COVID-19 versus non-COVID-19 pneumonia: A retrospective cohort study in Chengdu, China

  1. Xiao-Jin Li
  2. Bing-Xing Shuai
  3. Zhong-Wei Zhang
  4. Yan Kang

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Abstract

Since the outbreak of coronavirus disease 2019 (COVID-19) in December 2019 in Wuhan, Hubei Province, China, it has spread throughout the world and become a global public health emergency. It is important to distinguish COVID-19 from other viral pneumonias to properly screen and diagnose patients, reduce nosocomial infections, and complement the inadequacy of nucleic acid testing. In this study, we retrospectively analysed the clinical data of COVID-19 versus non-COVID-19 patients treated at our hospital between January 17 and February 27, 2020 to summarize our clinical experience in the differential diagnosis of COVID-19.

Methods

In this retrospective cohort study, 23 confirmed COVID-19 patients were consecutively enrolled from January 17 to February 27, 2020, and 29 confirmed non-COVID-19 patients were enrolled in the West China Hospital of Sichuan University. We collected baseline data, epidemiological data, clinical characteristics, imaging findings, viral nucleic acid test results, and survival data. SPSS v22.0 was used for the statistical analysis. Outcomes were followed-up until March 25.

Results

A total of 52 patients were included in this study, including 23 COVID-19 patients and 29 non-COVID-19 patients. No significant between-group differences were observed for age, sex, primary signs or symptoms, cellular immunity, or platelet count. Significant between-group differences were observed in clinical characteristics such as dry cough, contact with individuals from Wuhan, some underlying diseases, nucleated cell count, chest imaging findings, viral nucleic acid test results, 28-day mortality, and 28-day survival.

Conclusion

Epidemiological data, clinical symptoms, nucleic acid test results for COVID-19 and chest CT manifestation may help distinguish COVID-19 from non-COVID-19 cases, prevent imported cases and nosocomial infections.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.28.20082784: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics review: This retrospective study was approved by the Ethics Committee of the West China Hospital, Sichuan University, on February 10, 2020 (EC Number: 2019 No. 130).
    RandomizationFirst, this was a retrospective study with a short observation time, so the level of evidence was lower than that of prospective randomized controlled trials.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The statistical tool used was SPSS 22.0 (SPSS Science Inc., Chicago, IL, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2020.04.28.20082784 on medRxiv