<?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.132214.4</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 association between vitamin D deficiency and the clinical outcomes of hospitalized COVID-19 patients</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 4; peer review: 2 approved, 2 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Rachman</surname>
                        <given-names>Andhika</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/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</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/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</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/0000-0003-3246-3352</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Rahmaniyah</surname>
                        <given-names>Rizky</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/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</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>Khomeini</surname>
                        <given-names>Andi</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/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Iriani</surname>
                        <given-names>Anggraini</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/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</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="a4">4</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Division of Hematology and Oncology, Department of Internal Medicine, Dr. Cipto Mangunkusumo National Referral Hospital, Faculty of Medicine, Universitas Indonesia, Centra Jakarta, DKI Jakarta, 10430, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Central Jakarta, DKI Jakarta, 10430, Indonesia</aff>
                <aff id="a3">
                    <label>3</label>Department of Internal Medicine, Wisma Atlet COVID-19 Emergency Hospital, North Jakarta, DKI Jakarta, 14360, Indonesia</aff>
                <aff id="a4">
                    <label>4</label>Department of Clinical Pathology, Yarsi University, Central Jakarta, DKI Jakarta, 10510, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:andhika.rachman@office.ui.ac.id">andhika.rachman@office.ui.ac.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>5</day>
                <month>2</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>394</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>1</day>
                    <month>2</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Rachman A 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/12-394/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Vitamin D deficiency is an emerging public health problem that affects more than one billion people worldwide. Vitamin D has been shown to be effective in preventing and reducing the severity of viral respiratory diseases, including influenza. However, the role of vitamin D in COVID-19 infection remains controversial. This study aimed to analyze the association of vitamin D deficiency on the clinical outcome of hospitalized COVID-19 patients.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>A prospective cohort study was conducted among hospitalized COVID-19 patients at two COVID-19 referral hospitals in Indonesia from October 2021 until February 2022.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The median serum 25(OH)D level in 191 hospitalized COVID-19 patients was 13.6 [IQR=10.98] ng/mL. The serum 25(OH)D levels were significantly lower among COVID-19 patients with vitamin D deficiency who had cardiovascular disease (p-value=0.04), the use of a ventilator (p-value=0.004), more severe COVID-19 cases (p-value=0.047), and mortality (p-value=0.002). Furthermore, serum 25(OH)D levels were significantly different between patients with mild and severe COVID-19 cases (p-value=0.019). Serum 25(OH)D levels in moderate and severe COVID-19 cases were significantly different (p-value=0.031). Lower serum 25(OH)D levels were significantly associated with an increased number of comorbidities (p-value=0.03), the severity of COVID-19 (p-value=0.002), and the use of mechanical ventilation (p-value=0.032). Mortality was found in 7.3% of patients with deficient vitamin D levels. However, patients with either sufficient or insufficient vitamin D levels did not develop mortality.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>COVID-19 patients with vitamin D deficiency were significantly associated with having cardiovascular disease, mortality, more severe COVID-19 cases, and the used of mechanical ventilation. Lower serum 25(OH)D levels were associated with an increased number of comorbidities, COVID-19 severity, and the use of mechanical-ventilation. Thus, we suggest hospitalized COVID-19 patients to reach a sufficient vitamin D status to improve the clinical outcome of the disease.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Vitamin D</kwd>
                <kwd>25(OH)D</kwd>
                <kwd>clinical outcome</kwd>
                <kwd>COVID-19</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>This research was funded by Directorate of Research and Development, Universitas Indonesia&#x2019;s grant program &#x201c;Hibah PUTI 2022&#x201d;</funding-source>
                    <award-id>ND-5463/UN2.F1.D1.4/PPM.00.00/2022</award-id>
                </award-group>
                <funding-statement>This research was funded by Directorate of Research and Development, Universitas Indonesia&#x2019;s grant program &#x201c;Hibah PUTI 2022&#x201d; (grant number: ND-5463/UN2.F1.D1.4/PPM.00.00/2022). </funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 3</title>
                <p>The reviewer did raise a very important concern which will improve our manuscript.&#x00a0; -The title was updated. -We have included additional information in the discussion section. -We have included several factors that are considered to be limitations of our study. -We added more references to enhance the quality of our paper.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>Coronavirus Disease-2019 (COVID-19) is a rapidly spreading pandemic disease caused by Severe Acute Respiratory Syndrome Corona-Virus-2 (SARS-CoV-2), the seventh coronavirus that infect humans. This highly contagious virus spreads through phonation and breathing droplets or through direct contact with an infected person.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> The disease can exhibit a wide range of symptoms, from asymptomatic to dramatic, such as hypoxia and multiorgan failure.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> There is a lack of evidence-based data about the risk factors for the infection, as well as the most effective treatments. Current hospital-based management is focused on the excessive inflammatory response and respiratory support due to the fact that targeted antiviral therapies have not been widely accessible.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>Vitamin D is a versatile steroid hormone that plays multiple roles in the body, including the regulation of bone and calcium metabolism.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> It also supports the innate and adaptive immune systems against respiratory viruses.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> It controls the innate immune system by stimulating the synthesis of antimicrobial peptides such as IL-37, cathelicidins, and defensivins.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Vitamin D also modulates adaptive immunity by regulating the formation of inflammatory T helper type 17 (Th17) cells toward the anti-inflammatory regulatory T cells and altering the primary pro-inflammatory cytokines, such as interferon-
                <inline-formula>
                    <mml:math display="inline">
                        <mml:mi>&#x03b3;</mml:mi>
                    </mml:math>
                </inline-formula>, TNF-
                <inline-formula>
                    <mml:math display="inline">
                        <mml:mi>&#x03b1;</mml:mi>
                    </mml:math>
                </inline-formula> and IL-6.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> This regulation is considered to be less effective in cases of vitamin D deficiency, although it might be obtained if vitamin D had reached a sufficient level.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
            </p>
            <p>Deficient vitamin D is a global health crisis, affecting over a billion people.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> Vitamin D deficiency was widespread across Southeast Asian countries, despite extensive exposure to sunlight.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup> Based on current evidence, vitamin D helps prevent and mitigate the severity of viral respiratory diseases, such as influenza.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> However, the role of vitamin D in COVID-19 infection remains unclear.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
            </p>
            <p>Furthermore, this is the first study that analyzes the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC-4C) score in a group of patients with vitamin D deficiency. The ISARIC 4C mortality score provides an approach for evaluating the risk of mortality upon admission by utilizing demographic and physiological parameters. This scoring system is derived from a comprehensive population cohort study conducted at the national level in the United Kingdom.
                <sup>
                    <xref ref-type="bibr" rid="ref81">21</xref>
                </sup> Understanding the clinical course of COVID-19 is crucial until a viable vaccination becomes widely accessible, due to the lack of specific therapies and the tremendous health and economic impact of the pandemic.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">22</xref>
                </sup> In this situation, deficient vitamin D is a modifiable risk factor due to its safety and affordability.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">23</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref23">24</xref>
                </sup> The aim of this study was to assess the association of vitamin D deficiency on the clinical outcome of hospitalized COVID-19 patients. Thus, a comprehensive understanding can be obtained as a promising strategy for evaluating the prognosis and treatment for COVID-19 patients.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Study design</title>
                <p>This study was a cross-sectional study conducted at two COVID-19 referral hospitals in Jakarta, Indonesia (National Emergency Hospital Wisma Atlet Kemayoran and Dr. Cipto Mangunkusumo General Hospital), from October 2021 until February 2022. The included subjects were COVID-19 positive (confirmed by reverse transcription-polymerase chain reaction [RT-PCR]) and admitted to the hospital; aged 18 years and older. The exclusion criteria were COVID-19 patients with clinically asymptomatic and severely affected COVID-19 patients who arrived using mechanical ventilation prior to admission. This study specifically involved subjects registered with mild, moderate, or severe disease according to WHO interim guidance and Indonesian government policy at admission.
                    <sup>
                        <xref ref-type="bibr" rid="ref82">25</xref>
                    </sup> The STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology) were followed for this study.</p>
            </sec>
            <sec id="sec4">
                <title>Data collection</title>
                <p>The SARS-CoV-2 infection was confirmed through positive RT-PCR obtained from nasal and oropharyngeal swabs collected.
                    <sup>
                        <xref ref-type="bibr" rid="ref77">26</xref>
                    </sup> The examination was carried out in the Biosafety Level 3-facility (BSL-3) with Biological Safety Cabinet Class II (BSC-II).</p>
                <p>During the admission, each patient had 3&#x2013;5 mL of blood collected in an acid citrate dextrose tube from a cuffed venous sample. The samples were transported to the laboratory in a cold chain for the measurement of vitamin D. Vitamin D status was evaluated by measuring serum 25(OH) D or 25-hydroxyvitamin D levels. The results were gathered using Roche Diagnostics&#x2019; Cobas e411, a competitive electrochemiluminescent protein binding assay.</p>
                <p>According to Endocrine Society Clinical Practice Guideline, a serum 25(OH) D level of less than 20 ng/mL (50 nmol/L) was considered as deficient.
                    <sup>
                        <xref ref-type="bibr" rid="ref31">27</xref>
                    </sup> In this study, we divided serum 25(OH) D level into three categories, subjects with serum 25(OH) D levels &#x2264; 20 ng/mL (&#x2264;50 nmol/L) were considered as deficient, serum 25(OH) D levels 21-29 ng/mL (51-74 nmol/L) were considered as insufficient, and serum 25(OH) D levels 
                    <inline-formula>
                        <mml:math display="inline">
                            <mml:mo>&#x2265;</mml:mo>
                        </mml:math>
                    </inline-formula> 30 ng/mL (
                    <inline-formula>
                        <mml:math display="inline">
                            <mml:mo>&#x2265;</mml:mo>
                        </mml:math>
                    </inline-formula>75 nmol/L) were considered as sufficient.</p>
            </sec>
            <sec id="sec1.1">
                <title>ISARIC-4C Score</title>
                <p>Characteristics examined in the ISARIC-4C mortality score were obtained from each included patient during their admission, as defined by Knight et al.
                    <sup>
                        <xref ref-type="bibr" rid="ref81">21</xref>
                    </sup> The determinant factors include sex, age, respiratory rate (RR), peripheral oxygen saturation (%), Glasgow Coma Scale (GCS) score, urea serum (mmol/L), and C-reactive protein (mmol/L; CRP).
                    <sup>
                        <xref ref-type="bibr" rid="ref6">6</xref>
                    </sup>
                    <sup>,</sup>
                    <sup>
                        <xref ref-type="bibr" rid="ref27">31</xref>
                    </sup> The total scores were categorized into low risk (score 0&#x2013;3), intermediate risk (score 4&#x2013;8), high risk (score 9&#x2013;14), and very high risk (score &#x2265; 15).
                    <sup>
                        <xref ref-type="bibr" rid="ref81">21</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec5">
                <title>Statistical analysis</title>
                <p>Statistical Package for the Social Sciences (SPSS) version 27 for Macintosh was used to analyze the data that was collected. The serum 25(OH) D levels between two subgroups were analyzed with either Mann-Whitney U test for 2 subgroups and Kruskal-Wallis test for more than 2 subgroups.</p>
            </sec>
            <sec id="sec6">
                <title>Ethical approval</title>
                <p>Ethical approval for this study was granted by Ethics Committee of the Faculty of Medicine, Universitas Indonesia (ethical approval number: KET533/UN2.F1/ETIK/PPM.00.01/2021) and by the Ethics Committee of Wisma Atlet Hospital Jakarta (029/KERSDCWA/2021). The Declaration of Helsinki was implemented during this study.</p>
            </sec>
        </sec>
        <sec id="sec7" sec-type="results">
            <title>Results</title>
            <p>This cross-sectional study included 191 subjects. Before being enrolled, each participant signed a written consent form. The characteristics of the included subjects can be observed in 
                <xref ref-type="table" rid="T1">Table 1</xref>. From the 191 subjects, 54.5% were female.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Subject characteristics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N = 191</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Age, median [IQR]</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">42 [28]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Serum 25(OH) D level, median [IQR], in ng/mL</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13.6 [10.98]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Sex, N (%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">104 (54.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">87 (45.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Body mass index (BMI), median [IQR]</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">22.66 [4.13]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">COVID-19 categories, n (%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">93 (48.7)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Moderate</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">67 (35.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Severe &#x2013; critical</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Number of comorbid, N (%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">None</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">72 (37.7)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">40 (20.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">79 (41.4)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Type of comorbidities</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Type 2 DM, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">63 (32.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Hypertension, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">60 (31.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Cardiovascular disease, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (8.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Chronic liver disease, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Chronic kidney failure, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">19 (9.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Cerebrovascular disease, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Malignancy, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">19 (9.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">HIV, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.6)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Autoimmune diseases, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">COPD, N (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Vaccination status, n (%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Unvaccinated</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">60 (31.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">One dose</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Two doses</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (67.1)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Three doses</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Simple oxygenation, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">61 (31.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">ISARIC-4C Score, N (%)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Low risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">109 (57)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Intermediate risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">39 (20.4)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">High risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Very high risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Abbreviations: COPD, chronic obstructive pulmonary disease; Type 2 DM, Type 2 Diabetes Mellitus.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>Subjects who had a history of diabetes mellitus, peripheral vascular disease, stroke or transient ischaemic index, cardiovascular disease, chronic obstructive pulmonary disease, chronic liver disease, and chronic kidney disease were considered to have comorbidities according to the Charlson Comorbidity Index (CCI).
                <sup>
                    <xref ref-type="bibr" rid="ref24">28</xref>
                </sup>
            </p>
            <p>
                <xref ref-type="table" rid="T2">Table 2</xref> provided the significance levels of serum 25(OH) D level across all included subgroups using the chi-square (&#x03c7;
                <sup>2</sup>) analysis. Vitamin D deficiency was found in 74.4% of COVID-19 patients, including 65.4% of patients under the age of 60 and 11% of patients over the age of 60. Lower serum 25(OH) D levels were associated with an increased number of comorbidities, the severity of COVID-19, and the use of mechanical ventilation. Among 191 patients, mortality was found in 7.3% of patients with deficient vitamin D levels. However, subjects with either sufficient or insufficient vitamin D levels did not develop mortality.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>The categorized levels of serum 25(OH) D levels based on the influencing factors.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">Categories</th>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="3" rowspan="1" valign="top">Serum 25(OH) D Level</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">p</italic>-value</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Deficient (
                                <inline-formula>
                                    <mml:math display="inline">
                                        <mml:mo>&#x2264;</mml:mo>
                                    </mml:math>
                                </inline-formula>20 ng/mL)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Insufficient (21-29 ng/mL)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Sufficient (&#x2265;30 ng/mL)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Age</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.928</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="2"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2264;60 years old</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">164 (85.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">125 (65.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">30 (15.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9 (4.7%)</td>
                            <td colspan="1" rowspan="2"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&gt;60 years old</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">27 (14.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (11.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">5 (2.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">ISARIC-4C score</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.135</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="4"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Low risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">109 (57.07%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">77 (40.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">23 (12%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9 (4.7%)</td>
                            <td colspan="1" rowspan="4"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Intermediate risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">39 (20.42%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">30 (15.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8 (4.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">High risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.23%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">27 (14.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4 (2.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Very high risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.28%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Number of comorbidities</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>0.03</bold>
                            </td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="3"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">72 (37.70%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">42 (24.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (8.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9 (4.7%)</td>
                            <td colspan="1" rowspan="3"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">40 (20.90%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">33 (17.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">79 (41.40%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">67 (35.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Type of comorbidities</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">DM type II</td>
                            <td align="left" colspan="1" rowspan="1" valign="bottom">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (67.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">93 (48.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (13.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.051</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">63 (33.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">53 (27.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Hypertension</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">131 (68.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">96 (50.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (13.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.072</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">60 (31.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">50 (26.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Cardiovascular disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">174 (91.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">133 (69.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.534</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (8.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (6.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4 (2.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Chronic liver disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">185 (96.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">140 (73.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35 (18.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.385</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Chronic kidney disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">172 (90.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (67.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">34 (17.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.136</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">19 (9.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">18 (9.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Malignancy</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">172 (90.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (67.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">34 (17.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.136</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">19 (9.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">18 (9.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">COPD</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">189 (99.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">145 (75.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">34 (17.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.497</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0 %)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">HIV</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">190 (99.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">145 (75.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35 (18.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.856</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="middle">Autoimmune diseases</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">181 (94.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">139 (72.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">32 (16.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.498</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">7 (3.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (1.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">BMI</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.435</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="4"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Underweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">103 (53.93%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">84 (44%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (6.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.1%)</td>
                            <td colspan="1" rowspan="4"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Normoweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8 (4.19%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6 (3.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Overweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">34 (17.80%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (13.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8 (4.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Obesity grade I</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">46 (24.08%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (1.6%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mortality</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.097</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="2"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">177 (92.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">132 (69.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35 (18.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td colspan="1" rowspan="2"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (7.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">14 (7.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">COVID-19 severity</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>0.002</bold>
                            </td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="3"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">93 (48.69%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">62 (32.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (11.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td colspan="1" rowspan="3"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Moderate</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">67 (35.07%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">55 (28.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (6.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Severe</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">31 (16.24%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">29 (15.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Vaccine doses</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.339</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="4"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">60 (31.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">52 (27.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">7 (3.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td colspan="1" rowspan="4"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (1.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (67.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">91 (47.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">28 (14.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9 (4.7%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">HFNC or ventilator use</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>0.032</bold>
                            </td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="2"/>
                            <td align="left" colspan="1" rowspan="1" valign="middle">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">171 (89.53%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">126 (66%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35 (18.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (5.2%)</td>
                            <td colspan="1" rowspan="2"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (10.50%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">20 (10.5%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0 (0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="bottom">
                                <bold>Total</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>191 (100%)</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="bottom">
                                <bold>146 (76.4%)</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="bottom">
                                <bold>35 (18.4%)</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="bottom">
                                <bold>10 (5.2)</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Abbreviations: BMI, body mass index; HFNC, High-flow nasal canule; DM type II, diabetes mellitus type II; HIV, human immunodeficiency virus; COPD, chronic obstructive pulmonary disease</p>
                    <p>Bold value denotes statistical significance.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T3">Table 3</xref> showed that serum 25(OH) D levels were significantly lower among COVID-19 patients with vitamin D deficiency who had cardiovascular disease, the use of a ventilator, more severe COVID-19 cases, and mortality. Mortality was found in 9.59% of COVID-19 patients with vitamin D deficiency.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>The effect of vitamin D deficiency among each subgroup.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">Categories</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">N (%)</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">Serum 25(OH) D Level</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Mean &#x00b1; SD or median [IQR], in ng/mL</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
                                <italic toggle="yes">p</italic>-value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Age groups</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;60 years old</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">125 (85.62%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.94 [7.69]</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.186
                                <xref ref-type="table-fn" rid="tfn1">
                                    <sup>a</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;60 years old</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (14.38%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.74 &#x00b1; 5.15</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="4" valign="top">ISARIC-4C score</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Low risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">77 (52.74%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.07 &#x00b1; 4.55</td>
                            <td align="left" colspan="1" rowspan="4" valign="middle">0.067
                                <xref ref-type="table-fn" rid="tfn2">
                                    <sup>b</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Intermediate risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30 (20.55%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.75 &#x00b1; 4.73</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">High risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27 (18.49%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.22 &#x00b1; 5.09</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Very high risk</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12 (8.22%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.97 &#x00b1; 6.15</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">Number of comorbidities</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">46 (31.51%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.30 [8.06]</td>
                            <td align="left" colspan="1" rowspan="3" valign="middle">0.133
                                <xref ref-type="table-fn" rid="tfn3">
                                    <sup>c</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33 (22.60%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.90 &#x00b1; 4.60</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">67 (45.89%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.52 &#x00b1; 5.12</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Type of comorbidities</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">DM type II</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">93 (63.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.05 &#x00b1; 4.79</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.675
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53 (36.30%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.41 &#x00b1; 5.12</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Hypertension</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">96 (65.75%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.21 &#x00b1; 4.84</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.914
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">50 (34.25%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.12 &#x00b1; 5.05</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Cardiovascular disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">133 (91.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.44 &#x00b1; 4.85</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>0.040</bold>
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>
                                        <bold>d</bold>
                                    </sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13 (8.90%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.52 &#x00b1; 4.72</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Chronic kidney disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">128 (87.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.49 &#x00b1; 4.72</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.051
                                <xref ref-type="table-fn" rid="tfn1">
                                    <sup>a</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18 (12.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.75 [9.56]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Malignancy</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">128 (87.67%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.37 &#x00b1; 4.93</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.211
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18 (12.33%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.83 &#x00b1; 4.56</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="4" valign="top">BMI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Underweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">84 (57.53%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.73 [8.09]</td>
                            <td align="left" colspan="1" rowspan="4" valign="middle">0.082
                                <xref ref-type="table-fn" rid="tfn3">
                                    <sup>c</sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Normoweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6 (4.11%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.97 &#x00b1; 3.54</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Overweight</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25 (17.12%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.47 &#x00b1; 4.90</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Obesity grade I</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">31 (21.23%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.93 &#x00b1; 4.94</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Mortality rate</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">132 (90.41%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.58 &#x00b1; 4.80</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>0.002</bold>
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>
                                        <bold>d</bold>
                                    </sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14 (9.59%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.44 &#x00b1; 4.26</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">COVID-19 severity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">62 (42.47%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.78 &#x00b1; 4.62</td>
                            <td align="left" colspan="1" rowspan="3" valign="middle">
                                <bold>0.047</bold>
                                <xref ref-type="table-fn" rid="tfn3">
                                    <sup>
                                        <bold>c</bold>
                                    </sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Moderate</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">55 (37.67%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.04 [6.64]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Severe</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">29 (19.86%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.37 [8.84]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">HFNC or ventilator use</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">126 (86.30%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.66 &#x00b1; 4.70</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>0.004</bold>
                                <xref ref-type="table-fn" rid="tfn1">
                                    <sup>
                                        <bold>a</bold>
                                    </sup>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20 (13.70%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.39 [7.99]</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Abbreviations: BMI, body mass index; DM type II, diabetes mellitus type II; HFNC, High-flow nasal canule.</p>
                    <p>Bold value denotes statistical significance.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>
                                <sup>a</sup>
                            </label>
                            <p>Analyzed using Mann-Whitney U test.</p>
                        </fn>
                        <fn id="tfn2">
                            <label>
                                <sup>b</sup>
                            </label>
                            <p>Analyzed using ANOVA test.</p>
                        </fn>
                        <fn id="tfn3">
                            <label>
                                <sup>c</sup>
                            </label>
                            <p>Analyzed using Kruskal-Wallis test.</p>
                        </fn>
                        <fn id="tfn4">
                            <label>
                                <sup>d</sup>
                            </label>
                            <p>Analyzed using t-test.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>
                <xref ref-type="fig" rid="f1">Figure 1</xref> presented the bivariate analysis performed on COVID-19 patients who were vitamin D deficiency. Serum 25(OH) D levels were significantly different between patients with mild and severe COVID-19 cases (p-value &lt; 0.001). Serum 25(OH) D levels in mild and moderate COVID-19 cases were also significantly different (p-value 0.002).</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>The bivariate analysis of serum 25(OH) D levels based on COVID-19 severity among deficient vitamin D subjects after adjusted with Bonferroni correction.</title>
                    <p>Analyzed using Mann-Whitney U test. Significant at p-value &lt; 0.05. The green double-arrow denotes statistically significant difference. The red double-arrow denotes non-statistically significant difference.</p>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/162135/b2d89749-f2ce-474f-8719-9a9dd32f6e6c_figure1.gif"/>
            </fig>
        </sec>
        <sec id="sec8" sec-type="discussion">
            <title>Discussion</title>
            <p>Prior studies indicates that Indonesia has a high prevalence of deficient vitamin D (60%), despite being located in a tropical zone where sunlight is abundant all year around.
                <sup>
                    <xref ref-type="bibr" rid="ref26">30</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref28">32</xref>
                </sup> Whereas the skin&#x2019;s absorption of sunlight is established as the primary source of vitamin D, other variables, including age, comorbidities, and skin pigmentation, may alter the vitamin D level.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref28">32</xref>
                </sup> Based on the skin&#x2019;s sensitivity to ultraviolet (UV) light, the majority of Indonesians have either Fitzpatrick skin phototype IV (with medium to dark brown) or phototype V (dark brown). A lower vitamin D is associated with darker skin pigmentation due to the higher melanin present in darker skin.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref28">32</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref29">33</xref>
                </sup> Other factors, including haze, altitude, and air pollution, also alter the ultraviolet B radiation.
                <sup>
                    <xref ref-type="bibr" rid="ref28">32</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref30">34</xref>
                </sup>
            </p>
            <p>The beneficial effect of vitamin D to reduce the severity of respiratory tract infection remains controversial.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Prior studies by Luigi et al. have shown that insufficient levels of vitamin D may have a detrimental effect on the prognosis of acute COVID-19, as well as on the development of Long-COVID and the long-term immune response to anti-SARS-CoV-2 vaccination.
                <sup>
                    <xref ref-type="bibr" rid="ref96">35</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref98">37</xref>
                </sup> The current study investigated the association of vitamin D deficiency to the clinical outcome of hospitalized patients at two COVID-19 referral hospitals in Indonesia. We found that compared to insufficient and sufficient, those with deficient vitamin D status had more number of comorbidities (
                <xref ref-type="table" rid="T2">Table 2</xref>). In COVID-19 patients with deficient vitamin D were significantly associated with cardiovascular disease (
                <xref ref-type="table" rid="T3">Table 3</xref>). Our findings was supported by de la Gu&#x00ed;a-Galipienso 
                <italic toggle="yes">et al.</italic>, that revealed vitamin D deficiency may play a critical role in the initiation of inflammation, myocardial calcification, and endothelial dysfunction, which are risk factors for cardiovascular disease.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref32">38</xref>
                </sup> The vitamin D receptor (VDR) and the enzyme 1&#x03b1;-hydroxylase, which are necessary for the formation of vitamin D&#x2019;s active form, are expressed in cardiomyocytes, vascular endothelial cells, fibroblasts, and smooth muscle cells.
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref36">42</xref>
                </sup> Left ventricular hypertrophy, vascular dysfunction, and arterial stiffness have been associated with vitamin D deficiency. A deficiency of the vitamin D receptor causes an increase in left ventricular mass and elevated levels of atrial natriuretic peptide, as well as cardiac metalloproteases and disturbances in homeostasis. Furthermore, the development of fibrotic extracellular matrix induces left ventricular dilation.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref37">43</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref38">44</xref>
                </sup>
            </p>
            <p>Vitamin D has been shown to have a number of beneficial effects on the cardiovascular system, including natriuretic peptide secretion, inhibition of the renin-angiotensin-aldosterone system (RAAS), anti-hypertrophic effects, and inhibition of cardiomyocyte proliferation.
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref39">45</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref40">46</xref>
                </sup> Calcitriol and its analogues activate VDR, which directly suppresses angiotensin I expression and local angiotensin II synthesis in myocardial, kidney tissue, and renal arteries.
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref41">47</xref>
                </sup> Studies have revealed that vitamin D enhances the anti-hypertensive effects of angiotensin 1&#x2013;7 by inducing the production of angiotensin-converting enzyme 2 (ACE2).
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref42">48</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref43">49</xref>
                </sup> MiR-106b-5p, which acts on juxtaglomerular cells to boost renin synthesis, has been shown to be directly influenced by VDR-deficient immune cells.
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref43">49</xref>
                </sup>
            </p>
            <p>Moreover, vitamin D affects the progression of HF through modulating the production of metalloproteinases. Evidence strongly suggests that vitamin D has an anti-inflammatory effect by preventing nuclear factor kappa B (NF-&#x03ba;B) and promoting the production of IL-10, which have a significant role in the progression of CVD.
                <sup>
                    <xref ref-type="bibr" rid="ref33">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref44">50</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref45">51</xref>
                </sup> Vitamin D deficiency induces arterial stiffness and endothelial dysfunction in blood vessels, which in turn leads to enhanced inflammation, endothelial cell malfunction, and atherogenesis.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref46">52</xref>
                </sup>
            </p>
            <p>The severity of COVID-19 were significantly associated with the lower serum 25(OH) D levels (
                <xref ref-type="table" rid="T2">Tables 2</xref>, 
                <xref ref-type="table" rid="T3">3</xref> and 
                <xref ref-type="fig" rid="f1">Figure 1</xref>). Vitamin D is an immunomodulatory hormone with antibacterial and anti-inflammatory properties, and it plays a crucial role in the immune system. Vitamin D has been reported to exert its effects against COVID-19 by limiting the viral transmission, diminishing viral replication, and optimizing viral clearance.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref47">53</xref>
                </sup> Vitamin D boosts the innate immune response and protects against excessive inflammation, by increasing anti-inflammatory IL-10 and decreasing pro-inflammatory cytokines and tumor necrosis factor alpha (TNF-&#x03b1;).
                <sup>
                    <xref ref-type="bibr" rid="ref25">29</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref47">53</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref51">57</xref>
                </sup> According to the research of Daneshkhah 
                <italic toggle="yes">et al.</italic>, a lack of vitamin D raises C-reaction protein (CRP) levels, which in turn elevates the risk of a cytokine storm.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref52">58</xref>
                </sup> The protective effects of vitamin D on the coagulation pathway led to a reduced risk of acute respiratory distress syndrome and thrombosis.
                <sup>
                    <xref ref-type="bibr" rid="ref47">53</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref53">59</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref55">61</xref>
                </sup> Thus, increasing vitamin D levels to adequate levels may help to prevent COVID-19 infection and complications.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref47">53</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref48">54</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref53">59</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref56">62</xref>
                </sup>
            </p>
            <p>Futhermore, Sabico 
                <italic toggle="yes">et al.</italic> that conducted a multi-center randomized clinical trial in Middle East, a region with high prevalence of vitamin D deficiency, revealed that a daily oral supplementation of 5000 IU vitamin D3 for 2 weeks reduced the recovery time for gustatory sensory loss and cough among patients with mild to moderate COVID-19 symptoms and sub-optimal vitamin D status.
                <sup>
                    <xref ref-type="bibr" rid="ref78">63</xref>
                </sup>
            </p>
            <p>To the best of our knowledge, this is the first study that analyse the ISARIC-4C score in a group of patients with vitamin D deficiency. We found that serum 25(OH) D levels had no significant association with ISARIC-4C Score (
                <xref ref-type="table" rid="T2">Tables 2</xref>, 
                <xref ref-type="table" rid="T3">3</xref>). In contrast with study by Wellbelove 
                <italic toggle="yes">et al.</italic> that concluded the ISARIC-4C mortality score is good predictors for 30-day mortality in COVID-19 (AUROC of 0.74&#x2013;0.88).
                <sup>
                    <xref ref-type="bibr" rid="ref57">64</xref>
                </sup> The ISARIC-4C consortium established the ISARIC-4C Mortality Score to predict the mortality of hospitalized COVID-19 patients. Multicentre cohort study was conducted among 74,944 participants at 260 different hospitals. However, the ISARIC-4C has been internally validated but not externally validated. Hence, further study is warranted to fully understand the potential of ISARIC-4C as a prognostic tool to classify patients into specific management groups.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref25">29</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref58">65</xref>
                </sup>
            </p>
            <p>Serum 25(OH) D levels were significantly lower among subjects that used the ventilator (
                <xref ref-type="table" rid="T2">Tables 2</xref>, 
                <xref ref-type="table" rid="T3">3</xref>). Among all patients, mortality was found in 7.3% of patients with deficient vitamin D levels. However, patients with either sufficient or insufficient vitamin D levels did not develop mortality (
                <xref ref-type="table" rid="T2">Table 2</xref>). Serum 25(OH) D levels in vitamin D deficiency subjects were significantly lower in the COVID-19 patients with mortality status (
                <xref ref-type="table" rid="T3">Table 3</xref>). Our findings were consistent with the cohort study by Angelidi 
                <italic toggle="yes">et al.</italic> and the single-center retrospective study by Alguwaihes 
                <italic toggle="yes">et al.</italic>, which discovered that lower 25(OH) D levels were associated with increased mechanical ventilation needs and mortality risk among hospitalized patients.
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref79">67</xref>
                </sup>
            </p>
            <p>Prior studies have revealed that vitamin D deficiency has been correlated to a 58% increased risk of acute respiratory infection, prolonged mechanical ventilation, and a 10-fold increase in mortality risk.
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref60">68</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref80">69</xref>
                </sup>
            </p>
            <p>In contrast, a single-center prospective study conducted in the Indian subcontinent, a region with a high prevalence of deficient vitamin D, demonstrated no statistically significant difference in the median length of stay (LOS) between patients with sufficient vitamin D and deficient vitamin D (p-value = 0.176). The LOS for patients with deficient vitamin D was 12 days (95% CI: 10, 12 days), and the LOS for patients with sufficient vitamin D was 11 days (95% CI: 10, 13 days). They also showed that deficient vitamin D (defined as 25(OH) D &lt; 30 ng/mL) in patients with COVID-19 was not associated with the length of hospital stay, the need for mechanical ventilation, or the mortality rate.
                <sup>
                    <xref ref-type="bibr" rid="ref83">70</xref>
                </sup> These different results could be explained by different cut-offs to define deficient vitamin D. In our study, a serum 25(OH) D level of less than 20 ng/mL (50 nmol/L) was considered deficient according to the Endocrine Society Clinical Practice Guidelines.
                <sup>
                    <xref ref-type="bibr" rid="ref31">27</xref>
                </sup> On the other hand, most hospitalized patients with COVID-19 have numerous comorbidities, and this population tends to have lower vitamin D levels. Another cohort study by Luigi et al., which excluded the effect of reverse causality and the concomitant comorbidities, demonstrated that vitamin D levels upon admission to the hospital can be used to prospectively predict worse outcomes for both severe and non-severe COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref99">71</xref>
                </sup> Thus, vitamin D levels in such a setting should be interpreted with caution.
                <sup>
                    <xref ref-type="bibr" rid="ref83">70</xref>
                </sup>
            </p>
            <p>As a steroid hormone, vitamin D interacts with the vitamin D receptor located in the nucleus of cells to have physiologic effects.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup> The interaction of 25(OH) D with other steroid hormone receptors may have physiological effects similar to glucocorticoids.
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref61">72</xref>
                </sup> Although the underlying mechanisms of vitamin D&#x2019;s protection against severe COVID-19 are unknown, it is established that vitamin D reduces the production of proinflammatory cytokines such as Th1, TNF-&#x03b1;, interferon-&#x03b2;, IL-6, and promotes the production of anti-inflammatory responses such as T regulatory cells and Th2.
                <sup>
                    <xref ref-type="bibr" rid="ref49">55</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref62">73</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref64">75</xref>
                </sup> There are several explanations for vitamin D&#x2019;s beneficial effects on critically ill patients. Initially, critically ill patients who are given vitamin D supplements will have their plasma vitamin D concentrations restored. Furthermore, vitamin D regulates the synthesis of immune system effector molecules such as &#x03b2;-defensin and cathelicidin, which are both antimicrobial peptide.
                <sup>
                    <xref ref-type="bibr" rid="ref49">55</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref59">66</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref65">76</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref66">77</xref>
                </sup> Cathelicidin enhances the production of anti-inflammatory cytokines while decreasing the synthesis of pro-inflammatory cytokines. As a result, vitamin D deficiency could increase the risk of sepsis and inflammation in severely ill patients by diminishing the immune response and modulatory effects on innate immunity.
                <sup>
                    <xref ref-type="bibr" rid="ref67">78</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref72">83</xref>
                </sup>
            </p>
            <p>Furthermore, several COVID-19 pandemic studies contained some substantial biases and were not representative of the real-world conditions of the COVID-19 pandemic.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref85">85</xref>
                </sup> In regions where authorities implemented home isolation and social distancing measures, individuals with mild to moderate cases of COVID-19 were generally not hospitalized.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref86">86</xref>
                </sup> In contrast, in urban areas experiencing a high prevalence of COVID-19 cases and facing constraint intensive care resources, particularly mechanical ventilation, the majority of the hospital admissions were primarily for the individuals with severe or critical cases of COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref87">87</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref89">89</xref>
                </sup> Hospitalized people from a single center or a few centers were unlikely to represent the distribution of COVID-19 cases in an area. Also, there were evident selection biases in why and where people were hospitalized in these studies.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref90">90</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref91">91</xref>
                </sup> Multiple studies have reported the presence of censoring among subjects who were still hospitalized leading to potential biases in the interpretation of the findings.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref87">87</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref92">92</xref>
                </sup> On the contrary, we were able to identify every COVID-19 patient in our area, all of whom were admitted to the hospital. We also conducted a comprehensive follow-up for all the patients. The characteristics of our subjects were more similar to they who were exposed to the SARS-CoV-2 infection in a non-epidemic setting. As the result, our study provided a significant potential for widespread applicability and reflected the real-world conditions of the COVID-19 pandemic.
                <sup>
                    <xref ref-type="bibr" rid="ref84">84</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref93">93</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref95">95</xref>
                </sup>
            </p>
            <p>The strength of this study lies in the fact that it is the first study to analyze the ISARIC-4C Score in COVID-19 patients with deficient vitamin D. The majority of this study&#x2019;s data were collected during the Omicron variation&#x2019;s development and can be utilized to make comparisons to the Delta variant or any other variants. However, this study has several limitations that should be considered to improve the further research. First, this study did not include a healthy control group as a reference population. Second, after patients were discharged, serum 25(OH) D levels were not measured. Third, the observational design and small sample size could potentially miss an important finding in this present study. Fourth, we did not collect any information on the use of vitamin D supplementation. Fifth, it was not possible to determine the impact of disease on vitamin D levels due to reverse causality. Furthermore, considering the established associations between vitamin D levels and comorbidities, and relationship between comorbidities and COVID-19 outcomes, it is difficult not to consider the possibility that vitamin D may become an epiphenomenon typically present in those with a more severe disease.</p>
            <p>Hence, despite these limitations, our study clearly showed that lower vitamin D levels at admission represent a strong and reliable factor predicting worse outcomes. We demonstrates that hospitalized COVID-19 patients with vitamin D deficiency had a higher risk of using mechanical ventilation and mortality from respiratory failure and other complications. Additionally, a prior meta-analysis revealed that people with a deficient vitamin D level had an increased risk of SARS-CoV-2 infection and COVID-19-related hospitalization. Our data are consistent with the findings of recent pilot studies and a meta-analysis showing that a sufficient vitamin D status is able to reduce COVID-19 severity, indicating that it may be beneficial in minimizing the clinical and economic burden associated with COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref73">96</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref75">98</xref>
                </sup>
            </p>
        </sec>
        <sec id="sec9" sec-type="conclusion">
            <title>Conclusion</title>
            <p>We found that lower serum 25(OH) D levels were associated with an increased number of comorbidities, COVID-19 severity, and the use of mechanical ventilation. COVID-19 patients with vitamin D deficiency status were significantly associated with having cardiovascular disease, mortality, more severe COVID-19 cases, and the used of high-flow nasal canule (HFNC) or ventilator. This study doesn&#x2019;t diminish the significance of the continuing vaccine effort against the health-economic burden of SARS-CoV-2 infection. As a result, we strongly suggest achieving sufficient vitamin D status, which may serve as an important adjuvant strategy to improve clinical outcomes before vaccines become widely available.</p>
        </sec>
    </body>
    <back>
        <sec id="sec12" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec13">
                <title>Underlying data</title>
                <p>Figshare: Impact of Vitamin D Deficiency in Relation to the Clinical Outcomes of Hospitalized COVID-19 Patients, DOI: 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.22145768.v2">https://doi.org/10.6084/m9.figshare.22145768.v2</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref76">99</xref>
</sup>
                </p>
                <p>This project contains the following data:
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>The data here is only for research paper validation of corresponding author Andhika Rachman entitled: &#x201c;Impact of Vitamin D Deficiency in Relation to the Clinical Outcomes of Hospitalized COVID-19 Patients&#x201d;. The raw data consists of subjects characteristics and the levels of serum 25-hydroxy-vitamin D of hospitalized COVID-19 patients.
</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://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>
        <ack>
            <title>Acknowledgements</title>
            <p>The authors would like to thank all the participants for their involvement.</p>
        </ack>
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    <sub-article article-type="reviewer-report" id="report243971">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.162135.r243971</article-id>
            <title-group>
                <article-title>Reviewer response for version 4</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>di Filippo</surname>
                        <given-names>Luigi</given-names>
                    </name>
                    <xref ref-type="aff" rid="r243971a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r243971a1">
                    <label>1</label>Institute of Endocrine and Metabolic Sciences, Universit&#x00e0; Vita-Salute San Raffaele, IRCCS Ospedale San Raffaele, Milan, Italy</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>27</day>
                <month>2</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 di Filippo L</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="relatedArticleReport243971" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.4"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Approved</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>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>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>endocrine diseases</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="report233579">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.155718.r233579</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Chen</surname>
                        <given-names>Guo-Xun</given-names>
                    </name>
                    <xref ref-type="aff" rid="r233579a1">1</xref>
                    <xref ref-type="aff" rid="r233579a2">2</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r233579a1">
                    <label>1</label>College of Food Science and Technology at Huazhong Agricultural University, Huazhong Agricultural University, Wuhan, Hubei, China</aff>
                <aff id="r233579a2">
                    <label>2</label>Department of Nutrition, University of Tennessee, Knoxville, USA</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>19</day>
                <month>1</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Chen GX</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="relatedArticleReport233579" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.3"/>
            <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 association studies like this does not ensure that there is a role of vitamin D (VD) deficiency in COVID-19 outcomes. VD deficiency has been associated with many diseases. However, its supplementation appears to lack conclusions. It will be helpful to show that VD supplementation will help outcomes of COVID-19. Without it, the value of this study is limited.</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>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>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Biochemistry and nutrition.</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>
        <sub-article article-type="response" id="comment10991-233579">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Rachman</surname>
                            <given-names>Andhika</given-names>
                        </name>
                        <aff>Internal Medicine, Universitas Indonesia, Jakarta, DKI Jaya, Indonesia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>Authors have no conflict of interest to declare.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>31</day>
                    <month>1</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Dear Doctor Guo-xun Chen,</p>
                <p> Thank you for your valuable advice.</p>
                <p> </p>
                <p> The objective of this study was to examine the association between vitamin D serum level deficiency and the clinical outcomes of hospitalized COVID-19 patients. Unfortunately, we did not collect any information on the use of vitamin D supplementation. Thus, we mentioned this as one of our limitation that should be considered in order to improve further study design.</p>
                <p> </p>
                <p> Please don't be hesitant to respond if you have any concerns or suggestions about the revised manuscript. If you have any further suggestion, please don&#x2019;t hesitate to contact us.</p>
                <p> </p>
                <p> </p>
                <p> Sincerely,</p>
                <p> Andhika Rachman, MD, PhD</p>
                <p> Medical staff, Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report233590">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.155718.r233590</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>di Filippo</surname>
                        <given-names>Luigi</given-names>
                    </name>
                    <xref ref-type="aff" rid="r233590a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r233590a1">
                    <label>1</label>Institute of Endocrine and Metabolic Sciences, Universit&#x00e0; Vita-Salute San Raffaele, IRCCS Ospedale San Raffaele, Milan, Italy</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>4</day>
                <month>1</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 di Filippo L</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="relatedArticleReport233590" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.3"/>
            <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>Dear Editor,</p>
            <p> thanks for the opportunity to revise the manuscript &#x201c;Impact of vitamin D deficiency in relation to the clinical outcomes of hospitalized COVID-19 patients&#x201d; submitted by Dr. Rachman et al.</p>
            <p> The authors aimed to evaluate the impact of vitamin D deficiency on COVID-19 outcomes and reported lower vitamin D as potential risk factor, consistently with the most available literature.</p>
            <p> The authors had the novelty to use ISARIC-4C Score in assessing COVID-19 severity.</p>
            <p> The main limitation of the study is in assessment of vitamin D levels at admission in hospital where a proper exclusion of effects of disease in lowering vitamin D levels as an effect of reverse causality was not possible. Moreover, given the known associations and relationships between vitamin D levels and comorbidities, and, at the same time, comorbidities and COVID-19 outcomes, it is not possible to exclude that vitamin D should be represent only an epiphenomenon typically present in those with a more severe disease.</p>
            <p> Besides these limitations, that should be mentioned in the paper, the authors clearly show that lower vitamin D levels at admission represent a strong and reliable factor predicting worse outcomes. In this light, authors should mention that vitamin D levels, evaluated at admission in hospital, were previously demonstrated to prospectively predict worse outcomes in both those with severe and non-severe disease (therefore, excluding the reverse causality effect) also in multivariate analyses (therefore, excluding the effect of concomitant comorbidities) (DOI: 10.1007/s12020-023-03331-9).</p>
            <p> In addition, should be of interest for the readers, to mention the
                <bold> </bold>novelties
                <bold> </bold>regarding vitamin D role in Long COVID and COVID-19 vaccination (DOI: 10.1210/clinem/dgad207; DOI: 10.1210/clinem/dgad327 ; DOI: 10.1007/s12020-023-03481-w).</p>
            <p> Thanks.</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>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>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>endocrine diseases</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>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-233590-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Lack of vitamin D predicts impaired long-term immune response to COVID-19 vaccination.</article-title>
                        <source>
                            <italic>Endocrine</italic>
                        </source>.<year>2023</year>;<volume>82</volume>(<issue>3</issue>) :
                        <elocation-id>10.1007/s12020-023-03481-w</elocation-id>
                        <fpage>536</fpage>-<lpage>541</lpage>
                        <pub-id pub-id-type="pmid">37592162</pub-id>
                        <pub-id pub-id-type="doi">10.1007/s12020-023-03481-w</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-233590-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Low vitamin D levels predict outcomes of COVID-19 in patients with both severe and non-severe disease at hospitalization.</article-title>
                        <source>
                            <italic>Endocrine</italic>
                        </source>.<year>2023</year>;<volume>80</volume>(<issue>3</issue>) :
                        <elocation-id>10.1007/s12020-023-03331-9</elocation-id>
                        <fpage>669</fpage>-<lpage>683</lpage>
                        <pub-id pub-id-type="pmid">36854858</pub-id>
                        <pub-id pub-id-type="doi">10.1007/s12020-023-03331-9</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment10990-233590">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Rachman</surname>
                            <given-names>Andhika</given-names>
                        </name>
                        <aff>Internal Medicine, Universitas Indonesia, Jakarta, DKI Jaya, Indonesia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>Authors have no conflict of interest to declare.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>31</day>
                    <month>1</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Dear Doctor Luigi di Filippo,</p>
                <p> Thank you for your and time consideration in handling our manuscript.</p>
                <p> </p>
                <p> 1. The main limitation of the study is in assessment of vitamin D levels at admission in hospital where a proper exclusion of effects of disease in lowering vitamin D levels as an effect of reverse causality was not possible. Moreover, given the known associations and relationships between vitamin D levels and comorbidities, and, at the same time, comorbidities and COVID-19 outcomes, it is not possible to exclude that vitamin D should be represent only an epiphenomenon typically present in those with a more severe disease. Besides these limitations, that should be mentioned in the paper, the authors clearly show that lower vitamin D levels at admission represent a strong and reliable factor predicting worse outcomes.</p>
                <p> </p>
                <p> &#8232;Response: Thank you for your constructive comments. We have improved our paper by considering these as our limitations of the study.</p>
                <p> </p>
                <p> Fifth, it was not possible to determine the impact of disease on vitamin D levels due to reverse causality. Furthermore, considering the established associations between vitamin D levels and comorbidities, and relationship between comorbidities and COVID-19 outcomes, it is difficult not to consider the possibility that vitamin D may become an epiphenomenon typically present in those with a more severe disease.</p>
                <p> Hence, despite these limitations, our study clearly showed that lower vitamin D levels at admission represent a strong and reliable factor predicting worse outcomes.</p>
                <p> </p>
                <p> 2. In this light, authors should mention that vitamin D levels, evaluated at admission in hospital, were previously demonstrated to prospectively predict worse outcomes in both those with severe and non-severe disease (therefore, excluding the reverse causality effect) also in multivariate analyses (therefore, excluding the effect of concomitant comorbidities) (DOI: 10.1007/s12020-023-03331-9).</p>
                <p> </p>
                <p> Response:</p>
                <p> We appreciate the helpful feedback you provided, which allowed us to improve our work. We have added more details on our discussion section.</p>
                <p> </p>
                <p> Another cohort study by Luigi et al., which excluded the effect of reverse causality and the concomitant comorbidities, demonstrated that vitamin D levels upon admission to the hospital can be used to prospectively predict worse outcomes for both severe and non-severe COVID-19.</p>
                <p> </p>
                <p> Moreover, it is not possible to conduct a multivariate analysis in this study as vitamin D level was the only independent variable in this study. Combining them with any comorbidity (Hypertension, Chronic kidney disease, diabetes mellitus type II, etc.) or vaccination implies that vitamin D is not an independent variable as both comorbidity and COVID-19 vaccination have been already found to be associated with vit D level.</p>
                <p> </p>
                <p> 3. In addition, should be of interest for the readers, to mention the
                    <bold> </bold>novelties
                    <bold> </bold>regarding vitamin D role in Long COVID and COVID-19 vaccination (DOI: 10.1210/clinem/dgad207; DOI: 10.1210/clinem/dgad327 ; DOI: 10.1007/s12020-023-03481-w).</p>
                <p> </p>
                <p> Response:</p>
                <p> Thank you for your insightful advice that helped us improve our work. We have added more details on our discussion section.</p>
                <p> </p>
                <p> Prior studies by Luigi 
                    <italic>et al</italic>. have shown that insufficient levels of vitamin D may have a detrimental effect on the prognosis of acute COVID-19, as well as on the development of Long-COVID and the long-term immune response to anti-SARS-CoV-2 vaccination.</p>
                <p> </p>
                <p> Please don't be hesitant to respond if you have any concerns or suggestions about the revised manuscript. If you have any suggestions, we would greatly appreciate hearing them.</p>
                <p> </p>
                <p> Sincerely,</p>
                <p> Andhika Rachman, MD, PhD</p>
                <p> Medical staff, Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report205417">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.155718.r205417</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Koul</surname>
                        <given-names>Parvaiz A</given-names>
                    </name>
                    <xref ref-type="aff" rid="r205417a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-1700-9285</uri>
                </contrib>
                <aff id="r205417a1">
                    <label>1</label>Department&#x00a0;of&#x00a0;Pulmonary&#x00a0;Medicine, Sher-i-Kashmir&#x00a0;Institute&#x00a0;of&#x00a0;Medical&#x00a0;Sciences, Srinagar, Jammu&#x00a0;and&#x00a0;Kashmir, India</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>17</day>
                <month>10</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Koul PA</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport205417" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>While the authors have made changes and updated the references, the moot question of hospitalising mild cases of COVID remains unanswered and that in my opinion is a significant enough reason for me to recommend 'Not Approved' for the revision too.</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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No</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>No</p>
            <p>Reviewer Expertise:</p>
            <p>NA</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>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report197568">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.148441.r197568</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Koul</surname>
                        <given-names>Parvaiz A</given-names>
                    </name>
                    <xref ref-type="aff" rid="r197568a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-1700-9285</uri>
                </contrib>
                <aff id="r197568a1">
                    <label>1</label>Department&#x00a0;of&#x00a0;Pulmonary&#x00a0;Medicine, Sher-i-Kashmir&#x00a0;Institute&#x00a0;of&#x00a0;Medical&#x00a0;Sciences, Srinagar, Jammu&#x00a0;and&#x00a0;Kashmir, India</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>29</day>
                <month>8</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Koul PA</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport197568" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.2"/>
            <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 manuscript provides an analysis of vitamin D levels in 189 patients with COVID-19 in Indonesia and correlates the vitamin D levels with the outcomes of illness using ISARIC-4C mortality score among others. While the concept of the study is good in a tropical country with high sunlight exposure, there are some issues in design that make me uncomfortable for the interpretation of the results. 
                <list list-type="order">
                    <list-item>
                        <p>The study has been put forth as a 'cohort' study. However it obviously is not a longitudinal one and hence needs to be classified as an observational cross sectional study.</p>
                    </list-item>
                    <list-item>
                        <p>The biggest issue in design is as to why were patients with mild COVID 19 illness included and hospitalized. No guidelines recommend hospital admission of mild cases of COVID 19 and inclusion of these cases involves a serious issue in design which would clearly affect the outcomes of the patients and the results of the study. Inclusion and the very hospitalization of such cases is as such flawed and seriously affects the results.&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>The details of the ISARIC-$C Mortality score should normally be a part of the Methods section. While the authors mention this as the first usage in COVID-19 studies, they have not unfortunately described this in the appropriate section of the manuscript.</p>
                    </list-item>
                    <list-item>
                        <p>An important study from India is missing from the 'Discussion' section. The study is also from an area where we expect abundance of sunlight too. In this study (Dhar A, Mir H, Koul PA. Vitamin D Levels and Length of Hospitalization in Indian Patients With COVID-19: A Single-Center Prospective Study. Cureus. 2022 Jul 9;14(7):e26704. doi: 10.7759/cureus.26704. PMID: 35959182; PMCID: PMC9359910.) of 200 patients, there was no statistically significant difference in the length of hospital stay between patients with normal serum vitamin D (VDS) and those with VDD, median LOS being 12 days (95% CI: 10, 12 days) in VDD cases and 11 days (95% CI: 10,13 days) in VDS cases (p = 0.176). The authors concluded that&#x00a0;In Indian patients, baseline vitamin D levels are not associated with the length of hospital stay, need for mechanical ventilation, or mortality.</p>
                        <p> </p>
                        <p> Such discrepant studies need to be part of the discussion of a study like the one that authors have conducted and the possible reasons for such dichotomy proposed.&#x00a0;</p>
                    </list-item>
                </list>
            </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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No</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>No</p>
            <p>Reviewer Expertise:</p>
            <p>Pulmonary Medicine</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-197568-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Vitamin D Levels and Length of Hospitalization in Indian Patients With COVID-19: A Single-Center Prospective Study.</article-title>
                        <source>
                            <italic>Cureus</italic>
                        </source>.<year>2022</year>;<volume>14</volume>(<issue>7</issue>) :
                        <elocation-id>10.7759/cureus.26704</elocation-id>
                        <fpage>e26704</fpage>
                        <pub-id pub-id-type="pmid">35959182</pub-id>
                        <pub-id pub-id-type="doi">10.7759/cureus.26704</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment10186-197568">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Rachman</surname>
                            <given-names>Andhika</given-names>
                        </name>
                        <aff>Internal Medicine, Universitas Indonesia, Jakarta, DKI Jaya, Indonesia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>The authors declare that we have no conflict of interest.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>6</day>
                    <month>9</month>
                    <year>2023</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Dear Prof. Parvaiz Koul,</p>
                <p> We sincerely appreciate the time and consideration you have provided in reviewing our manuscript.</p>
                <p> </p>
                <p> We would like to confirm that we have made revisions to the manuscript using the &#x201c;track changes&#x201d; system.</p>
                <p> </p>
                <p> If you have any further suggestion, please don&#x2019;t hesitate to contact us.</p>
                <p> </p>
                <p> Sincerely,</p>
                <p> Andhika Rachman, PhD</p>
                <p> Medical staff, Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital</p>
                <p> </p>
                <p> </p>
                <p> </p>
                <p> The manuscript provides an analysis of vitamin D levels in 189 patients with COVID-19 in Indonesia and correlates the vitamin D levels with the outcomes of illness using ISARIC-4C mortality score among others. While the concept of the study is good in a tropical country with high sunlight exposure, there are some issues in design that make me uncomfortable for the interpretation of the results.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>1.&#x00a0;</bold>The study has been put forth as a 'cohort' study. However it obviously is not a longitudinal one and hence needs to be classified as an observational cross sectional study.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Response:</bold>
                </p>
                <p> The reviewer did raise a very important concern which will improve our manuscript. We agree with the reviewer&#x2019;s constructive comments that our study is an observational cross sectional study.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>2.&#x00a0;</bold>The biggest issue in design is as to why were patients with mild COVID 19 illness included and hospitalized. No guidelines recommend hospital admission of mild cases of COVID 19 and inclusion of these cases involves a serious issue in design which would clearly affect the outcomes of the patients and the results of the study. Inclusion and the very hospitalization of such cases is as such flawed and seriously affects the results.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Response:</bold>
                </p>
                <p> We appreciate your constructive suggestions. We have provided additional explanations regarding the inclusion criteria in both the methods and discussion sections.</p>
                <p> </p>
                <p> During the initial phase of the pandemic, Indonesia encountered a challenging situation as it emerged as the first and enduring epicenter. The incidence of positive cases and deaths&#x00a0;has experienced a significant surge, leading to the highest numbers in the Southeast Asian region. The Indonesian government has established a national policy that emphasizes emergency&#x00a0;hospitals, which are intended to&#x00a0;isolate mild cases and stop&#x00a0;community transmission. This Indonesian government strategy has been proven to approach disease containment successfully in Wuhan, China, which was reflected by a significantly reduced COVID-19 mortality rate.
                    <sup>&#x00a0;</sup>Thus, this study includes patients who have been registered with mild, moderate, or severe disease in accordance with the policy established by the Indonesian government.
                    <sup>82</sup>
                </p>
                <p> </p>
                <p> Furthermore, several COVID-19 pandemic studies contained some substantial biases and were not representative of the real-world conditions of the COVID-19 pandemic.
                    <sup>84,85</sup> In regions where authorities implemented home isolation and social distancing measures, individuals with mild to moderate cases of COVID-19 were generally not hospitalized.
                    <sup>84,86</sup> In contrast, in urban areas experiencing a high prevalence of COVID-19 cases and facing constraint intensive care resources, particularly mechanical ventilation, the majority of the hospital admissions were primarily for the individuals with severe or critical cases of COVID-19
                    <sup>.84,87,88,89</sup> Hospitalized people from a single center or a few centers were unlikely to represent the distribution of COVID-19 cases in an area. Also, there were evident selection biases in why and where people were hospitalized in these studies.
                    <sup>84,90,91</sup> Multiple studies have reported the presence of censoring among subjects who were still hospitalized leading to potential biases in the interpretation of the findings.
                    <sup>84,87,92</sup> On the contrary, we were able to identify every COVID-19 patient in our area, all of whom were admitted to the hospital. We also conducted a comprehensive follow-up for all the patients. The characteristics of our subjects were more similar to they who were exposed to the SARS-CoV-2 infection in a non-epidemic setting. As the result, our study provided a significant potential for widespread applicability and reflected the real-world conditions of the COVID-19 pandemic.
                    <sup>84,93,94,95</sup>
                </p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Reference: </bold>
                </p>
                <p> 82. Susanto AD, Rozaliyani A, Prasetyo B, Agustin H, Baskoro H, Arifin AR, et al. Epidemiological and Clinical Features of COVID-19 Patients at National Emergency Hospital Wisma Atlet Kemayoran, Jakarta,Indonesia. Kesmas: National Public Health Journal. 2021;16(1):11-16. 10.21109/kesmas.v0i0.5233</p>
                <p> 83. Dhar A, Mir H, Koul PA. Vitamin D Levels and Length of Hospitalization in Indian Patients With COVID-19: A Single-Center Prospective Study. Cureus. 2022 Jul 9;14(7):e26704. 10.7759/cureus.26704</p>
                <p> 84. Xu J, Wang W, Ye H, Pang W, Pang P, Tang M, et al. A predictive score for progression of COVID-19 in hospitalized persons: a cohort study. NPJ Prim Care Respir Med. 2021 Jun 3;31(1):33.</p>
                <p> 85. Wynants L, Van Calster B, Collins GS, Riley RD, Heinze G, Schuit E, et al. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ. 2020. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1136/bmj.m1328">10.1136/bmj.m1328</ext-link>&#x00a0;</p>
                <p> 86. Gandhi RT, Lynch JB, del Rio C. Mild or Moderate Covid-19. New England Journal of Medicine. 2020 Oct 29;383(18):1757&#x2013;66. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1056/NEJMcp2009249">10.1056/NEJMcp2009249</ext-link>
                </p>
                <p> 87. Galloway JB, Norton S, Barker RD, Brookes A, Carey I, Clarke BD, et al. A clinical risk score to identify patients with COVID-19 at high risk of critical care admission or death: An observational cohort study. Journal of Infection. 2020 Aug;81(2):282&#x2013;8. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.jinf.2020.05.064">10.1016/j.jinf.2020.05.064</ext-link>
                </p>
                <p> 88. Di Bella S, Cesareo R, De Cristofaro P, Palermo A, Sanson G, Roman&#x2010;Pognuz E, et al. Neck circumference as reliable predictor of mechanical ventilation support in adult inpatients with COVID&#x2010;19: A multicentric prospective evaluation. Diabetes Metab Res Rev. 2021 Jan 14;37(1). 
                    <sup>1</sup>
                </p>
                <p> 89. Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. Journal of Allergy and Clinical Immunology. 2020 Jul;146(1):110&#x2013;8. 10.1016/j.jaci.2020.04.006</p>
                <p> 90. Liang W hua, Guan W jie, Li C chen, Li Y min, Liang H rui, Zhao Y, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China. European Respiratory Journal. 2020 Jun;55(6):2000562. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1183/13993003.00562-2020">10.1183/13993003.00562-2020</ext-link>
                </p>
                <p> 91. Bialek S, Bowen V, Chow N, Curns A, Gierke R, Hall A, et al. Geographic Differences in COVID-19 Cases, Deaths, and Incidence &#x2014; United States, February 12&#x2013;April 7, 2020. MMWR Morb Mortal Wkly Rep. 2020 Apr 17;69(15):465&#x2013;71.</p>
                <p> 92. Gong J, Ou J, Qiu X, Jie Y, Chen Y, Yuan L, et al. A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): A Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China. Clinical Infectious Diseases. 2020 Jul 28;71(15):833&#x2013;40. 10.1093/cid/ciaa443</p>
                <p> 93. Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. 2020 Jun;20(6):669&#x2013;77</p>
                <p> 94. Wu JT, Leung K, Bushman M, Kishore N, Niehus R, de Salazar PM, et al. Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nat Med. 2020 Apr 1;26(4):506&#x2013;10.</p>
                <p> 95. Bialek S, Boundy E, Bowen V, Chow N, Cohn A, Dowling N, et al. Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) &#x2014; United States, February 12&#x2013;March 16, 2020. MMWR Morb Mortal Wkly Rep. 2020 Mar 27;69(12):343&#x2013;6.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>3.&#x00a0;</bold>The details of the ISARIC-$C Mortality score should normally be a part of the Methods section. While the authors mention this as the first usage in COVID-19 studies, they have not unfortunately described this in the appropriate section of the manuscript.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Response:</bold>
                </p>
                <p> Thank you for your helpful suggestions. We have added and revised the details of the ISARIC-4C Mortality Score in the Method section of the manuscript.</p>
                <p> Characteristics examined in the ISARIC-4C mortality score were obtained from each included patient during their admission, as defined by Knight et al.
                    <sup>81</sup> The determinant factors include sex, age, respiratory rate (RR), peripheral oxygen saturation (%), Glasgow Coma Scale (GCS) score, urea serum (mmol/L), and C-reactive protein (mmol/L; CRP).
                    <sup>6</sup>
                    <sup> ,</sup> 
                    <sup>27</sup>
                    <sup>&#x00a0;</sup>The total scores were categorized into low risk (score 0&#x2013;3), intermediate risk (score 4&#x2013;8), high risk (score 9&#x2013;14), and very high risk (score &#x2265; 15).
                    <sup>81</sup>
                </p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Reference:</bold>
                </p>
                <p> 6. Mohamed RAE, Abdelsalam EM, Maghraby HM, et al.: Performance Features and Mortality Prediction of the 4C Score Early in COVID-19 Infection: A Retrospective Study in Saudi Arabia. 
                    <italic>J. Investig. Med.</italic> 2022 Feb 5;70(2):421&#x2013;427. 34836890 10.1136/jim-2021-001940 PMC8635889</p>
                <p> 27. Gupta RK, Harrison EM, Ho A, et al.: Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study. 
                    <italic>Lancet Respir. Med.</italic> 2021 Apr;9(4):349&#x2013;359. 33444539 10.1016/S2213-2600(20)30559-2 PMC7832571</p>
                <p> 81. Crocker-Buque T, Myles J, Brentnall A, Gabe R, Duffy S, Williams S, et al. Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. PLoS One. 2022 Oct 12;17(10):e0274158</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>4.&#x00a0;</bold>An important study from India is missing from the 'Discussion' section. The study is also from an area where we expect abundance of sunlight too. In this study (Dhar A, Mir H, Koul PA. Vitamin D Levels and Length of Hospitalization in Indian Patients With COVID-19: A Single-Center Prospective Study. Cureus. 2022 Jul 9;14(7):e26704. doi: 10.7759/cureus.26704. PMID: 35959182; PMCID: PMC9359910.) of 200 patients, there was no statistically significant difference in the length of hospital stay between patients with normal serum vitamin D (VDS) and those with VDD, median LOS being 12 days (95% CI: 10, 12 days) in VDD cases and 11 days (95% CI: 10,13 days) in VDS cases (p = 0.176). The authors concluded that&#x00a0;In Indian patients, baseline vitamin D levels are not associated with the length of hospital stay, need for mechanical ventilation, or mortality.</p>
                <p> </p>
                <p> Such discrepant studies need to be part of the discussion of a study like the one that authors have conducted and the possible reasons for such dichotomy proposed.&#x00a0;</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Response:</bold>
                </p>
                <p> Thank you for your valuable suggestions. We have improved our paper by citing the prospective study in the Indian subcontinent by Dhar et al. We have also provided the explanations for the possible reasons underlying the observed dichotomy in the discussion section.</p>
                <p> </p>
                <p> Interestingly, a single-center prospective study conducted in the Indian subcontinent, a region with a high prevalence of deficient vitamin D, demonstrated no statistically significant difference in the median length of stay (LOS) between patients with sufficient vitamin D and deficient vitamin D (p-value=0.176). The LOS for patients with deficient vitamin D was 12 days (95% CI: 10, 12 days), and the LOS for patients with sufficient vitamin D was 11 days (95% CI: 10, 13 days). They also showed that deficient vitamin D (defined as 25(OH)D &lt; 30 ng/mL) in patients with COVID-19 was not associated with the length of hospital stay, the need for mechanical ventilation, or the mortality rate.
                    <sup>83</sup> These different results could be explained by different cut-offs to define deficient vitamin D. In our study, a serum 25(OH)D level of less than 20 ng/mL (50 nmol/L) was considered deficient according to the Endocrine Society Clinical Practice Guidelines.
                    <sup>25</sup>On the other hand, most hospitalized patients with COVID-19 have numerous comorbidities, and this population tends to have lower vitamin D levels. Thus, vitamin D levels in such a setting should be interpreted with caution.
                    <sup>83</sup>
                </p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Reference:</bold>
                </p>
                <p> 25. de la Gu&#x00ed;a-Galipienso F , Mart&#x00ed;nez-Ferran M, Vallecillo N, et al.: Vitamin D and cardiovascular health. 
                    <italic>Clin. Nutr.</italic>2021 May;40(5):2946&#x2013;2957. 33397599 10.1016/j.clnu.2020.12.025 PMC7770490</p>
                <p> 83. Dhar A, Mir H, Koul PA. Vitamin D Levels and Length of Hospitalization in Indian Patients With COVID-19: A Single-Center Prospective Study. Cureus. 2022 Jul 9;14(7):e26704. 10.7759/cureus.26704</p>
                <p> </p>
                <p> </p>
                <p> </p>
                <p> If you have any suggestions, we would greatly appreciate hearing them. Thanks for your attention. We eagerly await your response.</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report178400">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.148441.r178400</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Sabico</surname>
                        <given-names>Shaun</given-names>
                    </name>
                    <xref ref-type="aff" rid="r178400a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-5248-2350</uri>
                </contrib>
                <aff id="r178400a1">
                    <label>1</label>Department of Biochemistry College of Science, King Saud University, Riyadh, Riyadh Province, Saudi Arabia</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>6</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Sabico S</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport178400" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>I commend the authors for satisfactorily addressing the comments. I have no further suggestions.</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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</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>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Nutrition, medical sciences, vitamin D, metabolism</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="report169546">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.145122.r169546</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Sabico</surname>
                        <given-names>Shaun</given-names>
                    </name>
                    <xref ref-type="aff" rid="r169546a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-5248-2350</uri>
                </contrib>
                <aff id="r169546a1">
                    <label>1</label>Department of Biochemistry College of Science, King Saud University, Riyadh, Riyadh Province, Saudi Arabia</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>11</day>
                <month>5</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Sabico S</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport169546" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.132214.1"/>
            <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 present prospective study by Rachman and colleagues analyzed the impact of vitamin D deficiency among covid-19 patients and found that those who had more comorbidities and had more severe manifestations of covid-19 were more likely to be vitamin D deficient. Although the data itself is not new, this is one of the very few studies coming from Southeast Asia where vitamin D deficiency is not expected to be as pronounced in other regions. The use of ISARIC-4C mortality score is also an added novelty. Despite this fact, their findings largely echo previous observations. I have several comments:</p>
            <p> Major: 
                <list list-type="order">
                    <list-item>
                        <p>Please add more details how covid-19 was diagnosed with reference. Was it through nasopharyngeal swab? And where was vitamin D measured? Was it in a BSL3 facility?</p>
                    </list-item>
                    <list-item>
                        <p>The statistics could have been expanded to control for confounders such as age and BMI. These were not explicitly mentioned in the data analysis. Furthermore, with the number of variables measured, the p-value should have been Bonferroni adjusted unless the authors prove this wasn&#x2019;t necessary.</p>
                    </list-item>
                    <list-item>
                        <p>Lastly, the study design appears to be cross-sectional and not prospective. The observational design and small sample size have limited the findings to at best, suggestive. The limitation section could have been expanded taking into consideration the points raised.</p>
                    </list-item>
                </list> Minor 
                <list list-type="order">
                    <list-item>
                        <p>Several studies that support your findings from the Middle East where deficiency is very pronounced are suggested to be added including clinical trials on vitamin D and covid-19. Similar findings from different regions and ethnic groups reinforce the role of vitamin D in severity of covid-19.</p>
                    </list-item>
                </list>
            </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>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</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>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Nutrition, medical sciences, vitamin D, metabolism</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>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-169546-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Effects of a 2-Week 5000 IU versus 1000 IU Vitamin D3 Supplementation on Recovery of Symptoms in Patients with Mild to Moderate Covid-19: A Randomized Clinical Trial.</article-title>
                        <source>
                            <italic>Nutrients</italic>
                        </source>.<year>2021</year>;<volume>13</volume>(<issue>7</issue>) :
                        <elocation-id>10.3390/nu13072170</elocation-id>
                        <pub-id pub-id-type="pmid">34202578</pub-id>
                        <pub-id pub-id-type="doi">10.3390/nu13072170</pub-id>
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                </ref>
                <ref id="rep-ref-169546-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Vitamin D status of Arab Gulf residents screened for SARS-CoV-2 and its association with COVID-19 infection: a multi-centre case-control study.</article-title>
                        <source>
                            <italic>J Transl Med</italic>
                        </source>.<year>2021</year>;<volume>19</volume>(<issue>1</issue>) :
                        <elocation-id>10.1186/s12967-021-02838-x</elocation-id>
                        <fpage>166</fpage>
                        <pub-id pub-id-type="pmid">33902635</pub-id>
                        <pub-id pub-id-type="doi">10.1186/s12967-021-02838-x</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-169546-3">
                    <label>3</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Severe vitamin D deficiency is not related to SARS-CoV-2 infection but may increase mortality risk in hospitalized adults: a retrospective case-control study in an Arab Gulf country.</article-title>
                        <source>
                            <italic>Aging Clin Exp Res</italic>
                        </source>.<year>2021</year>;<volume>33</volume>(<issue>5</issue>) :
                        <elocation-id>10.1007/s40520-021-01831-0</elocation-id>
                        <fpage>1415</fpage>-<lpage>1422</lpage>
                        <pub-id pub-id-type="pmid">33788172</pub-id>
                        <pub-id pub-id-type="doi">10.1007/s40520-021-01831-0</pub-id>
                    </mixed-citation>
                </ref>
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        </back>
        <sub-article article-type="response" id="comment9679-169546">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Rachman</surname>
                            <given-names>Andhika</given-names>
                        </name>
                        <aff>Internal Medicine, Universitas Indonesia, Jakarta, DKI Jaya, Indonesia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>The authors declare that we have no conflict of interest.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>18</day>
                    <month>5</month>
                    <year>2023</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>Response To The Reviewer:</bold>
                </p>
                <p> </p>
                <p> Dear Dr. Shaun Sabico,</p>
                <p> We would like to thank you for your time and consideration in handling our manuscript.</p>
                <p> </p>
                <p> We want to confirm that we have revised the manuscript with the tracked changes system.</p>
                <p> </p>
                <p> If you have any suggestions, please don&#x2019;t hesitate to contact us.</p>
                <p> </p>
                <p> Sincerely,</p>
                <p> Andhika Rachman, PhD</p>
                <p> Medical staff, Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Major:</bold> 
                    <list list-type="order">
                        <list-item>
                            <p>Please add more details how covid-19 was diagnosed with reference. Was it through nasopharyngeal swab? And where was vitamin D measured? Was it in a BSL3 facility?&#8232;&#x00a0;</p>
                        </list-item>
                    </list> </p>
                <p> Thank you for your construction feedback. We have added more details on the methods.</p>
                <p> The SARS-CoV-2 infection was confirmed through positive RT-PCR obtained from nasal and oropharyngeal swabs collected.
                    <sup>77</sup> The examination was carried out in the Biosafety Level 3-facility (BSL-3) with Biological Safety Cabinet Class II (BSC-II).</p>
                <p> During the admission, each patient had 3&#x2013;5 mL of blood collected in an acid citrate dextrose tube from a cuffed venous sample. The samples were transported to the laboratory in a cold chain for the measurement of vitamin D.</p>
                <p> </p>
                <p> Reference:</p>
                <p> 77. Torretta S, Zuccotti G, Cristofaro V, Ettori J, Solimeno L, Battilocchi L, D'Onghia A, Bonsembiante A, Pignataro L, Marchisio P, Capaccio P. Diagnosis of SARS-CoV-2 by RT-PCR Using Different Sample Sources: Review of the Literature. Ear Nose Throat J. 2021 Apr;100(2_suppl):131S-138S. doi: 10.1177/0145561320953231.</p>
                <p> </p>
                <p> &#x00a0; 
                    <list list-type="order">
                        <list-item>
                            <p>The statistics could have been expanded to control for confounders such as age and BMI. These were not explicitly mentioned in the data analysis. Furthermore, with the number of variables measured, the p-value should have been Bonferroni adjusted unless the authors prove this wasn&#x2019;t necessary.</p>
                        </list-item>
                    </list> </p>
                <p> The reviewer did raise a very important concern which will improve our manuscript. We strongly agree that the reviewer&#x2019;s suggestion should be considered for further researches regarding this issue. The confounders such as age and BMI could not be controlled due to the minimum sample size of the subgroups and the fact that the number of samples is unequally distributed, which has not fulfilled the criteria to conduct the analysis. Thus, we have raised the point that the small sample size has become our limitation. We plan to improve the design and participants selection in the next study.</p>
                <p> </p>
                <p> Furthermore, we have added Figure 1 (a bivariate analysis that has been adjusted with the Bonferoni correction).&#x00a0;Figure 1 presents&#x00a0;the bivariate analysis performed on COVID-19 patients with vitamin D deficiency. Serum 25(OH)D levels were significantly different between patients with mild and severe COVID-19 cases (p-value &lt; 0.001). Serum 25 (OH) D levels in mild and moderate COVID-19 cases were also significantly different (p-value 0.002).</p>
                <p> &#x00a0; 
                    <list list-type="order">
                        <list-item>
                            <p>Lastly, the study design appears to be cross-sectional and not prospective. The observational design and small sample size have limited the findings to at best, suggestive. The limitation section could have been expanded taking into consideration the points raised.</p>
                        </list-item>
                    </list> </p>
                <p> We have added the points of observational design and small sample size as limitations of our study. Additionally, we want to verified that our study's design is cohort prospective. Even if the risk variables (vitamin D levels) are measured upon admission, the outcome is followed and observed until the patient leaves the hospital, becomes worse, requires a ventilator, or passes away. The person had not used a ventilator when first recruited.</p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>Minor</bold> 
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                            <p>Several studies that support your findings from the Middle East where deficiency is very pronounced are suggested to be added including clinical trials on vitamin D and covid-19. Similar findings from different regions and ethnic groups reinforce the role of vitamin D in severity of covid-19.</p>
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                    </list> </p>
                <p> Thank you for your advice. We have improved our paper by citing the multi-center randomized clinical trial in the Middle East that conducted by Sabico et al. We have also cited the studies carried out by Al-Daghri et al. and Alguwaihes et al.</p>
                <p> </p>
                <p> </p>
                <p> Please don't be hesitant to contact us if you have any concerns or suggestions about the revised manuscript. If you have any suggestions, we would greatly appreciate hearing them. Thanks for your attention. We eagerly await your response.</p>
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