm pre-eclampsia.

Main Methods:

  • Prospective study of singleton pregnancies at 19-22 weeks gestation.
  • Maternal blood samples analyzed using three immunoassay platforms.
  • Risk assessment included maternal characteristics, medical history, MAP, mean UtAPI, serum PlGF MoM, and serum sFlt-1 MoM.
  • Calculated DR, FPR, and generated receiver operating characteristic curves.

Main Results:

  • Five hundred and twelve patients were included; preterm pre-eclampsia incidence was 1.6%.
  • The FMF algorithm using maternal factors, MAP, UtAPI, and PlGF MoM achieved 100% DR at FPRs of 9.3% (risk ≥ 1:60) and 100% DR at FPRs of 12.9-13.5% (risk ≥ 1:100).
  • Addition of sFlt-1 did not improve performance; different platforms showed similar PlGF MoM and sFlt-1 MoM values.

Conclusions:

  • Second-trimester screening for preterm pre-eclampsia using the FMF algorithm (maternal history, MAP, UtAPI, PlGF MoM) demonstrated excellent performance.
  • The combination of maternal factors, MAP, UtAPI, and PlGF MoM is a highly effective screening tool for preterm pre-eclampsia.
  • The FMF algorithm provides a reliable method for early identification of pregnancies at risk for preterm pre-eclampsia.