Epidemiological and clinical features of 2019-nCoV acute respiratory disease cases in Chongqing municipality, China: a retrospective, descriptive, multiple-center study

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Abstract

Background

In January 19, 2020, first case of 2019 novel coronavirus (2019-nCoV) pneumonia (COVID-19) was confirmed in Chongqing municipality, China.

Methods

In this retrospective, descriptive, multiple-center study, total of 267 patients with COVID-19 confirmed by real-time RT-PCR in Chongqing from Jan 19 to Feb 16, 2020 were recruited. Epidemiological, demographic, clinical, radiological characteristics, laboratory examinations, and treatment regimens were collected on admission. Clinical outcomes were followed up until Feb 16, 2020.

Results

267 laboratory-confirmed COVID-19 patients admitted to 3 designated-hospitals in Chongqing provincial municipality from January 19 to February 16, 2020 were enrolled and categorized on admission. 217 (81.27%) and 50 (18.73%) patients were categorized into non-severe and severe subgroups, respectively. The median age of patients was 48.0 years (IQR, 35.0-65.0), with 129 (48.3%) of the patients were more than 50 years of age. 149 (55.8%) patients were men. Severe patients were significantly older (median age, 71.5 years [IQR, 65.8-77.0] vs 43.0 years [IQR, 32.5-57.0]) and more likely to be male (110 [50.7%] vs 39 [78.0%]) and have coexisting disorders (15 [30.0%] vs 26 [12.0%]). 41 (15.4%) patients had a recent travel to Hubei province, and 139 (52.1%) patients had a history of contact with patients from Hubei. On admission, the most common symptoms of COVID-19 were fever 225(84.3%), fatigue (208 [77.9%]), dry cough (189 [70.8%]), myalgia or arthralgia (136 [50.9%]). Severe patients were more likely to present dyspnea (17 [34.0%] vs 26 [12.0%]) and confusion (10 [20.0%] vs 15 [6.9%]). Rales (32 [12.0%]) and wheezes (20 [7.5%]) are not common noted for COVID-19 patients, especially for the non-severe (11 [5.1%], 10 [4.6%]). 118 (44.2%). Most severe patients demonstrated more laboratory abnormalities. 231 (86.5%), 61 (22.8%) patients had lymphopenia, leukopenia and thrombocytopenia, respectively. CD4 + T cell counts decrease was observed in 77.1 % of cases, especially in the severe patients (45, 100%). 53.1% patients had decreased CD + 3 T cell counts, count of CD8 + T cells was lower than the normal range in part of patients (34.4%). More severe patients had lower level of CD4 + T cells and CD + 3 T cells (45 [100.0%] vs 29[56.9%], 31 [68.9%] vs 20 [39.2%]). Most patients had normal level of IL-2, IL-4, TNF-α and INF-γ, while high level of IL-6 and IL-17A was common in COVID-19 patients (47 [70.1%], 35 [52.2%]). Level of IL-6, IL-17A and TNF-α was remarkably elevated in severe patients (32 [84.2%] vs 15 [51.7%], 25 [65.8%] vs 10 [34.5%], 17 [44.7%] vs 5 [17.2%]). All patients received antiviral therapy (267, 100%). A portion of severe patients (38, 76.0%) received systemic corticosteroid therapy. Invasive mechanical ventilation in prone position, non-invasive mechanical ventilation, high-flow nasal cannula oxygen therapy was adopted only in severe patients with respiratory failure (5[10.0%], 35[70.0%], 12[24.0%]). Traditional Chinese medicine was adopted to most of severe patients (43,86.0%).

Conclusion

Our study firstly demonstrated the regional disparity of COVID-19 in Chongqing municipality and further thoroughly compared the differences between severe and non-severe patients. The 28-day mortality of COVID-19 patients from 3 designed hospitals of Chongqing is 1.5%, lower than that of Hubei province and mainland China including Hubei province. However, the 28-mortality of severe patients was relatively high, with much higher when complications occurred. Notably, the 28-mortality of critically severe patients complicated with severe ARDS is considerably as high as 44.4%. Therefore, early diagnosis and intensive care of critically severe COVID-19 cases, especially those combined with ARDS, will be considerably essential to reduce mortality.

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  1. SciScore for 10.1101/2020.03.01.20029397: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Informed consent was yielded due to the anonymous analysis of clinical data in retrospective study.
    IRB: This research was approved by the institutional ethics board of the Second Affiliated Hospital of Chongqing Medical University (No.2020-09), Chongqing public health medical center (No.2020-015-01-KY), Chongqing three gorges central hospital (No.2020-13) and Qianjiang central hospital of Chongqing (No.2020-07).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analyses were performed using GraphPad Prism 7.0 software and SPSS 19.0 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    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.