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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.2022.1014530</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>Clinical characteristics and prognosis of patient with leptospirosis: A multicenter retrospective analysis in south of China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Dianwu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Huaying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1610104"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yi</surname>
<given-names>Rong</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xiao</surname>
<given-names>Qian</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhu</surname>
<given-names>Yiqun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chang</surname>
<given-names>Qinyu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Lihua</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Bin</given-names>
</name>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>He</surname>
<given-names>Junjun</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Tianxing</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fan</surname>
<given-names>Zhijun</given-names>
</name>
<xref ref-type="aff" rid="aff12">
<sup>12</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheng</surname>
<given-names>Wei</given-names>
</name>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1478214"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Weizhong</given-names>
</name>
<xref ref-type="aff" rid="aff14">
<sup>14</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Yan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1539899"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Pan</surname>
<given-names>Pinhua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1182067"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Center of Respiratory Medicine, Xiangya Hospital of Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Clinical Research Center for Respiratory Diseases in Hunan Province</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>National Clinical Research Center for Geriatric Disorders, Xiangya Hospital</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Pulmonary and Critical Care Medicine, Zhuzhou Central Hospital</institution>, <addr-line>Zhuzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Department of Anaesthesiology, Hunan Provincial People&#x2019;s Hospital</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff8">
<sup>8</sup>
<institution>Department of Respiratory Medicine, Changsha Central Hospital</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff9">
<sup>9</sup>
<institution>Department of Emergency, Xiangtan Central Hospital</institution>, <addr-line>Xiangtan</addr-line>, <country>China</country>
</aff>
<aff id="aff10">
<sup>10</sup>
<institution>Department of General Surgery, Shaoyang Central Hospital</institution>, <addr-line>Shaoyang</addr-line>, <country>China</country>
</aff>
<aff id="aff11">
<sup>11</sup>
<institution>Department of Orthopaedic Surgery, Yongzhou Central Hospital</institution>, <addr-line>Yongzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff12">
<sup>12</sup>
<institution>Department of Cardiothoracic Surgery, Liuyang People&#x2019;s Hospital</institution>, <addr-line>Liuyang</addr-line>, <country>China</country>
</aff>
<aff id="aff13">
<sup>13</sup>
<institution>Department of Respiratory, The Second Xiangya Hospital of Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff14">
<sup>14</sup>
<institution>Department of Respiratory, The First Affiliated Hospital of University of South China</institution>, <addr-line>Hengyang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Natarajaseenivasan Kalimuthusamy, Bharathidasan University, India</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Wenlong Zhang, Jilin University, China; Edmond Puca, Service of Infection Diseases University Hospital Center, Albania; Galya Gancheva, Medical University Pleven, Bulgaria</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Pinhua Pan, <email xlink:href="mailto:pinhuapan668@csu.edu.cn">pinhuapan668@csu.edu.cn</email>; Yan Zhang, <email xlink:href="mailto:zhangy4290@csu.edu.cn">zhangy4290@csu.edu.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Bacteria and Host, a section of the journal Frontiers in Cellular and Infection Microbiology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>17</day>
<month>10</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>12</volume>
<elocation-id>1014530</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>08</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>09</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Li, Liang, Yi, Xiao, Zhu, Chang, Zhou, Liu, He, Liu, Fan, Cheng, Wang, Zhang and Pan</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Li, Liang, Yi, Xiao, Zhu, Chang, Zhou, Liu, He, Liu, Fan, Cheng, Wang, Zhang and Pan</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>
<sec>
<title>Purpose</title>
<p>Leptospirosis is a zoonotic disease caused by pathogenic spirochetes of the genus Leptospira. However, there is currently no consensual definition or diagnostic criteria for severe and different forms of leptospirosis. Therefore, more insight on clinical manifestations, risk factors, and outcomes of leptospirosis is warranted. The identification of leptospirosis with distinct clinical manifestations and prognosis in our population.</p>
</sec>
<sec>
<title>Methods</title>
<p>Multiple correspondence analysis and hierarchical classification on principal components were presented to identify different clinical types of leptospirosis. The outcomes were clinical phenotypes, laboratory and imaging findings, and prognosis.</p>
</sec>
<sec>
<title>Results</title>
<p>The 95 enrolled patients had median values of 54.0 years (39.0-65.0) for age, 9.0 (7.0-14.0) for total hospital stay lengths, of whom 86.3% was male and 40.0% was transferred to ICU. Three clinical types were distinguished: mild leptospirosis (n=43, 45.3%) with less organ dysfunction and shorter hospital stays; respiratory leptospirosis (n=28, 29.5%) with hemoptysis, and respiratory and circulatory failure; and hepato-renal leptospirosis (n=24, 25.3%) with worst liver and kidney dysfunction. Total hospital mortality was 15.8% and was associated with dyspnea and high levels of neutrophil counts.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>The identification of leptospirosis with distinct clinical manifestations and prognosis in our population may assist clinicians to distinguish leptospirosis-like disease. Moreover, dyspnea and neutrophil count were found to be independent risk factors for severe leptospirosis progression.</p>
</sec>
</abstract>
<kwd-group>
<kwd>leptospirosis</kwd>
<kwd>mortality rate</kwd>
<kwd>prognosis</kwd>
<kwd>temperate zone</kwd>
<kwd>China</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="55"/>
<page-count count="10"/>
<word-count count="6195"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Leptospirosis is a zoonotic disease caused by pathogenic spirochetes of the genus Leptospira, and is one of widespread acute febrile illness throughout the world, with fatality rate ranging as high as 20-25% in some regions (<xref ref-type="bibr" rid="B26">Leptospirosis worldwide, 1999</xref>). Leptospirosis is mostly transmitted to humans by ambient water contaminated with the urine of wild and domestic mammals that have been chronically colonized by Leptospira (<xref ref-type="bibr" rid="B3">Bharti et&#xa0;al., 2003</xref>). Specific occupational activities (e.g., farming, veterinary medicine, military training), recreational immersion in water, poor living conditions, and seasonal rainfall in the tropics are commonly connected with the disease (<xref ref-type="bibr" rid="B3">Bharti et&#xa0;al., 2003</xref>). In general, human leptospirosis is prevalent in east/southeast Asia, as well as South America (<xref ref-type="bibr" rid="B41">Ricaldi et&#xa0;al., 2013</xref>). However, in temperate zones, such as Europe, North America, and Africa (<xref ref-type="bibr" rid="B17">Hartskeerl et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B4">Biggs et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B12">Dupouey et&#xa0;al., 2014</xref>), it has been reported that the incidence of leptospirosis is increasing, due to global warming, hurricanes, or heavy rains with floods and proliferation of urban rodents (<xref ref-type="bibr" rid="B27">Levett, 2001</xref>; <xref ref-type="bibr" rid="B37">Pijnacker et&#xa0;al., 2016</xref>).</p>
<p>Even though leptospirosis is a serious but underappreciated infectious tropical illness, it continues to be a major public health concern throughout the world. In recent decades, there is a trend towards increasing incidence in many countries (<xref ref-type="bibr" rid="B25">Lee et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B19">Holla et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B45">Sasmal et&#xa0;al., 2019</xref>) including India, South Korea and America. In some endemic areas (<xref ref-type="bibr" rid="B53">Zhang et&#xa0;al., 2012</xref>) of China, there are periodically small-scale local outbreaks of human leptospirosis. Leptospirosis presents a diverse array of clinical manifestations, including jaundice, renal failure, thrombocytopenia, and possibly lethal pulmonary hemorrhage (<xref ref-type="bibr" rid="B27">Levett, 2001</xref>). Meanwhile, leptospirosis shares common clinical signs with many acute febrile diseases, such as influenza, dengue fever or malaria (<xref ref-type="bibr" rid="B48">Tubiana et&#xa0;al., 2013</xref>), causing various degrees of infections (<xref ref-type="bibr" rid="B10">Doudier et&#xa0;al., 2006</xref>). Additionally, some clinical symptoms of leptospirosis have been confirmed to be closely related to death, including oliguria, shock, altered mental status, dyspnea, pulmonary infiltrates, and more (<xref ref-type="bibr" rid="B22">Ko et&#xa0;al., 1999</xref>; <xref ref-type="bibr" rid="B10">Doudier et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B51">Wang et&#xa0;al., 2020</xref>). However, there is currently no consensual definition or diagnostic criteria for severe and different forms of leptospirosis. Leptospirosis has been classified in a variety of methods, ranging from clinical manifestations to genetic (<xref ref-type="bibr" rid="B31">Marquez et&#xa0;al., 2017</xref>) determination. Therefore, more insight on clinical manifestations, risk factors, and outcomes of leptospirosis is warranted.</p>
<p>This retrospective multicenter analysis was conducted to determine the association between clinical phenotypes of leptospirosis, laboratory findings, treatment strategies and prognosis.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Methods</title>
<sec id="s2_1">
<title>Patients</title>
<p>We retrospectively extracted and analyzed the clinical profile data on leptospirosis-diagnosed patients who were admitted to 9 tertiary care hospitals in Hunan, China, between January 1, 1998, and January 1, 2022. This study was approved by the institutional review boards (IRBs) in Xiangya Hospital of Central South University (No. 202104005).Leptospirosis was diagnosed as one of the following positive tests: microscopic agglutination test (MAT), enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR) or metagenomic next-generation sequencing on urine or blood, and dark field microscopy (<xref ref-type="bibr" rid="B5">Bleeker-Rovers et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B23">Koizumi, 2020</xref>). Clinical profiles including demographics, comorbidities, clinical symptoms, laboratory and imaging findings, and prognosis were obtained from the electronical record.</p>
</sec>
<sec id="s2_2">
<title>Definitions</title>
<p>Patients were classified as having severe leptospirosis (<xref ref-type="bibr" rid="B33">Miailhe et&#xa0;al., 2019</xref>) if they had required ICU admission. Acute respiratory failure (<xref ref-type="bibr" rid="B44">Roussos and Koutsoukou, 2003</xref>) was defined as a significant impairment of pulmonary gas exchange functions with inadequate oxygenation (PaO2 &lt;60&#x2009;mmHg) and carbon dioxide retention (PaCO2 &gt;45&#x2009;mmHg). Circulatory failure was classified as a collection of clinical syndromes caused by cardiac dysfunction that were characterized by pulmonary congestion, systemic congestion or tissue hypoperfusion. Acute liver injury was characterized as liver damage induced by a variety of factors in the absence of a history of chronic liver disease, accompanied by an increase in serum transaminase and bilirubin levels. Acute renal failure (<xref ref-type="bibr" rid="B43">Ronco et&#xa0;al., 2019</xref>) was defined as at least one positive laboratory test within 7 days of the following: creatinine greater than 1.5 times baseline (or a rise of 0.3 mg/dL within any 48-hour period), or urine output less than 0.5 mL/kg for more than 6 hours. Multiple organ failure was described as the dysfunction of two or more organs following severe injury.</p>
</sec>
<sec id="s2_3">
<title>Statistical analysis</title>
<p>All data in the current study was analyzed with SPSS 26.0 software (IBM SPSS Inc., USA). Continuous variables with skewed distribution were presented as medians and interquartile ranges, and compared by the Kruskal-Wallis H test. Categorical variables were expressed as frequencies and percentages (%), and analyzed by Chi-square test or Fisher&#x2019; s exact test. In addition, risk factors were assessed univariately, and variables of statistical and clinical significance in univariate analysis were including in the multivariate logistic regression analysis.</p>
<p>In order to identify different clinical phenotypes of leptospirosis, multiple correspondence analysis (MCA) and hierarchical classification on principal components (HCPC) were conducted using R 4.1.3 (FactoMineR package). The variables including age, sex and smoking history; clinical symptoms on admission (fever; fatigue; myalgia of the lower limbs; arthralgia; altered consciousness; headache; jaundice; vomiting; diarrhea; abdominal pain; dyspnea; cough; hemoptysis; other bleeding such as gastrointestinal haemorrhage, epistaxis, purpura and haematuria); organ dysfunction (acute respiratory failure; circulatory failure; acute liver injury; acute kidney injury) occurred during hospitalization, were used in the model. A value of P &lt; 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Clinical features of leptospirosis-infected patients with different clusters</title>
<p>A total of 95 patients with leptospirosis from 9 tertiary care hospitals in Hunan China, were enrolled in the study. Patients were classified into 3 clusters based on clinical features with MCA analysis (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The clinical features of patients from the 3 categories were compared and presented in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. Cluster 1 (n=43, 45.3%) was the most prevalent clinical phenotype, with the lowest prevalence of organ dysfunction and shortest hospital stay. Cluster 2 (n=28, 29.5%) was characterized by symptoms including dyspnea, coughing, hemoptysis, and respiratory and circulatory failure. Cluster 3 (n=24, 25.3%) was distinguished by acute liver and renal failure in contrast with a low incidence of respiratory and circulatory failure. The difference in age distribution across the groups was not statistically significant (<italic>p</italic>=0.096), but the percentage of those above 65 was significant higher in cluster 3 of hepato-renal leptospirosis (41.7%), followed by cluster 2 of respiratory leptospirosis (21.4%) and cluster 1 (9.3%, <italic>p</italic>=0.008). Males constitute a substantially greater proportion of the incidence population than females, but there is no statistically significant difference in the distribution of males and females within each group. Of the 95 patients enrolled for this study, 50 (52.6%) were smokers and 45 (47.4%) were non-smokers, with a significant difference in the distribution between the three groups (<italic>p</italic>=0.028). At admission, fatigue was the most frequently reported symptoms (n=89, 93.7%), followed by fever (n=87, 91.6%), myalgia of the lower limbs (n=76, 80.0%), cough (n=53, 55.8%), hemoptysis (n=46, 48.4%), dyspnea (n=45, 47.4%), and expectoration (n=34, 35.8%). Myalgia of the lower limbs, altered consciousness, central nervous system symptoms, jaundice, diarrhea, abdominal pain, dyspnea, cough, hemoptysis, expectoration, and chest pain were distributed differently across the three groups of patients.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Map of clinical features of different leptospirosis. Two&#x2212;dimensional distribution of clinical features of leptospirosis mapped along the two dimensions (dim 1 and dim 2) identified by multiple correspondence analysis. The relative positions of the patients in the plane are represented by different colors reflecting the subtypes distinguished by cluster analysis. Cluster 1 (black; n = 43) was the mild leptospirosis, cluster 2 (red; n = 28) was the respiratory presentation, cluster 3 (green; n = 25) was a hepato&#x2212;renal form.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-12-1014530-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinical manifestations of different clusters.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Total (n=95)</th>
<th valign="top" align="center">Cluster 1 Mild leptospirosis (n=43)</th>
<th valign="top" align="center">Cluster 2 Respiratory leptospirosis (n=28)</th>
<th valign="top" align="center">Cluster 3 Hepato-renal leptospirosis (n=24)</th>
<th valign="top" align="center">
<italic>p</italic> Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age, median (IQR), years</td>
<td valign="top" align="center">54.0 (39.0-65.0)</td>
<td valign="top" align="center">49.0 (35.0-61.0)</td>
<td valign="top" align="center">59,5 (38.2-65.0)</td>
<td valign="top" align="center">57.0 (44.0-68.7)</td>
<td valign="top" align="center">0.096</td>
</tr>
<tr>
<td valign="top" align="left">Age&gt;65 years</td>
<td valign="top" align="center">20 (21.1%)</td>
<td valign="top" align="center">4 (9.3%)</td>
<td valign="top" align="center">6 (21.4%)</td>
<td valign="top" align="center">10 (41.7%)</td>
<td valign="top" align="center">0.008</td>
</tr>
<tr>
<td valign="top" align="left">Male, n [%]</td>
<td valign="top" align="center">82 (86.3%)</td>
<td valign="top" align="center">35 (81.4%)</td>
<td valign="top" align="center">24 (85.7%)</td>
<td valign="top" align="center">23 (95.8%)</td>
<td valign="top" align="center">0.273</td>
</tr>
<tr>
<td valign="top" align="left">Female, n[%]</td>
<td valign="top" align="center">13 (13.7%)</td>
<td valign="top" align="center">8 (18.6%)</td>
<td valign="top" align="center">4 (14.3%)</td>
<td valign="top" align="center">1 (4.2%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Smoking, n[%]</td>
<td valign="top" align="center">50 (52.6%)</td>
<td valign="top" align="center">25 (58.1%)</td>
<td valign="top" align="center">9 (32.1%)</td>
<td valign="top" align="center">16 (66.7%)</td>
<td valign="top" align="center">0.028</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Symptoms and signs, n[%]</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Fever</td>
<td valign="top" align="center">87 (91.6%)</td>
<td valign="top" align="center">41 (95.3%)</td>
<td valign="top" align="center">25 (89.3%)</td>
<td valign="top" align="center">21 (87.5%)</td>
<td valign="top" align="center">0.404</td>
</tr>
<tr>
<td valign="top" align="left">Fatigue</td>
<td valign="top" align="center">89 (93.7%)</td>
<td valign="top" align="center">40 (93.0%)</td>
<td valign="top" align="center">25 (89.3%)</td>
<td valign="top" align="center">24 (100.0%)</td>
<td valign="top" align="center">0.363</td>
</tr>
<tr>
<td valign="top" align="left">Myalgia of lower limbs</td>
<td valign="top" align="center">76 (80.0%)</td>
<td valign="top" align="center">35 (81.4%)</td>
<td valign="top" align="center">18 (64.3%)</td>
<td valign="top" align="center">23 (95.8%)</td>
<td valign="top" align="center">0.018</td>
</tr>
<tr>
<td valign="top" align="left">Arthralgia</td>
<td valign="top" align="center">6 (6.3%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">1 (3.6%)</td>
<td valign="top" align="center">4 (16.7%)</td>
<td valign="top" align="center">0.063</td>
</tr>
<tr>
<td valign="top" align="left">Altered consciousness</td>
<td valign="top" align="center">19 (20.0%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">13 (46.4%)</td>
<td valign="top" align="center">5 (20.8%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Headache</td>
<td valign="top" align="center">21 (22.1%)</td>
<td valign="top" align="center">9 (20.9%)</td>
<td valign="top" align="center">4 (14.3%)</td>
<td valign="top" align="center">8 (33.3%)</td>
<td valign="top" align="center">0.248</td>
</tr>
<tr>
<td valign="top" align="left">CNS symptoms</td>
<td valign="top" align="center">25 (26.3%)</td>
<td valign="top" align="center">6 (14.0%)</td>
<td valign="top" align="center">11 (39.3%)</td>
<td valign="top" align="center">8 (33.3%)</td>
<td valign="top" align="center">0.040</td>
</tr>
<tr>
<td valign="top" align="left">Jaundice</td>
<td valign="top" align="center">26 (27.4%)</td>
<td valign="top" align="center">5 (11.6%)</td>
<td valign="top" align="center">2 (7.1%)</td>
<td valign="top" align="center">19 (79.2%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Vomiting</td>
<td valign="top" align="center">16 (16.8%)</td>
<td valign="top" align="center">7 (16.3%)</td>
<td valign="top" align="center">3 (10.7%)</td>
<td valign="top" align="center">6 (25.0%)</td>
<td valign="top" align="center">0.389</td>
</tr>
<tr>
<td valign="top" align="left">Diarrhea</td>
<td valign="top" align="center">10 (10.5%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">2 (7.1%)</td>
<td valign="top" align="center">7 (29.2%)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" align="left">Abdominal pain</td>
<td valign="top" align="center">11 (11.6%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">3 (10.7%)</td>
<td valign="top" align="center">7 (29.2%)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" align="left">Dyspnea</td>
<td valign="top" align="center">45 (47.4%)</td>
<td valign="top" align="center">6 (14.0%)</td>
<td valign="top" align="center">27 (96.4%)</td>
<td valign="top" align="center">12 (50.0%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Cough</td>
<td valign="top" align="center">53 (55.8%)</td>
<td valign="top" align="center">22 (51.2%)</td>
<td valign="top" align="center">21 (75.0%)</td>
<td valign="top" align="center">10 (41.7%)</td>
<td valign="top" align="center">0.039</td>
</tr>
<tr>
<td valign="top" align="left">Hemoptysis</td>
<td valign="top" align="center">46 (48.4%)</td>
<td valign="top" align="center">22 (51.2%)</td>
<td valign="top" align="center">19 (67.9%)</td>
<td valign="top" align="center">5 (20.8%)</td>
<td valign="top" align="center">0.003</td>
</tr>
<tr>
<td valign="top" align="left">Expectoration</td>
<td valign="top" align="center">34 (35.8%)</td>
<td valign="top" align="center">11 (25.6%)</td>
<td valign="top" align="center">18 (64.3%)</td>
<td valign="top" align="center">5 (20.8%)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">Chest pain</td>
<td valign="top" align="center">9 (9.5%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">3 (10.7%)</td>
<td valign="top" align="center">6 (25.0%)</td>
<td valign="top" align="center">0.002</td>
</tr>
<tr>
<td valign="top" align="left">Other bleeding</td>
<td valign="top" align="center">16 (16.8%)</td>
<td valign="top" align="center">4 (9.3%)</td>
<td valign="top" align="center">7 (25.0%)</td>
<td valign="top" align="center">5 (20.8%)</td>
<td valign="top" align="center">0.177</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Gastrointestinal bleeding</td>
<td valign="top" align="center">10 (10.5%)</td>
<td valign="top" align="center">4 (9.3%)</td>
<td valign="top" align="center">4 (14.3%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Epistaxis</td>
<td valign="top" align="center">3 (3.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">2 (7.1%)</td>
<td valign="top" align="center">1 (4.2%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Haematuria</td>
<td valign="top" align="center">5 (5.3%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">3 (10.7%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Purpura</td>
<td valign="top" align="center">3 (3.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">1 (3.6%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Hepatomegaly</td>
<td valign="top" align="center">3 (3.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">1 (3.6%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center">0.094</td>
</tr>
<tr>
<td valign="top" align="left">Splenomegaly</td>
<td valign="top" align="center">3 (3.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">1 (3.6%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center">0.094</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Comorbidities, n[%]</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Hypertension</td>
<td valign="top" align="center">11 (11.6%)</td>
<td valign="top" align="center">5 (11.6%)</td>
<td valign="top" align="center">2 (7.1%)</td>
<td valign="top" align="center">4 (16.7%)</td>
<td valign="top" align="center">0.598</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes</td>
<td valign="top" align="center">5 (5.3%)</td>
<td valign="top" align="center">2 (4.7%)</td>
<td valign="top" align="center">1 (3.6%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center">0.715</td>
</tr>
<tr>
<td valign="top" align="left">Viral hepatitis</td>
<td valign="top" align="center">2 (2.1%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">1 (4.2%)</td>
<td valign="top" align="center">0.730</td>
</tr>
<tr>
<td valign="top" align="left">Anemia</td>
<td valign="top" align="center">4 (4.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">2 (7.1%)</td>
<td valign="top" align="center">2 (8.3%)</td>
<td valign="top" align="center">0.112</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Data are presented as medians (IQR) and n (%). P values were calculated by Kruskal-Wallis H test, Chi-square test or Fisher&#x2019;s exact test, as appropriate. P values indicate differences among different clusters. IQR, interquartile range; CNS symptoms, central nervous system symptoms.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Laboratory findings across the three clusters of patients</title>
<p>The laboratory findings were summarized in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. The distribution of leukocytes, platelets, hemoglobin, neutrophil ratio, and lymphocyte ratio in routine blood tests varied significantly among the three groups of patients. In comparison to cluster 1 and cluster 2, the cluster 3 group had significantly more white blood cells (12.5[10.6-17.3 vs. 9.8[6.7-12.1] vs. 11.1[9.7-12.3], <italic>p</italic>=0.017), but significantly lower platelets (52.5[37.8-100.0] vs. 109.0[65.5-223.0] vs. 93.0[48.0-168.0], <italic>p</italic>=0.009) than other groups. In comparison to cluster 1, hemoglobin levels were significantly lower in the cluster 2 group, but not in the other groups. Additionally, the distribution of myocardial injury mediators was also considerably varied between the three groups of patients. Cluster 3 had a lower median albumin (27.5[24.2-30.1] vs. 34.5[30.6-37.7] vs 31.3[29.4-33.0], <italic>p</italic>&lt;0.001), and higher levels of total (87.0[38.0-205.0] vs. 15.3[10.7-21.8] vs. 19.5[12.6-38.2], <italic>p</italic>&lt;0.001) and direct bilirubin (53.0[20.1-156.0] vs. 6.1[4.4-11.2] vs. 9.6[5.2-19.5], <italic>p</italic>&lt;0.001), which was in accordance with the classification methods in the article. Cluster 3 patients exhibited higher levels of renal dysfunction indicators such as blood urea nitrogen (22.6[11.3-25.6] vs. 7.8[5.0-10.4] vs. 11.3[8.3-14.8], <italic>p</italic>&lt;0.001), creatinine (276.0[141.0-453.0] vs. 76.0[66.3-119.0] vs. 120.0[98.4-174.0], <italic>p</italic>&lt;0.001) and uric acid (400.0[296.0-561.0] vs. 252.0[175.0-299.0] vs. 262.0[199,0-413.0], <italic>p</italic>=0.004) than the individuals in the other clusters. Creatine kinase and creatine kinase isoenzymes were significantly higher in cluster 2 patients than those in cluster 1 and cluster 3. Patients in cluster 3 exhibited significantly longer prothrombin time, activated partial thrombin time, and higher fibrinogen level than patients in the other clusters, with no statistically significant differences in thrombin time, d-dimer, globulin, alanine aminotransferase, aspartate aminotransferase and inflammatory mediators across the three groups.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Laboratory findings of different clusters.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Total (n=95)</th>
<th valign="top" align="center">Cluster 1 Mild leptospirosis (n=43)</th>
<th valign="top" align="center">Cluster 2 Respiratory leptospirosis (n=28)</th>
<th valign="top" align="center">Cluster 3 Hepato-renal leptospirosis (n=24)</th>
<th valign="top" align="center">
<italic>p</italic> Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Blood Routine</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">White blood cell count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">11.1 (7.8-12.9)</td>
<td valign="top" align="center">9.8 (6.7-12.1)</td>
<td valign="top" align="center">11.1 (9.7-12.3)</td>
<td valign="top" align="center">12.5 (10.6-17.3)</td>
<td valign="top" align="center">0.017</td>
</tr>
<tr>
<td valign="top" align="left">Platelet count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">90.0 (46.0-168.0)</td>
<td valign="top" align="center">109.0 (65.5-223.0)</td>
<td valign="top" align="center">93.0 (48.0-168.0)</td>
<td valign="top" align="center">52.5 (37.8-100.0)</td>
<td valign="top" align="center">0.009</td>
</tr>
<tr>
<td valign="top" align="left">Hemoglobin, g/L</td>
<td valign="top" align="center">104.0 (85.3-122.0)</td>
<td valign="top" align="center">114.0 (93.8-125.0)</td>
<td valign="top" align="center">89.0 (78.5-118.0)</td>
<td valign="top" align="center">101.0 (82.5-118.0)</td>
<td valign="top" align="center">0.037</td>
</tr>
<tr>
<td valign="top" align="left">Neutrophil count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">9.4 (6.8-11.4)</td>
<td valign="top" align="center">7.7 (5.2-11.1)</td>
<td valign="top" align="center">9.7 (8.7-10.9)</td>
<td valign="top" align="center">10.4 (8.4-15.1)</td>
<td valign="top" align="center">0.102</td>
</tr>
<tr>
<td valign="top" align="left">Neutrophil percentage, %</td>
<td valign="top" align="center">87.2 (78.9-91.7)</td>
<td valign="top" align="center">82.2 (66.6-91.3)</td>
<td valign="top" align="center">88.3 (84.6-92.4)</td>
<td valign="top" align="center">88.0 (84.2-90.7)</td>
<td valign="top" align="center">0.026</td>
</tr>
<tr>
<td valign="top" align="left">Lymphocyte count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">0.8 (0.4-1.4)</td>
<td valign="top" align="center">1.0 (0.5-1.5)</td>
<td valign="top" align="center">0.7 (0.4-1.1)</td>
<td valign="top" align="center">0.7 (0.4-1.1)</td>
<td valign="top" align="center">0.323</td>
</tr>
<tr>
<td valign="top" align="left">Lymphocyte percentage, %</td>
<td valign="top" align="center">6.7 (4.1-14.7)</td>
<td valign="top" align="center">10.9 (4.7-22.9)</td>
<td valign="top" align="center">5.8 (3.7-10.0)</td>
<td valign="top" align="center">5.6 (3.4-11.0)</td>
<td valign="top" align="center">0.040</td>
</tr>
<tr>
<td valign="top" align="left">Eosinophil count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">0.0 (0.0-0.1)</td>
<td valign="top" align="center">0.0 (0.0-0.2)</td>
<td valign="top" align="center">0.0 (0.0-0.1)</td>
<td valign="top" align="center">0.0 (0.0-0.1)</td>
<td valign="top" align="center">0.061</td>
</tr>
<tr>
<td valign="top" align="left">Eosinophil percentage, %</td>
<td valign="top" align="center">0.1 (0-0.6)</td>
<td valign="top" align="center">0.1 (0.0-1.7)</td>
<td valign="top" align="center">0.01 (0.0-0.1)</td>
<td valign="top" align="center">0.120 (0.0-0.525)</td>
<td valign="top" align="center">0.134</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Blood Biochemistry</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Albumin, g/L</td>
<td valign="top" align="center">31.0 (27.9-34.9)</td>
<td valign="top" align="center">34.5 (30.6-37.7)</td>
<td valign="top" align="center">31.1 (29.4-33.0)</td>
<td valign="top" align="center">27.5 (24.2-30.1)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Globulin, g/L</td>
<td valign="top" align="center">25.8 (21.0-29.4)</td>
<td valign="top" align="center">25.8 (22.5-29.6)</td>
<td valign="top" align="center">24.9 (18.8-28.8)</td>
<td valign="top" align="center">27.5 (22.1-29.4)</td>
<td valign="top" align="center">0.432</td>
</tr>
<tr>
<td valign="top" align="left">Total bilirubin, &#x3bc;mol/L</td>
<td valign="top" align="center">20.8 (13.0-55.7)</td>
<td valign="top" align="center">15.3 (10.7-21.8)</td>
<td valign="top" align="center">19.5 (12.6-38.2)</td>
<td valign="top" align="center">87.0 (38.0-205.0)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Direct bilirubin, &#x3bc;mol/L</td>
<td valign="top" align="center">10.6 (5.0-33.1)</td>
<td valign="top" align="center">6.1 (4.4-11.2)</td>
<td valign="top" align="center">9.6 (5.2-19.5)</td>
<td valign="top" align="center">53.0 (20.1-156.0)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Alanine aminotransferase, U/L</td>
<td valign="top" align="center">50.9 (33.5-87.4)</td>
<td valign="top" align="center">49.7 (33.8-73.0)</td>
<td valign="top" align="center">45.6 (29.9-87.4)</td>
<td valign="top" align="center">55.5 (38.0-107.0)</td>
<td valign="top" align="center">0.435</td>
</tr>
<tr>
<td valign="top" align="left">Aspartate aminotransferase, U/L</td>
<td valign="top" align="center">53.0 (32.6-103.0)</td>
<td valign="top" align="center">44.0 (24.9-68.0)</td>
<td valign="top" align="center">57.0 (41.2-118.0)</td>
<td valign="top" align="center">58.6 (37.7-212.0)</td>
<td valign="top" align="center">0.068</td>
</tr>
<tr>
<td valign="top" align="left">Lactate dehydrogenase, U/L</td>
<td valign="top" align="center">311.0 (249.0-453.0)</td>
<td valign="top" align="center">287.0 (231.0-388.0)</td>
<td valign="top" align="center">391.0 (283.0-567.0)</td>
<td valign="top" align="center">346.0 (279.0-480.0)</td>
<td valign="top" align="center">0.047</td>
</tr>
<tr>
<td valign="top" align="left">Blood urea nitrogen, mmol/L</td>
<td valign="top" align="center">10.2 (6.4-15.2)</td>
<td valign="top" align="center">7.8 (5.0-10.4)</td>
<td valign="top" align="center">11.3 (8.3-14.8)</td>
<td valign="top" align="center">22.6 (11.3-25.6)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Creatinine, &#x3bc;mol/L</td>
<td valign="top" align="center">116.0 (70.0-214.0)</td>
<td valign="top" align="center">76.0 (66.3-119.0)</td>
<td valign="top" align="center">120.0 (98.4-174.0)</td>
<td valign="top" align="center">276.0 (141.0-453.0)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Uric acid, &#x3bc;mol/L</td>
<td valign="top" align="center">267.0 (191.0-395.0)</td>
<td valign="top" align="center">252.0 (175.0-299.0)</td>
<td valign="top" align="center">262.0 199.0-413.0)</td>
<td valign="top" align="center">400.0 (296.0-561.0)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Myocardial Injury Mediators</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Creatine kinase, U/L</td>
<td valign="top" align="center">246.0 (95.0-919.0)</td>
<td valign="top" align="center">118.0 (55.9-456.0)</td>
<td valign="top" align="center">535.0 (231.0-1060.0)</td>
<td valign="top" align="center">443.0 (159.0-2030.0)</td>
<td valign="top" align="center">0.010</td>
</tr>
<tr>
<td valign="top" align="left">Creatine kinase isoenzyme, U/L</td>
<td valign="top" align="center">23.0 (17.6-38.7)</td>
<td valign="top" align="center">18.4 (13.0-34.0)</td>
<td valign="top" align="center">28.0 (20.0-44.0)</td>
<td valign="top" align="center">24.1 (20.9-54.8)</td>
<td valign="top" align="center">0.031</td>
</tr>
<tr>
<td valign="top" align="left">Myoglobin, g/L</td>
<td valign="top" align="center">177.0 (86.0-604.0)</td>
<td valign="top" align="center">96.0 (46.9-281.0)</td>
<td valign="top" align="center">283.0 (136.0-785.0)</td>
<td valign="top" align="center">409.0 (165.0-868.0)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Blood Coagulation</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Prothrombin time, s</td>
<td valign="top" align="center">13.6 (12.5-14.8)</td>
<td valign="top" align="center">13.0 (12.1-14.0)</td>
<td valign="top" align="center">13.3 (12.5-14.7)</td>
<td valign="top" align="center">14.5 (13.7-16.0)</td>
<td valign="top" align="center">0.017</td>
</tr>
<tr>
<td valign="top" align="left">Activated partial thrombin time, s</td>
<td valign="top" align="center">40.0 (30.6-47.5)</td>
<td valign="top" align="center">33.4 (28.7-42.0)</td>
<td valign="top" align="center">38.3 (33.4-46.3)</td>
<td valign="top" align="center">44.8 (33.3-48.9)</td>
<td valign="top" align="center">0.044</td>
</tr>
<tr>
<td valign="top" align="left">Thrombin time, s</td>
<td valign="top" align="center">16.3 (14.8-17.2)</td>
<td valign="top" align="center">17.0 (16.0-17.9)</td>
<td valign="top" align="center">15.4 (14.1-16.8)</td>
<td valign="top" align="center">16.0 (13.9-16.8)</td>
<td valign="top" align="center">0.058</td>
</tr>
<tr>
<td valign="top" align="left">Fibrinogen, g/L</td>
<td valign="top" align="center">5.2 (4.2-6.6)</td>
<td valign="top" align="center">4.9 (3.2-6.0)</td>
<td valign="top" align="center">5.1 (4.3-5.7)</td>
<td valign="top" align="center">6.3 (5.2-7.8)</td>
<td valign="top" align="center">0.012</td>
</tr>
<tr>
<td valign="top" align="left">D-dimer, &#x3bc;g/mL</td>
<td valign="top" align="center">1.7(0.8-2.5)</td>
<td valign="top" align="center">1.2 (0.6-2.1)</td>
<td valign="top" align="center">2.3 (1.1-3.2)</td>
<td valign="top" align="center">1.6 (0.8-2.8)</td>
<td valign="top" align="center">0.171</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Inflammatory Mediators</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">C-reactive protein, mg/L</td>
<td valign="top" align="center">114.0 (70.2-178.0)</td>
<td valign="top" align="center">89.0 (51.1-157.0)</td>
<td valign="top" align="center">114.0 (98.6-146.0)</td>
<td valign="top" align="center">180.0 (93.6-216.0)</td>
<td valign="top" align="center">0.063</td>
</tr>
<tr>
<td valign="top" align="left">Procalcitonin, &#xb5;g/L</td>
<td valign="top" align="center">4.0 (1.2-23.0)</td>
<td valign="top" align="center">2.1 (0.6-8.3)</td>
<td valign="top" align="center">16.4 (1.3-49.1)</td>
<td valign="top" align="center">6.2 (2.9-21.0)</td>
<td valign="top" align="center">0.055</td>
</tr>
<tr>
<td valign="top" align="left">ESR, mm/h</td>
<td valign="top" align="center">56.5 (34.0-82.3)</td>
<td valign="top" align="center">48.5 (36.5-74.5)</td>
<td valign="top" align="center">57.0 (24.0-87.5)</td>
<td valign="top" align="center">67.5 (40.5-84.8)</td>
<td valign="top" align="center">0.642</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Data are presented as medians (IQR). P values were calculated by Kruskal-Wallis H test as appropriate. P values indicate differences among different clusters. IQR, interquartile range, ESR, Erythrocyte sedimentation rate.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Organ dysfunction and outcomes of different clusters</title>
<p>We compared the organ dysfunction and outcomes across the various clusters in <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>. Organ dysfunction occurred in the following proportion of all hospitalized leptospirosis patients: acute kidney injury (n=39, 41.1%), acute respiratory failure (n=38, 40.0%), acute liver injury (n=33, 35.1%), circulatory failure (n=31, 32.6%), multiple organ functional impairment (n=38, 40.0%), with significant differences between the three clusters. Specially, a <italic>post-hoc</italic> two-by-two assessment of significance levels using the Bonferroni method revealed that the incidence of acute respiratory failure and acute kidney injury was significantly different between any of two clusters. The incidence of acute liver injury was less common in cluster 1(7[16.3%] vs. 20[87.0%], <italic>p</italic>&lt;0.001) and cluster 2(6[21.4%] vs. 20[87.0%], <italic>p</italic>&lt;0.001) patients compared to cluster 3 individually. Multiple organ failure was more prevalent in cluster 2 (19[67.9%] vs. 4[9.3%] vs. 15[62.5%], <italic>p</italic>&lt;0.001), resulting in more possibility to develop into severe leptospirosis requiring ICU admission (23[82.1%] vs. 5[11.6%] vs. 10[41.7%], <italic>p</italic>&lt;0.001), more endotracheal intubation (17[60.7%] vs. 0[0.0%] vs. 5[20.8%], <italic>p</italic>&lt;0.001) and longer ICU stays (8.0[1.0-10.7] vs. 0.0[0.0-0.0] vs. 0.0[0.0-3.5], <italic>p</italic>&lt;0.001). In terms of prognosis, 80(84.2%) patients recovered from the disease while 15(15.8%) patients died. Individually, patients in cluster 2 (8[28.6%]) and cluster 3 (7[29.2%]) patients had a considerably greater mortality rate than those in cluster 1. However, no significant difference in mortality was observed between cluster 2 and cluster 3.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Organ dysfunction and outcomes of different clusters.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Total (n=95)</th>
<th valign="top" align="center">Cluster 1 Mild leptospirosis (n=43)</th>
<th valign="top" align="center">Cluster 2 Respiratory leptospirosis (n=28)</th>
<th valign="top" align="center">Cluster 3 Hepato-renal leptospirosis (n=24)</th>
<th valign="top" align="center">
<italic>p</italic> Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Organ dysfunction, n[%]</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Acute respiratory failure</td>
<td valign="top" align="center">38 (40.0%)</td>
<td valign="top" align="center">1 (2.3%)</td>
<td valign="top" align="center">28 (100%)</td>
<td valign="top" align="center">9 (37.5%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Circulatory failure</td>
<td valign="top" align="center">31 (32.6%)</td>
<td valign="top" align="center">7 (16.3%)</td>
<td valign="top" align="center">15 (53.6%)</td>
<td valign="top" align="center">9 (37.5%)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" align="left">Acute liver injury</td>
<td valign="top" align="center">33 (35.1%)</td>
<td valign="top" align="center">7 (16.3%)</td>
<td valign="top" align="center">6 (21.4%)</td>
<td valign="top" align="center">20 (87.0%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Acute kidney injury</td>
<td valign="top" align="center">39 (41.1%)</td>
<td valign="top" align="center">5 (11.6%)</td>
<td valign="top" align="center">13 (46.4%)</td>
<td valign="top" align="center">21 (87.5%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Multiple organ failure</td>
<td valign="top" align="center">38 (40.0%0</td>
<td valign="top" align="center">4 (9.3%)</td>
<td valign="top" align="center">19 (67.9%)</td>
<td valign="top" align="center">15 (62.5%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Clinical Outcomes</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Endotracheal intubation, n[%]</td>
<td valign="top" align="center">22 (23.2%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">17 (60.7%)</td>
<td valign="top" align="center">5 (20.8%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">ICU admission, n[%]</td>
<td valign="top" align="center">38 (40.0%)</td>
<td valign="top" align="center">5 (11.6%)</td>
<td valign="top" align="center">23 (82.1%)</td>
<td valign="top" align="center">10 (41.7%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">ICU stay length, median (IQR), days</td>
<td valign="top" align="center">0.0 (0.0-5.0)</td>
<td valign="top" align="center">0.0 (0.0-0.0)</td>
<td valign="top" align="center">8.0 (1.0-10.7)</td>
<td valign="top" align="center">0.0 (0.0-3.5)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Total hospital stay length, median (IQR), days</td>
<td valign="top" align="center">9.0 (7.0-14.0)</td>
<td valign="top" align="center">9.0 (7.0-12.2)</td>
<td valign="top" align="center">10.0 (6.0-17.0)</td>
<td valign="top" align="center">11.0 (6.2-17.0)</td>
<td valign="top" align="center">0.773</td>
</tr>
<tr>
<td valign="top" align="left">Death, n[%]</td>
<td valign="top" align="center">15 (15.8%)</td>
<td valign="top" align="center">0 (0.0%)</td>
<td valign="top" align="center">8 (28.6%)</td>
<td valign="top" align="center">7 (29.2%)</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Data are presented as medians (IQR) and n (%). P values were calculated by Kruskal-Wallis H test, Chi-square test or Fisher&#x2019;s exact test, as appropriate. P values indicate differences among different clusters. IQR, interquartile range; ICU, intensive care unit.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<title>Risk factors for ICU admission in severe leptospirosis patients</title>
<p>Univariate logistic regression analysis of risk factors for ICU admission in patients with severe leptospirosis revealed that dyspnea, altered consciousness, neutrophil count, lactate dehydrogenase, blood urea nitrogen, creatine kinase isoenzyme, activated partial thrombin time, d-dimer, c-reactive protein were significantly associated with ICU admission (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Several factors in univariate analysis plus age, gender and smoking situation were involved in the multivariate logistic regression analysis, which suggested that dyspnea (OR=19.051, 95%CI: 1.218-692.730, <italic>p</italic>=0.037) and neutrophil count (OR=1.611, 95%CI: 1.033-2.513, <italic>p</italic>=0.036) were risk factors for ICU admission. However, no promising predictors for mortality were identified in the current study (data not shown).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Logistic regression analysis of risk factors for ICU admission in patients with severe leptospirosis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" colspan="2" align="center">Univariate analysis</th>
<th valign="top" colspan="4" align="center">Multivariate analysis</th>
</tr>
<tr>
<th valign="top" align="left">
</th>
<th valign="top" align="center">OR (95%CI)</th>
<th valign="top" align="center">
<italic>p</italic> value</th>
<th valign="top" colspan="2" align="center">OR (95%CI)</th>
<th valign="top" colspan="2" align="center">
<italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">1.026 (1.000-1.053)</td>
<td valign="top" align="center">0.048</td>
<td valign="top" align="center">1.043 (0.968-1.124)</td>
<td valign="top" colspan="2" align="center">0.270</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">0.747 (0.230-2.423)</td>
<td valign="top" align="center">0.627</td>
<td valign="top" align="center">0.347 (0.007-18.282)</td>
<td valign="top" colspan="2" align="center">0.601</td>
</tr>
<tr>
<td valign="top" align="left">Smoking</td>
<td valign="top" align="center">0.492 (0.214-1.132)</td>
<td valign="top" align="center">0.095</td>
<td valign="top" align="center">0.973 (0.086-11.012)</td>
<td valign="top" colspan="2" align="center">0.982</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Clinical symptoms</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Fever</td>
<td valign="top" align="center">0.642 (0.150-2.738)</td>
<td valign="top" align="center">0.549</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Fatigue</td>
<td valign="top" align="center">1.358 (0.236-7.813)</td>
<td valign="top" align="center">0.731</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Myalgia</td>
<td valign="top" align="center">0.525 (0.190-1.447)</td>
<td valign="top" align="center">0.213</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Jaundice</td>
<td valign="top" align="center">0.915 (0.363-2.307)</td>
<td valign="top" align="center">0.851</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Vomiting</td>
<td valign="top" align="center">0.634 (0.201-1.997)</td>
<td valign="top" align="center">0.436</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Dyspnea</td>
<td valign="top" align="center">6.588 (2.630-16.504)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">29.051 (1.218-692.730)</td>
<td valign="top" colspan="2" align="center">0.037</td>
</tr>
<tr>
<td valign="top" align="left">Hemoptysis</td>
<td valign="top" align="center">1.891 (0.823-4.342)</td>
<td valign="top" align="center">0.133</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Altered consciousness</td>
<td valign="top" align="center">3.297 (1.159-9.380)</td>
<td valign="top" align="center">0.025</td>
<td valign="top" align="center">0.172 (0.008-3.874)</td>
<td valign="top" colspan="2" align="center">0.268</td>
</tr>
<tr>
<td valign="top" colspan="6" align="left">
<bold>Laboratory findings on admission</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">White blood cell count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">1.077 (0.993-1.167)</td>
<td valign="top" align="center">0.072</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Platelet count, &#xd7;10<sup>9</sup>/L</td>
<td valign="top" align="center">0.996 (0.991-1.001)</td>
<td valign="top" align="center">0.082</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Neutrophil count</td>
<td valign="top" align="center">1.121 (1.016-1.238)</td>
<td valign="top" align="center">0.023</td>
<td valign="top" align="center">1.611 (1.033-2.513)</td>
<td valign="top" colspan="2" align="center">0.036</td>
</tr>
<tr>
<td valign="top" align="left">Eosinophil count</td>
<td valign="top" align="center">0.100 (0.005-2.205)</td>
<td valign="top" align="center">0.144</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Albumin, g/L</td>
<td valign="top" align="center">0.933 (0.868-1.003)</td>
<td valign="top" align="center">0.060</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Total bilirubin, &#x3bc;mol/L</td>
<td valign="top" align="center">0.998 (0.995-1.002)</td>
<td valign="top" align="center">0.421</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Alanine aminotransferase, U/L</td>
<td valign="top" align="center">0.999 (0.997-1.002)</td>
<td valign="top" align="center">0.683</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Lactate dehydrogenase, U/L</td>
<td valign="top" align="center">1.005 (1.002-1.008)</td>
<td valign="top" align="center">0.003</td>
<td valign="top" align="center">1.004 (0.988-1.019)</td>
<td valign="top" colspan="2" align="center">0.631</td>
</tr>
<tr>
<td valign="top" align="left">Blood urea nitrogen, mmol/L</td>
<td valign="top" align="center">1.059 (1.005-1.116)</td>
<td valign="top" align="center">0.033</td>
<td valign="top" align="center">1.066 (0.898-1.265)</td>
<td valign="top" colspan="2" align="center">0.465</td>
</tr>
<tr>
<td valign="top" align="left">Creatinine, &#x3bc;mol/L</td>
<td valign="top" align="center">1.002 (0.999-1.005)</td>
<td valign="top" align="center">0.119</td>
<td valign="top" align="center"/>
<td valign="top" colspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Creatine kinase isoenzyme, U/L</td>
<td valign="top" align="center">1.025 (1.004-1.046)</td>
<td valign="top" align="center">0.022</td>
<td valign="top" align="center">1.010 (0.964-1.059)</td>
<td valign="top" colspan="2" align="center">0.672</td>
</tr>
<tr>
<td valign="top" align="left">Activated partial thrombin time, s</td>
<td valign="top" align="center">1.046 (1.003-1.092)</td>
<td valign="top" align="center">0.036</td>
<td valign="top" align="center">1.060 (0.922-1.218)</td>
<td valign="top" colspan="2" align="center">0.414</td>
</tr>
<tr>
<td valign="top" align="left">D-dimer, &#x3bc;g/mL</td>
<td valign="top" align="center">1.701 (1.044-2.773)</td>
<td valign="top" align="center">0.033</td>
<td valign="top" align="center">0.686 (0.257-1.832)</td>
<td valign="top" colspan="2" align="center">0.452</td>
</tr>
<tr>
<td valign="top" align="left">C-reactive protein, mg/L</td>
<td valign="top" align="center">1.010 (1.002-1.018)</td>
<td valign="top" align="center">0.009</td>
<td valign="top" align="center">1.005 (0.991-1.019)</td>
<td valign="top" colspan="2" align="center">0.519</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>OR, odds ratio; CI, confidence interval.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>Leptospirosis is a zoonosis of protean manifestations (<xref ref-type="bibr" rid="B36">Peter, 1982</xref>) and can be easily misdiagnosed. Our study found a significantly higher incidence of leptospirosis in male than in female, which was consistent with the results of most previous studies (<xref ref-type="bibr" rid="B21">Kawaguchi et&#xa0;al., 2008</xref>). This might be related not only to occupation and exposure (<xref ref-type="bibr" rid="B2">Alvarado-Esquivel et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B24">Lau et&#xa0;al., 2016</xref>), but also to gender-based genetic and immune susceptibility (<xref ref-type="bibr" rid="B40">Puca et&#xa0;al., 2018</xref>). The age of onset was concentrated around the age of 50, which might be associated with more frequent exposure to risk factors for leptospirosis such as farming and fishing in this age group (<xref ref-type="bibr" rid="B40">Puca et&#xa0;al., 2018</xref>). These demographic features were less helpful for diagnosis.</p>
<p>Furthermore, the symptoms spectrum of leptospirosis is extremely broad, and there is no good clinical method to differentiate patients with leptospirosis by demographics, clinical symptoms, laboratory testing, and prognosis. In the current study, we conducted a MCA analysis based on clinical features, laboratory findings and outcomes, and identified three subtypes of populations with differences in ICU admission and mortality rate, which could be effective indicators for prognosis of patients with leptospirosis. Traditionally, distinct clinical syndromes of leptospirosis have been considered to be linked to specific serogroups. However, this view was questioned by some authorities (<xref ref-type="bibr" rid="B13">Edwards and Domm, 1960</xref>; <xref ref-type="bibr" rid="B1">Alexander et&#xa0;al., 1963</xref>; <xref ref-type="bibr" rid="B14">Feigin and Anderson, 1975</xref>), and more intense study over the past 50 years has refuted this hypothesis. In humans, severe leptospirosis is frequently but not invariably caused by serovars of the icterohaemorrhagiae serogroup. The infection of the specific serovars largely depend on the geographic location and the ecology of local maintenance hosts.</p>
<p>We identified three clusters: mild leptospirosis (cluster 1), respiratory leptospirosis (cluster 2), and hepato-renal leptospirosis (cluster 3).The current study did not identify a subtype of neurological leptospirosis, while, notably, we discovered that respiratory and hepato-renal leptospirosis had a higher prevalence of altered awareness and CNS symptoms than mild leptospirosis. Therefore, we speculated that neuro-leptospirosis was implicated in the kind of respiratory and hepato-renal leptospirosis due to the low incidence of neuro-leptospirosis, and the neurological symptoms were concealed by pulmonary or digestive symptoms, and the limitation of statistical approach. Studies suggested that neurological symptoms occurred in 10-15% of cases and were often neglected, so we should consider leptospirosis-associated neurological symptoms in areas where leptospirosis is endemic (<xref ref-type="bibr" rid="B38">Puca et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B34">Nabity et&#xa0;al., 2020</xref>). Mild leptospirosis of Cluster 1, which accounted for 45.3% of our patients, had the best prognosis among three clusters in this study, which was highly accordance with anicteric leptospirosis. The anicteric leptospirosis commonly begins abruptly and frequently presents with vague symptoms such as headache, myalgia (particularly in the calf muscles), ocular abnormalities, fever, nausea, vomiting, rash and epistaxis. Puca E et&#xa0;al. also showed that ocular and cutaneous involvement of leptospirosis usually did not cause serious complications and death (<xref ref-type="bibr" rid="B39">Puca et&#xa0;al., 2016</xref>). Cluster 2, mainly characterized by respiratory failure, had the high rate of endotracheal intubation that required ICU admission, was comparable with a pattern previously described in severe leptospirosis (<xref ref-type="bibr" rid="B15">Gouveia et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B18">Herath et&#xa0;al., 2019</xref>). The incidence of respiratory leptospirosis was about 10% in Brazil and French (<xref ref-type="bibr" rid="B15">Gouveia et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B33">Miailhe et&#xa0;al., 2019</xref>), compared to 29.5% in our population. Cluster 3 was distinguished by acute liver and kidney failure in contrast with slightly lower incidence of respiratory and circulatory failure. Second, as a temperate zone, there were still some outbreaks and a high incidence of leptospirosis in Hunan. Leptospirosis is a neglected zoonosis that causes considerable public health concerns throughout the world, particularly in Southeast Asian countries such as China, Indonesia, Vietnam, Malaysia, Cambodia and South Korea (<xref ref-type="bibr" rid="B53">Zhang et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B29">Loan et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B54">Zhang et&#xa0;al., 2019</xref>). It was discovered that leptospirosis morbidity rates varied across China&#x2019;s provinces, with the warm and moist areas of the southern and central China being the predominant regions of leptospirosis infection (<xref ref-type="bibr" rid="B55">Zhang et&#xa0;al., 2020</xref>). Frequent rainfall can flush leptospirosis-contaminated soil into bodies of water, increasing the risk of human exposure to leptospirosis.</p>
<p>Notably, this study revealed that 40% of hospitalized leptospirosis cases in a temperate zone was adequately severe to transfer to ICU ward, 23.2% of patients required endotracheal intubation and longer ICU stays. The death rate for icteric leptospirosis has been reported to be as high as 5&#x2013;15% (<xref ref-type="bibr" rid="B27">Levett, 2001</xref>) and 30&#x2013;70% for leptospirosis-associated pulmonary hemorrhage syndrome (<xref ref-type="bibr" rid="B8">Dolhnikoff et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B15">Gouveia et&#xa0;al., 2008</xref>), compared to 20.8% and 60.7%, respectively, in our population. Leptospira interrogans serogroup Icterohaemorrh agiae serovar Lai (<xref ref-type="bibr" rid="B20">Hu et&#xa0;al., 2014</xref>) was the most common pathogen in Chinese leptospirosis patients, which was also the causative pathogen in 75% of the pulmonary diffuse hemorrhagic leptospirosis. The 15.8% mortality rate was slightly higher than the mean case fatality ratio of 6.85% (<xref ref-type="bibr" rid="B7">Costa et&#xa0;al., 2015</xref>), and the majority of leptospirosis deaths was due to renal failure and/or gastrointestinal, pulmonary, or cerebral hemorrhage (<xref ref-type="bibr" rid="B49">Vijayachari et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B9">Dong and Chen, 2021</xref>) caused by extensive capillary damage including extensive renal necrosis and glomerular atrophy. Moreover, leptospira increased the permeability and engorgement of blood vascular cells (<xref ref-type="bibr" rid="B35">Narayanavari et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B32">Matsunaga and Haake, 2018</xref>; <xref ref-type="bibr" rid="B52">Zavala-Alvarado et&#xa0;al., 2020</xref>). Given the prevalence and predominance of L. interrogans in China, the mortality rate was significantly higher than in other countries.</p>
<p>In this study, 11 patients were diagnosed using metagenomic next-generation sequencing (mNGS) of clinical samples including blood or alveolar lavage fluid. Several diagnostic methods have been used to confirm leptospirosis infection including pathogen culture, pathogen-specific antibodies detection, and genetic way such as mNGS. However, several limitations exist for above testing, for example: (1) Leptospirosis culture is less helpful and not commonly used for clinical diagnosis since it is technically difficult to culture due to the demand of fastidious culture media and long incubation time (<xref ref-type="bibr" rid="B42">Rodriguez et&#xa0;al., 2014</xref>); (2) The traditional antibody test of MAT is the most commonly used method to confirm leptospiraosis infection (<xref ref-type="bibr" rid="B47">Sykes et&#xa0;al., 2011</xref>), while identifying infecting serovar is difficult based on the cross-reactive MAT tests due to laboratory variation and differences in host-specific humoral immune responses (<xref ref-type="bibr" rid="B30">Markovich et&#xa0;al., 2012</xref>); (3) Several ELISAs for detecting IgM, IgG, or both antibodies have been developed to detect specific antibodies in leptospirosis, however, it has not been priorly recommended due to lower sensitivity compared to MAT test; (4) Genetic identification, such as mNGS, have become widely available for the diagnosis of leptospirosis although it is relatively expensive than traditional methods (<xref ref-type="bibr" rid="B16">Harkin et&#xa0;al., 2003</xref>). However, false-negative results can be avoided when facing low bacterial loads due to disease phase, complicated immune response, or administration of antimicrobial drugs (<xref ref-type="bibr" rid="B28">Levett et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B50">Waggoner and Pinsky, 2016</xref>). Thus, to some extends, mNGS, as a method allowing for high-throughputand massively parallel sequencing, benefits leptospirosis patients a lot, particular for those patients with suspicious symptoms, negative traditional testing, or emergent conditions, thus avoiding inadequate diagnosis, delayed treatment, and increased morbidity and mortality. Over the past five years, mNGS testing has been widely used for clinical diagnosis of microbiology examinations (<xref ref-type="bibr" rid="B46">Simner et&#xa0;al., 2018</xref>) due to the advantages of quicker diagnosis, higher sensitivity, and even detecting pathogen subtypes as well. Therefore, to some extends, mNGS can avoid some disadvantages of traditional testing, and represent as a promising supplementary tool for some uncommon pathogen diagnosis.</p>
<p>In the current study, we identified several possible predictors, such as dyspnea and neutrophil count, for ICU admission in hospitalized leptospirosis. However, no significant predictors were determined to be associated with mortality of leptospirosis in the current investigation, which might be due to the small sample size. Age has already been shown as a significant predictor of leptospirosis mortality (<xref ref-type="bibr" rid="B6">Chang et&#xa0;al., 2005</xref>). Oliguria, hypotension and abnormal chest auscultation were all found to be independent predictors of severe leptospirosis mortality in a Polynesian cohort (<xref ref-type="bibr" rid="B10">Doudier et&#xa0;al., 2006</xref>). According to a French study, the following variables including dyspnea, oliguria, increased white blood cell count, repolarization abnormalities on electrocardiograms and alveolar infiltrates on chest radiographs were reported to be associated with leptospirosis mortality (<xref ref-type="bibr" rid="B11">Dupont et&#xa0;al., 1997</xref>). Additionally, a Thai cohort demonstrated that hypotension, oliguria, hyperkalaemia, and presence of pulmonary rales were linked to the mortality of leptospirosis. While oliguria has been frequently shown to be related to mortality in numerous earlier studies, our findings are different, and we believe they are justified. Patients in the current study were admitted to tertiary care referral centers with fully functional haemodialysis units, and the patients with AKI were dialyzed whenever indicated. This, we believe, is the cornerstone of leptospirosis care and is likely to have resulted in a decrease in AKI mortality.</p>
<sec id="s4_1">
<title>Strengths and limitations</title>
<p>This study was limited by a few factors that should be considered. First, this was a retrospective study in which a relatively small subset of leptospirosis patients from Hunan. Second, selection bias may have been introduced since female were less likely to be included, and a large cohort study would be warranted to further strengthen our findings. Thirdly, limited cases of neurological leptospirosis were included in the study; thus, the conclusions may not apply to patients with neuro-leptospirosis.</p>
</sec>
</sec>
<sec id="s5">
<title>Conclusions</title>
<p>In the current study, we identified three phenotypes of leptospirosis with distinct clinical features and prognosis, which would assist clinicians in recognizing leptospirosis-like illness while also providing prognostic predictors. Additionally, dyspnea and neutrophil count were found to be independent risk factors for severe leptospirosis progression. When patients are infected with leptospira, it is prudent to consider more rigorous surveillance and therapy.</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/supplementary material. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving human participants were reviewed and approved by The institutional review boards (IRBs) in Xiangya Hospital of Central South University (No. 202104005). 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>All authors contributed to the study conception and design. Material preparation was performed by DL, HL. Data collection and analysis were performed by DL, HL and other authors. The first draft of the manuscript was written by DL and HL. Supervision was performed by PP and YAZ. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by Natural Science Foundation of China (No.82100037, No.81770080), National Key R&amp;D Program of China (No. 2016YFC1304204), National Science Foundation for Post-doctoral Scientists of China (No. 2021TQ0375), Hunan Outstanding Postdoctoral Innovative Talents Program (No.2021RC2018), Key R&amp;D Prpgram of Hunan Province (No.2022SK2038) and Youth Foundation of Xiangya Hospital (No.2020Q06).</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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