Evidence map›Paper›PMID 35268548›Full record

ArticleJournal of clinical medicine2022

Adverse Pregnancy Outcomes and Maternal Chronic Diseases in the Future: A Cross-Sectional Study Using KoGES-HEXA Data.

Geum Joon Cho, Jiae Kim, Ji Young Kim, Sung Won Han, Soo Bin Lee, Min-Jeong Oh, Sa Jin Kim, Jae Eun Shin

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% 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, 5 citations in OpenAlex.

  1. Article
  2. Article
  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

8 authors at 2 institutions in 1 country.

Geum Joon ChoDepartment of Obstetrics and Gynecology, College of Medicine, Korea University, Seoul 02841, Korea.
Jiae KimDepartment of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Ji Young KimDepartment of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Sung Won HanSchool of Industrial Management Engineering, Korea University, Seoul 02841, Korea.
Soo Bin LeeSchool of Industrial Management Engineering, Korea University, Seoul 02841, Korea.
Min-Jeong OhDepartment of Obstetrics and Gynecology, College of Medicine, Korea University, Seoul 02841, Korea.
Sa Jin KimDepartment of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Jae Eun ShinDepartment of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.ORCID 0000-0002-8326-8541
Catholic University of Korea · KRKorea University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adverse pregnancy outcomes (APOs) are associated with an increased risk of chronic diseases, including cardiovascular disease (CVD) and metabolic syndrome (MS), in the future. We designed a large-scale cohort study to evaluate the influence of APOs (preeclampsia, gestational diabetes mellitus (GDM), stillbirth, macrosomia, and low birth weight) on the incidence of chronic diseases, body measurements, and serum biochemistry in the future and investigate whether combinations of APOs had additive effects on chronic diseases. We used health examinee data from the Korean Genome and Epidemiology Study (KoGES-HEXA) and extracted data of parous women (

Indexed as

cardiovascular diseasegestational diabetes mellituslow birth weightmacrosomiametabolic syndromepreeclampsia

Identifiers

PMID35268548
PMCPMC8911450
OpenAlexW4220839575

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.