Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 363

The DOI matches its Crossref record; 170 of the 170 references it cites were found in a registry or an index.

First trimester preeclampsia screening and prediction

Chaemsaithong, Piya, Sahota, Daljit Singh, Poon, Liona C.·2022·American Journal of Obstetrics and Gynecology

Abstract

Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. Early onset disease requiring preterm delivery is associated with a higher risk of complications in both mothers and babies. Evidence suggests that the administration of low dose aspirin initiated prior to 16 weeks' gestation significantly reduces the rate of preterm preeclampsia. Therefore, it is important to identify pregnant women at risk of developing preeclampsia during the first trimester of pregnancy, thus allowing timely therapeutic intervention. Several professional organizations such as American College of Obstetricians and Gynecologists (ACOG) and National Institute for Health and Care Excellence (NICE) have proposed screening for preeclampsia based on maternal risk factors. The approach recommended by the ACOG and NICE essentially treats each risk factor as a separate screening test with additive detection rate and screen positive rate. Evidence has shown that preeclampsia screening based on the NICE and ACOG approach has suboptimal performance as the NICE recommendation only achieves detection rates of 41% and 34%, at 10% false positive rate, for preterm and term preeclampsia, respectively. Screening based on the ACOG (2013) recommendation can only achieve detection rates of 5% and 2% for preterm and term preeclampsia, respectively, at 0.2% false positive rate. Various first trimester prediction models have been developed. Most of them have not undergone or failed external validation. However, it is worthy of note that the Fetal Medicine Foundation (FMF) first trimester prediction model (namely "the triple test"), which consists of a combination of maternal factors, and measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has undergone successful internal and external validation. The FMF triple test has detection rates of 90% and 75% for the prediction of early and preterm preeclampsia, respectively, at 10% false positive rate. Such performance of screening is superior to that of the traditional method by maternal risk factors alone. The use of the FMF prediction model, followed by the administration of low dose aspirin, has been shown to reduce the rate of preterm preeclampsia by 62%. Number needed to screen to prevent one case of preterm preeclampsia by the FMF triple test is 250. The key to maintain optimal screening performance is to establish standardized protocols for biomarker measurements and regular biomarker quality assessment as inaccurate measurement can affect screening performance. Tools frequently used to assess quality control include the cumulative sums and target plot. Cumulative sums is a sensitive method to detect small shifts over time and point of shift can be easily identified. Target plot is a tool to evaluate deviation from expected multiple of median and expected median of standard deviation. Target plot is easy to interpret and visualize. However, it is insensitive to detect small deviation. Adherence to well-defined protocols for the measurements of mean arterial pressure, uterine artery pulsatility index and placental growth factor is required. This article summarizes the existing literature on the different methods, recommendations by professional organizations, quality assessment of different components of risk assessment and clinical implementation of the first trimester screening for preeclampsia.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.ajog.2020.07.020

Cites

170 of 170 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 170 references

Cited by

See all 363

Metadata

Authors
Chaemsaithong, P., Sahota, D. S., & Poon, L. C.
Venue
American Journal of Obstetrics and Gynecology
Publisher
Elsevier BV
Published
2022-02
Volume
226
Issue
2
Pages
S1071-S1097.e2
ISSN
0002-9378 (ISSN-L)
OpenAlex
W3042661563
Cited by
363
References
170
FWCI
20.27
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: First trimester preeclampsia screening and prediction. https://app.cochat.ai/papers/10.1016/j.ajog.2020.07.020
The paper
Chaemsaithong, P., Sahota, D. S., & Poon, L. C. (2022). First trimester preeclampsia screening and prediction. American Journal of Obstetrics and Gynecology. https://doi.org/10.1016/j.ajog.2020.07.020

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.