<?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.141573.1</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>Corticosteroids and invasive fungal infections in hospitalized COVID-19 patients &#x2013; A single-center cross-sectional study</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Ramanathan</surname>
                        <given-names>Venkateswaran</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</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/0000-0002-1602-5785</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Pari Thenmozhi</surname>
                        <given-names>Hariswar</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/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</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/0000-0002-8628-976X</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Singh</surname>
                        <given-names>Rakesh</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Bheemanathi Hanuman</surname>
                        <given-names>Srinivasan</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Adithan</surname>
                        <given-names>Subathra</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Medical ICU, Department of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, Puducherry, India</aff>
                <aff id="a2">
                    <label>2</label>Department of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, Puducherry, India</aff>
                <aff id="a3">
                    <label>3</label>Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, Puducherry, India</aff>
                <aff id="a4">
                    <label>4</label>Department of Pathology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, Puducherry, India</aff>
                <aff id="a5">
                    <label>5</label>Department of Radiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, Puducherry, India</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:hariswarjipneu@gmail.com">hariswarjipneu@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>6</day>
                <month>10</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>1282</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>18</day>
                    <month>9</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Ramanathan V et al.</copyright-statement>
                <copyright-year>2023</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/12-1282/pdf"/>
            <abstract>
                <p>
                    <bold>Background</bold>: During the coronavirus disease 2019 (COVID-19) epidemic, an increase in the incidence of fungal infections was observed. However, the real magnitude of these fungal infections and their risk factors among COVID-19 patients in the Indian population is unknown.</p>
                <p>
                    <bold>Aim:</bold> To study the frequency, and spectrum of invasive fungal infections (IFI) among hospitalized COVID-19 patients, and the risk factors associated with invasive fungal infections.</p>
                <p>
                    <bold>Methods</bold>: We performed a retrospective, cross-sectional study; including all adult patients, admitted to Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), a tertiary care hospital in Southern India between April 2020 and August 2021, with COVID-19. Based on clinical-radiological features, patients with fungal infections were grouped into three diagnostic categories. Demographics, clinical, and laboratory features of patients with fungal infections were analyzed to identify the risk factors.</p>
                <p>
                    <bold>Results</bold>: About 10% (449 out of 4650) of the admitted patients with recent COVID-19, had some form of IFI. Among the patients with IFI, 80% (366 out of 449) were hospitalized for active COVID-19, whereas almost all the patients admitted with post-COVID complications had IFI. Of the 449 patients with IFI, 377 had mold infections and 88 had invasive candidiasis. Mucormycosis was the most common mold infection. Diabetes and diabetic ketoacidosis were strong independent predictors of IFI. We also found an association between end-stage renal disease, central venous catheterization, antibiotic usage, prior stroke, and corticosteroid therapy with IFI.</p>
                <p>
                    <bold>Conclusions</bold>: The frequency of fungal infections among hospitalized COVID-19 patients was high. Special precautions in COVID-19 patients with diabetes mellitus, corticosteroid therapy, and prior antibiotic usage may help to reduce invasive fungal infections.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19; Invasive fungal infections; Mucormycosis; Corticosteroids</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>When the epidemic of coronavirus disease 2019 (COVID-19) started, therapeutic options were few and were purported with no evidence. With platform trials, several agents were tried, and corticosteroid therapy was found to be beneficial in a subset of COVID-19 patients who had severe illness-causing hypoxia and not across the entire spectrum of severity.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> It helped us to buttress the hypothesis that corticosteroids mitigate the detrimental effect of exuberant inflammatory response-related morbidity and mortality. However, the patient population included in these platform trials was predominantly from the Western world.</p>
            <p>Having established the role of corticosteroids in severe COVID-19 infection, dexamethasone therapy became the standard of care for all hypoxic COVID-19 patients across the world. In India, while the use of corticosteroids was not routine in the first wave of COVID-19, corticosteroid therapy became a standard of care for the management of hospitalized COVID-19 patients during the second wave as evidence from RECOVERY trial was available by then.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> Being familiar, cheap, and the first drug to show evidence of survival benefit, corticosteroid therapy was welcomed with a lot of enthusiasm. Soon after, in India, several case reports of invasive fungal infections in COVID-19 patients emerged during the second wave. Though corticosteroid therapy was quite beneficial in the Western world, in the Indian population, the real extent of benefit which is probably offset by the increased risk of fungal infections, is not known. Unless the real extent of the benefit of corticosteroid therapy is ascertained in Indian patients, clinicians may tend to use corticosteroids in off-label indications like non-COVID ARDS also.</p>
            <p>There are several reasons for the possible increase in the incidence of fungal infections among Indian patients with COVID-19. Indian people are more susceptible than the Western population to diabetes as indicated by the Y-Y paradox.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Hence, it is possible that corticosteroid therapy, by producing hyperglycemia in non-diabetics, may increase the incidence of fungal infections. Though debatable, other causes like the unscrupulous use of high-dose corticosteroids, climatic conditions favoring fungal spore dissemination, genetic susceptibility, and poor blood sugar control may be leading to an increased incidence of fungal infections in India, especially mucormycosis.</p>
            <p>Though at the outset it appeared as if the corticosteroid therapy increased the incidence of fungal infections in India,
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> we are uncertain about the actual frequency of fungal infections and their risk factors in these Indian patients with COVID-19. There are very few studies from India showing the type of fungal infections. Hence, we undertook the study to determine the frequency of invasive fungal infections in hospitalized COVID-19 patients from India. We also studied the spectrum of fungal infections, the risk factors of fungal infections, and their clinical outcomes in hospitalized COVID-19 patients.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <p>
                <bold>
                    <italic toggle="yes">Study design</italic>
                </bold>: We performed a single center, retrospective, cross-sectional analytical study, among patients admitted at a tertiary care hospital at Pondicherry (JIPMER) between April 1
                <sup>st</sup>, 2020, to August 31
                <sup>st</sup>, 2021.</p>
            <p>
                <bold>
                    <italic toggle="yes">Study participants</italic>
                </bold>: We defined a patient to have recent COVID-19 if they had tested positive for COVID-19 by RT-PCR/Antigen detection test either at admission or within 90 days of hospital admission. From our hospital electronic health records (EHR), all patients aged 13 and above hospitalized at JIPMER during the study period were identified using a structured query language (SQL) based query. These patients were screened for recent COVID-19 reports, and patients who had recent COVID-19 were included in the study. Patients with either unavailable clinical data or COVID-19 reports were excluded.</p>
            <p>
                <bold>
                    <italic toggle="yes">Ethical statement</italic>
                </bold>: The study protocol was reviewed and approved by the Institute Ethics Committee (Human Studies) of Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry (DHR REG.NO.EC/NEW/INST/2020/331). A waiver of Informed consent was approved by the Institute Ethics Committee (Human Studies).</p>
            <p>
                <bold>
                    <italic toggle="yes">Sample size estimation</italic>
                </bold>: Based on prior studies,
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> the frequency of IFI among hospitalized COVID-19 patients was assumed to be 15%, with an error margin of 5%, with a level of significance at 0.05, the sample size estimated was 196 patients. Our study is a retrospective case record-based study and included all patients who met the selection criteria.</p>
            <p>
                <bold>
                    <italic toggle="yes">Study procedure</italic>
                </bold>: We had complete access to our hospital EHR, from which, all patients admitted during the study period were identified, and screened for COVID-19 reports. The data from EHR was exported in CSV format and cleaned using the software OpenRefine (version 3.6.2, for Microsoft Windows 11). For patients who had recent COVID-19, baseline characteristics including comorbidities and severity of COVID-19 illness, requirement for ICU admission, treatment details, duration of hospital stay, and clinical outcome at discharge were collected. Fungal culture, and histopathological biopsy reports were noted. In patients who underwent computed tomography based on clinical suspicion, image findings suggestive of fungal etiology were analyzed. Based on the European Organization for Research and Treatment of Cancer (EORTC) guidelines,
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> which were modified accordingly for COVID-19 patients (see 
                <italic toggle="yes">Extended data</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup>), these patients were then categorized to have Possible, Probable or Proven Invasive fungal infection. For the study purpose, patients who had more than one group of IFI were classified as belonging to the IFI group with the highest category of likelihood. Clinical and laboratory data of patients with fungal infection were analyzed to identify the predictors of fungal infection among hospitalized COVID-19 patients.</p>
            <p>
                <bold>
                    <italic toggle="yes">Statistical analysis</italic>
                </bold>: The data were compiled using Microsoft Excel and analyzed using 
                <ext-link ext-link-type="uri" xlink:href="https://www.ibm.com/products/spss-statistics">SPSS</ext-link> version 19.0 (SPSS for Windows, version 19.0, Chicago, SPSS Inc.) and 
                <ext-link ext-link-type="uri" xlink:href="https://www.r-project.org/">R</ext-link> software (version 3.3.1, R Foundation for Statistical Computing). Categorical variables were expressed as percentages and frequencies, and continuous variables were reported as mean and standard deviation or median with the interquartile range. Categorical variables were compared by Chi-square test. The strength of association was expressed as odds ratios. Normality was assessed by the Kolmogorov-Smirnov test. To compare continuous normally distributed data, the two-tailed unpaired t-test was used. All tests were two-sided, and 
                <italic toggle="yes">P</italic>&lt;0.05 was considered statistically significant. Before performing multivariable analysis, we reduced the dimensions of the variables by multiple correspondence analysis. We found collinearity between the predictors 'corticosteroid and heparin' as well as 'diabetes mellitus and hypertension'. Considering biological plausibility, we chose corticosteroids and diabetes mellitus as predictors from each of the clusters for further analysis. We observed a similar clustering between 'end-stage renal disease (ESRD) and central venous catheter (CVC) usage'. We included both ESRD and CVC for the invasive fungal infection group and removed CVC for the subgroup analysis involving invasive mold infection. Multivariable logistic regression using Enter method was performed to identify the predictors.</p>
        </sec>
        <sec id="sec3" sec-type="results">
            <title>Results</title>
            <p>During the study period, there were 69792 admissions, and 4650 patients had a history of recent COVID-19 (including patients admitted for COVID-19 and post-COVID-19 patients), among them, 4565 patients were hospitalized for active COVID-19 and 85 patients were admitted with post-COVID-19 complications.
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> These post-COVID patients had received treatment for COVID-19 elsewhere and were hospitalized at JIPMER for post-COVID sequelae (
                <xref ref-type="fig" rid="f1">Figure 1</xref>).</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>Patient flow diagram.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/155032/7d2736c4-603d-41db-845f-52fafeb321db_figure1.gif"/>
            </fig>
            <p>Among the hospitalized patients, who had recent COVID-19 (n=4650), the median age was 50 years (interquartile range [IQR], 35 to 62), with 27% of patients aged above 60 years; 59% were male. The most common comorbid illness in these patients was diabetes mellitus (31%) followed by systemic hypertension (25%), chronic cardiac disease (8%), and chronic kidney disease (6.7%). Recent immunosuppressive therapy (corticosteroid or other immunosuppressants) was present in 113 patients (2.4%) (
                <xref ref-type="table" rid="T1">Table 1</xref>).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Clinical characteristics of hospitalized patients with recent COVID-19.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Patients with recent COVID-19</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">All patients (n=4650)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">With IFI
                                <xref ref-type="table-fn" rid="tfn1">
                                    <sup>a</sup>
                                </xref> (n=449)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
                                <italic toggle="yes">Unadjusted OR (95% CI)</italic>
                            </th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Age, years</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">50 (35 &#x2013; 62)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">55 (44 &#x2013; 64)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.02 (1.01 to 1.03)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Male sex</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2738 (58.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">294 (65.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.36 (1.11 to 1.67)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Coexisting conditions</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Diabetes mellites
                                <xref ref-type="table-fn" rid="tfn2">
                                    <sup>b</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1419 (30.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">269 (59.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.95 (3.23 to 4.82)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Diabetic keto-acidosis</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">72 (1.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">26 (5.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.57 (3.41 to 9.10)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Hypertension</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1165 (25.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">151 (33.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.60 (1.30 to 1.97)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">End-stage renal disease
                                <xref ref-type="table-fn" rid="tfn3">
                                    <sup>c</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">313 (6.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">62 (13.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.53 (1.88 to 3.40)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Chronic cardiac disease
                                <xref ref-type="table-fn" rid="tfn4">
                                    <sup>d</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">372 (8.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">30 (6.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.81 (0.55 to 1.19)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Cerebrovascular accident
                                <xref ref-type="table-fn" rid="tfn5">
                                    <sup>e</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">99 (2.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21 (4.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.60 (1.59 to 4.25)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Asthma</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">73 (1.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (0.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.40 (0.13 to 1.27)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Other chronic lung diseases</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">172 (3.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (2.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.70 (0.38 to 1.26)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Chronic liver disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">31 (0.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.31 (0.04 to 2.29)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Autoimmune disease</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">86 (1.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (2.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.54 (0.83 to 2.85)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Immunosuppressive state</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Prior systemic steroid usage</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">95 (2.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11 (2.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.23 (0.65 to 2.33)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Prior non-steroidal immunosuppressants usage</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">95 (2.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">10 (2.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.11 (0.57 to 2.15)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">HIV/AIDS</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13 (0.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2 (0.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.71 (0.38 to 7.73)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Malignancy
                                <xref ref-type="table-fn" rid="tfn6">
                                    <sup>f</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">203 (4.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">18 (4.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.91 (0.56 to 1.49)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Data are n (%) or median (IQR). IFI=Invasive Fungal infection. ESRD=End stage renal disease. HIV/AIDS=Human immunodeficiency Virus/Acquired immunodeficiency syndrome.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>
                                <sup>a</sup>
                            </label>
                            <p>Patients with possible, probable, or proven IFI.</p>
                        </fn>
                        <fn id="tfn2">
                            <label>
                                <sup>b</sup>
                            </label>
                            <p>Includes patients with diabetic ketoacidosis and steroid-induced hyperglycemia.</p>
                        </fn>
                        <fn id="tfn3">
                            <label>
                                <sup>c</sup>
                            </label>
                            <p>Includes ESRD patients who have received renal transplant.</p>
                        </fn>
                        <fn id="tfn4">
                            <label>
                                <sup>d</sup>
                            </label>
                            <p>Includes patients with congenital heart disease, coronary artery disease, and rheumatic heart disease.</p>
                        </fn>
                        <fn id="tfn5">
                            <label>
                                <sup>e</sup>
                            </label>
                            <p>Patients with a history of cerebrovascular patient in the past.</p>
                        </fn>
                        <fn id="tfn6">
                            <label>
                                <sup>f</sup>
                            </label>
                            <p>Both active and recently treated malignancy.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>Among the patients admitted with active COVID-19 (n=4565), 1283 patients (28%) had severe illness at admission, with 85 patients (1.9%) requiring mechanical ventilation at admission and 870 patients (19%) requiring admission to intensive care during their hospital stay. Corticosteroids were used in 2014 patients (44%), remdesivir was given to 448 patients (9.8%), and 26 patients received tocilizumab (0.6%). Many of the patients with COVID-19, also received antibiotics (42%), and 10% of the patients received more than three antibiotics during their hospital stay (
                <xref ref-type="table" rid="T2">Table 2</xref>).</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Severity of illness and treatment received in patients with active COVID-19
                        <xref ref-type="table-fn" rid="tfn7">
                            <sup>a</sup>
                        </xref>.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Patients with Active COVID-19</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">All patients (n=4565)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">With IFI (n=366)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
                                <italic toggle="yes">Unadjusted OR (95% CI)</italic>
                            </th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Illness severity at admission</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Hypoxia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2184 (47.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">276 (75.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.69 (2.88 to 4.71)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Only supplemental oxygen</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1963 (43.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">234 (63.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Non-invasive ventilated</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">111 (2.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">17 (4.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mechanical ventilated</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">110 (2.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">25 (6.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Severe COVID-19
                                <xref ref-type="table-fn" rid="tfn8">
                                    <sup>b</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1283 (28.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">172 (47.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.46 (1.99 to 3.06)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Maximal respiratory support</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Only supplemental oxygen</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1295 (28.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">136 (37.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Non-invasive ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">143 (3.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">18 (4.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">849 (18.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">137 (37.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Central venous catheter usage</bold>
                                <xref ref-type="table-fn" rid="tfn9">
                                    <sup>c</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">638 (14.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">128 (35.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.89 (3.08 to 4.92)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>ICU admission</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">864 (18.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">146 (39.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.22 (2.57 to 4.03)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Pharmacotherapy</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Corticosteroids</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2014 (44.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">233 (63.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.38 (1.91 to 2.97)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Dexamethasone</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1913 (41.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">217 (59.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.15 (1.73 to 2.67)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Methylprednisolone</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">260 (5.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">69 (18.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.88 (3.61 to 6.58)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Prednisolone</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">93 (2.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12 (3.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.72 (0.93 to 3.19)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Hydrocortisone</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">51 (1.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">13 (3.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.03 (2.13 to 7.64)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&gt; 2 steroid formulations</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">290 (6.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">75 (20.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.78 (3.58 to 6.37)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Parenteral anticoagulation
                                <xref ref-type="table-fn" rid="tfn10">
                                    <sup>d</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2064 (45.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">235 (64.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.33 (1.86 to 2.90)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Remdesvir</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">448 (9.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">36 (9.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.00 (0.70 to 1.44)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Tocilizumab</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9 (0.2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (0.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.78 (1.44 to 23.19)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Baricitinib</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">23 (0.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3 (0.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.73 (0.51 to 5.84)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Antibiotic usage</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1935 (42.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">238 (65.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.74 (2.19 to 3.43)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Exposure to multiple antibiotics
                                <xref ref-type="table-fn" rid="tfn11">
                                    <sup>e</sup>
                                </xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">462 (10.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">95 (26.0)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.66 (2.83 to 4.73)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Data are n (%).</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn7">
                            <label>
                                <sup>a</sup>
                            </label>
                            <p>Before the development of Invasive Fungal infection.</p>
                        </fn>
                        <fn id="tfn8">
                            <label>
                                <sup>b</sup>
                            </label>
                            <p>Severe COVID-19 according to WHO 10-point ordinal scale (Score of 6 or more).</p>
                        </fn>
                        <fn id="tfn9">
                            <label>
                                <sup>c</sup>
                            </label>
                            <p>Includes hemodialysis catheter.</p>
                        </fn>
                        <fn id="tfn10">
                            <label>
                                <sup>d</sup>
                            </label>
                            <p>Includes low molecular weight heparin and unfractionated heparin.</p>
                        </fn>
                        <fn id="tfn11">
                            <label>
                                <sup>e</sup>
                            </label>
                            <p>Multiple antibiotic therapy was defined as usage of &#x2265; 3 antibiotics of different class either concurrently or sequentially.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <sec id="sec4">
                <title>Spectrum of invasive fungal infections</title>
                <p>Of the 4650 hospitalized patients with recent COVID-19 infection, 449 (9.7%) had an invasive fungal infection (
                    <xref ref-type="fig" rid="f1">Figure 1</xref>). Among those admitted for active COVID-19, 366 (8%) developed an invasive fungal infection during their hospital stay, whereas 83 out of 85 post-COVID-19 patients had an invasive fungal infection. The number of patients with proven or probable invasive fungal infections was 48.2 per 1000 COVID-19 patients.</p>
                <p>The most common invasive fungal infections were due to mold infections (
                    <italic toggle="yes">Mucorales &amp; Aspergillus</italic>) occurring in 377 patients, followed by candidiasis (n=88). Out of 4650 patients, proven or probable mold infection occurred in 139 (3.0%) patients, among them 127 (91%) patients had mucormycosis and 36 (26%) had aspergillosis. Radiological evidence of pulmonary mold infection was present in 173 patients. In patients with mucormycosis, rhino-nasal or rhino-orbital-cerebral presentation (96.1%) was the most common presentation, followed by disseminated infection (3.9%), whereas among patients with isolated aspergillosis, pulmonary aspergillosis (67%) was common than rhino-nasal presentation (33%). Invasive candidiasis occurred in 88 patients, with positive fungal blood culture in 64 (73%) patients. Non-Albicans spp. (n=59) were more common than 
                    <italic toggle="yes">Candida albicans</italic> (n=7) (
                    <xref ref-type="table" rid="T3">Table 3</xref>).</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>Table 3. </label>
                    <caption>
                        <title>Clinical spectrum of invasive fungal infections.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Active COVID-19 (n=4565)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Post COVID-19 (n=85)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Total (%) (n=4650)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Total invasive fungal infection</bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">366</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">83</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">449</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Proven</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">108</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">58</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">166</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Probable</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">47</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">58</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Possible</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">211</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">225</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Clinical syndrome of IFI</bold>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Mold infections</bold>
                                    <xref ref-type="table-fn" rid="tfn12">
                                        <sup>
                                            <bold>a</bold>
                                        </sup>
                                    </xref>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Rhinosinusitis</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">76 (1.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">73 (85.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">149</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Only Rhinosinusitis</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">32</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">52</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">RO</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">41</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">62</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">ROC/RC</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">35</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Pulmonary</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">171 (3.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5 (5.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">176 (3.8)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Disseminated</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Candidiasis</bold>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Candidemia</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">64 (1.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">64</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Others</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">25 (0.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Fungal species</bold>
                                    <xref ref-type="table-fn" rid="tfn13">
                                        <sup>b</sup>
                                    </xref>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Mucorales. spp</italic>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">60</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">67</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">127</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Aspergillus. spp</italic>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">36</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Candida. spp</italic>
                                    <xref ref-type="table-fn" rid="tfn14">
                                        <italic toggle="yes">
                                            <sup>c</sup>
                                        </italic>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">64</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">64</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Candida albicans</italic>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Non albicans spp</italic>
                                    <xref ref-type="table-fn" rid="tfn15">
                                        <italic toggle="yes">
                                            <sup>d</sup>
                                        </italic>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">59</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">59</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <italic toggle="yes">Candida auris</italic>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Data are n (%) or n. RO= Rhino-orbital; ROC/RC=Rhino-orbito-cerebral/Rhino-cerebral.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn12">
                                <label>
                                    <sup>a</sup>
                                </label>
                                <p>Includes patients with proven, probable, and patients with radiological evidence of IFI.</p>
                            </fn>
                            <fn id="tfn13">
                                <label>
                                    <sup>b</sup>
                                </label>
                                <p>Includes patients with coinfection with both molds and candidiasis isolated by fungal culture or by histopathological examination of infected tissue.</p>
                            </fn>
                            <fn id="tfn14">
                                <label>
                                    <sup>c</sup>
                                </label>
                                <p>Patients with candidemia.</p>
                            </fn>
                            <fn id="tfn15">
                                <label>
                                    <sup>d</sup>
                                </label>
                                <p>Including 
                                    <italic toggle="yes">Candida auris.</italic>
                                </p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec5">
                <title>Risk factors associated with Invasive fungal infections</title>
                <p>After adjusting for confounding by multivariable logistic regression, diabetes, diabetic ketoacidosis, prior stroke, steroid usage, and central venous catheter usage were found to be independent predictors of IFI in patients with active COVID-19 (i.e., after excluding patients admitted for post-COVID sequelae). Diabetic ketoacidosis was the most important predictor (odds ratio, 3.31; 95%CI, 1.93 to 5.58). As compared to the risk of IFI among patients who received dexamethasone, the risk of IFI in patients who received methylprednisolone was 2.82 (95%CI, 2.07 to 3.85). In the subgroup of invasive mold infections diabetes, diabetic ketoacidosis, steroid usage, antibiotic usage, and chronic kidney disease were identified as independent predictors and prior stroke did not show an association (
                    <xref ref-type="table" rid="T4">Table 4</xref>, 
                    <xref ref-type="table" rid="T5">5</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>Table 4. </label>
                    <caption>
                        <title>Univariate and multivariate analysis of factors associated with invasive fungal infections in patients with active COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">With IFI (n=366)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Without IFI (n=4119)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Univariate OR (95% CI)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Multivariate OR (95% CI)</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"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;18 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.27)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">55 (1.31)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.21 (0.03 &#x2013; 1.50)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">18 to 60 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">236 (64.5)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3043 (72.5)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.69 (0.55 &#x2013; 0.86)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&gt; 60 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">129 (35.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1101 (26.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.53 (1.22 &#x2013; 1.92)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Male sex</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">231 (63.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2443 (58.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.23 (0.99 &#x2013; 1.53)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Diabetes mellitus
                                    <xref ref-type="table-fn" rid="tfn16">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">195 (53.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1149 (27.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.03 (2.44 &#x2013; 3.76)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>2.06 (1.62 &#x2013; 2.62)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Diabetic ketoacidosis
                                    <xref ref-type="table-fn" rid="tfn16">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26 (7.10)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">46 (1.10)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.90 (4.22 &#x2013; 11.31)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>3.31 (1.93 &#x2013; 5.58)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">End-stage renal disease
                                    <xref ref-type="table-fn" rid="tfn17">
                                        <sup>
                                            <styled-content style="#0563C1" style-type="color">&#x2020;</styled-content>
                                        </sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">59 (16.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">251 (5.98)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.02 (2.23 &#x2013; 4.11)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.44 (0.99 &#x2013; 2.10)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cerebrovascular accident
                                    <xref ref-type="table-fn" rid="tfn18">
                                        <sup>&#x2021;</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20 (5.5)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">78 (1.85)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.07 (1.81 &#x2013; 4.98)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>2.23 (1.28 &#x2013; 3.72)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Steroid usage for COVID
                                    <xref ref-type="table-fn" rid="tfn19">
                                        <sup>&#x00a7;</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">233 (63.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1781 (42.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.38 (1.91 &#x2013; 2.97)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.39 (1.07 &#x2013; 1.81)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Immunosuppression</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28 (7.65)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">282 (6.72)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.15 (0.77 &#x2013; 1.72)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Antibiotic use
                                    <xref ref-type="table-fn" rid="tfn16">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">238 (65.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1697 (40.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.74 (2.19 &#x2013; 3.43)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.65 (1.27 &#x2013; 2.14)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Severe COVID-19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">172 (47.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1111 (26.5)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.46 (1.99 &#x2013; 3.06)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">CVC
                                    <xref ref-type="table-fn" rid="tfn16">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">128 (35.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">510 (12.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.99 (3.08 &#x2013; 4.92)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.96 (1.43 &#x2013; 2.67)</bold>
                                </td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Data are n (%). OR=Odds ratio, CVC=Central venous catheterization, including hemodialysis catheter, IFI=Invasive Fungal infection. All variables were analyzed but only statistically significant variables or variables of interest are presented.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn16">
                                <label>
                                    <sup>*</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> &lt; 0.001.</p>
                            </fn>
                            <fn id="tfn17">
                                <label>
                                    <sup>&#x2020;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.057.</p>
                            </fn>
                            <fn id="tfn18">
                                <label>
                                    <sup>&#x2021;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.003.</p>
                            </fn>
                            <fn id="tfn19">
                                <label>
                                    <sup>&#x00a7;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.013.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>Table 5. </label>
                    <caption>
                        <title>Univariate and multivariate analysis of factors associated with invasive mold infections in patients with active COVID-19.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">With IMI (n=294)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Without IMI (n=4271)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Univariate OR (95% CI)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Multivariate OR (95% CI)</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"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;18 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1 (0.34)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">55 (1.29)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.26 (0.04 &#x2013; 1.90)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">18 to 60 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">186 (63.27)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3093 (72.42)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.66 (0.51 &#x2013; 0.84)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&gt; 60 years</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">107 (36.39)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1123 (26.29)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.60 (1.25 &#x2013; 2.05)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Male sex</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">188 (63.95)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2486 (58.21)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.27 (1.00 &#x2013; 1.63)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Diabetes mellitus
                                    <xref ref-type="table-fn" rid="tfn20">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">163 (55.44)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1181 (27.65)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.26 (2.56 &#x2013; 4.14)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>2.34 (1.80 &#x2013; 3.05)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Diabetic ketoacidosis
                                    <xref ref-type="table-fn" rid="tfn20">
                                        <sup>*</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21 (7.14)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">51 (1.19)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.37 (3.77 &#x2013; 10.74)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>3.30 (1.87 &#x2013; 5.64)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">End-stage renal disease
                                    <xref ref-type="table-fn" rid="tfn21">&#x2020;</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">42 (14.29)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">268 (6.27)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.49 (1.76 &#x2013; 3.53)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.81 (1.24 &#x2013; 2.59)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cerebrovascular accident
                                    <xref ref-type="table-fn" rid="tfn22">&#x2021;</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14 (4.76)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">84 (1.97)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.51 (1.35 &#x2013; 4.35)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.90 (1.00 &#x2013; 3.36)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Steroid usage for COVID 
                                    <xref ref-type="table-fn" rid="tfn21">&#x2020;</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">192 (65.31)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1822 (42.66)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.53 (1.98 &#x2013; 3.24)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.65 (1.27 &#x2013; 2.19)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Immunosuppression</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23 (7.82)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">287 (6.72)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.18 (0.76 &#x2013; 1.83)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Antibiotic use
                                    <xref ref-type="table-fn" rid="tfn23">
                                        <sup>&#x00a7;</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">180 (61.22)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1755 (41.09)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.26 (1.78 &#x2013; 2.89)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>1.46 (1.11 &#x2013; 1.92)</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Severe COVID-19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">131 (44.56)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1152 (26.97)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.17 (1.71 &#x2013; 2.77)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Data are n (%). OR=Odds ratio, CVC=Central venous catheterization, including hemodialysis catheter. All variables were analyzed but only statistically significant variables or variables of interest are presented. IMI = Invasive mold infections.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn20">
                                <label>
                                    <sup>*</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> &lt; 0.001.</p>
                            </fn>
                            <fn id="tfn21">
                                <label>
                                    <sup>&#x2020;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.001.</p>
                            </fn>
                            <fn id="tfn22">
                                <label>
                                    <sup>&#x2021;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.037.</p>
                            </fn>
                            <fn id="tfn23">
                                <label>
                                    <sup>&#x00a7;</sup>
                                </label>
                                <p>
                                    <italic toggle="yes">P</italic> =0.008.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec6">
                <title>Outcome</title>
                <p>Compared to patients without IFI, patients with IFI had a longer duration of hospital stay (8 days vs 14 days, 
                    <italic toggle="yes">P</italic> &lt;0.001), and the in-hospital mortality was more in the IFI group (21.2 vs 41.0%, 
                    <italic toggle="yes">P</italic>&lt;0.001) (
                    <xref ref-type="table" rid="T6">Table 6</xref>).</p>
                <table-wrap id="T6" orientation="portrait" position="float">
                    <label>Table 6. </label>
                    <caption>
                        <title>Outcomes in active COVID-19 patients with and without IFI.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Patients with Active COVID-19</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">With IFI (n=366), n(%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Without IFI (n=4199), n(%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">P value</italic>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Unadjusted OR (95% CI)</italic>
                                </th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Escalation of respiratory support</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">158 (43.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">887 (21.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.84 (2.28 to 3.53)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Duration of hospital stay, median (IQR) in days</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14 (10-23)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8 (6-11)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001
                                    <xref ref-type="table-fn" rid="tfn24">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.07 (1.06 to 1.08)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">In-hospital mortality</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">150 (41.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">892 (21.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.57 (2.06 to 3.21)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Data are n (%). OR=Odds ratio; IFI, Invasive Fungal Infection.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn24">
                                <label>*</label>
                                <p>Mann&#x2013;Whitney U test.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec7" sec-type="discussion">
            <title>Discussion</title>
            <p>At a global scale, both the absolute incidence of IFI as well as its geographical extent are increasing probably secondary to changing climatic conditions, ease of international travel, increased antifungal use, and frequent immunosuppression.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> Recently, the World Health Organization has enlisted several fungal infections as a major threat to public health.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> In the Indian context, even though IFI is associated with significant morbidity and mortality in hospitalized and immunocompromised patients, the real magnitude of IFI remains largely unknown. In India, during the second wave of COVID-19, there was a sudden increase in the number of IFI cases among COVID-19 patients. Numerous risk factors, such as corticosteroid therapy, diabetes mellitus, climatic conditions favoring fungal spread, genetic predisposition for developing IFI, and COVID-19 per se were implicated in such occurrences.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> A recent systematic review found that around 4.1% of Indians have some form of fungal infection and the occurrence of mucormycosis was 70 to 80-fold higher in India compared to Western countries.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> In our study, we found about 8% of the hospitalized COVID patients to have IFI and 60 out of 4565 patients (13 per 1000) hospitalized for COVID-19 to have mucormycosis, which are higher than that of previous estimates and the Western population.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>Invasive mold infections were present in around 8% of our patients hospitalized with recent COVID-19. While it has been established that pulmonary mold infections are associated with immunosuppression, the rhino-orbital form has previously shown an association with both corticosteroids and hyperglycemia.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> In our patients hospitalized for COVID-19, both rhino-orbital and pulmonary invasive mold infections were common, whereas, among patients hospitalized with post-COVID-19 complications, the rhino-orbital form was more common. The difference could be due to two possible explanations. Firstly, all of our post-COVID-19 patients were previously treated for active COVID-19 in outside hospitals, wherein the possible use of unwarranted and higher than the recommended dose of corticosteroids cannot be ruled out. Both high-dose corticosteroids and related hyperglycemia might have contributed to predominant rhino-orbital mucormycosis in this post-COVID-19 group. Secondly, in this subset of post-COVID-19 patients, early mortality compounded by the difficulty in the detection of pulmonary mold infections might have led to a lesser number of patients with pulmonary presentations among this group. Among patients hospitalized with recent COVID-19, 1.9% had invasive candidiasis. Non-albicans spp. of candida were the predominant species causing candidemia and alarmingly, 
                <italic toggle="yes">Candida auris</italic> constituted one-third of the entire isolates causing candidemia.</p>
            <p>We found that both diabetes mellitus (adjusted OR, 2.06; 95%CI, 1.62 to 2.62) and diabetic ketoacidosis (adjusted OR, 3.31; 95%CI, 1.93 to 5.58) were associated with invasive fungal infections. Hyperglycaemia causes defective chemotaxis, phagocyte dysfunction, and impaired intracellular killing of fungi.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> In addition, the acidosis seen in ketoacidosis and CKD has been shown to predispose to mucormycosis.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> We also found corticosteroids to be associated with invasive fungal infections (adjusted OR, 1.39; 95%CI, 1.07 to 1.81). Steroids predispose fungal infections by causing phagocyte dysfunction and hyperglycemia. We found no association between the occurrence of invasive fungal infections and other immunosuppressive states, however, the numbers were small. About 40% of patients admitted for COVID-19 received antibiotics during their hospital stay before the development of IFI and it was associated with IFI (adjusted OR, 1.65; 95%CI, 1.27 to 2.14). Exposure to antibiotics can disrupt the commensal flora and can predispose to IFI.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
            </p>
            <p>Prior stroke, which has not been shown to be associated with fungal infections, emerged as an independent predictor of IFI (adjusted OR, 2.23; 95%CI, 1.28 to 3.72). Longer duration of hospital stay, a known risk factor for the development of Candida infections,
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> is probably responsible for increased candidiasis in these patients with stroke. Both CVC usage (adjusted OR, 2.23; 95%CI, 1.28 to 3.72) and ESRD (adjusted OR, 2.23; 95%CI, 1.28 to 3.72) are known risk factors for invasive candidiasis and invasive mold infections, respectively. Unlike other studies, we did not find any association between sex, age, and severity of COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup> As expected, we found poor outcomes associated with IFI. The number of patients studied, and the proportion of patients with diabetes mellitus and end-stage renal disease in our study were similar to the RECOVERY trial. The dose of corticosteroids used were also similar.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> However, the incidence of IFI was higher among our patients. This may be interpreted as a unique susceptibility of Indians to invasive fungal infections and may be due to the high baseline risk of diabetes mellitus,
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> and environmental and probable genetic factors.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup>
            </p>
            <p>Our institute being one of the COVID care centres, catered to a large population during the epidemic. Thus, despite being a single-center study, we have included a large patient population. To make the study reliable, we have included only those patients with laboratory confirmation of COVID-19. Extensive workup (microbiological, histopathological, and radiological investigations) was done on every patient in whom IFI was suspected to classify based on EORTC guidelines for IFI. In our institute there was no routine screening of patients for fungal colonization was not done as it is not a recommended practice and hence exact prevalence of colonization/infection of IFI could not be estimated in this retrospective case record-based study. Possible confounding due to poor socioeconomic status, drug therapy before hospitalization, seasonal and environmental factors could not be adjusted for.</p>
            <p>While there is no doubt that higher than the recommended dose or unwarranted use of corticosteroids in COVID needs to be avoided, the possibility that corticosteroid directly or indirectly by inducing hyperglycemia, poses an increased risk of IFI in the Indian population needs to be borne in mind before extrapolating the use of corticosteroid in severe COVID as per Western recommendations. Recently hydrocortisone has shown mortality benefits in severe community-acquired pneumonia.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> Given the high prevalence of IFI in the Indian population especially in the context of steroid usage, extreme caution has to be observed in extrapolating the above findings in the Indian population. This is one of the important implications of our study findings. In the Indian population, the benefits of corticosteroid therapy shown in clinical trials for various indications conducted in Western countries may be offset by fungal infections and may not be applicable. Due caution needs to be exercised before extending corticosteroid use in the Indian population.</p>
            <p>The occurrence of IFI is higher in Indian COVID-19 patients as compared to the Western population. Corticosteroids appear to be a significant predictor of IFI, and methylprednisolone appears to have a slightly higher risk than dexamethasone. We also found that diabetes mellitus, diabetic ketoacidosis, end-stage renal disease, and central venous catheterization as independent risk factors of IFI. Corticosteroid use, though shown to be beneficial, the increased incidence of IFI in the Indian population may negate the beneficial efforts of corticosteroids in the Indian population. To reduce the risk of IFI, we recommend adherence to the rational use of corticosteroids and antibiotics, along with monitoring of serum glucose levels.</p>
        </sec>
    </body>
    <back>
        <sec id="sec10" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec11">
                <title>Underlying data</title>
                <p>Figshare: Invasive Fungal Infections in Patients with Recent COVID-19. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.24014898.v2">https://doi.org/10.6084/m9.figshare.24014898.v2</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref33">33</xref>
</sup>
                </p>
            </sec>
            <sec id="sec12">
                <title>Extended data</title>
                <p>Figshare: Supplementary figure: Modified EORTC based definitions of invasive fungal infections used in the study. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.24156471.v1">https://doi.org/10.6084/m9.figshare.24156471.v1</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref34">34</xref>
</sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
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                    <xref ref-type="aff" rid="r251702a2">2</xref>
                    <role>Co-referee</role>
                </contrib>
                <contrib contrib-type="author">
                    <name>
                        <surname>Sinha</surname>
                        <given-names>Sony</given-names>
                    </name>
                    <xref ref-type="aff" rid="r251702a1">1</xref>
                    <role>Co-referee</role>
                </contrib>
                <aff id="r251702a1">
                    <label>1</label>Ophthalmology, ESIC Medical College and Hospital, Patna, Bihar, India</aff>
                <aff id="r251702a2">
                    <label>2</label>Community Medicine, Patna Medical College, Patna, Bihar, 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>3</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Nishant P 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 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="relatedArticleReport251702" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.141573.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Corticosteroids and invasive fungal infections in hospitalized COVID-19 patients &#x2013; A single-center cross-sectional study: the authors have provided a&#x00a0;retrospective analysis of patients admitted during the COVID-19 pandemic and evaluated the association of invasive&#x00a0;fungal infections (IFI) with&#x00a0;demographic, clinical, and laboratory features of the patients.</p>
            <p> </p>
            <p> Here are my comments:</p>
            <p> 1. "When the epidemic of coronavirus disease 2019 (COVID-19) started, therapeutic options were few and were purported with no evidence." Consider revising.</p>
            <p> 2. "Though corticosteroid therapy was quite beneficial in the Western world.,," Provide a reference showing real-world evidence, or consider revising.</p>
            <p> 3. "the unscrupulous use of high-dose corticosteroids..."&#x00a0; and "Unless the real extent of the benefit of corticosteroid therapy is ascertained in Indian patients, clinicians may tend to use corticosteroids in off-label indications like non-COVID ARDS also." Provide references showing real-world evidence, or consider revising.</p>
            <p> 4. "Recent immunosuppressive therapy (corticosteroid or other immunosuppressants) was present in" consider revising.</p>
            <p> 5. Expand RO, ROC, RC in table 3</p>
            <p> 6. Sections of the text are repeating the data provided in the table, making it unnecessarily long. Consider revising.</p>
            <p> 7. "Among those admitted for active COVID-19, 366 (8%) developed an invasive fungal infection during their hospital stay..." Do we have information on the association of the severity of illness at presentation with the time interval of onset and causative organism of the IFI? If yes, kindly include this analysis. If not, kindly mention it as a limitation of this report.</p>
            <p> 8. State the abbreviation IMI from table 5 in the text prior to the table</p>
            <p> 9. "There are several reasons for the possible increase in the incidence of fungal infections among Indian patients with COVID-19. Indian people are more susceptible than the Western population to diabetes as indicated by the Y-Y paradox.
                <sup>
                    <ext-link ext-link-type="uri" xlink:href="https://f1000research.com/my/referee/report/251702#ref2">2</ext-link>
                </sup>
                <sup>,</sup>
                <sup>
                    <ext-link ext-link-type="uri" xlink:href="https://f1000research.com/my/referee/report/251702#ref3">3</ext-link>
                </sup>&#x00a0;Hence, it is possible that corticosteroid therapy, by producing hyperglycemia in non-diabetics, may increase the incidence of fungal infections. Though debatable, other causes like the unscrupulous use of high-dose corticosteroids, climatic conditions favoring fungal spore dissemination, genetic susceptibility, and poor blood sugar control may be leading to an increased incidence of fungal infections in India, especially mucormycosis." Consider migrating to discussion section, as well as shortening the paragraph as it does not add much information to what is already known.</p>
            <p> 10. "Among patients hospitalized with recent COVID-19, 1.9% had invasive candidiasis. Non-albicans spp. of candida were the predominant species causing candidemia and alarmingly,&#x00a0;
                <italic>Candida auris</italic>&#x00a0;constituted one-third of the entire isolates causing candidemia." Avoid repeating results in the discussion section and provide context in the light of which these findings are relevant to the subject matter. The phrase "causing candidemia" need not be repeated.</p>
            <p> 11. Kindly refer to COVID-19 as a pandemic and IFI during COVID-19 as an epidemic.</p>
            <p> 12. "Extensive workup (microbiological, histopathological, and radiological investigations) was done on every patient in whom IFI was suspected to classify based on EORTC guidelines for IFI." While this is a strength of the study, the implications of this exercise have not been elucidated.</p>
            <p> 13.&#x00a0;It would be helpful to analyse levels of inflammatory markers for risk stratification.</p>
            <p> 14. The conclusion that "methylprednisolone appears to have a slightly higher risk than dexamethasone" needs to be substantiated further in the results.</p>
            <p> 15. "In the Indian population, the benefits of corticosteroid therapy shown in clinical trials for various indications conducted in Western countries may be offset by fungal infections and may not be applicable. Due caution needs to be exercised before extending corticosteroid use in the Indian population." ... "Corticosteroid use, though shown to be beneficial, the increased incidence of IFI in the Indian population may negate the beneficial efforts of corticosteroids in the Indian population. To reduce the risk of IFI, we recommend adherence to the rational use of corticosteroids and antibiotics, along with monitoring of serum glucose levels." This is apparently the key message of the manuscript, but it does not add anything to the existing literature.</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>Partly</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>Ophthalmology, public health, nanotechnology</p>
            <p>We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment11554-251702">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Pari Thenmozhi</surname>
                            <given-names>Hariswar</given-names>
                        </name>
                        <aff>Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India, Pondicherry, Pondicherry, India</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>13</day>
                    <month>5</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Reviewer Comment:</p>
                <p> 1. "When the epidemic of coronavirus disease 2019 (COVID-19) started, therapeutic options were few and were purported with no evidence." Consider revising.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have revised it as &#x2018;when the pandemic of coronavirus disease 2019 (COVID-19) started, therapeutic options were unavailable and many were recommended without robust evidence&#x2019;.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 2. "Though corticosteroid therapy was quite beneficial in the Western world.,," Provide a reference showing real-world evidence, or consider revising.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have revised it as "Though corticosteroid therapy was quite beneficial, in the Indian population, the real extent of benefit which is probably offset by the increased risk of fungal infections, is not known." We have removed the comparison with the Western world.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 3. "the unscrupulous use of high-dose corticosteroids..."&#x00a0; and "Unless the real extent of the benefit of corticosteroid therapy is ascertained in Indian patients, clinicians may tend to use corticosteroids in off-label indications like non-COVID ARDS also." Provide references showing real-world evidence, or consider revising.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have revised it as &#x201c;Though debatable, other causes like the possible overuse of high-dose corticosteroids, climatic conditions favoring fungal spore dissemination, genetic susceptibility, and poor blood sugar control may be leading to an increased incidence of fungal infections in India, especially mucormycosis&#x201d;.</p>
                <p> We have removed the statement &#x201c;Unless the real extent of the benefit of corticosteroid therapy is ascertained in Indian patients, clinicians may tend to use corticosteroids in off-label indications like non-COVID ARDS also&#x201d;.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 4. "Recent immunosuppressive therapy (corticosteroid or other immunosuppressants) was present in" consider revising.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have revised it as &#x201c;Ongoing immunosuppressive therapy (corticosteroid or other immunosuppressants) for other indications was present in 113 patients (2.4%) (Table 1)&#x201d;.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 5. Expand RO, ROC, RC in table 3</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have made the suggested changes in the table 3.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 6. Sections of the text are repeating the data provided in the table, making it unnecessarily long. Consider revising.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have revised the Results section as suggested.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 7. "Among those admitted for active COVID-19, 366 (8%) developed an invasive fungal infection during their hospital stay..." Do we have information on the association of the severity of illness at presentation with the time interval of onset and causative organism of the IFI? If yes, kindly include this analysis. If not, kindly mention it as a limitation of this report.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We do not have the adequate information on the time interval of onset. Hence, we have included it as a limitation of the study. We have included the following statement &#x201c;Also, data pertaining to time interval of onset of COVID-19 is not available, its association with severity of illness could not be explored.&#x201d;</p>
                <p> Though we have provided the analysis pertaining to the association of severity and organism, we could not stratify based on time interval since onset of COVID-19.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 8. State the abbreviation IMI from table 5 in the text prior to the table</p>
                <p> </p>
                <p> Author Response:</p>
                <p> The expansion &#x2018;Invasive mold infections&#x2019; to the abbreviation IMI is added within the text prior to table 5.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 9. "There are several reasons for the possible increase in the incidence of fungal infections among Indian patients with COVID-19. Indian people are more susceptible than the Western population to diabetes as indicated by the Y-Y paradox.2,3 Hence, it is possible that corticosteroid therapy, by producing hyperglycemia in non-diabetics, may increase the incidence of fungal infections. Though debatable, other causes like the unscrupulous use of high-dose corticosteroids, climatic conditions favoring fungal spore dissemination, genetic susceptibility, and poor blood sugar control may be leading to an increased incidence of fungal infections in India, especially mucormycosis." Consider migrating to discussion section, as well as shortening the paragraph as it does not add much information to what is already known.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have moved the elaborate justification for the study to the Discussion section.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 10. "Among patients hospitalized with recent COVID-19, 1.9% had invasive candidiasis. Non-albicans spp. of candida were the predominant species causing candidemia and alarmingly, Candida auris constituted one-third of the entire isolates causing candidemia." Avoid repeating results in the discussion section and provide context in the light of which these findings are relevant to the subject matter. The phrase "causing candidemia" need not be repeated.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have removed the results that have been repeated in the discussion section. We have removed the following statement &#x201c;Among patients hospitalized with recent COVID-19, 1.9% had invasive candidiasis.&#x201d; We have removed the phrase "causing candidemia".</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 11. Kindly refer to COVID-19 as a pandemic and IFI during COVID-19 as an epidemic.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> We have corrected the term epidemic to pandemic.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 12. "Extensive workup (microbiological, histopathological, and radiological investigations) was done on every patient in whom IFI was suspected to classify based on EORTC guidelines for IFI." While this is a strength of the study, the implications of this exercise have not been elucidated.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> The likelihood of IFI is categorised into three levels based on EORTC guidelines. The major implication of this exercise is in case definition. This would help the readers to appreciate the certainty with which the diagnosis of IFI was made. We do not see any other implications to be mentioned in the article.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 13. It would be helpful to analyse levels of inflammatory markers for risk stratification.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> Inflammatory markers were not measured routinely. Since, this is a case record based retrospective study, inflammatory markers could be retrieved for less than 5% of the study participants. Hence, we could not analyse the levels of inflammatory markers.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 14. The conclusion that "methylprednisolone appears to have a slightly higher risk than dexamethasone" needs to be substantiated further in the results.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> The risk of invasive fungal infections with methylprednisolone, as compared to the baseline risk of dexamethasone was estimated separately using chi-square statistics. The odds ratio can be calculated from the numbers available in Table-2.</p>
                <p> </p>
                <p> Reviewer Comment:</p>
                <p> 15. "In the Indian population, the benefits of corticosteroid therapy shown in clinical trials for various indications conducted in Western countries may be offset by fungal infections and may not be applicable. Due caution needs to be exercised before extending corticosteroid use in the Indian population." ... "Corticosteroid use, though shown to be beneficial, the increased incidence of IFI in the Indian population may negate the beneficial efforts of corticosteroids in the Indian population. To reduce the risk of IFI, we recommend adherence to the rational use of corticosteroids and antibiotics, along with monitoring of serum glucose levels." This is apparently the key message of the manuscript, but it does not add anything to the existing literature.</p>
                <p> </p>
                <p> Author Response:</p>
                <p> In our study, we have clearly documented the frequency of invasive fungal infections in COVID-19 patients and its association with corticosteroid therapy. Though we have not estimated the extent to which fungal infection related mortality offsets the benefit of corticosteroids, we have provided a rough estimation of the burden of fungal infections among hospitalised patients. The estimate of mortality related to fungal infections would help clinicians to appreciate the complication rates, and hence be cautious of this complication and not to be over enthusiastic in the use of corticosteroid therapy.</p>
            </body>
        </sub-article>
    </sub-article>
</article>
