Evidence mapPaperPMID 34398644Full record

ArticleJournal of the American Heart Association2021

Preeclampsia Across Pregnancies and Associated Risk Factors: Findings From a High-Risk US Birth Cohort.

S Michelle Ogunwole, George Mwinnyaa, Xiaobin Wang, Xiumei Hong, Janice Henderson, Wendy L Bennett

Open access · goldAbstract read
In one paragraph

Article in Journal of the American Heart Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

14 citing papers in PubMed, 18 citations in OpenAlex.

  1. ISUOG Consensus Statement on maternal hemodynamic assessment in hypertensive disorders of pregnancy and fetal growth restriction.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025
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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

6 authors at 1 institution in 1 country.

S Michelle OgunwoleDepartment of Medicine Division of General Internal MedicineJohns Hopkins University School of Medicine Baltimore MD.ORCID 0000-0001-9479-7695
George MwinnyaaDepartment of International HealthJohns Hopkins University Bloomberg School of Public Health Baltimore MD.ORCID 0000-0002-1924-6065
Xiaobin WangDepartment of PediatricsJohns Hopkins University School of Medicine Baltimore MD.ORCID 0000-0003-4451-302X
Xiumei HongCenter on the Early Life Origins of Disease Department of Population, Family and Reproductive Health Johns Hopkins University Bloomberg School of Public Health Baltimore MD.
Janice HendersonDepartment of Gynecology and Obstetrics Johns Hopkins University School of Medicine Baltimore MD.
Wendy L BennettDepartment of Medicine Division of General Internal MedicineJohns Hopkins University School of Medicine Baltimore MD.ORCID 0000-0001-9828-0706
Johns Hopkins University · US

Funding

Preterm Birth and Child Long-term Cardiometabolic Risk: Integrate Proteomics with Birth CohortR01HD041702 · JOHNS HOPKINS UNIVERSITY · 2001 to 2025
$1.9M
Maternal Exposure to Low Level Mercury, Metabolome, and Child Cardiometabolic Risk in Multi-Ethnic Prospective Birth CohortsR01ES031272 · NIEHS · JOHNS HOPKINS UNIVERSITY · PI XIAOBIN WANG, Guoying Wang · 2022 to 2024
$704k
NIAID NIH HHS R21 AI154233NICHD NIH HHS R01 HD041702NICHD NIH HHS R01 HD086013NICHD NIH HHS R01 HD098232NICHD NIH HHS R03 HD096136NIEHS NIH HHS R01 ES031272
6 · The paper itself

Abstract

Background Preeclampsia increases women's risks for maternal morbidity and future cardiovascular disease. The aim of this study was to identify opportunities for prevention by examining the association between cardiometabolic risk factors and preeclampsia across 2 pregnancies among women in a high-risk US birth cohort. Methods and Results Our sample included 618 women in the Boston Birth Cohort with index and subsequent pregnancy data collected using standard protocols. We conducted log-binomial univariate regression models to examine the association between preeclampsia in the subsequent pregnancy (defined as incident or recurrent preeclampsia) and cardiometabolic risk factors (ie, obesity, hypertension, diabetes mellitus, preterm birth, low birth weight, and gestational diabetes mellitus) diagnosed before and during the index pregnancy, and between index and subsequent pregnancies. At the subsequent pregnancy, 7% (36/540) had incident preeclampsia and 42% (33/78) had recurrent preeclampsia. Compared with women without obesity, women with obesity had greater risk of incident preeclampsia (unadjusted risk ratio [RR], 2.2 [95% CI, 1.1-4.5]) and recurrent preeclampsia (unadjusted RR, 3.1 [95% CI, 1.5-6.7]). Preindex pregnancy chronic hypertension and diabetes mellitus were associated with incident, but not recurrent, preeclampsia (hypertension unadjusted RR, 7.9 [95% CI, 4.1-15.3]; diabetes mellitus unadjusted RR, 5.2 [95% CI, 2.5-11.1]. Women with new interpregnancy hypertension versus those without had a higher risk of incident and recurrent preeclampsia (incident preeclampsia unadjusted RR, 6.1 [95% CI, 2.9-13]); recurrent preeclampsia unadjusted RR, 2.4 [95% CI, 1.5-3.9]). Conclusions In this diverse sample of high-risk US women, we identified modifiable and treatable risk factors, including obesity and hypertension for the prevention of preeclampsia.

Indexed as

Pre-EclampsiaPremature BirthBirth CohortDiabetes MellitusFemaleHumansHypertensionInfant, NewbornObesityPregnancyRisk FactorsUnited Stateshypertensionobesitypreeclampsia/pregnancypregnancy and postpartumpreventionwomen and minorities

Identifiers

PMID34398644
PMCPMC8649269
OpenAlexW3194775748

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.