CLINICAL PROPERTIES AND DIAGNOSTIC METHODS OF COVID-19 INFECTION IN PREGNANCIES: META-ANALYSIS

  1. Banu Uygun-Can
  2. Bilge Acar-Bolat

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Abstract

We aimed to summarize reliable medical evidence by the meta-analysis of all published retrospective studies that examined data based on the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by clinical symptoms, molecular (RT-PCR) diagnosis and characteristic CT imaging features in pregnant women. MEDLINE PubMed, SCOPUS, ISI Web of Science, Clinical Key, and CINAHL databases were used to select the studies. Then, 384 articles were received, including the studies until 01/MAY/2020. As a result of the full-text evaluation, 12 retrospective articles covering all the data related were selected. A total of 181 pregnant cases with SARS-CoV-2 infections were included in the meta-analysis within the scope of these articles. According to the results, the incidence of fever was 38.1% (95% CI: 14.2–65%), and cough was 22% (95% CI: 10.8–35.2%) among all clinical features of pregnant cases with SARS-CoV-2 infection. So, fever and cough are the most common symptoms in pregnant cases with SARS-CoV- infection, and 91.8% (95% CI: 76.7–99.9%) of RT-PCR results are positive. Moreover, abnormal CT incidence is 97.9% (95% CI: 94.2–99.9%) positive. No case was death. However, as this virus spreads globally, it should not be overlooked that the incidence will increase in pregnant women and may be in the risky group. RT-PCR and CT can be used together in an accurate and safe diagnosis. In conclusion, these findings will provide important guidance for current studies regarding the clinical features and correct detection of SARS-CoV-2 infection in pregnant women, as well as whether it will create emergency tables that will require the use of a viral drug.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.06.20123901: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sources of Information: MEDLINE PubMed, SCOPUS, Clinical Key Library, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and ISI Web of Science were searched using combined keywords: 2019- nCoV and/or pregnancy”, “COVID-19 and/or pregnancy” and “SARS-CoV-2 and/or pregnancy”. 2.2.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, this review also has some limitations. As of the current period, there are few studies for the content. Data from all countries are urgently needed on this issue. Thus, it would be more appropriate to include a large number of studies in a broad geographical scope in order to obtain a more comprehensive view of COVID-19 in pregnant women as a result. Since detailed patient information was not given in all studies, especially regarding clinical findings, this could not be included in the meta-analysis. In particular, there were negative results, although the case showed positive clinical signs, since CT contained radiation, and its use was not preferred or repeated. The data in this analysis allow for the first synthesis of the clinical, molecular, and CT diagnostic features of COVID-19. Also, it is not included in the meta-analysis results, since deaths were not reported in pregnant women in the studies conducted. In this study, the patients were diagnosed with SARS-CoV-2 infection. Therefore, asymptomatic cases are not emphasized. However, because the clinical symptoms are rare in the findings of our study, the prevalence may be higher among pregnant women. As there is a lack of data in newborns as part of the studies we have included, it could not be covered in this study. As a result, the importance of vertical transmission is not emphasized. Based on the limitations reported above, the results need to be supported by more extensive studies with larger sample size...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.06.20123901v1 on medRxiv
  3. Version published to 10.1155/2020/1708267