Cargando…

Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population

BACKGROUND: To evaluate the performance of the Fetal Medicine Foundation (FMF) preterm preeclampsia (PE) screening algorithm in an indigenous South Asian population. METHODS: This was a prospective observational cohort study conducted in a tertiary maternal fetal unit in Delhi, India over 2 years. T...

Descripción completa

Detalles Bibliográficos
Autores principales: Prasad, Smriti, Sahota, Daljit Singh, Vanamail, P., Sharma, Akshatha, Arora, Saloni, Kaul, Anita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642869/
https://www.ncbi.nlm.nih.gov/pubmed/34863125
http://dx.doi.org/10.1186/s12884-021-04283-6
_version_ 1784609761499545600
author Prasad, Smriti
Sahota, Daljit Singh
Vanamail, P.
Sharma, Akshatha
Arora, Saloni
Kaul, Anita
author_facet Prasad, Smriti
Sahota, Daljit Singh
Vanamail, P.
Sharma, Akshatha
Arora, Saloni
Kaul, Anita
author_sort Prasad, Smriti
collection PubMed
description BACKGROUND: To evaluate the performance of the Fetal Medicine Foundation (FMF) preterm preeclampsia (PE) screening algorithm in an indigenous South Asian population. METHODS: This was a prospective observational cohort study conducted in a tertiary maternal fetal unit in Delhi, India over 2 years. The study population comprised of 1863 women carrying a singleton pregnancy and of South Asian ethnicity who were screened for preterm pre-eclampsia (PE) between 11 and 14 weeks of gestation using Mean Arterial Pressure (MAP), transvaginal Mean Uterine Artery Pulsatility Index (UtAPI) and biochemical markers - Pregnancy Associated Plasma Protein-A (PAPP-A) and Placental Growth Factor.. Absolutemeasurements of noted biomarkers were converted to multiples of the expected gestational median (MoMS) which were then used to estimate risk for preterm PE < 37 weeks using Astraia software. Women with preterm PE risk of ≥1:100 was classified as as high risk. Detection rates (DR) at 10% false positive rate were calculated after adjusting for prophylactic aspirin use (either 75 or 150 mg). RESULTS: The incidence of PE and preterm PE were 3.17% (59/1863) and 1.34% (25/1863) respectively. PAPP-A and PlGF MoM distribution medians were 0.86 and 0.87 MoM and significantly deviated from 1 MoM. 431 (23.1%) women had a risk of ≥1:100, 75 (17.8%) of who received aspirin. Unadjusted DR using ≥1:100 threshold was 76%.Estimated DRs for a fixed 10% FPR ranged from 52.5 to 80% depending on biomarker combination after recentering MoMs and adjusting for aspirin use. CONCLUSION: The FMF algorithm whilst performing satisfactorily could still be further improved to ensure that biophysical and biochemical markers are correctly adjusted for indigenous South Asian women.
format Online
Article
Text
id pubmed-8642869
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-86428692021-12-06 Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population Prasad, Smriti Sahota, Daljit Singh Vanamail, P. Sharma, Akshatha Arora, Saloni Kaul, Anita BMC Pregnancy Childbirth Research BACKGROUND: To evaluate the performance of the Fetal Medicine Foundation (FMF) preterm preeclampsia (PE) screening algorithm in an indigenous South Asian population. METHODS: This was a prospective observational cohort study conducted in a tertiary maternal fetal unit in Delhi, India over 2 years. The study population comprised of 1863 women carrying a singleton pregnancy and of South Asian ethnicity who were screened for preterm pre-eclampsia (PE) between 11 and 14 weeks of gestation using Mean Arterial Pressure (MAP), transvaginal Mean Uterine Artery Pulsatility Index (UtAPI) and biochemical markers - Pregnancy Associated Plasma Protein-A (PAPP-A) and Placental Growth Factor.. Absolutemeasurements of noted biomarkers were converted to multiples of the expected gestational median (MoMS) which were then used to estimate risk for preterm PE < 37 weeks using Astraia software. Women with preterm PE risk of ≥1:100 was classified as as high risk. Detection rates (DR) at 10% false positive rate were calculated after adjusting for prophylactic aspirin use (either 75 or 150 mg). RESULTS: The incidence of PE and preterm PE were 3.17% (59/1863) and 1.34% (25/1863) respectively. PAPP-A and PlGF MoM distribution medians were 0.86 and 0.87 MoM and significantly deviated from 1 MoM. 431 (23.1%) women had a risk of ≥1:100, 75 (17.8%) of who received aspirin. Unadjusted DR using ≥1:100 threshold was 76%.Estimated DRs for a fixed 10% FPR ranged from 52.5 to 80% depending on biomarker combination after recentering MoMs and adjusting for aspirin use. CONCLUSION: The FMF algorithm whilst performing satisfactorily could still be further improved to ensure that biophysical and biochemical markers are correctly adjusted for indigenous South Asian women. BioMed Central 2021-12-04 /pmc/articles/PMC8642869/ /pubmed/34863125 http://dx.doi.org/10.1186/s12884-021-04283-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Prasad, Smriti
Sahota, Daljit Singh
Vanamail, P.
Sharma, Akshatha
Arora, Saloni
Kaul, Anita
Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title_full Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title_fullStr Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title_full_unstemmed Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title_short Performance of Fetal Medicine Foundation algorithm for first trimester preeclampsia screening in an indigenous south Asian population
title_sort performance of fetal medicine foundation algorithm for first trimester preeclampsia screening in an indigenous south asian population
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642869/
https://www.ncbi.nlm.nih.gov/pubmed/34863125
http://dx.doi.org/10.1186/s12884-021-04283-6
work_keys_str_mv AT prasadsmriti performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation
AT sahotadaljitsingh performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation
AT vanamailp performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation
AT sharmaakshatha performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation
AT arorasaloni performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation
AT kaulanita performanceoffetalmedicinefoundationalgorithmforfirsttrimesterpreeclampsiascreeninginanindigenoussouthasianpopulation