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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cell. Infect. Microbiol.</journal-id>
<journal-title>Frontiers in Cellular and Infection Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cell. Infect. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">2235-2988</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcimb.2021.770551</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cellular and Infection Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Pulmonary Mucormycosis as the Leading Clinical Type of Mucormycosis in Western China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Qu</surname>
<given-names>Junyan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/810555"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Xijiao</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1446556"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lv</surname>
<given-names>Xiaoju</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/710158"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Center of Infectious Disease, West China Hospital, Sichuan University</institution>, <addr-line>Chengdu</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Radiology Department, West China Hospital, Sichuan University</institution>, <addr-line>Chengdu</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Kai Huang, University of Texas Medical Branch at Galveston, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Muhammad Usman Tariq, Abu Dhabi School of Management, United Arab Emirates; Valentina Giudice, University of Salerno, Italy; Dora Edith Corzo-Leon, University of Aberdeen, United Kingdom</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Xiaoju Lv, <email xlink:href="mailto:lvxj33966@126.com">lvxj33966@126.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Clinical Microbiology, a section of the journal Frontiers in Cellular and Infection Microbiology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>22</day>
<month>11</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>770551</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>09</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>04</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Qu, Liu and Lv</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Qu, Liu and Lv</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>The aim was to better understand the clinical characteristics of patients with mucormycosis in western China. We retrospectively investigated the clinical, laboratory, radiological and treatment profiles of mucormycosis patients during a 10-year period (2010&#x2013;2019). As a result, 59 proven mucormycosis were enrolled in this study. It was found that 52.5% of patients had worse clinical outcomes. Pulmonary mucormycosis (PM) was the most common clinical manifestation. The most frequent risk factor was diabetes mellitus (38, 64.4%) for mucormycosis patients. Cough (43, 93.5%), fever (24, 52.2%) and hemoptysis/bloody phlegm (21, 45.7%) were the most common manifestations of PM. There were no differences in clinical manifestations, risk factors and laboratory tests between different clinical outcome groups (P&gt;0.05). Lymph node enlargement (30, 65.2%), patchy shadows (28, 60.9%), cavitation (25, 53.3%) and bilateral lobe involvement (39, 84.8%) were the most common on chest CT. Nodule was more common in good outcome group (P &lt;0.05). A total of 48 cases (81.4%) were confirmed by histopathological examination, 22 cases (37.3%) were confirmed by direct microscopy. PM patients were treated with amphotericin B/amphotericin B liposome or posaconazale had better clinical outcomes (P &lt;0.05). In conclusion, PM was the most common clinical type of mucormycosis in China. Diabetes mellitus was the most common risk factor. PM has diverse imaging manifestations and was prone to bilateral lobes involvement. Early diagnosis and effective anti-mucor treatment contribute to successful treatment.</p>
</abstract>
<kwd-group>
<kwd>mucormycosis</kwd>
<kwd>pulmonary mucormycosis</kwd>
<kwd>diabetes</kwd>
<kwd>clinical analysis</kwd>
<kwd>clinical outcome</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="29"/>
<page-count count="10"/>
<word-count count="5017"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Mucormycosis is a rare, emerging and opportunistic fungal infection with high morbidity and mortality caused by filamentous fungi of the Mucoraceae family, order Mucorales. Mucorales fungi are ubiquitous in nature. Humans are infected mainly by inhaling sporangiospores, occasionally through the ingestion of contaminated food or traumatic inoculation (<xref ref-type="bibr" rid="B17">Prakash and Chakrabarti, 2019</xref>; <xref ref-type="bibr" rid="B20">Shariati et&#xa0;al., 2020</xref>). The prevalence of mucormycosis varies between developing and developed countries, ranging from 0.01 to 14 per 100 000 population in Europe and India (<xref ref-type="bibr" rid="B2">Bitar et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B3">Chakrabarti and Singh, 2014</xref>; <xref ref-type="bibr" rid="B19">Ruhnke et&#xa0;al., 2015</xref>). With the growth of the number of immunocompromised patients, increased awareness and development of diagnostic techniques, the incidence of mucormycosis is rising (<xref ref-type="bibr" rid="B18">Prakash et&#xa0;al., 2019</xref>). According to clinical presentations, mucormycosis is mainly classified as rhino-orbito-cerebral, pulmonary, cutaneous, gastrointestinal and disseminated types (<xref ref-type="bibr" rid="B24">Skiada et&#xa0;al., 2020</xref>). The common risk factors of mucormycosis are diabetes, hematological malignancy, use of corticosteroids or immunosuppressants, and trauma (<xref ref-type="bibr" rid="B16">Petrikkos et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B6">Jeong et&#xa0;al., 2019</xref>). However, the main cause of mucormycosis also varies in different countries. Hematological malignancies are the main cause in countries with high income, while diabetes mellitus (DM) or trauma are the main cause in developing countries (<xref ref-type="bibr" rid="B3">Chakrabarti and Singh, 2014</xref>). Diagnosis of mucormycosis is challenging because of the low sensitivity and specificity of clinical diagnostic methods (<xref ref-type="bibr" rid="B22">Skiada et&#xa0;al., 2018</xref>).</p>
<p>The mortality of mucormycosis remains high, it may be related to delayed diagnosis, high cost of managing mucormycosis and limited treatment options (<xref ref-type="bibr" rid="B22">Skiada et&#xa0;al., 2018</xref>). Previous studies on the characteristics of mucormycosis have been conducted mainly in America, Europe and India (<xref ref-type="bibr" rid="B17">Prakash and Chakrabarti, 2019</xref>). Data about mucormycosis from China is sparse. The causative agents of mucormycosis vary with different geographical locations (<xref ref-type="bibr" rid="B17">Prakash and Chakrabarti, 2019</xref>), and the epidemiology, the clinical disease pattern of mucormycosis vary from country to country.</p>
<p>To better understand the clinical characteristics of patients with mucormycosis in China, in this retrospective study, we compared the demographic features, clinical presentations, laboratory data, radiographic findings and therapeutic strategies in mucormycosis patients with different clinical outcomes who were admitted to a university hospital from Jan 2010 to Dec 2019 in western China.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="s2_1">
<title>Patients</title>
<p>From Jan 2010 to Dec 2019, the patients with a diagnosis of mucormycosis at hospital discharge were retrospectively reviewed in West China Hospital, Sichuan University, a 4,300-bed academic tertiary hospital in Chengdu, China. According to the European Organization for Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG) criteria and previous references (<xref ref-type="bibr" rid="B5">De Pauw et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B16">Petrikkos et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B22">Skiada et&#xa0;al., 2018</xref>), inclusion in the final study group required the diagnosis of proven mucormycosis as defined as follows: (1) age &#x2265; 14 years; (2) clinical manifestations and radiographic findings consistent with mucormycosis; and (3) histological presence of mucormycosis in tissue specimens, and/or broad-based, ribbon-like, non-septate hyphae with right-angle branching filamentous fungi on direct microscopy of clinical specimens, and/or Mucorales species cultured from clinical specimens. Based on clinical presentation and the involvement of the body sites, rhino-orbital-cerebral, pulmonary, cutaneous and disseminated mucormycosis were classified (<xref ref-type="bibr" rid="B6">Jeong et&#xa0;al., 2019</xref>). The following data of demographic information, underlying diseases, use of corticosteroid or immunosuppressive agent, clinical manifestations, laboratory data, radiologic findings, diagnostic procedures, therapeutic strategies and clinical outcomes at 90 days were collected.</p>
<p>The study was approved by the Ethics Committee of West China Hospital, Sichuan University. Because all the data in this study were routinely obtained, written informed consent was waived.</p>
</sec>
<sec id="s2_2">
<title>Laboratory Studies</title>
<p>Laboratory tests including complete blood count, blood biochemistry, procalcitionin (PCT), C-reactive protein, T lymphocyte subset, HIV testing, serum (1,3)-beta-D-glucan test (BDG test), and galactomannan test (GM test) were performed. Clinical samples (including blood, sputum, secretions, urine) were aseptically collected and cultured under aerobic or anaerobic conditions. Bacterial species were isolated and identified using MicroScan WalkAway-96 System (Siemens, USA). Fungal culture was performed on Sabouraud dextrose agar (SDA) and incubated at 30&#xb0;C. All the items were performed in the Department of Laboratory Medicine of our hospital.</p>
</sec>
<sec id="s2_3">
<title>Radiological Assessment</title>
<p>Imaging examinations such as chest computed tomography (CT), abdominal CT, fibroptic bronchoscopy were performed at the discretion of the treating physicians. The CT scans were performed using 64-row multi-slice spiral CT scanner (SOMATOM definition AS+, Siemens) in our hospital. All images were reviewed independently by two experienced radiologists. For patients with PM, chest CT findings including nodule, mass, cavity, patchy consolidation, ground glass opacity, reversed halo sign, lymph node enlargement, pleural effusion and the distribution of the lesion in the lungs were recorded.</p>
</sec>
<sec id="s2_4">
<title>Treatment Strategies and Clinical Outcomes</title>
<p>The patients with mucormycosis were treated with amphotericin B (AmB, 0.5-1 mg/kg per day) (North China Pharmaceutical Co., Ltd., China) or amphotericin B liposome (LAmB, 3-6 mg/kg per day) in accordance with the drug instructions, guidelines (<xref ref-type="bibr" rid="B21">Skiada et&#xa0;al., 2013</xref>) and patient tolerance. Posaconazole oral suspension (40mg/ml, 10ml, twice daily) (Patheon Inc, Whitby, ON, Canada) was used in patients who have contraindications to amphotericin B or who cannot tolerate the side effects of amphotericin B like reduced kidney function, electrolyte imbalances, nausea and vomiting. The treatment duration was determined by the treating physicians according to the patient&#x2019;s treatment response and the size of the focus. Management of patients with diabetes included dietary guidance, tight glucose control with insulin and/or hypoglycemic drugs, multiple flash glucose monitoring daily and treatment of complications. A multidisciplinary consulting team, including diabetes, infectious disease, nutrition, wound therapy, surgery, clinical microbiology, and clinical pharmacy, that offered specialist advice, on-going management. Other underlying diseases of these patients such as immune system disease, chronic lung disease were treated normally and systematically. For bacterial co-infection patients, empirical or targeted antimicrobial therapy were given. Clinical outcomes of patients with mucormycosis were evaluated at 90 days after diagnosis. According to clinical manifestations, laboratory findings and image changes, their clinical outcomes were divided into good and worse outcome. Death or disease progression or persistence were classified as worse outcome. The continuous improvement of clinical symptoms and imaging findings were classified as good outcome.</p>
</sec>
<sec id="s2_5">
<title>Statistical Analysis</title>
<p>Statistical analyses were performed using IBM SPSS Statistics for Windows v.26.0 (IBM Corp., Armonk, NY, USA). The Shapiro-Wilk normality test was used to test the normality of all quantitative variables. Continuous variables with normal distribution were presented as mean&#xb1; standard deviation (SD) and compared by Student&#x2019;s t-test. The relationship between categorical variables was assessed using Chi-square test or Fisher&#x2019;s exact test. A two-tailed P value lower than 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Demographic Characteristics and Clinical Outcomes of Mucormycosis Patients</title>
<p>A total of 68 patients with mucormycosis were admitted to our hospital from January 2010 to December 2019, 59 of whom with proven mucormycosis (mean age 54.75 &#xb1; 14.72 years; 44 males) were enrolled in this retrospective study. Pulmonary mucormycosis (PM) was the most commonly observed manifestation (46/59, 78.0%), followed by rhino-orbital-cerebral (9/59, 15.3%) and disseminated mucormycosis (3/59, 5.0%). There was only one case of cutaneous mucormycosis. These patients were classified as pulmonary type and other type mucormycosis based on clinical type. The demographic and clinical outcomes of these patients were summarized in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. The ages of patients with PM was higher than that of patients with non-pulmonary mucormycosis (P=0.015). The most frequent underlying disease was diabetes mellitus (38, 64.4%) for mucormycosis patients. More patients with PM had diabetes mellitus than patients with non-pulmonary mucormycosis (P=0.027). A total of 31 mucormycosis patients (52.5%) had worse clinical outcomes, clinical outcome was not obviously different between the two groups (P&gt;0.05).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Demographic and clinical outcomes in patients with mucormycosis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Variables</th>
<th valign="top" align="center"/>
<th valign="top" colspan="2" align="center">Clinical type</th>
<th valign="top" rowspan="2" align="center">P-value</th>
</tr>
<tr>
<th valign="top" align="center">All (N = 59)</th>
<th valign="top" align="center">Pulmonary type (N = 46)</th>
<th valign="top" align="center">Other type (N = 13)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Male</bold>
</td>
<td valign="top" align="center">44 (74.6)</td>
<td valign="top" align="center">35 (76.1)</td>
<td valign="top" align="center">9 (69.2)</td>
<td valign="top" align="center">0.616</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Age (years) (mean &#xb1; SD)</bold>
</td>
<td valign="top" align="center">54.75 &#xb1; 14.72</td>
<td valign="top" align="center">57.41 &#xb1; 12.40</td>
<td valign="top" align="center">45.31 &#xb1; 18.64</td>
<td valign="top" align="center">
<bold>0.015*</bold>
</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Underlying diseases or risk factors</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes mellitus</td>
<td valign="top" align="center">38 (64.4)</td>
<td valign="top" align="center">33 (71.7)</td>
<td valign="top" align="center">5 (38.5)</td>
<td valign="top" align="center">
<bold>0.027*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Immune system disease</td>
<td valign="top" align="center">2 (3.4)</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (7.7)</td>
<td valign="top" align="center">0.395</td>
</tr>
<tr>
<td valign="top" align="left">Corticosteroid medication or immunosuppressive drugs</td>
<td valign="top" align="center">4 (6.8)</td>
<td valign="top" align="center">3 (6.5)</td>
<td valign="top" align="center">1 (7.7)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Hematological malignancy</td>
<td valign="top" align="center">3 (5.1)</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">2 (15.4)</td>
<td valign="top" align="center">0.119</td>
</tr>
<tr>
<td valign="top" align="left">Solid tumor</td>
<td valign="top" align="center">2 (3.4)</td>
<td valign="top" align="center">2 (4.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Chronic kidney diseases</td>
<td valign="top" align="center">3 (5.1)</td>
<td valign="top" align="center">3 (6.5)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Chronic lung disease</td>
<td valign="top" align="center">8 (13.6)</td>
<td valign="top" align="center">7 (15.2)</td>
<td valign="top" align="center">1 (7.7)</td>
<td valign="top" align="center">0.671</td>
</tr>
<tr>
<td valign="top" align="left">Chronic liver disease</td>
<td valign="top" align="center">2 (1.7)</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (7.7)</td>
<td valign="top" align="center">0.395</td>
</tr>
<tr>
<td valign="top" align="left">Truma</td>
<td valign="top" align="center">2 (3.4)</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (7.7)</td>
<td valign="top" align="center">0.395</td>
</tr>
<tr>
<td valign="top" align="left">None</td>
<td valign="top" align="center">8 (13.6)</td>
<td valign="top" align="center">6 (13.0)</td>
<td valign="top" align="center">2 (15.4)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Co-infection of other pathogens</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Bacteria</td>
<td valign="top" align="center">42 (71.2)</td>
<td valign="top" align="center">32 (69.6)</td>
<td valign="top" align="center">10 (76.9)</td>
<td valign="top" align="center">0.738</td>
</tr>
<tr>
<td valign="top" align="left">Other fungi</td>
<td valign="top" align="center">16 (23.7)</td>
<td valign="top" align="center">14 (30.4)</td>
<td valign="top" align="center">2 (15.4)</td>
<td valign="top" align="center">0.481</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Clinical outcome</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Good outcome</td>
<td valign="top" align="center">28 (47.5)</td>
<td valign="top" align="center">23 (50.0)</td>
<td valign="top" align="center">5 (38.5)</td>
<td valign="top" rowspan="1" align="center">0.462</td>
</tr>
<tr>
<td valign="top" align="left">Worse outcome</td>
<td valign="top" align="center">31 (52.5)</td>
<td valign="top" align="center">23 (50.0)</td>
<td valign="top" align="center">8 (61.5)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*P &lt; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Demographic and Clinical Characteristics in Patients With PM</title>
<p>Demographic and clinical features of PM patients with different clinical outcomes were shown in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. The most common clinical symptoms of PM patients were cough (43, 93.5%), fever (24, 52.2%) and hemoptysis/bloody phlegm (21, 45.7%). Diabetes mellitus (33, 71.7%) was the most frequent underlying disease. There were no significant difference in the gender, age, clinical symptoms and underlying diseases beween good and worse outcome group (P&gt;0.05). For laboratory results, there was no significant difference between the two groups (P&#x2009;&gt;&#x2009;0.05).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Demographic and clinical characteristics in patients with pulmonary mucormycosis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">All (N = 46) (n,%)</th>
<th valign="top" align="center">Good outcome (N = 23) (n,%)</th>
<th valign="top" align="center">Worse outcome (N = 23) (n,%)</th>
<th valign="top" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">35 (76.1)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">6 (26.1)</td>
<td valign="top" align="center">0.288</td>
</tr>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">57.41 &#xb1; 12.40</td>
<td valign="top" align="center">56.00 &#xb1; 13.44</td>
<td valign="top" align="center">58.82 &#xb1; 11.38</td>
<td valign="top" align="center">0.446</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Presenting symptoms and signs</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Fever</td>
<td valign="top" align="center">24 (52.2)</td>
<td valign="top" align="center">13 (56.5)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">0.768</td>
</tr>
<tr>
<td valign="top" align="left">Cough</td>
<td valign="top" align="center">43 (93.5)</td>
<td valign="top" align="center">21 (91.3)</td>
<td valign="top" align="center">22 (95.7)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">hemoptysis or bloody phlegm</td>
<td valign="top" align="center">21 (45.7)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">12 (52.2)</td>
<td valign="top" align="center">0.554</td>
</tr>
<tr>
<td valign="top" align="left">Chest pain</td>
<td valign="top" align="center">7 (15.2)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">0.414</td>
</tr>
<tr>
<td valign="top" align="left">Shortness of breath</td>
<td valign="top" align="center">14 (30.4)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">0.200</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Underlying diseases or risk factors</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes mellitus</td>
<td valign="top" align="center">33 (71.7)</td>
<td valign="top" align="center">16 (69.6)</td>
<td valign="top" align="center">17 (73.9)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Immune system disease</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Corticosteroid medication or immunosuppressive drugs</td>
<td valign="top" align="center">3 (6.5)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Hematological malignancy</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Solid tumor</td>
<td valign="top" align="center">2 (4.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">0.489</td>
</tr>
<tr>
<td valign="top" align="left">Chronic kidney diseases</td>
<td valign="top" align="center">3 (6.5)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Chronic lung disease</td>
<td valign="top" align="center">7 (15.2)</td>
<td valign="top" align="center">4 (17.4)</td>
<td valign="top" align="center">3 (13.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Chronic liver disease</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Truma</td>
<td valign="top" align="center">1 (2.2)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">None</td>
<td valign="top" align="center">6 (13.0)</td>
<td valign="top" align="center">4 (17.4)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">0.665</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Laboratory data</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">White blood cell (&#xd7; 10<sup>9</sup>/L)</td>
<td valign="top" align="char" char="&#xb1;">9.13 &#xb1; 6.84</td>
<td valign="top" align="char" char="&#xb1;">9.58 &#xb1; 9.02</td>
<td valign="top" align="char" char="&#xb1;">8.69 &#xb1; 3.76</td>
<td valign="top" align="center">0.665</td>
</tr>
<tr>
<td valign="top" align="left">Neutrophil (%)</td>
<td valign="top" align="char" char="&#xb1;">71.96 &#xb1; 12.24</td>
<td valign="top" align="char" char="&#xb1;">74.42 &#xb1; 12.11</td>
<td valign="top" align="char" char="&#xb1;">69.38 &#xb1; 12.10</td>
<td valign="top" align="center">0.170</td>
</tr>
<tr>
<td valign="top" align="left">Lymphocyte (&#xd7; 10<sup>9</sup>/L)</td>
<td valign="top" align="char" char="&#xb1;">1.48 &#xb1; 0.67</td>
<td valign="top" align="char" char="&#xb1;">1.35 &#xb1; 0.60</td>
<td valign="top" align="char" char="&#xb1;">1.62 &#xb1; 0.73</td>
<td valign="top" align="center">0.180</td>
</tr>
<tr>
<td valign="top" align="left">Eosinophil (&#xd7; 10<sup>9</sup>/L)</td>
<td valign="top" align="char" char="&#xb1;">0.33 &#xb1; 1.17</td>
<td valign="top" align="char" char="&#xb1;">0.48 &#xb1; 1.46</td>
<td valign="top" align="char" char="&#xb1;">0.19 &#xb1; 0.26</td>
<td valign="top" align="center">0.397</td>
</tr>
<tr>
<td valign="top" align="left">Mononuclear cell (&#xd7; 10<sup>9</sup>/L)</td>
<td valign="top" align="char" char="&#xb1;">0.49 &#xb1; 0.23</td>
<td valign="top" align="char" char="&#xb1;">0.47 &#xb1; 0.26</td>
<td valign="top" align="char" char="&#xb1;">0.50 &#xb1; 0.20</td>
<td valign="top" align="center">0.539</td>
</tr>
<tr>
<td valign="top" align="left">Procalcitionin (ng/mL)</td>
<td valign="top" align="char" char="&#xb1;">0.21 &#xb1; 0.49</td>
<td valign="top" align="char" char="&#xb1;">0.29 &#xb1; 0.66</td>
<td valign="top" align="char" char="&#xb1;">0.12 &#xb1; 0.13</td>
<td valign="top" align="center">0.289</td>
</tr>
<tr>
<td valign="top" align="left">C-reactive protein (mg/L)</td>
<td valign="top" align="char" char="&#xb1;">70.31 &#xb1; 87.94</td>
<td valign="top" align="char" char="&#xb1;">66.75 &#xb1; 97.40</td>
<td valign="top" align="char" char="&#xb1;">73.17 &#xb1; 82.08</td>
<td valign="top" align="center">0.831</td>
</tr>
<tr>
<td valign="top" align="left">Eerythrocyte sedimentation rate (mm/h)</td>
<td valign="top" align="char" char="&#xb1;">55.23 &#xb1; 24.06</td>
<td valign="top" align="char" char="&#xb1;">49.00 &#xb1; 24.64</td>
<td valign="top" align="char" char="&#xb1;">60.42 &#xb1; 23.31</td>
<td valign="top" align="center">0.278</td>
</tr>
<tr>
<td valign="top" align="left">CD4+ T lymphocyte (%)</td>
<td valign="top" align="char" char="&#xb1;">36.94 &#xb1; 10.33</td>
<td valign="top" align="char" char="&#xb1;">37.32 &#xb1; 8.00</td>
<td valign="top" align="char" char="&#xb1;">36.55 &#xb1; 12.54</td>
<td valign="top" align="center">0.771</td>
</tr>
<tr>
<td valign="top" align="left">CD8<sup>+</sup> T lymphocyte (%)</td>
<td valign="top" align="char" char="&#xb1;">31.61 &#xb1; 9.49</td>
<td valign="top" align="char" char="&#xb1;">32.92 &#xb1; 8.17</td>
<td valign="top" align="char" char="&#xb1;">30.30 &#xb1; 10.80</td>
<td valign="top" align="center">0.475</td>
</tr>
<tr>
<td valign="top" align="left">CD4/CD8 ratio</td>
<td valign="top" align="char" char="&#xb1;">1.36 &#xb1; 0.77</td>
<td valign="top" align="char" char="&#xb1;">1.23 &#xb1; 0.40</td>
<td valign="top" align="center">1.48 &#xb1; 1.01</td>
<td valign="top" align="center">0.409</td>
</tr>
<tr>
<td valign="top" align="left">CD4<sup>+</sup> T lymphocyte (cells/&#x3bc;l)</td>
<td valign="top" align="char" char="&#xb1;">565.45 &#xb1; 288.69</td>
<td valign="top" align="char" char="&#xb1;">419.83 &#xb1; 92.04</td>
<td valign="top" align="char" char="&#xb1;">740.2 &#xb1; 357.47</td>
<td valign="top" align="center">0.062</td>
</tr>
<tr>
<td valign="top" align="left">CD8<sup>+</sup> T lymphocyte (cells/&#x3bc;l)</td>
<td valign="top" align="char" char="&#xb1;">396.82 &#xb1; 176.78</td>
<td valign="top" align="char" char="&#xb1;">338.50 &#xb1; 45.12</td>
<td valign="top" align="char" char="&#xb1;">466.80 &#xb1; 253.69</td>
<td valign="top" align="center">0.250</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Co-infecting agent</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Bacteria</td>
<td valign="top" align="center">25 (54.3)</td>
<td valign="top" align="center">12 (52.2)</td>
<td valign="top" align="center">13 (56.5)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Virus</td>
<td valign="top" align="center">2 (4.3)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Fungi</td>
<td valign="top" align="center">18 (39.1)</td>
<td valign="top" align="center">10 (43.5)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">0.763</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Findings of CT Scan in Patients With PM</title>
<p>The chest CT features of patients with PM were diverse, as shown in <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>. The detail of chest CT findings in these patients were shown in <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>. The most common manifestations were lymph node enlargement (30, 65.2%), patchy shadows (28, 60.9%), cavitation (25, 53.3%) and nodules (24, 52.2%). Nodule was more common in good outcome group than in worse outcome group (P &lt;0.05). Lymph node enlargement were more common in patients with worse outcome (P&lt;0.05). Bilateral lungs were involved in 84.8% (39/46) of patients, with the left lower lobe (20, 43.5%) and right lower lobe (18, 39.1%) most commonly involved. There was no significant difference in the lobe of lesion distribution between the two groups (P&gt;0.05). There were 13 patients with <italic>Mucor</italic> and <italic>Aspergillus</italic> co-infection and 1 patient with lung cancer. Based on imaging findings, 12 patients were suspected to be tumors, and 2 patients were suspected to be aspergillosis in the absence of concomitant <italic>Aspergillus</italic>. <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref> showed the changes of chest CT lesions during the follow-up of a patient with pulmonary fungal infection (<italic>Mucor</italic> with <italic>Aspergillus</italic>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The findings of chest computed tomography of pulmonary mucormycosis (patients with good outcome: <bold>A, B</bold>; patients with worse outcome: <bold>C&#x2013;H</bold>). <bold>(A)</bold> Multiple pleomorphic lesions in both lungs; <bold>(B)</bold> cavity with muralnodule (<italic>Mucor</italic> co-infecting with <italic>Aspergillus</italic>); <bold>(C)</bold> cavity in left lung; <bold>(D)</bold> thick-walled cavity shadow with gas-fluid level (<italic>Mucor</italic> co-infecting with <italic>Klebsiella pneumoniae</italic>); <bold>(E)</bold> mass shadow in the upper lobe of the left lung; <bold>(F)</bold> patchy shadow, nodules and consolidation in right lung; <bold>(G)</bold> cavity and ground-glass opacity; <bold>(H)</bold> reversed halo sign.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-770551-g001.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Chest CT findings of proven patients with pulmonary mucormycosis .</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Morphology</th>
<th valign="top" align="center">All (N = 46) (n,%)</th>
<th valign="top" align="center">Good outcome (N = 23) (n,%)</th>
<th valign="top" align="center">Worse outcome (N = 23) (n,%)</th>
<th valign="top" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Consolidation</td>
<td valign="top" align="center">20 (43.5)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">0.767</td>
</tr>
<tr>
<td valign="top" align="left">Nodule</td>
<td valign="top" align="center">24 (52.2)</td>
<td valign="top" align="center">16 (69.6)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">
<bold>0.038*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Ground-glass opacity</td>
<td valign="top" align="center">7 (15.2)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">0.414</td>
</tr>
<tr>
<td valign="top" align="left">Mass</td>
<td valign="top" align="center">15 (32.6)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">7 (30.4)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Cavitation</td>
<td valign="top" align="center">25 (53.3)</td>
<td valign="top" align="center">10 (43.5)</td>
<td valign="top" align="center">15 (65.2)</td>
<td valign="top" align="center">0.139</td>
</tr>
<tr>
<td valign="top" align="left">Patchy shadow</td>
<td valign="top" align="center">28 (60.9)</td>
<td valign="top" align="center">14 (60.9)</td>
<td valign="top" align="center">14 (60.9)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Fibrosis</td>
<td valign="top" align="center">17 (37.0)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Pleural effusion</td>
<td valign="top" align="center">22 (47.8)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">10 (43.5)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Pleural thickening</td>
<td valign="top" align="center">17 (37.0)</td>
<td valign="top" align="center">6 (26.1)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">0.221</td>
</tr>
<tr>
<td valign="top" align="left">Lymph node enlargement</td>
<td valign="top" align="center">30 (65.2)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">19 (82.6)</td>
<td valign="top" align="center">
<bold>0.029*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Reversed halo sign</td>
<td valign="top" align="center">5 (10.9)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">3 (13.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">Lobe of lesion distribution</td>
</tr>
<tr>
<td valign="top" align="left">Left upper lobe</td>
<td valign="top" align="center">12 (26.1)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">7 (30.4)</td>
<td valign="top" align="center">0.738</td>
</tr>
<tr>
<td valign="top" align="left">Left lower lobe</td>
<td valign="top" align="center">20 (43.5)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">0.767</td>
</tr>
<tr>
<td valign="top" align="left">Right upper lobe</td>
<td valign="top" align="center">12 (26.1)</td>
<td valign="top" align="center">7 (30.4)</td>
<td valign="top" align="center">5 (21.7)</td>
<td valign="top" align="center">0.738</td>
</tr>
<tr>
<td valign="top" align="left">Right middle lobe</td>
<td valign="top" align="center">11 (23.9)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">3 (13.0)</td>
<td valign="top" align="center">0.165</td>
</tr>
<tr>
<td valign="top" align="left">Right lower lobe</td>
<td valign="top" align="center">18 (39.1)</td>
<td valign="top" align="center">8 (34.8)</td>
<td valign="top" align="center">10 (43.5)</td>
<td valign="top" align="center">0.763</td>
</tr>
<tr>
<td valign="top" align="left">Bilateral involvement</td>
<td valign="top" align="center">39 (84.8)</td>
<td valign="top" align="center">20 (87.0)</td>
<td valign="top" align="center">19 (82.6)</td>
<td valign="top" align="center">1.000</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*P &lt; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Pulmonary fungal infection (<italic>Mucor</italic> with <italic>Aspergillus</italic>) in a 69-year-old man with uncontrolled diabetes, chronic obstructive pulmonary disease and liver cirrhosis. CT imaging showed thick-walled cavity shadow with gas-fluid level in the right upper lobe and left lower lobe of the lung <bold>(A)</bold>. The lesion was significantly reduced after half a month of treatment with posaconazole <bold>(B)</bold>. The lesion continued to shrink after 40 days <bold>(C)</bold>, three months <bold>(D)</bold>, five months <bold>(E)</bold> and 1 year <bold>(F)</bold> of treatment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-770551-g002.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>Diagnostic Procedures and Treatment Strategies</title>
<p>Of the 59 proven patients with mucormycosis, 48 cases (81.4%) were confirmed by histopathological examination, 22 cases (37.3%) were confirmed by direct microscopy. There was no significant difference in the diagnostic procedures between the two groups (P&gt;0.05). A total of 47 patients (79.7%) received treatment. Treatment strategies for these patients with mucormycosis include antifungal drugs, surgery, or both. Most patients (38/59, 64.4%) were treated with amphotericin B/LAmB. More patients with PM were treated with AmB/LAmB (P=0.006) or posaconazale (P=0.004) in good outcome group than in worse outcome group.</p>
<p>For patients with PM, only 3 patients were treated with surgery and LAmB, but there was no statistical difference in clinical outcome (P&gt;0.05). The most common adverse events of AmB/LAmB included renal insufficiency (16/42, 38.1%) and hypokalemia (9/42, 21.4%) in this study. The severity of all adverse events were mild to moderate (grade 1-2) according to the US National Cancer Institute Common Toxicity Criteria (NCI-CTC) (<xref ref-type="bibr" rid="B29">US, National Cancer Institute, 2017</xref>). The adverse reaction ratio of AmB/LAmB has not statistical difference between the two groups (P&gt;0.05). As shown in <xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>.</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Diagnostic procedures and treatment strategies for proven patients with mucormycosis .</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Diagnostic method</th>
<th valign="top" align="center">All (N = 59) (n,%)</th>
<th valign="top" align="center">Good outcome (N = 28) (n,%)</th>
<th valign="top" align="center">Worse outcome (N = 31) (n,%)</th>
<th valign="top" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Cluture</td>
<td valign="top" align="center">13 (22.0)</td>
<td valign="top" align="center">7 (25.0)</td>
<td valign="top" align="center">6 (19.4)</td>
<td valign="top" align="center">0.755</td>
</tr>
<tr>
<td valign="top" align="left">Direct microscopy</td>
<td valign="top" align="center">22 (37.3)</td>
<td valign="top" align="center">7 (25.0)</td>
<td valign="top" align="center">15 (48.4)</td>
<td valign="top" align="center">0.105</td>
</tr>
<tr>
<td valign="top" align="left">Histology</td>
<td valign="top" align="center">48 (81.4)</td>
<td valign="top" align="center">23 (82.1)</td>
<td valign="top" align="center">25 (80.6)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Cluture positive only</td>
<td valign="top" align="center">8 (13.6)</td>
<td valign="top" align="center">5 (17.9)</td>
<td valign="top" align="center">3 (9.7)</td>
<td valign="top" align="center">0.458</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Direct microscopy positive only</td>
<td valign="top" align="center">2 (3.4)</td>
<td valign="top" align="center">1 (3.6)</td>
<td valign="top" align="center">1 (3.2)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Histology positive only</td>
<td valign="top" align="center">25 (52.4)</td>
<td valign="top" align="center">14 (50.1)</td>
<td valign="top" align="center">11 (35.5)</td>
<td valign="top" align="center">0.260</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Cluture+histology</td>
<td valign="top" align="center">4 (6.8)</td>
<td valign="top" align="center">2 (7.1)</td>
<td valign="top" align="center">2 (6.5)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Direct microscopy+histology</td>
<td valign="top" align="center">19 (32.2)</td>
<td valign="top" align="center">6 (21.4)</td>
<td valign="top" align="center">13 (41.9)</td>
<td valign="top" align="center">0.105</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Cluture+Direct microscopy</td>
<td valign="top" align="center">1 (1.7)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (3.2)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">BDG test</td>
<td valign="top" align="center">3 (5.1)</td>
<td valign="top" align="center">1/24 (4.2)</td>
<td valign="top" align="center">2/25 (8.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">GM test</td>
<td valign="top" align="center">3 (5.1)</td>
<td valign="top" align="center">2/20 (10.0)</td>
<td valign="top" align="center">1/20 (5.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Therapeutic strategies</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Pulmonary</bold>
</td>
<td valign="top" align="center">All<break/> (N=46) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=23) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=23) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">AmB/LAmB</td>
<td valign="top" align="center">28 (60.9)</td>
<td valign="top" align="center">19 (82.6)</td>
<td valign="top" align="center">9 (39.1)</td>
<td valign="top" align="center">
<bold>0.006*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Posaconazale</td>
<td valign="top" align="center">11 (23.9)</td>
<td valign="top" align="center">10 (43.5)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">
<bold>0.004*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">LAmB+Surgery</td>
<td valign="top" align="center">3 (6.5)</td>
<td valign="top" align="center">1 (4.3)</td>
<td valign="top" align="center">2 (8.7)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">untreated</td>
<td valign="top" align="center">11 (23.9)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">11 (47.8)</td>
<td valign="top" align="center">
<bold>0.000*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Rhino-orbito-cerebral</bold>
</td>
<td valign="top" align="center">All<break/> (N=9) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=3) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=6) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">AmB/LAmB</td>
<td valign="top" align="center">7 (77.8)</td>
<td valign="top" align="center">2 (66.7)</td>
<td valign="top" align="center">5 (83.3)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Posaconazale</td>
<td valign="top" align="center">1 (11.1)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (16.7)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">AmB+Surgery</td>
<td valign="top" align="center">1 (22.2)</td>
<td valign="top" align="center">1 (33.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">0.333</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Disseminated</bold>
</td>
<td valign="top" align="center">All<break/> (N=3) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=1) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=2) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">AmB</td>
<td valign="top" align="center">2 (66.7)</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">untreated</td>
<td valign="top" align="center">1 (33.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Cutaneous</bold>
</td>
<td valign="top" align="center">All<break/> (N=1) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=1) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=0) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">AmB+Surgery</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">0 (100.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Adverse reactions of AmB</bold>/<bold>LAmB</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Pulmonary</bold>
</td>
<td valign="top" align="center">All<break/> (N=31) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=20) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=11) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">Hypokalemia</td>
<td valign="top" align="center">7 (22.6)</td>
<td valign="top" align="center">5 (25.0)</td>
<td valign="top" align="center">2 (18.2)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Renal insufficiency</td>
<td valign="top" align="center">11 (35.5)</td>
<td valign="top" align="center">8 (40.0)</td>
<td valign="top" align="center">3 (27.3)</td>
<td valign="top" align="center">0.698</td>
</tr>
<tr>
<td valign="top" align="left">Phlebophlogosis</td>
<td valign="top" align="center">1 (3.2)</td>
<td valign="top" align="center">1 (5.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Allergic reaction</td>
<td valign="top" align="center">1 (3.2)</td>
<td valign="top" align="center">1 (5.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Gastrointestinal toxicity</td>
<td valign="top" align="center">4 (12.9)</td>
<td valign="top" align="center">2 (10.0)</td>
<td valign="top" align="center">2 (18.2)</td>
<td valign="top" align="center">0.601</td>
</tr>
<tr>
<td valign="top" align="left">Cardiotoxicity</td>
<td valign="top" align="center">3 (10.7)</td>
<td valign="top" align="center">2 (10.0)</td>
<td valign="top" align="center">1 (9.1)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Rhino-orbito-cerebral</bold>
</td>
<td valign="top" align="center">All<break/> (N=8) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=3) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=5) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">Hypokalemia</td>
<td valign="top" align="center">1 (1.3)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (20.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">Renal insufficiency</td>
<td valign="top" align="center">4 (50.0)</td>
<td valign="top" align="center">3 (100.0)</td>
<td valign="top" align="center">1 (20.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Disseminated</bold>
</td>
<td valign="top" align="center">All<break/> (N=2) (n,%)</td>
<td valign="top" align="center">Good outcome<break/> (N=1) (n,%)</td>
<td valign="top" align="center">Worse outcome<break/> (N=1) (n,%)</td>
<td valign="top" align="center">P-value</td>
</tr>
<tr>
<td valign="top" align="left">Hypokalemia</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">Renal insufficiency</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">Gastrointestinal toxicity</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">Agranulocytosis</td>
<td valign="top" align="center">1 (50.0)</td>
<td valign="top" align="center">0 (0.0)</td>
<td valign="top" align="center">1 (100.0)</td>
<td valign="top" align="center">NA</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>AmB, amphotericin B; BDG test, (1,3)-beta-D-glucan test; GM test, galactomannan test; LAmB, liposomal amphotericin B.</p>
</fn>
<fn>
<p>*P &lt; 0.05; NA, Not Applicable.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>Mucormycosis is rare, neglected, and associated with high mortality rates. The study found that 52.5% of patients with mucormycosis had poor clinical outcomes. Which is similar to previous research results (<xref ref-type="bibr" rid="B6">Jeong et&#xa0;al., 2019</xref>). PM was the most common form of mucormycosis, accounting for 78.0% of all the patients with mucormycosis. Although previous studies have reported that rhino-orbital mucormycosis was the most common clinical type (<xref ref-type="bibr" rid="B14">Patel et&#xa0;al., 2020</xref>), PM maybe more common in China (<xref ref-type="bibr" rid="B15">Peng et&#xa0;al., 2019</xref>). This study also found the most common underlying disease was diabetes mellitus. Previous studies have shown that PM mainly occurred in patients with hematological malignancies, while rhino-orbital mucormycosis mostly occurred in patients with diabetes mellitus (<xref ref-type="bibr" rid="B23">Skiada et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B3">Chakrabarti and Singh, 2014</xref>). However, our results were consistent with those from China (<xref ref-type="bibr" rid="B15">Peng et&#xa0;al., 2019</xref>). Perhaps because the number of diabetes patients in China is much larger than that of hematological malignancies (<xref ref-type="bibr" rid="B9">Liu et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B7">Khan et&#xa0;al., 2020</xref>), the underlying disease of more mucormycosis patients is diabetes. The high prevalence of diabetes in China and endemic mucor species different from other countries may also be the reasons for the high incidence of PM in diabetic patients in China. More detailed etiological studies of mucormycosis need to be done. We found the incidence of mucormycosis was tended to rise, which may be owing to the improvement of fungal diagnostic technology, health awareness and the visiting rate. In addition, diabetes incidence is on the rise worldwide, especially in China and India (<xref ref-type="bibr" rid="B7">Khan et&#xa0;al., 2020</xref>), which may be the reason for the increase in the incidence of mucormycosis in China.</p>
<p>For PM, the most common clinical symptoms were cough, fever, and hemoptysis/bloody phlegm. This result was similar to some previous studies (<xref ref-type="bibr" rid="B23">Skiada et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B15">Peng et&#xa0;al., 2019</xref>). Molecular-based assays can help to identify different fungal species and it can be used as a supplement to conventional diagnostic methods (<xref ref-type="bibr" rid="B10">Machouart et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B27">Springer et&#xa0;al., 2016</xref>). The study also found that laboratory results were not associated with patient outcomes. Most previous studies have not found a correlation between laboratory results and clinical outcomes in patients with mucormycosis (<xref ref-type="bibr" rid="B14">Patel et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B25">Son et&#xa0;al., 2020</xref>), and only a few studies have found that neutropenia may be associated with increased mortality (<xref ref-type="bibr" rid="B26">Spellberg et&#xa0;al., 2012</xref>). Neutropenia was not found in our patients with PM, it might not be an important risk factor for mortality in these patients.</p>
<p>The most frequent imaging findings of PM were patchy shadows, cavitation and pulmonary nodules in this study. According to the imaging findings, PM might be misdiagnosed as tumor or pulmonary aspergillosis. Nodule was more common in good outcome group. Lymph node enlargement were more common in patients with worse outcome. Many previous studies have found multiple nodules, reversed halo sign, and cavities associated with PM (<xref ref-type="bibr" rid="B12">McAdams et&#xa0;al., 1997</xref>; <xref ref-type="bibr" rid="B11">Marom and Kontoyiannis, 2011</xref>). Pulmonary nodules, halo sign and cavitation was also found in patients pulmonary invasive aspergillosis (<xref ref-type="bibr" rid="B1">Althoff Souza et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B13">Muldoon et&#xa0;al., 2016</xref>). The reversed halo sign has been considered an important clue to the diagnosis of PM, however, it has also been described in other pulmonary diseases, including invasive pulmonary aspergillosis, tuberculosis, organising pneumonia and malignancy (<xref ref-type="bibr" rid="B28">Sullivan and Rana, 2019</xref>). Therefore, early biopsy to establish the underlying cause is very important in patients with suspected pulmonary fungal infections.</p>
<p>Diagnosis of mucormycosis is challenging. In clinical practice, laboratory diagnosis of mucormycosis includes histopathology, direct examination and cultures (<xref ref-type="bibr" rid="B24">Skiada et&#xa0;al., 2020</xref>). Most patients in this study were diagnosed by histopathology. Many previous studies have also reported that histopathology was the main diagnostic method of mucormycosis (<xref ref-type="bibr" rid="B17">Prakash and Chakrabarti, 2019</xref>). In this study, Mucorales culture positive was found only in 13 patients. It was previously reported that the positive rate of Mucorales culture could reach 79% (<xref ref-type="bibr" rid="B17">Prakash and Chakrabarti, 2019</xref>). Which may be related to the low vigilance of doctors to invasive pulmonary mycosis and the absence of fungal culture for puncture specimens. More needs to be done to raise awareness of pulmonary mycosis among doctors.</p>
<p>In this study, twelve patients did not receive treatment and left the hospital against medical advice after diagnosis because of their critical condition and financial constraints. PM patients were treated with amphotericin B or posaconazole had better clinical outcomes, while untreated patients had poor outcomes. For rhino-orbito-cerebral and disseminated mucormycosis patients, there was no statistically significant difference in clinical outcome between different treatment strategies, which maybe related to the small number of cases. In addition, patients with rhino-orbito-cerebral mucormycosis who underwent surgery and antifungal therapy had better clinical outcomes. At present, treatment options for mucormycosis remain very limited. LAmB combined with surgery are strongly recommend as first-line therapy. Isavuconazole and posaconazole are also options as second-line agents (<xref ref-type="bibr" rid="B4">Cornely et&#xa0;al., 2019</xref>). For patients with PM, only 3 patients in this study were received pulmonary lobectomy, so no benefit of antifungal combined surgical treatment over antifungal therapy alone was observed. Bilateral lobe involvement occurred in 84.8% of patients in this study, which was similar to previous studies (<xref ref-type="bibr" rid="B15">Peng et&#xa0;al., 2019</xref>). Multifocal involvement limited the surgical options, early and effective antifungal therapy may be more important for patients with PM. The recommended combination of antifungal agents and surgical treatment as a treatment option for mucormycosis may be based on the presence of more rhino-orbito-cerebral mucormycosis in other countries. More researches may be needed to optimize treatment options for different types of mucormycosis. New treatment drugs or methods, such as combination of lipid amphotericin B and caspofungin or posaconazole, VT-1161, deferasirox in combination with a polyene, hyperbaric oxygen and so on, still deserve to be expected to improve clinical outcome (<xref ref-type="bibr" rid="B22">Skiada et&#xa0;al., 2018</xref>).</p>
<p>This study has some limitations. First, it was a retrospective observational study. Only some patients have complete follow-up data in our hospital, especially imaging data, and the follow-up of some patients could only be completed by telephone. Second, the detection rate of tissue culture was low, the pathological diagnosis was determined mainly by morphology and special staining. It is important to raise the awareness of doctors about fungal disease and the importance of tissue culture. Third, because mucormycosis is a relatively rare fungal disease in China (<xref ref-type="bibr" rid="B8">Liao et&#xa0;al., 2013</xref>), the number of cases in this study was limited. More larger-scale,&#x2002;multicenter studies of mucormycosis in the real world should be done.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<title>Conclusions</title>
<p>The most common clinical type of mucormycosis in China was PM. The most common risk factor was diabetes mellitus. Diabetic patients with clinical manifestations of febrile and hemoptysis, CT findings of nodules, cavities and bilateral lung involvement should be vigilant against PM. Early diagnosis and effective anti-mucor treatment are very important to improve the prognosis of patients with mucormycosis.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Ethics Committee of West China Hospital, Sichuan University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author Contributions</title>
<p>XL and JQ conceived of and designed the study. JQ and XL collected, analysed or interpreted data. JQ wrote the draft. All authors read, revised and approved the final manuscript.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>This study was supported by Sichuan Province Science and Technology Support Program of China (grant number: 2021YFS0170), 1&#x2022;3&#x2022;5 project for disciplines of excellence-Clinical Research Incubation Project, West China Hospital, Sichuan University (grant number: 2021HXFH032).</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
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