Evidence map›Paper›PMID 35414616›Full record

ArticleSaudi medical journal2022

COVID-19 in pregnant women: An evaluation of clinical symptoms and laboratory parameters based on the 3 trimesters.

Şeyhmus Tunç, Mehmet Rifat Göklü, Süleyman Cemil Oğlak

Open access · diamondAbstract read
In one paragraph

Article in Saudi medical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  4. Review
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  6. Observational
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

3 authors at 1 institution in 2 countries.

Şeyhmus TunçFrom the Department of Obstetrics and Gynecology, Health Sciences University, Gazi Yaşargil Training and Research Hospital, Diyarbakır, Turkey.
Mehmet Rifat GöklüFrom the Department of Obstetrics and Gynecology, Health Sciences University, Gazi Yaşargil Training and Research Hospital, Diyarbakır, Turkey.
Süleyman Cemil OğlakFrom the Department of Obstetrics and Gynecology, Health Sciences University, Gazi Yaşargil Training and Research Hospital, Diyarbakır, Turkey.
Sağlık Bilimleri Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the association between the hospitalization rates, symptoms, and laboratory parameters of pregnant women diagnosed with coronavirus disease 2019 (COVID-19) and the gestational week, and determine their symptoms or laboratory parameters predictive of the need for possible admission in the intensive care unit (ICU).

methodsWe retrospectively analyzed the symptoms, laboratory parameters, and treatment modalities of 175 pregnant women with COVID-19 who were admitted to a tertiary referral hospital between March 2020 and March 2021 and investigated their association with pregnancy trimesters.

resultsThe COVID-19-related hospitalization rates in the first trimester was 24.1%, second trimesters was 36%, and third trimester was 57.3%. Cough and shortness of breath were significantly higher in the pregnant women in their third trimester than those in the first 2 trimesters (

conclusionThe presence of respiratory symptoms and the need for hospitalization increased significantly with later trimesters in pregnant women with COVID-19. The presence of shortness of breath or high CRP level at the time of admission could predict the need for ICU admission.

Indexed as

COVID-19Pregnancy Complications, InfectiousDyspneaFemaleHumansPregnancyPregnancy TrimestersPregnant PeopleRetrospective StudiesSARS-CoV-2COVID-19pregnancypregnancy trimesters

Identifiers

PMID35414616
PMCPMC9998050
OpenAlexW4223428308

What OpenQuestion holds

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LicenceCC BY
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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.