First 12 patients with coronavirus disease 2019 (COVID-19) in the United States

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Abstract

Introduction

More than 93,000 cases of coronavirus disease (COVID-19) have been reported worldwide. We describe the epidemiology, clinical course, and virologic characteristics of the first 12 U.S. patients with COVID-19.

Methods

We collected demographic, exposure, and clinical information from 12 patients confirmed by CDC during January 20–February 5, 2020 to have COVID-19. Respiratory, stool, serum, and urine specimens were submitted for SARS-CoV-2 rRT-PCR testing, virus culture, and whole genome sequencing.

Results

Among the 12 patients, median age was 53 years (range: 21–68); 8 were male, 10 had traveled to China, and two were contacts of patients in this series. Commonly reported signs and symptoms at illness onset were fever (n=7) and cough (n=8). Seven patients were hospitalized with radiographic evidence of pneumonia and demonstrated clinical or laboratory signs of worsening during the second week of illness. Three were treated with the investigational antiviral remdesivir. All patients had SARS-CoV-2 RNA detected in respiratory specimens, typically for 2–3 weeks after illness onset, with lowest rRT-PCR Ct values often detected in the first week. SARS-CoV-2 RNA was detected after reported symptom resolution in seven patients. SARS-CoV-2 was cultured from respiratory specimens, and SARS-CoV-2 RNA was detected in stool from 7/10 patients.

Conclusions

In 12 patients with mild to moderately severe illness, SARS-CoV-2 RNA and viable virus were detected early, and prolonged RNA detection suggests the window for diagnosis is long. Hospitalized patients showed signs of worsening in the second week after illness onset.

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  1. SciScore for 10.1101/2020.03.09.20032896: (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
    Data were analyzed and visualized using Excel, SAS 9.4, R 3.6.2, and Python 3.7.3.10–13 Laboratory Methods: Specimens were evaluated using SARS-CoV-2 RNA detection, virus culture, whole genome sequencing, and phylogenetic analysis.
    Excel
    suggested: None
    Python
    suggested: (IPython, RRID:SCR_001658)

    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:
    Several limitations should be considered when interpreting our findings. Our sample of patients is small. Information collected from patient interviews may have been subject to response bias. The threshold for admitting patients and for monitoring in the hospital was likely lower than for other respiratory infections because of uncertainty about the clinical course of COVID-19. Dates of illness resolution may be imprecise due to non-specific lingering symptoms or symptoms from chronic or unrelated conditions. Clinical laboratory tests and radiographic studies were ordered as a part of routine patient care and were not collected systematically. SARS-CoV-2 RNA detection does not necessarily reflect the presence of infectious virus, and rRT-PCR Ct values may have varied due to specimen collection or handling. Specimen collection is ongoing to inform both clinical management and infection prevention and control practices, and findings will be updated as more information becomes available.

    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.
    • Thank you for including a protocol registration statement.

    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.