Evidence map›Paper›PMID 32013922›Full record

ArticleBMC pregnancy and childbirth2020

Women with a predisposition for diabetes have an increased risk of pregnancy complications, especially in combination with pregestational overweight.

Ulrika Moll, Håkan Olsson, Mona Landin-Olsson

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Ulrika MollDepartment of Endocrinology, Lasarettsgatan 15, Skane University Hospital, S-221 85, Lund, Sweden. ulrika.moll@med.lu.se.ORCID http://orcid.org/0000-0002-7038-9475
Håkan OlssonDepartment of Clinical Sciences, Lund University, Lund, Sweden.
Mona Landin-OlssonDepartment of Endocrinology, Lasarettsgatan 15, Skane University Hospital, S-221 85, Lund, Sweden.
Lund University · SE

Funding

Cancerfonden .Region Skåne .Skånes universitetssjukhus .
6 · The paper itself

Abstract

backgroundOverweight and gestational diabetes are risk factors for pregnancy complications. We hypothesized that the metabolic impact of overweight on pregnancy outcome, would be different if it was combined with a predisposition for diabetes. The aim of this study was to compare the outcome of pregnancies in women with diabetes diagnosed later in life, to the outcome of pregnancies of women who did not develop diabetes.

methodsWomen in a population-based cohort who also were registered in the Swedish Medical Birth Registry (n = 4738) were included. A predisposition for diabetes (GDM or diabetes after pregnancy) was found in 455 pregnancies. The number of pregnancies with maternal BMI ≥ 25 kg/m

resultsPregnancies with normal maternal BMI ≤25 kg/m

conclusionsIn pregnancy, there is an increased frequency of LGA, macrosomia and caesarean section if the woman has a predisposition for diabetes. The frequency of overweight young women is increasing, and it is urgent to identify pregnant women with a predisposition to diabetes. How to distinguish the women with the highest risk for adverse pregnancy outcome and the highest risk of future disease, remains to be studied.

Indexed as

Diabetes ComplicationsAdultAgedDiabetes, GestationalDisease SusceptibilityFemaleHumansMiddle AgedOverweightPregnancyPregnancy ComplicationsPregnancy OutcomeRegistriesRetrospective StudiesRisk FactorsSwedenCaesarean sectionGestational diabetesMacrosomiaOverweightPregnancy outcome

Identifiers

PMID32013922
PMCPMC6998083
OpenAlexW3007635736

What OpenQuestion holds

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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.