Fetal Growth Restriction Perinatal Outcome Decision Support – improve perinatal outcomes in early-onset fetal growth restriction by rationalizing the decision of timing of delivery

FGR PODS aims to develop a decision support tool for obstetricians to optimize birth timing in early-onset fetal growth restriction, enhancing outcomes through data integration and machine learning analysis.

Subsidie
€ 2.000.000
2024

Projectdetails

Introduction

Early-onset foetal growth restriction <32 weeks’ gestation is a severe pregnancy disorder that affects an estimated 15,000 European pregnancies annually and puts the babies at risk of severe morbidity and mortality. The underlying mechanism of the disorder is placental insufficiency leading to failure to meet the foetal metabolic and respiratory demands (the first leading to the growth disorder, the latter leading to fetal demise).

Challenges of Prematurity

Birth of the foetus prevents further damage from the intrauterine environment but exposes the neonate to the challenges of severe prematurity. When women are admitted to the hospital with this complication of pregnancy, the obstetrician monitors the progressive signs of placental insufficiency and decides to expedite birth when the risks of foetal demise outweigh the risks of prematurity.

Current Limitations

Currently, there is lacking evidence on how to weigh all prognosticators in this balance; therefore, it takes place in the black box of the obstetrician's mind.

Project Overview

In FGR PODS (Fetal Growth Restriction Perinatal Outcome Decision Support), I aim to develop and validate a ground-breaking decision support tool that will aid the obstetrician with objectively determining the optimal timing of birth.

Tool Features

The decision support tool will:

  • Integrate a combination of foetal and maternal prognosticators
  • Be implemented in electronic patient charts
  • Be provided as freeware

Data Feedback

Centres that have implemented the tool will feed back pseudonymized patient data in order to continuously refine the model.

Innovative Analysis

Also, within FGR PODS, I will perform innovative analysis (including machine learning) of fetal heart rate signals and of serially measured biomarkers to pick up placental respiratory failure.

Research Goals

These studies will:

  1. Further our understanding of the foetal pathophysiological mechanisms resulting from placental insufficiency
  2. Potentially identify targets for therapeutic interventions.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 2.000.000
Totale projectbegroting€ 2.000.000

Tijdlijn

Startdatum1-1-2024
Einddatum31-12-2028
Subsidiejaar2024

Partners & Locaties

Projectpartners

  • STICHTING AMSTERDAM UMCpenvoerder
  • ACADEMISCH ZIEKENHUIS GRONINGEN
  • NEMO HEALTHCARE BV

Land(en)

Netherlands

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