<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.145713.3</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>The top 50 most-cited articles about COVID-19 and the complications of COVID-19: A bibliometric analysis</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 3; peer review: 2 approved, 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Singh</surname>
                        <given-names>Tanya</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Rao Padubidri</surname>
                        <given-names>Jagadish</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Shetty</surname>
                        <given-names>Pavanchand H.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Antony Manoj</surname>
                        <given-names>Matthew</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-7386-0384</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Mary</surname>
                        <given-names>Therese</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Thejaswi Pallempati</surname>
                        <given-names>Bhanu</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-1932-0082</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, India</aff>
                <aff id="a2">
                    <label>2</label>Department of Forensic Medicine and Toxicology, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, India</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:ppjrao@gmail.com">ppjrao@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>3</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>105</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>30</day>
                    <month>4</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Singh T et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-105/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The focus is primarily on 2020 publications (96%), with all articles being open access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26-65 years (63.2%). Complications of COVID-19 affected 13.9% of patients, with a recovery rate of 57.8%.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19</kwd>
                <kwd>Complications</kwd>
                <kwd>Bibliometry Analysis</kwd>
                <kwd>Citations</kwd>
                <kwd>SARS-COV-2</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 2</title>
                <p>In Version 2 of this article, we have expanded our discussion on the treatments available for COVID-19, particularly focusing on antivirals and steroids.&#x00a0;Additionally, this revised version delves into the pathology behind the most common complications of COVID-19. The article's conclusion has been restructured to better highlight the complications of COVID-19.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>In December 2019, the first outbreak of Coronavirus disease (COVID-19) was detected in Wuhan.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> On 30
                <sup>th</sup> January 2020, the World Health Organization (WHO) declared COVID-19 outbreak as a &#x201c;public health emergency of international concern&#x201d; and on 11
                <sup>th</sup> March 2020, COVID-19 was declared a pandemic by the WHO.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> As of September 2023, the coronavirus SARS-COV-2 (severe acute respiratory syndrome coronavirus-2) is responsible for a total of 770 million confirmed cases and 6.9 million confirmed deaths. With the start of COVID-19 vaccination, a total of 3 billion vaccine doses have been administered as per WHO.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> While, SARS-COV-2 is primarily considered as a respiratory disease known to cause pneumonia and acute respiratory distress syndrome (ARDS), there have been numerous reports about its many extra pulmonary manifestations. Literature suggests that the cardiovascular, gastrointestinal, renal, haematological, neurologic, endocrinologic, ophthalmologic, hepatobiliary and dermatologic systems can all be affected.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> This can result either due to the extrapulmonary dissemination and replication of the SARS-COV-2 or due to the widespread immunopathological sequelae of the disease.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>Bibliometric analysis is the application of statistical methods to evaluate the impact of a manuscript, research performance, author contribution to a particular field and to quantitatively analyse the most influential articles related to a particular field.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>According to our literature search, no current bibliometric analysis has focused on COVID-19 complications. The purpose of this bibliometric analysis was to compile and analyse the top 50 most-cited articles regarding COVID-19 complications across all peer-reviewed scientific journals.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <p>A bibliometric analysis of the most cited articles about COVID-19 complications was conducted in July 2021 using all journals indexed in Elsevier&#x2019;s Scopus and Thomas Reuter&#x2019;s Web of Science from November 1, 2019 to July 1, 2021. All journals were selected for inclusion regardless of country of origin, language, medical speciality, or electronic availability of articles or abstracts. The terms were combined as follows:</p>
            <p>(&#x201c;COVID-19&#x201d; OR &#x201c;COVID19&#x201d; OR &#x201c;SARS-COV-2&#x201d; OR &#x201c;SARSCOV2&#x201d; OR &#x201c;SARS 2&#x201d; OR &#x201c;Novel coronavirus&#x201d; OR &#x201c;2019-nCov&#x201d; OR &#x201c;Coronavirus&#x201d;)</p>
            <p>AND</p>
            <p>(&#x201c;Complication&#x201d; OR &#x201c;Long Term Complication&#x201d; OR &#x201c;Post-Intensive Care Syndrome&#x201d; OR &#x201c;Venous Thromboembolism&#x201d; OR &#x201c;Acute Kidney Injury&#x201d; OR &#x201c;Acute Liver Injury&#x201d; OR &#x201c;Post COVID-19 Syndrome&#x201d; OR &#x201c;Acute Cardiac Injury&#x201d; OR &#x201c;Cardiac Arrest&#x201d; OR &#x201c;Stroke&#x201d; OR &#x201c;Embolism&#x201d; OR &#x201c;Septic Shock&#x201d; OR &#x201c;Disseminated Intravascular Coagulation&#x201d; OR &#x201c;Secondary Infection&#x201d; OR &#x201c;Blood Clots&#x201d; OR &#x201c;Cytokine Release Syndrome&#x201d; OR &#x201c;Paediatric Inflammatory Multisystem Syndrome&#x201d; OR &#x201c;Vaccine Induced Thrombosis with Thrombocytopenia Syndrome&#x201d; OR &#x201c;Aspergillosis&#x201d; OR &#x201c;Mucormycosis&#x201d; OR &#x201c;Autoimmune Thrombocytopenia Anaemia&#x201d; OR &#x201c;Immune Thrombocytopenia&#x201d; OR &#x201c;Subacute Thyroiditis&#x201d; OR &#x201c;Acute Respiratory Failure&#x201d; OR &#x201c;Acute Respiratory Distress Syndrome&#x201d; OR &#x201c;Pneumonia&#x201d; OR &#x201c;Subcutaneous Emphysema&#x201d; OR &#x201c;Pneumothorax&#x201d; OR &#x201c;Pneumomediastinum&#x201d; OR &#x201c;Encephalopathy&#x201d; OR &#x201c;Pancreatitis&#x201d; OR &#x201c;Chronic Fatigue&#x201d; OR &#x201c;Rhabdomyolysis&#x201d; OR &#x201c;Neurologic Complication&#x201d; OR &#x201c;Cardiovascular Complications&#x201d; OR &#x201c;Psychiatric Complication&#x201d; OR &#x201c;Respiratory Complication&#x201d; OR &#x201c;Cardiac Complication&#x201d; OR &#x201c;Vascular Complication&#x201d; OR &#x201c;Renal Complication&#x201d; OR &#x201c;Gastrointestinal Complication&#x201d; OR &#x201c;Haematological Complication&#x201d; OR &#x201c;Hepatobiliary Complication&#x201d; OR &#x201c;Musculoskeletal Complication&#x201d; OR &#x201c;Genitourinary Complication&#x201d; OR &#x201c;Otorhinolaryngology Complication&#x201d; OR &#x201c;Dermatological Complication&#x201d; OR &#x201c;Paediatric Complication&#x201d; OR &#x201c;Geriatric Complication&#x201d; OR &#x201c;Pregnancy Complication&#x201d;) in the Title, Abstract or Keyword.</p>
            <p>A total of 5940 articles were accessed, of which the top 50 most cited articles about COVID-19 and Complications of COVID-19 were selected through Scopus. Each article was reviewed for its appropriateness for inclusion. The articles were independently reviewed by three researchers (JRP, MAM and TS) (
                <xref ref-type="table" rid="T1">Table 1</xref>). Differences in opinion with regards to article inclusion was resolved by consensus.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Top 50 most cited articles about COVID-19 and the complications of COVID-19.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Rank</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Article</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Number of citations</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Average number of citations per year</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y 
                                <italic toggle="yes">et al.</italic> Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395 (10223): 497-506
                                <sup>
                                    <xref ref-type="bibr" rid="ref7">7</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24775</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8258</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, 
                                <italic toggle="yes">et al.</italic> Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395(100229): 1054-1062
                                <sup>
                                    <xref ref-type="bibr" rid="ref8">8</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14341</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4780</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J 
                                <italic toggle="yes">et al.</italic> Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus&#x2013;Infected Pneumonia in Wuhan, China. 
                                <italic toggle="yes">JAMA</italic> 2020; 323(11): 1061&#x2013;1069
                                <sup>
                                    <xref ref-type="bibr" rid="ref9">9</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12740</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4247</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, 
                                <italic toggle="yes">et al.</italic> Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, Chine: a description study. Lancet 2020; 395 (10223): 507-513
                                <sup>
                                    <xref ref-type="bibr" rid="ref10">10</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11163</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3721</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, 
                                <italic toggle="yes">et al.</italic> A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 2020; 579: 270-273
                                <sup>
                                    <xref ref-type="bibr" rid="ref11">11</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10780</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3593</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wu F, Zhao S, Yu B, Chen MY, Wang W, Song GZ, 
                                <italic toggle="yes">et al.</italic> A new coronavirus associated with human respiratory disease in China. Nature 2020; 579: 265-269
                                <sup>
                                    <xref ref-type="bibr" rid="ref12">12</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5417</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1806</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, 
                                <italic toggle="yes">et al.</italic> Clinical course and outcomes of critically ill patients with SARS-COV-2 pneumonia in Wuhan, China: a single centered, retrospective, observational study. Lancet Respir Med 2020; 8(5): 475-481
                                <sup>
                                    <xref ref-type="bibr" rid="ref13">13</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5369</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1790</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet 2020; 395(10229): 1033-1034
                                <sup>
                                    <xref ref-type="bibr" rid="ref14">14</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5196</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1732</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW 
                                <italic toggle="yes">et al.</italic> Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA 2020; 323(20): 2052-2059
                                <sup>
                                    <xref ref-type="bibr" rid="ref15">15</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4811</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1604</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S 
                                <italic toggle="yes">et al.</italic> Risk Factors Associated with Acute Respiratory Distress Syndrome and Death in Patients with Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med 2020; 180(7): 934-943
                                <sup>
                                    <xref ref-type="bibr" rid="ref16">16</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4427</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1476</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, 
                                <italic toggle="yes">et al.</italic> Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int J Environ Res Public Health 2020; 17(5): 1729
                                <sup>
                                    <xref ref-type="bibr" rid="ref17">17</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4371</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1457</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Baden LR, Sahly HM, Essink B, Kotloff K, Frey S, Novak R, 
                                <italic toggle="yes">et al.</italic> Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. N Engl J Med 2021; 384: 403-416
                                <sup>
                                    <xref ref-type="bibr" rid="ref18">18</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3758</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1879</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">13.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mao L, Jin H, Wang M, Hu Y, Chen S, He Q, 
                                <italic toggle="yes">et al.</italic> Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China. JAMA Neurol 2020; 77(6): 683-690
                                <sup>
                                    <xref ref-type="bibr" rid="ref19">19</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3576</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1192</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cao B, Wang Y, Wen D, Liu W, Wang J, Fan G, 
                                <italic toggle="yes">et al.</italic> A trial of lopinavir-ritonavir in adults hospitalized with severe covid-19. N Engl J Med 2020; 382: 1787-1799
                                <sup>
                                    <xref ref-type="bibr" rid="ref20">20</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3228</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1076</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">15.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cucinotta D, Vanelli M. WHO Declares COVID-19 a Pandemic. Acta Biomed 2020; 91(1):157-60
                                <sup>
                                    <xref ref-type="bibr" rid="ref21">21</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2774</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">925</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020; 46: 846-848
                                <sup>
                                    <xref ref-type="bibr" rid="ref22">22</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2633</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">878</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">17.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Holmes EA, Connor RC,Perry VH, Tracey I, Wessely S, Arseneault L, 
                                <italic toggle="yes">et al.</italic> Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. The Lancet Psychiatry 2020; 7(6): 547-560
                                <sup>
                                    <xref ref-type="bibr" rid="ref23">23</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2628</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">876</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">18.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Liang W, Guan W, Chen R, Wang W, Li J, Xu K, 
                                <italic toggle="yes">et al.</italic> Cancer patients in SARS-COV-2 infection: a nationwide analysis in China. Lancet Oncol 2020; 21(3): 335-337
                                <sup>
                                    <xref ref-type="bibr" rid="ref24">24</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2600</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">867</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">19.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Klok FA, Kruip MJHA, Van der Meer NJM, Arbous MS, Gommers DAMPJ, Kant KM, 
                                <italic toggle="yes">et al.</italic> Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thromb Res 2020; 191: 145-147
                                <sup>
                                    <xref ref-type="bibr" rid="ref25">25</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2479</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">826</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">20.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H 
                                <italic toggle="yes">et al.</italic> Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest 2020; 130(5): 2620-2629
                                <sup>
                                    <xref ref-type="bibr" rid="ref26">26</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2473</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">824</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Shi S, Qin M, Shen B. Association of cardiac injury with mortality in hospitalised patients with COVID-19 in Wuhan, China. JAMA Cardiol 2020; 5(7): 802-810
                                <sup>
                                    <xref ref-type="bibr" rid="ref27">27</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2347</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">782</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">22.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Guo T, Fan Y, Chen M, 
                                <italic toggle="yes">et al.</italic> Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiol 2020; 5(7): 811-818
                                <sup>
                                    <xref ref-type="bibr" rid="ref28">28</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2225</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">742</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">23.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Chen T, Wu D, Chen H, Yan W, Yang D, Chen G 
                                <italic toggle="yes">et al.</italic> Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ 2020; 368: m1091
                                <sup>
                                    <xref ref-type="bibr" rid="ref29">29</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2187</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">729</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">24.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Chen H, Guo J, Wang C, Luo F, Yu X, Zhang W 
                                <italic toggle="yes">et al.</italic> Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records. Lancet 2020; 395(10226): 809-815
                                <sup>
                                    <xref ref-type="bibr" rid="ref30">30</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2172</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">724</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">25.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, 
                                <italic toggle="yes">et al.</italic> Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. The Lancet Infectious Diseases, Volume 20, Issue 4, 425-434
                                <sup>
                                    <xref ref-type="bibr" rid="ref31">31</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2124</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">708</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">26.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Zhang JJ, Dong X, Cao YY, Yuan YD, Yang YB, Yan YQ, 
                                <italic toggle="yes">et al.</italic> Clinical characteristics of 140 patients infected with SARS-COV-2 in Wuhan, China. Allergy 2020; 75(7): 1730-1741
                                <sup>
                                    <xref ref-type="bibr" rid="ref32">32</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2084</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">695</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">27.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wang Y, Zhang D, Du G, Du R, Zhou J, Jin Y 
                                <italic toggle="yes">et al.</italic> Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial. The Lancet 2020; 395(10236): 1569-1578
                                <sup>
                                    <xref ref-type="bibr" rid="ref33">33</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2016</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">672</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">28.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Tang N, Bai H, Chen X,Gong J, Li D, Sun Z. Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost 2020; 18: 1094-1099
                                <sup>
                                    <xref ref-type="bibr" rid="ref34">34</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1997</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">666</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">29.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hui DS, Azhar EI, Madani TA, Ntoumi F, Kock R, Dar O, 
                                <italic toggle="yes">et al.</italic> The continuing 2019-nCov epidemic threat of novel coronaviruses to global health- The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis 2020; 91: 264-266
                                <sup>
                                    <xref ref-type="bibr" rid="ref35">35</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1859</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">620</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">30.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Fang Y, Zhang H, Xie J, Minjie L, Ying L, Pang P, 
                                <italic toggle="yes">et al.</italic> Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology 2020; 296(2): E115-E117
                                <sup>
                                    <xref ref-type="bibr" rid="ref36">36</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1859</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">620</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">31.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Peiris JSM, Chu CM, Cheng VCC, Chan KS, Hung IFN, Poon LLM 
                                <italic toggle="yes">et al.</italic> Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. Lancet 2003; 361(9371): 1767-1772
                                <sup>
                                    <xref ref-type="bibr" rid="ref37">37</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1793</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">90</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">32.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Zheng YY, Ma YT, Zhang JY, 
                                <italic toggle="yes">et al.</italic> COVID-19 and the cardiovascular system. Nat Rev Cardiol 2020; 17: 259&#x2013;260
                                <sup>
                                    <xref ref-type="bibr" rid="ref38">38</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1785</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">595</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">33.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Grein J,Ohmagari N, Shin D, Diaz G, 
                                <italic toggle="yes">et al.</italic> Compassionate use of Remdesivir for patients with severe covid-19. N Engl J Med 2020; 382: 2327-2336
                                <sup>
                                    <xref ref-type="bibr" rid="ref39">39</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1692</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">564</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">34.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Carfi A, Bernabei R, Landi F. Persistent symptoms in patients after acute COVID-19. JAMA 2020; 324(6): 603-605
                                <sup>
                                    <xref ref-type="bibr" rid="ref40">40</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1588</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">529</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">35.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeno X. CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology 2020; 295(1): 202-207
                                <sup>
                                    <xref ref-type="bibr" rid="ref41">41</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1587</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">529</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">36.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Helms J, Tacquard C, Severac F, 
                                <italic toggle="yes">et al.</italic> High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study. Intensive Care Med 2020; 46:1089-1098
                                <sup>
                                    <xref ref-type="bibr" rid="ref42">42</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1531</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">510</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">37.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Bhatraju PK, Ghassemieh BJ, Nichols M, Kim R, Jerome KR, Naila AK, 
                                <italic toggle="yes">et al.</italic> Covid-19 in critically ill patients in the Seattle region-Case series. N Engl J Med 2020; 382: 2012-2022
                                <sup>
                                    <xref ref-type="bibr" rid="ref43">43</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1505</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">502</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">38.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Lechien JR, Chinese-Estomba CM, De Siati DR, 
                                <italic toggle="yes">et al.</italic> Olfactory and gustatory dysfunctions as a clinical presentation of mild-to-moderate forms of the coronavirus disease (COVID-19): a multicenter European study. Eur Arch Otorhinolaryngol 2020; 277: 2251-2261
                                <sup>
                                    <xref ref-type="bibr" rid="ref44">44</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1448</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">483</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">39.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Zhang H, Penninger JM, Li y, 
                                <italic toggle="yes">et al.</italic> Angiotensin-converting enzyme 2 (ACE2) as a SARS-CoV-2 receptor: molecular mechanisms and potential therapeutic target. Intensive care Med 2020; 46: 586-590
                                <sup>
                                    <xref ref-type="bibr" rid="ref45">45</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1443</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">481</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">40.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cheng Y, Lou R, Wang K, Yao Y, Ge S, Xu G, 
                                <italic toggle="yes">et al.</italic> Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney Int 2020;97(5): 829-838
                                <sup>
                                    <xref ref-type="bibr" rid="ref46">46</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1425</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">475</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">41.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Helms J, Kramer S, Merdji H, Clere-Jehl R, Schenck M, Kummerlen C, 
                                <italic toggle="yes">et al.</italic> Neurologic features in severe SARS-CoV-2 infection. N Engl J Med 2020; 382: 2268-2270
                                <sup>
                                    <xref ref-type="bibr" rid="ref47">47</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1415</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">472</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">42.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Wichmann D, Sperhake JP, Lutgehetmann M, Steurer S, Edler C, Heinemann A, 
                                <italic toggle="yes">et al.</italic> Autopsy findings and venous thromboembolism in patients with COVID-19. Ann Intern Med 2020; 173 (4): 268-277
                                <sup>
                                    <xref ref-type="bibr" rid="ref48">48</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1351</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">450</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">43.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Reynolds HR, Adhikari S, Pulgarin C, Troxel AB, Iturrate E, Johnson SB, 
                                <italic toggle="yes">et al.</italic> Renin-angiotensin-aldosterone system inhibitors and risk of covid-19. N Engl J Med 2020; 382: 2441-2448
                                <sup>
                                    <xref ref-type="bibr" rid="ref49">49</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1338</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">446</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">44.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Russell CD, Millar JE,Baillie JK. Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. Lancet 2020; 395(10223): 473-475
                                <sup>
                                    <xref ref-type="bibr" rid="ref50">50</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1332</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">444</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">45.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Kanji M, Katsushi K, Alexander Z, Gerardo C. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Euro Surveill 2020; 25 (10): 2000180
                                <sup>
                                    <xref ref-type="bibr" rid="ref51">51</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1330</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">443</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">46.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Arentz M, Yim E, Klaff L, Lokhandwala S, Riedo FX, Chong M. Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington state. JAMA 2020; 323(16): 1612-1614
                                <sup>
                                    <xref ref-type="bibr" rid="ref52">52</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1317</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">439</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">47.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Oxley TJ, Mocco J, Majidi S, Kellner CP, Shoirah H, Singh IP, 
                                <italic toggle="yes">et al.</italic> Large-vessel stroke as a presenting feature of Covid-19 in the young. N Engl J Med 2020; 382: e60
                                <sup>
                                    <xref ref-type="bibr" rid="ref53">53</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1314</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">438</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">48.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Macro C, Mulvey JJ, Berlin D, Harp J, Baxter-Stoltzfus A, Laurence J. Complement associated microvascular injury and thrombosis in the pathogenesis of severe COVID-19 infection: A report of five cases. Transl Res 2020; 220: 1-13
                                <sup>
                                    <xref ref-type="bibr" rid="ref54">54</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1294</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">431</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">49.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Goyal P, Choi JJ, Pinheiro LC, Schenck EJ, Chen R, Jabri A, Stalin MJ, 
                                <italic toggle="yes">et al.</italic> Clinical characteristics of Covid-19 in New York City. N Engl J Med 2020; 382: 2372-2374
                                <sup>
                                    <xref ref-type="bibr" rid="ref55">55</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1271</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">424</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">50.</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Monteil V, Kwon H, Prado P, Hagelkruys A, Wimmer RA, Stahl M. Inhibition of SARS-CoV-2 infections in engineered human tissues using clinical-grade soluble human ACE2. Cell 2020; 181(4): 905-913
                                <sup>
                                    <xref ref-type="bibr" rid="ref56">56</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1251</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">417</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>The inclusion criteria specified articles that were focused on COVID-19 and Complications of COVID-19. Articles were excluded if they did not relate to COVID-19 and or complications of COVID-19, Basic Science Research and studies using animal models or phantoms. Review articles, Viewpoints, Guidelines, Perspectives and Meta-analysis were also excluded from the top 50 most-cited articles (
                <xref ref-type="table" rid="T1">Table 1</xref>).</p>
            <p>The top 50 most-cited articles were compiled in a single database and the relevant data was extracted. The database included: Article Title, Scopus Citations, Year of Publication, Journal, Journal Impact Factor, Authors, Number of Authors, Department Affiliation, Number of Institutions, Country of Origin, Study Topic, Study Design, Sample Size, Open Access, Non-Original Articles, Patient/Participants Age, Gender, Symptoms, Signs, Co-morbidities, Complications, Imaging Modalities Used and outcome.</p>
        </sec>
        <sec id="sec7" sec-type="results">
            <title>Results</title>
            <sec id="sec8">
                <title>Year of publication</title>
                <p>Of the total 50 articles that were analyzed, 48 (96%) articles were published in the year 2020, while 1 (2%) article was published in 2021 and 1 (2%) article was published in the year 2003 (
                    <xref ref-type="table" rid="T2">Table 2</xref>).</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>Table 2. </label>
                    <caption>
                        <title>Year of publications of the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Year of Publication</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (50)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2020</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">48</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">96</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2021</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2003</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec9">
                <title>Open access</title>
                <p>All of the 50 (100%) articles analyzed in the bibliometric study were open access articles.</p>
            </sec>
            <sec id="sec10">
                <title>Journals</title>
                <p>Of the total 50 articles that were analyzed, the journals that published the most number of articles published were in the The Lancet (9), NEJM (7) and JAMA (4), while Eurosurveillance, Transitional Research and Annals of Internal Medicine published one each (
                    <xref ref-type="table" rid="T3">Table 3</xref>).</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>Table 3. </label>
                    <caption>
                        <title>Peer-reviewed journals that published the top 50 most cited articles of COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Journal</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (50)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">The Lancet</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">NEJM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">JAMA</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Springer link</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">nature</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">JAMA cardiology</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Radiology (RSNA)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec11">
                <title>Authors</title>
                <p>Among the 50 articles that were analyzed, the most frequently cited authors contributed 4 articles each to the list (
                    <xref ref-type="table" rid="T4">Table 4</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>Table 4. </label>
                    <caption>
                        <title>Authors contributing to the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Name of the author</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yeming Wang</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Zhang Li</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Guohui Fan</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Jiuyang Xu</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Xiaoying Gu</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Ting Yu</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yuan Wei</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Bin Cao</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec12">
                <title>Departmental affiliations</title>
                <p>Among the top 50 most-cited articles, the departmental affiliations were primarily in Internal Medicine (46.9%), Pulmonary Medicine (14.5%), and Bioscience and Technology (12.1%). Conversely, the Departments of Immunology, Paediatrics, and Urology had the lowest representation (
                    <xref ref-type="table" rid="T5">Table 5</xref>).</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>Table 5. </label>
                    <caption>
                        <title>Departmental affiliations of the authors contributing to the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Department</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (595)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Internal Medicine</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">279</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Pulmonary Medicine</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14.5</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Bioscience and Biotechnology</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Critical Care and Anaesthesiology</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Psychiatry</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.5</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Laboratory Medicine</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">24</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CTVS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.5</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Radiology</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Public health and statistics</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">OBG</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.0</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec13">
                <title>Country of origin</title>
                <p>In the research analyzed within the top 50 COVID-19 articles, a total of 83 countries participated. Notably, China played a substantial role, contributing to 29 articles (34.9%). France and Belgium closely followed; each being involved in 10 articles (12.1%). Additional contributing nations included Canada with 3 articles (3.6%), the UK with 2 articles (2.4%), and Switzerland with 1 article (1.2%) (
                    <xref ref-type="table" rid="T6">Table 6</xref>).</p>
                <table-wrap id="T6" orientation="portrait" position="float">
                    <label>Table 6. </label>
                    <caption>
                        <title>Countries involved in the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Country</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (83)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">China</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">France</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Belgium</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">USA</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Italy</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Spain</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Canada</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.7</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec14">
                <title>Study topic</title>
                <p>Among the 50 most-cited articles examined in this analysis, the predominant research themes were clinical features, comprising 34 articles (68%). Following closely were articles related to drug trials and interactions, accounting for 6 articles (12%). Additionally, there were 3 articles (6%) dedicated to analytical studies. Mortality studies constituted 2 articles (4%), while a single article each (2%) delved into the psychological impact and molecular mechanisms of COVID-19 (
                    <xref ref-type="table" rid="T7">Table 7</xref>).</p>
                <table-wrap id="T7" orientation="portrait" position="float">
                    <label>Table 7. </label>
                    <caption>
                        <title>Study topic distribution among the top 50 most-cited articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Study topic</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (50)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Clinical Features</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">68</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Drug Trials and Interactions</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Analysis and Surveillance</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Laboratory Investigations</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Mortality Study</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec15">
                <title>Study design</title>
                <p>Among the 50 most-cited articles examined, the most common study designs were retrospective (24%), followed by prospective (16%) and correspondence (12%). Other study designs included prospective cohort (4%), randomized controlled trial (4%), and cross-sectional (2%) (
                    <xref ref-type="table" rid="T8">Table 8</xref>).</p>
                <table-wrap id="T8" orientation="portrait" position="float">
                    <label>Table 8. </label>
                    <caption>
                        <title>Study designs among the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Study design</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (50)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Retrospective</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">24</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Prospective</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Correspondence</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Case Series</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Comment</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Retrospective Cohort</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Prospective Cohort</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Randomised Controlled Trial</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec16">
                <title>Patient statistics/demographics</title>
                <p>A total of 22477 patients were analyzed from the top 50 most-cited articles.</p>
            </sec>
            <sec id="sec17">
                <title>Gender</title>
                <p>Of the total 22477 patients, 12318 (54.8%) were males while 10159 (45.2%) were females (
                    <xref ref-type="table" rid="T9">Table 9</xref>).</p>
                <table-wrap id="T9" orientation="portrait" position="float">
                    <label>Table 9. </label>
                    <caption>
                        <title>Gender distribution among the patients with COVID-19 from the top 50 most-cited COVID-19 articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Gender</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (22477)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12318</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">54.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10159</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45.2</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec18">
                <title>Age distribution</title>
                <p>The most common age group among the patients was 26-65 years of age with 14255 (63.2%) patients, followed by the age of 65 years with 6018 (26.8%) patients and then 12-25 years with 2204 (9.8%) patients (
                    <xref ref-type="table" rid="T10">Table 10</xref>).</p>
                <table-wrap id="T10" orientation="portrait" position="float">
                    <label>Table 10. </label>
                    <caption>
                        <title>Age distribution among the patients with COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (22477)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">12-25 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2204</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">26-65 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14255</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">63.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;65 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6018</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">26.8</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec19">
                <title>Clinical features</title>
                <p>Among the 22477 patients, the most common clinical features were fever in 6333 (28.2%) patients, tachycardia in 4022 (17.9%) patients and dry cough in 3107 (13.8%) patients. Other common features included impaired sense of smell in 412 (1.8%) patients, impaired taste sensation in 404 (1.8%) patients and headache in 330 (1.5%) patients (
                    <xref ref-type="table" rid="T11">Table 11</xref>).</p>
                <table-wrap id="T11" orientation="portrait" position="float">
                    <label>Table 11. </label>
                    <caption>
                        <title>Clinical features among the patients with COVID-19 from the top 50 most-cited articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Clinical features</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (22477)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Fever</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6333</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Tachycardia</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4022</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Dry Cough</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3107</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Tachypnoea</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2113</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Fatigue</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1812</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Myalgia</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1785</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Dyspnoea</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1337</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Productive Cough</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">514</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Diarrhoea</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">500</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Nausea</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">449</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Impaired smell</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">412</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Impaired taste</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">404</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2023</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.0</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec20">
                <title>Investigations</title>
                <p>A total of 22477 patients underwent RT-PCR testing and were positive for COVID-19. Out of which, 18055 (80.3) patients underwent additional laboratory investigations. CT-chest was done for 11110 (49.4%) patients, chest X-ray was done for 8327 (22.7%) patients, and ECG done for 5098 (22.7%) patients. MRI brain and EEG were done for 8 (0.04%) patients with neurological complications (
                    <xref ref-type="table" rid="T12">Table 12</xref>).</p>
                <table-wrap id="T12" orientation="portrait" position="float">
                    <label>Table 12. </label>
                    <caption>
                        <title>Investigations used in patients with COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Investigations</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (22477)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RT-PCR</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22477</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Lab investigations</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18055</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">80.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CT chest</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11110</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">49.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X-ray chest</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8327</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">ECG</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5098</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">MRI brain, EEG</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.04</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec21">
                <title>Comorbidities</title>
                <p>Out of the total 22477 patients, 21989 (97.8%) patients were found to have comorbidities. Of the 21989 patients with comorbidities, hypertension was present in 6720 (30.6%) patients, diabetes mellitus in 5082 (23.1%) patients and obesity in 2666 (12.1%) patients. Other comorbidities found included chronic liver disease in 74 (0.34%) patients, endocrine disorders in 53 (0.24%) patients and psychiatric disorders in 13 (0.06%) patients (
                    <xref ref-type="table" rid="T13">Table 13</xref>).</p>
                <table-wrap id="T13" orientation="portrait" position="float">
                    <label>Table 13. </label>
                    <caption>
                        <title>List of comorbidities among the patients analyzed from the top 50 most-cited articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Comorbidities</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (21989)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Hypertension</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6720</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Diabetes mellitus</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5082</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Obesity</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2666</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Chronic Kidney Disease</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1605</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Chronic Obstructive Pulmonary Disease </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1357</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Congestive Heart Failure</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1091</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Coronary Heart Disease</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">782</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cardiovascular Disease</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">721</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Asthma</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">576</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cancer</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">435</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">954</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.3</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec22">
                <title>Complications</title>
                <p>Out of the total 22477 patients, 3143 (13.9%) patients developed complications. The most common complication seen among the patients were acute kidney injury in 707 (22.5%) patients, ARDS in 576 (18.3%) patients and Sepsis in 347 (11.0%) patients. Other complications included electrolyte imbalance in 81 (2.6%) patients, acute hepatic injury in 74 (2.4%) patients and arrhythmias in 63 (2.0%) patients (
                    <xref ref-type="table" rid="T14">Table 14</xref>).</p>
                <table-wrap id="T14" orientation="portrait" position="float">
                    <label>Table 14. </label>
                    <caption>
                        <title>Complications among the patients analyzed from the top 50 most-cited articles.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Complications</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (3143)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Acute Kidney Injury</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">707</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22.5</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Acute Respiratory Distress Syndrome</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">576</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sepsis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">347</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Respiratory Failure</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">295</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Lower Respiratory Tract Infection</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">194</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Myocardial injury</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">184</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Shock</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">183</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Heart Failure</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">119</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Pulmonary Embolism/Deep Vein Thrombosis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">115</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Electrolyte imbalance</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">81</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">342</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.9</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec23">
                <title>Outcome</title>
                <p>Of the total 22477 patients who tested positive with COVID-19, 12981 (57.8%) recovered without any complications, while 6998 (31.1%) patients were hospitalised, and 2498 (11.1%) patients deceased due to the illness (
                    <xref ref-type="table" rid="T15">Table 15</xref>).</p>
                <table-wrap id="T15" orientation="portrait" position="float">
                    <label>Table 15. </label>
                    <caption>
                        <title>Outcomes of the patients with COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Outcome</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N (22477)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Recovered/Discharged</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12981</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">57.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Hospitalised</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6998</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">31.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Dead</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2498</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.1</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec24" sec-type="discussion">
            <title>Discussion</title>
            <p>In the bibliometric analysis of the top 50 most-cited COVID-19 articles, the most cited article was &#x201c;Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China&#x201d; by Huang C et al., in The Lancet published in 2020. This article has the highest total number of citations (24775) as well as the highest average number of citations per year (8258) among the top 50 most-cited articles.</p>
            <p>The Lancet published the greatest number of articles from the top 50 most-cited list with a total of 9 articles, followed by NEJM with 7 articles and JAMA with 4 articles published respectively. Most of the articles (n=48, 96%) were published in the year 2020 with China (n=29, 34.9%), France (n=10, 12.1%) and Belgium (n=10,12.1%) being the top contributing countries.</p>
            <p>In this bibliometric analysis, we found that 54.8% of the total patients were males while 45.2% were female patients. In an article written by Bwire, it was reported that females were more resistant to Covid-19 infection. This could be attributed to various factors such as sex hormones, higher expression of ACE-2 receptors in men and also difference in the lifestyles.
                <sup>
                    <xref ref-type="bibr" rid="ref57">57</xref>
                </sup>
            </p>
            <p>The incidence of COVID-19 infection was highest in adults between 26-65 years (63.2%), followed by the adults over 65 years of age (26.8%), and least in 12-25 years age group (9.8%). Though it is evident that the older population were more at risk for hospitalizations and deaths due to COVID-19, researchers have not been able to pinpoint a particular reason for the same. The current hypothesis is that this could be as a result of changes to the immune cell repertoire, the epigenome, NAD+ levels, inflammasome activity, biological clocks, and covalent modifications of human and viral proteins.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> In addition to this, it is not really understood why SARS-CoV-2 damages such a broad array of tissues in older people.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
            </p>
            <p>Similar findings were reported in a study conducted by Jakhmola S et al, with the highest incidence of Covid-19 infection in the age groups of 20-49 years and above 50 years, and the least in the paediatric age group. This could possibly be due to lesser expression of the coronavirus (ACE-2) receptors in the nasal epithelium in younger age groups, leading to reduced susceptibility to Covid 19 infection.
                <sup>
                    <xref ref-type="bibr" rid="ref58">58</xref>
                </sup> Centers for Disease Control and Prevention (CDC) reported the highest incidence of COVID-19 infection among adults above the age of 80 years and in the age group of 18-24 years during 2020.
                <sup>
                    <xref ref-type="bibr" rid="ref59">59</xref>
                </sup>
            </p>
            <p>In our analysis, the most common clinical features were fever (28.2%), tachycardia (17.9%) and dry cough (13.8%). Other common features included impaired sense of smell (1.8%), impaired taste sensation (1.8%) and headache (1.5%). Similar to the above-mentioned findings, a study by Cascella M et al, reported the most common symptoms in patients to be fever, dry cough and dyspnoea. Other lesser common symptoms included malaise and headache.
                <sup>
                    <xref ref-type="bibr" rid="ref60">60</xref>
                </sup> In a study by Mullol J et al., it was concluded that most viral respiratory infections such as COVID-19 are associated with impairment of sense of smell. The incidence of olfactory and gustatory symptoms varies due to the varied methodology used in various studies.
                <sup>
                    <xref ref-type="bibr" rid="ref61">61</xref>
                </sup> In addition to this, it is also worth noting that recent studies about COVID-19 have identified possible long-term effects as a result of COVID-19 such as memory loss, difficulty concentrating, disturbances in sleep, and mild irreversible multi organ damage.</p>
            <p>Of the total patients analysed in our study, 97.8% patients were found to have comorbidities. Of which, hypertension (30.6%), diabetes mellitus (23.1%) and obesity (12.1%) were the commonest comorbidities found in the patients. Other comorbidities included chronic liver disease (0.34%), endocrine disorders (0.24%) and psychiatric disorders (0.06%). In a study by Sanyaolu et al, that the common comorbidities found were hypertension, diabetes mellitus and obesity, which were associated with poorer outcomes in COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref62">62</xref>
                </sup>
            </p>
            <p>Of all the patients analysed in our study, 13.9% of patients developed complications following COVID-19 infection. The common complications seen among the patients were acute kidney injury (22.5%), ARDS (18.3%) and sepsis (11.0%). Other complications included thrombosis (3.6%), acute hepatic injury (2.4%) and arrhythmias (2.0%). In the study by Cascella M et al, it was reported that ARDS was the most common pulmonary complication of COVID-19 while extra-pulmonary complications included AKI, cardiovascular complications and prothrombotic complications.
                <sup>
                    <xref ref-type="bibr" rid="ref60">60</xref>
                </sup> Similarly, in another study by Isath A et al., the most common complications reported were respiratory failure, AKI, sepsis and thrombosis.
                <sup>
                    <xref ref-type="bibr" rid="ref63">63</xref>
                </sup> ARDS due to COVID-19 usually represents a specific sub type in which the hypoxia occurs as a result of coexistence of non-aerated regions and large areas of low ventilation-perfusion ratio.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> Additionally, the excessive inflammatory reactions that occur during COVID-19 can damage the lung cells which then disrupt the alveolar-capillary barrier which is crucial for gas exchange.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> Acute kidney injury occurring as a complication in patients with COVID-19 are thought to occur as a result of multiple factors interplaying with each other. This could arise as a result of the direct effects of the virus, cardiovascular morbidity, activation of coagulation pathways, endothelial injury or activation of the renin-angiotensin pathways. Patients with sepsis could develop AKI as a result of the cytopathic effects of SARS-COV-2 on the podocytes and proximal tubule cells.
                <sup>
                    <xref ref-type="bibr" rid="ref60">60</xref>
                </sup> In addition to this, the presence of viral particles in renal endothelial cells may also cause endothelial damage which in turn promotes a state of hypercoagulability, and macrophage activation leading to formation of microthrombi and renal microvasculature injury.
                <sup>
                    <xref ref-type="bibr" rid="ref60">60</xref>
                </sup>
            </p>
            <p>In our analysis, 57.8% patients recovered without any complications, while 31.1% were hospitalised, and 11.1% deceased due to the illness. Similar findings were reported in a study by Isath A et al., where 51.4% patients recovered and were discharged home, and the overall inpatient mortality was reported to be 13.2%. Most of the patients with comorbidities were associated with higher number of complications and mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref63">63</xref>
                </sup>
            </p>
            <p>During the early days of COVID-19, remdesivir was a popular treatment in the course of a COVID-19 infection. However, in a study held by Wang Y, it was found that the use of remdesivir did not significantly change the time to clinical improvement compared to placebo. In the subgroup of patients who had symptoms for 10 days or less, those treated with remdesivir showed a non-statistically significant, yet faster improvement.
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> Adverse events were slightly more common in the remdesivir group, affecting 66% of its recipients, compared to 64% in the placebo group.
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> In a study held among critically ill patients, it was found that patients had a shorter duration of mechanical ventilation when treated with oseltamivir.
                <sup>
                    <xref ref-type="bibr" rid="ref64">64</xref>
                </sup> Additionally, in the same study it was also found that there was no significant difference in the hospital mortality rates of these patients.
                <sup>
                    <xref ref-type="bibr" rid="ref64">64</xref>
                </sup> As per current guidelines, the United States National Institute of Health (NIH) recommends against the use of systemic corticosteroid therapy for patients with mild to moderate COVID-19 infection and in those patients that do not require supplemental oxygen therapy.
                <sup>
                    <xref ref-type="bibr" rid="ref65">65</xref>
                </sup> It was found that systemic corticosteroid therapy is only beneficial when used in patients who require supplement oxygen therapy (conventional oxygen, high flow nasal cannula oxygen, non-invasive ventilation, mechanical ventilation or extracorporeal membrane oxygenation).
                <sup>
                    <xref ref-type="bibr" rid="ref65">65</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref66">66</xref>
                </sup> Although there was a widespread use of corticosteroids during the early days of COVID-19,
                <sup>
                    <xref ref-type="bibr" rid="ref66">66</xref>
                </sup> the NIH has now recommended against the use of it in mild or moderate cases.
                <sup>
                    <xref ref-type="bibr" rid="ref65">65</xref>
                </sup> In another study, the authors researched the benefit of using anticoagulants as a treatment for COVID-19. The authors found that there was no significant difference in 28-day mortality rates between patients treated with heparin and those who were not. However, among patients with a SIC score of 4 or higher, or with D-dimer levels more than six times the upper limit of normal, those who received heparin had significantly lower 28-day mortality rates compared to those who did not receive heparin.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup>
            </p>
            <p>The authors of the studies have recommended and stated that vaccination campaigns have been pivotal. Empirical studies demonstrate a marked reduction in infection rates, severity of clinical manifestations, and mortality associated with COVID-19 following the administration of authorized vaccines. These biological agents not only confer individual protection but also contribute to herd immunity, thereby attenuating community-level transmission.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
            </p>
            <p>Moreover, mechanical barriers such as facial masks have emerged as critical in impeding viral dissemination. A consensus in the scientific community advocates for the utilization of higher filtration efficiency respirators (e.g., N95, KN95) in public settings, especially where physical distancing cannot be maintained and in poorly ventilated indoor environments.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
            </p>
            <p>As a limitation of the present study, it is important to note that the analysis does not delve into network visualizations among authors or collaborative research endeavors involving multiple institutions and countries. These aspects are beyond the scope of the bibliometric analysis conducted in this research. Furthermore, the authors did not utilize specialized analysis tools such as VOS viewer or Biblioshiny. Additionally, the validation of article contents was performed manually by individual authors and recorded in a data sheet.
                <sup>
                    <xref ref-type="bibr" rid="ref67">67</xref>
                </sup>
            </p>
        </sec>
        <sec id="sec25" sec-type="conclusion">
            <title>Conclusion</title>
            <p>This article offers a quick overview of the most influential literature and how COVID-19 research has evolved over time. This insight can be instrumental for authors, offering guidance on creating impactful research in the future. In conclusion, as evidenced by the analysis of the 50 most-cited articles on COVID-19 and its complications, it is apparent that understanding the most common symptoms such as fever, tachycardia, and dry cough is crucial for both clinicians and researchers. In this analysis, it was found that the most common complications found in patients with COVID-19 were acute kidney injury (AKI) and acute respiratory distress syndrome. The occurrence of AKI can be explained as a result of the direct effects of the virus or as a result of activation of multiple physiologic pathways which eventually lead to renal microvascular injury. ARDS can occur as a result of the excessive inflammatory reactions during the infection leading to a disruption of the alveolar-capillary barrier thereby affecting the individuals gas exchange. With China leading in publications on the subject and The Lancet emerging as the primary journal for disseminating COVID-19 research, it is clear that the global scientific community has mobilized to address this pressing issue. Moreover, recognizing prevalent comorbidities like hypertension (HTN) and diabetes underscores the need for comprehensive management strategies. By leveraging insights from these influential publications, researchers can navigate the complex landscape of COVID-19 research effectively, ultimately contributing to our collective efforts to combat this pandemic. Overall, this method serves as a strategic tool for staying updated and contributing meaningfully to the field of COVID-19 research.</p>
        </sec>
    </body>
    <back>
        <sec id="sec28" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec29">
                <title>Underlying data</title>
                <p>Dryad: Data of top 50 most cited articles about COVID-19 and the complications of COVID-19, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5061/dryad.tx95x6b4m">https://doi.org/10.5061/dryad.tx95x6b4m</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref67">67</xref>
</sup>
                </p>
                <p>This project contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>
Data_of_top_50_most_cited_articles_about_COVID-19_and_the_complications_of_COVID-19.xlsx</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">Creative Commons Zero &#x201c;No rights reserved&#x201d; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            </sec>
        </sec>
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    <sub-article article-type="reviewer-report" id="report260932">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.165741.r260932</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Liu</surname>
                        <given-names>Chen</given-names>
                    </name>
                    <xref ref-type="aff" rid="r260932a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-5149-2496</uri>
                </contrib>
                <aff id="r260932a1">
                    <label>1</label>department of radiology, Third Military Medical University, Chongqing, China</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>14</day>
                <month>8</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Liu C</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport260932" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145713.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The article provides a bibliometric analysis of the 50 most-cited articles on COVID-19 complications, aiming to highlight influential studies and identify factors contributing to high citation rates. The authors successfully analyze the publication trends, study characteristics, and demographic data related to these articles, offering insights into the multifaceted impacts of COVID-19 across various organ systems. The study emphasizes the significant role of publications from China and fields such as Internal Medicine and Pulmonary Medicine.</p>
            <p> Detailed Comments: 
                <list list-type="order">
                    <list-item>
                        <p>
                            <bold>Presentation and Literature Citation:</bold>The work is generally well-organized, providing a comprehensive overview of the top-cited literature on COVID-19 complications. The inclusion of various complications across multiple organ systems makes the analysis robust and relevant.</p>
                    </list-item>
                    <list-item>
                        <p>
                            <bold>Study Design and Technical Soundness:</bold>&#x00a0;The study design is appropriate for a bibliometric analysis, and the work is technically sound. The authors have employed a rigorous selection process, which is crucial for ensuring the relevance and quality of the articles analyzed.</p>
                    </list-item>
                    <list-item>
                        <p>
                            <bold>Methodology and Replicability:</bold>The authors describe their methodology in detail, particularly in terms of the criteria for article selection and the parameters analyzed.</p>
                    </list-item>
                    <list-item>
                        <p>
                            <bold>Source Data Availability:</bold>The authors have provided a comprehensive dataset of the top 50 most-cited articles, which serves as a valuable resource for further research.</p>
                    </list-item>
                    <list-item>
                        <p>
                            <bold>Conclusions and Support from Results:</bold>
                            <bold>Positive Aspects:</bold> The conclusions drawn are adequately supported by the results, reflecting a clear understanding of the factors contributing to the citation impact of COVID-19 research. The discussion around the predominance of studies from certain countries and fields provides valuable insights.
                            <bold>Constructive Feedback:</bold> The authors might consider expanding their conclusions to reflect on how these citation patterns could influence future research priorities and the potential biases in the current COVID-19 literature.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Not applicable</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Partly</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Strengths：&#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; Comprehensive Review: The study effectively identifies and analyzes the top 50 most-cited articles on COVID-19 complications, providing valuable insights into the most influential research in this field.Methodological Rigor: The use of Scopus as a data source and the detailed criteria for article selection and evaluation ensure a high level of methodological rigor.Detailed Analysis: The study provides extensive data on various aspects of the articles, including publication year, journal impact, geographical distribution, and study focus, offering a thorough overview of the research landscape.Clinical Relevance: By focusing on complications and clinical features, the study provides information that is directly relevant to healthcare professionals dealing with COVID-19 patients.&#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0;Recommendations：&#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0;Expand the Time Frame: The study focuses on articles published up to July 2021. Extending the analysis to include more recent publications would provide a more current view of influential research.Include More Databases: Incorporating other databases like PubMed and Web of Science could offer a broader scope and capture additional influential articles not indexed in Scopus.Deeper Analysis of Complications: A more detailed analysis of specific complications and their management could enhance the practical utility of the study for clinicians.Visualization Tools: Utilizing visual tools like graphs and charts to represent data on citations, geographical distribution, and study focus could make the findings more accessible and easier to interpret.Addressing Bias: Discuss potential biases, such as the overrepresentation of certain countries or journals, and suggest ways to mitigate these in future research.&#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0;Limitations：&#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0; &#x00a0;Publication Bias: The study may be influenced by publication bias, where more prominent journals and articles with positive findings are more likely to be cited.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report290243">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.165741.r290243</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>G&#x00fc;lhan</surname>
                        <given-names>Pinar Yildiz</given-names>
                    </name>
                    <xref ref-type="aff" rid="r290243a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r290243a1">
                    <label>1</label>Duzce University, Konuralp, Duzce, Turkey</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>14</day>
                <month>8</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 G&#x00fc;lhan PY</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport290243" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145713.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The article provides a valuable overview of the 50 most cited articles on COVID-19 and its complications, highlighting key trends in publication, authorship, and research focus. The analysis of patient demographics, clinical features, and comorbidities offers insights into the factors influencing disease severity and outcomes. The discussion on complications and treatment options further enhances the clinical relevance of the study. However, the article could be strengthened by incorporating visual aids, expanding the discussion of certain findings, and providing more specific recommendations for future research. Overall, despite some limitations, the study serves as a useful resource for researchers and clinicians seeking a concise overview of the influential literature on COVID-19 complications.&#x00a0;Tables can be visualised with VOSviewer and other bibliometric analysis programs.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>&#x0131; m a pulmonogist and my research area is molecular biology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report273085">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.165741.r273085</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Khuluq</surname>
                        <given-names>Husnul</given-names>
                    </name>
                    <xref ref-type="aff" rid="r273085a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r273085a1">
                    <label>1</label>Universitas Muhammadiyah Gombong, Kebumen, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>10</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Khuluq H</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport273085" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145713.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The third revision of the document is substantially complete; however, it lacks a crucial element in the conclusion section, specifically concerning recommendations for future research.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>bibliometric , big data , machine learning, clinical pharmacy</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report266882">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.164836.r266882</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Khuluq</surname>
                        <given-names>Husnul</given-names>
                    </name>
                    <xref ref-type="aff" rid="r266882a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r266882a1">
                    <label>1</label>Universitas Muhammadiyah Gombong, Kebumen, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>4</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Khuluq H</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport266882" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145713.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>1.&#x00a0;In the discussion session, the utilization of remdesivir and anticoagulants for therapy was addressed. However, this topic was not supported by bibliometric analysis data, unlike other discussed variables such as comorbidities, age, gender, clinical symptoms, complications, and outcomes. On the other hand, several other antiviral agents such as oseltamivir and favipiravir have not been discussed. Furthermore, the use of other drug classes, including corticosteroids, HCQ (Hydroxychloroquine), and antibiotics, which significantly influence therapy outcomes, was also not covered. This omission highlights a gap in the comprehensive evaluation of therapeutic strategies.</p>
            <p> 2.&#x00a0;In the conclusion, it would be advisable for the authors to concentrate more closely on the designated topic of the paper, which is complications. This focus would enhance the relevance and coherence of the findings in relation to the stated objectives of the research.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>bibliometric , big data , machine learning, clinical pharmacy</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment11484-266882">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Antony Manoj</surname>
                            <given-names>Matthew</given-names>
                        </name>
                        <aff>Manipal Academy of Higher Education, Manipal, Karnataka, India</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>The authors declare that they have no competing interests.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>29</day>
                    <month>4</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>We would first like to thank you for taking the time to review this version of our article. We have tried to address each comment and incorporate the same into the article.&#x00a0;</p>
                <p> </p>
                <p> Q1.&#x00a0;In the discussion session, the utilization of remdesivir and anticoagulants for therapy was addressed. However, this topic was not supported by bibliometric analysis data, unlike other discussed variables such as comorbidities, age, gender, clinical symptoms, complications, and outcomes. On the other hand, several other antiviral agents such as oseltamivir and favipiravir have not been discussed. Furthermore, the use of other drug classes, including corticosteroids, HCQ (Hydroxychloroquine), and antibiotics, which significantly influence therapy outcomes, was also not covered. This omission highlights a gap in the comprehensive evaluation of therapeutic strategies</p>
                <p> </p>
                <p> A1. Thank you for the comment. In the current version of the article, we have discussed the use of anti-virals and steroids in patients with COVID-19. Additionally, we have also highlighted the current guidelines for steroid use in COVID-19 patients.&#x00a0;</p>
                <p> </p>
                <p> Q2.&#x00a0;In the conclusion, it would be advisable for the authors to concentrate more closely on the designated topic of the paper, which is complications. This focus would enhance the relevance and coherence of the findings in relation to the stated objectives of the research.</p>
                <p> </p>
                <p> A2. Thank you for the comment. The conclusion has been edited to better highlight the complications of COVID-19.</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report253907">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.159695.r253907</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Khuluq</surname>
                        <given-names>Husnul</given-names>
                    </name>
                    <xref ref-type="aff" rid="r253907a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r253907a1">
                    <label>1</label>Universitas Muhammadiyah Gombong, Kebumen, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>3</day>
                <month>4</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Khuluq H</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport253907" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145713.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The literature is up-to-date, but it is insufficient with only 14 references. Bibliometric research is a review-based study, so it requires a more extensive collection of literature than experimental or observational research.</p>
            <p> The study design is sound, utilizing two databases: Scopus and Web of Science. However, a drawback of using these two databases is the difficulty in visualization with tools like VOSviewer or Biblioshiny. Bibliometric research should display network visualizations among institutions, countries, and author collaborations. Utilizing only Web of Science might actually be sufficient due to its more comprehensive visualization capabilities. The main weakness of this article is the absence of such visualizations, as explained above.</p>
            <p> Overall, bibliometric analysis should ideally utilize applications such as VOSviewer or Biblioshiny, wherein citation counts will automatically appear. The utilization of these applications is not explicitly stated within the research methodology.</p>
            <p> This article bears closer resemblance to a review article rather than a bibliometric analysis.</p>
            <p> </p>
            <p> The literature is relevant, but the discussion lacks depth due to the scarcity of literature. The discussion on complications, which is the main topic, should be more detailed with literature from various countries, as complications may vary.</p>
            <p> </p>
            <p> The conclusion remains too general and is not sufficiently relevant to its title, which is complications in COVID-19 cases. Please formulate a more specific conclusion and add recommendations.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>bibliometric , big data , machine learning, clinical pharmacy</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-253907-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>The Impact of the COVID-19 Pandemic on Cardiovascular Disease Research: A Bibliometric Analysis</article-title>.<volume>225</volume>:
                        <elocation-id>10.2991/978-94-6463-284-2_80</elocation-id>
                        <fpage>745</fpage>-<lpage>757</lpage>
                        <pub-id pub-id-type="doi">10.2991/978-94-6463-284-2_80</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-253907-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>A bibliometric analysis of coronavirus disease (COVID-19) mortality rate</article-title>.
                        <source>
                            <italic>Bali Medical Journal</italic>
                        </source>.<year>2022</year>;<volume>11</volume>(<issue>2</issue>) :
                        <elocation-id>10.15562/bmj.v11i2.3423</elocation-id>
                        <fpage>579</fpage>-<lpage>586</lpage>
                        <pub-id pub-id-type="doi">10.15562/bmj.v11i2.3423</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment11399-253907">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Antony Manoj</surname>
                            <given-names>Matthew</given-names>
                        </name>
                        <aff>Manipal Academy of Higher Education, Manipal, Karnataka, India</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>10</day>
                    <month>4</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>We would like to express our gratitude to the reviewer for dedicating their time to thoroughly review our article. We have carefully examined each comment provided and have made every effort to comprehensively address each one.&#x00a0;</p>
                <p> </p>
                <p> Q. The literature is up-to-date, but it is insufficient with only 14 references. Bibliometric research is a review-based study, so it requires a more extensive collection of literature than experimental or observational research.</p>
                <p> </p>
                <p> Ans.</p>
                <p> We have now expanded our list of references and have incorporated this additional information into our discussion section to ensure a more comprehensive discussion.</p>
                <p> </p>
                <p> QThe study design is sound, utilizing two databases: Scopus and Web of Science. However, a drawback of using these two databases is the difficulty in visualization with tools like VOSviewer or Biblioshiny. Bibliometric research should display network visualizations among institutions, countries, and author collaborations. Utilizing only Web of Science might actually be sufficient due to its more comprehensive visualization capabilities. The main weakness of this article is the absence of such visualizations, as explained above. Overall, bibliometric analysis should ideally utilize applications such as VOSviewer or Biblioshiny, wherein citation counts will automatically appear. The utilization of these applications is not explicitly stated within the research methodology. This article bears closer resemblance to a review article rather than a bibliometric analysis.</p>
                <p> </p>
                <p> Ans. Thank you for your comment. We wish to clarify that we did not employ visual representation tools such as VOSviewer or Biblioshiny. The data analysis was conducted individually by each author and subsequently verified by all authors. This approach has been acknowledged as a limitation in the discussion section of our study.&#x00a0;</p>
                <p> </p>
                <p> Q. The literature is relevant, but the discussion lacks depth due to the scarcity of literature. The discussion on complications, which is the main topic, should be more detailed with literature from various countries, as complications may vary.</p>
                <p> </p>
                <p> Ans.</p>
                <p> Thank you for your comment. We've now enriched the discussion section of the article with additional information as mentioned previously. Furthermore, we wish to clarify that this bibliometric study does not focus exclusively on the complications of COVID-19. Instead, it broadly covers COVID-19 and its complications. Through our data analysis, we discovered that the complications of COVID-19 remained relatively consistent across the various countries we analyzed. Hence as a result of this, we had focussed the content in the discussion revolving around the most common types of complications in COVID-19</p>
                <p> </p>
                <p> Q.The conclusion remains too general and is not sufficiently relevant to its title, which is complications in COVID-19 cases. Please formulate a more specific conclusion and add recommendations.</p>
                <p> </p>
                <p> Ans.&#x00a0;</p>
                <p> In response to your feedback, we have now revised the conclusion to be more specific and directly relevant to the content of the article.</p>
            </body>
        </sub-article>
    </sub-article>
</article>
