Precision Medicine for Prediction & Prevention of Early Pre-eclampsia
NCT ID: NCT04412681
Last Updated: 2021-03-22
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
1000 participants
INTERVENTIONAL
2021-03-01
2022-06-01
Brief Summary
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Detailed Description
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The traditional approach to screening for preeclampsia endorsed by national guidelines is based on a combination of maternal characteristics along with medical, obstetric and family history.
However, although these methods are simple and easy to perform, maternal factors can only identify less than 35% of all preeclampsia and approximately 40% of preterm-preeclampsia at a false- positive rate of 10%.
More recently, multivariate analysis has been used to develop predictive models for preeclampsia that can be applied as early as 11-13+6 weeks gestation. One such algorithm, developed by the Fetal Medicine Foundation UK(MFM UK), incorporates maternal risk factors, uterine artery doppler, mean arterial pressure, and serum markers of placental function and placental growth factor. The FMFUK algorithm has been shown to predict approximately 75-90% of those women destined to develop preeclampsia prior to 37 and 34 weeks respectively, at a false positive rate of 10%. This algorithm has been validated prospectively in several studies, including the prediction of other placental mediated complications of pregnancy, such as fetal growth restriction and perinatal death.
The new clinical model will include the following additions to the existing first trimester screening for aneuploidy:
* Additional Clinical History
* Blood pressure measurements
* Ultrasound for uterine artery Doppler measurements
* Expanded prenatal screening requisition
* Quality assurance training of ultrasound technicians for the uterine artery doppler measurements
* Fetal Medicine Foundation validated risk calculation algorithm
* Communicate results of the risk calculation algorithm from NYGH to SHSC and participant health care providers.
While the ultimate goal will be to scale up and adapt this new clinical model, this protocol focuses on the feasibility of implementing the new clinical model at a single centre, Sunnybrook Health Sciences Centre.
Conditions
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Study Design
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NA
SINGLE_GROUP
PREVENTION
NONE
Study Groups
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PE Enhanced Screening
The PE screening program entails the following for all participants:
* provision of additional demographic and risk factors
* provision of mean arterial pressure
* standard nuchal translucency scan as part of their first trimester screening (FTS) with the addition of the measurement of the uterine artery Doppler by a certified sonographer
* standard blood sample (as part of the FTS)
* results of the PE screening (in the format of a screening report) will be provided to the study team and participant's healthcare provider
Enhanced PE Screening
To better identify women at risk for pre-eclampsia during pregnancy.
Interventions
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Enhanced PE Screening
To better identify women at risk for pre-eclampsia during pregnancy.
Eligibility Criteria
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Inclusion Criteria
2. Not on low dose aspirin
3. Carrying a live fetus with crown rump length (CRL) between 41 and 84mm
4. Able to provide informed consent
5. Having a nuchal translucency ultrasound
Exclusion Criteria
2. Women currently taking low dose aspirin
3. Women declining a nuchal translucency ultrasound
4. Women unable to provide informed consent
5. Women with a multiple pregnancy
6. Women with a demised fetus or a CRL \<41mm and \>84mm
18 Years
FEMALE
Yes
Sponsors
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North York General Hospital
OTHER
Sunnybrook Health Sciences Centre
OTHER
Responsible Party
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Principal Investigators
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Ronzoni
Role: PRINCIPAL_INVESTIGATOR
Sunnybrook Health Sciences Center
Locations
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Sunnybrook Health Sciences center
Toronto, Ontario, Canada
Countries
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Central Contacts
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Facility Contacts
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References
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Wright D, Syngelaki A, Akolekar R, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal characteristics and medical history. Am J Obstet Gynecol. 2015 Jul;213(1):62.e1-62.e10. doi: 10.1016/j.ajog.2015.02.018. Epub 2015 Feb 25.
O'Gorman N, Wright D, Poon LC, Rolnik DL, Syngelaki A, de Alvarado M, Carbone IF, Dutemeyer V, Fiolna M, Frick A, Karagiotis N, Mastrodima S, de Paco Matallana C, Papaioannou G, Pazos A, Plasencia W, Nicolaides KH. Multicenter screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation: comparison with NICE guidelines and ACOG recommendations. Ultrasound Obstet Gynecol. 2017 Jun;49(6):756-760. doi: 10.1002/uog.17455.
Park FJ, Leung CH, Poon LC, Williams PF, Rothwell SJ, Hyett JA. Clinical evaluation of a first trimester algorithm predicting the risk of hypertensive disease of pregnancy. Aust N Z J Obstet Gynaecol. 2013 Dec;53(6):532-9. doi: 10.1111/ajo.12126. Epub 2013 Aug 6.
Mosimann B, Pfiffner C, Amylidi-Mohr S, Risch L, Surbek D, Raio L. First trimester combined screening for preeclampsia and small for gestational age - a single centre experience and validation of the FMF screening algorithm. Swiss Med Wkly. 2017 Aug 25;147:w14498. doi: 10.4414/smw.2017.14498. eCollection 2017.
O'Gorman N, Wright D, Poon LC, Rolnik DL, Syngelaki A, Wright A, Akolekar R, Cicero S, Janga D, Jani J, Molina FS, de Paco Matallana C, Papantoniou N, Persico N, Plasencia W, Singh M, Nicolaides KH. Accuracy of competing-risks model in screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation. Ultrasound Obstet Gynecol. 2017 Jun;49(6):751-755. doi: 10.1002/uog.17399. Epub 2017 May 14.
Ananth CV, Keyes KM, Wapner RJ. Pre-eclampsia rates in the United States, 1980-2010: age-period-cohort analysis. BMJ. 2013 Nov 7;347:f6564. doi: 10.1136/bmj.f6564.
Ronzoni S, Rashid S, Santoro A, Mei-Dan E, Barrett J, Okun N, Huang T. Preterm preeclampsia screening and prevention: a comprehensive approach to implementation in a real-world setting. BMC Pregnancy Childbirth. 2025 Jan 15;25(1):32. doi: 10.1186/s12884-025-07154-6.
Other Identifiers
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PEprotocol
Identifier Type: -
Identifier Source: org_study_id
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