Evidence map›Paper›PMID 32225087›Full record

ArticleDiagnostics (Basel, Switzerland)2020

Diagnostic Performance of First Trimester Screening of Preeclampsia Based on Uterine Artery Pulsatility Index and Maternal Risk Factors in Routine Clinical Use.

Max Mönckeberg, Valentina Arias, Rosario Fuenzalida, Santiago Álvarez, Victoria Toro, Andrés Calvo, Juan P Kusanovic, Lara J Monteiro, Manuel Schepeler, Jyh K Nien and 2 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Max MönckebergDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Valentina AriasFaculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Rosario FuenzalidaFaculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Santiago ÁlvarezFaculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Victoria ToroFaculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Andrés CalvoFaculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Juan P KusanovicCenter for Research and Innovation in Maternal-Fetal Medicine (CIMAF), Hospital Sótero del Río, Santiago 8207257, Chile.
Lara J MonteiroCentre for Biomedical Research, Laboratory of Reproductive Biology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.ORCID 0000-0003-2078-380X
Manuel SchepelerDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Jyh K NienDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Jaime MartinezDepartment of Obstetrics and Gynecology, Clínica Dávila, Santiago 8420384, Chile.
Sebastián E IllanesDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Universidad de Los Andes, Chile · CLClínica Dávila · CLPontificia Universidad Católica de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preeclampsia is a pregnancy-specific disorder defined by new onset of hypertension and proteinuria after 20 weeks of gestation. The early detection of patients at risk of developing preeclampsia is crucial, however, predictive models are still controversial. We aim to evaluate the diagnostic performance of a predictive algorithm in the first trimester of pregnancy, in order to identify patients that will subsequently develop preeclampsia, and to study the effect of aspirin on reducing the rate of this complication in patients classified as high risk by this algorithm. A retrospective cohort including 1132 patients attending prenatal care at Clínica Dávila in Santiago, Chile, was conceived. The risk of developing preeclampsia (early and late onset) was calculated using algorithms previously described by Plasencia et al. Patients classified as high risk, in the first trimester of pregnancy, by these algorithms, were candidates to receive 100 mg/daily aspirin as prophylaxis at the discretion of the attending physician. The overall incidence of preeclampsia in this cohort was 3.5% (40/1132), and the model for early onset preeclampsia prediction detected 33% of patients with early onset preeclampsia. Among the 105 patients considered at high risk of developing preeclampsia, 56 received aspirin and 49 patients did not. Among those who received aspirin, 12% (7/56) developed preeclampsia, which is equal to the rate of preeclampsia (12% (6/49)) of those who did not receive this medication. Therefore, the diagnostic performance of an algorithm combining uterine artery Doppler and maternal factors in the first trimester predicted only one third of patients that developed preeclampsia. Among those considered at high risk for developing the disease using this algorithm, aspirin did not change the incidence of preeclampsia, however, this could be due either to the small study sample size or the type of the study, a retrospective, non-interventional cohort study.

Indexed as

aspirinearly predictiongestational hypertensionpredictive algorithmpreeclampsiaprenatal careroutine careultrasounduterine artery Doppler

Identifiers

PMID32225087
PMCPMC7235780
OpenAlexW3013183482

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.