Clinical Characteristics of Coronavirus Disease 2019 (COVID-19): An Updated Systematic Review

  1. Zhangfu Fang
  2. Fang Yi
  3. Kang Wu
  4. Kefang Lai
  5. Xizhuo Sun
  6. Nanshan Zhong
  7. Zhigang Liu

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Abstract

OBJECTIVE

Clinical characteristics of novel coronavirus disease (COVID-19) have been described in numerous studies but yielded varying results. We aimed to conduct a systematic review on scientific literatures and to synthesize critical data on clinical traits of COVID-19 from its initial outbreak to pandemic.

METHODS

Systematic searches were conducted to identify retrospective observational study that contained clinical characteristics on COVID-19 through multiple databases. Two reviewers independently evaluated eligible publications. Data on clinical characteristics of COVID-19 were extracted and analyzed.

RESULTS

Seventy-two retrospective studies demonstrating the clinical characteristics of COVID-19 were included. A total of 3470 COVID-19 patients were synthesized to the final analysis in an unbiased manner. The most common symptom was fever (2878 [83.0%]), and 63.4% of the patients presented fever as onset symptom. There were 2528 [88.2%] of 2866 cases had abnormal lung findings on chest CT scan. Laboratory findings showed that 1498 [62.8%] of 2387 cases had lymphopenia, and 1354 [64.8%] of 2091 cases had an increased level of C-reactive protein (CRP). A total of 185 [11.5%] patients were admitted to intensive care unit (ICU) while the overall case fatality rate (CFR) was 3.7%. Compared to patients admitted outside of Hubei, China, those from Hubei had a significant higher ICU admission rate (21.9% vs. 2.5%, p <0.001). Also, CFR attributed to COVID-19 was significantly higher in Hubei than that of non-Hubei admissions (10.4% vs. 0.6%, p <0.001).

INTERPRETATION

This large patient-based systematic review presents a more precise profiling of the COVID-19 from its outbreak to current pandemic. Dynamic evolvements of COVID-19 are needed to be characterized in future studies.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.07.20032573: (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
    Identification of Documents on COVID-9: Systematic searches were performed via the Medline database (PubMed) and Embase combining the terms (novel coronavirus OR 2019 novel coronavirus OR 2019-nCoV OR Coronavirus disease 2019 OR COVID-19 OR SARS-CoV-2).
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    Statistical analyses were conducted using SPSS version 18 (IBM SPSS Statistics, IBM Corporation).
    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: We detected the following sentences addressing limitations in the study:
    This systematic review has some limitations. First, due to the retrospective nature of selected literatures, not all clinical characteristics have been well documented. This have resulted in an inconsistence of the total numbers of each item being calculated. Second, some of the selected patients may not have discharged before the studies were finalized. This might have affected the clinical outcomes of COVID-19 to some extents. Third, since the disease is still ongoing, newly published data on COVID-19 might not be included at the time of manuscript submission. Nevertheless, we have summarized the largest number of patients demonstrating the clinical characteristics of COVID-19 in the present study. Finally, we could not determine the incubation periods of COVID-19 due to heterogeneity across studies in reporting the timeline of cases. In summary, COVID-19 represents an emerging acute respiratory infection with various clinical presentations that share similarities as well as discrepancies with SARS and MERS. Combining clinical presentations with radiographic findings as well as blood tests may add value in early diagnosis and managements. Dynamic changes of clinical features in the course of COVID-19 are needed to be characterized in future studies. Since specific treatments are not available at the moment, urgent efforts should be taken to explore for this emerging disease.

    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 10.1101/2020.03.07.20032573v2 on medRxiv
  3. Version published to 10.1101/2020.03.07.20032573v1 on medRxiv