Epidemiological and Clinical Characteristics of 17 Hospitalized Patients with 2019 Novel Coronavirus Infections Outside Wuhan, China

  1. Jie Li
  2. Shilin Li
  3. Yurui Cai
  4. Qin Liu
  5. Xue Li
  6. Zhaoping Zeng
  7. Yanpeng Chu
  8. Fangcheng Zhu
  9. Fanxin Zeng

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Abstract

An increasing number of cases of novel coronavirus pneumonia (NCP) infected with 2019-nCoV have been identified in Wuhan and other cities in China, since December 2019. We analyzed data on the 17 confirmed cases in Dazhou to provide the epidemiologic characteristics of NCP outside Wuhan. Among them, 12 patients were still quarantined in the hospital, 5 patients were discharged NCP patients according to the national standards. Compared with non-discharged NCP patients, the discharged NCP patients had younger ages. Moreover, discharged NCP patients had higher heart rate, lymphocytes levels and monocytes levels than non-discharged NCP patients on admission to the hospital. Notably, all of 17 patients had abnormal increased C-reactive protein levels, and 16 patients had abnormal computed tomography images. This study provided some information that younger age, higher lymphocytes levels and monocytes levels at the diagnoses of 2019-nCoV may contributed to faster recovery and better therapeutic outcome.

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    SciScore for 10.1101/2020.02.11.20022053: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the ethics committee of the Dazhou Central Hospital with written informed consent from the patients (IRB00000001-20001).
    Consent: The study was approved by the ethics committee of the Dazhou Central Hospital with written informed consent from the patients (IRB00000001-20001).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were performed using SPSS version 20.0 (IBM, Armonk, NY, 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 10.1101/2020.02.11.20022053v1 on medRxiv