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All patients who collected a reverse transcriptase-polymerase chain reaction &#40;RT-PCR&#41; for the diagnosis of COVID-19 were eligible&#46; The study included consecutive patients with suspected pneumonia that underwent chest CT&#44; at the discretion of the attending physician&#46; Chest CT was ordered according to the institutional protocol taking into account pneumonia severity criteria&#44; laboratory tests and comorbidities&#46; Exclusion criteria were age &#60;18 years&#44; lack of data in medical records&#44; and severe respiratory motion artifacts on chest CT&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">COVID-19 was confirmed with one positive RT-PCR result&#46; Patients with one negative RT-PCR result were considered non-COVID-19 if clinical&#44; laboratory&#44; and radiological findings indicated a low likelihood of COVID-19&#46; Two consecutive &#40;at least 48&#8239;h apart&#41; negative results were required for excluding COVID-19 diagnosis in those judged to have a higher probability of disease&#44; according to the independent evaluation of two infectious diseases specialists of institutional infection control team&#44; as recommended by Infectious Diseases Society of America Guidelines&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a></p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Molecular diagnosis</span><p id="par0030" class="elsevierStylePara elsevierViewall">One oropharyngeal and two nasopharyngeal &#40;from both nostrils&#41; rayon swabs were collected&#46; RNA extraction and real-time RT-PCR were performed at an external laboratory &#40;Grupo Fleury&#41;&#44; a reference private laboratory in Brazil&#44; using primer and probes according to the Charit&#233; protocol&#44; as previously described&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> Molecular tests for other respiratory pathogens were performed per request of the attending physician&#44; and included either PCR for influenza A &#40;H3N2 and H1N1&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> geneXpert&#174; &#40;Cepheid&#41; for influenza A &#40;H3N2 and H1N1&#41; and B&#44; or FilmArray&#174; PCR Multiplex &#40;Biom&#233;rieux&#41;&#44; including adenovirus&#59; coronavirus 229E&#44; coronav&#237;rus HKU1&#44; NL63 and OC43&#59; human metapneumovirus&#59; influenza A &#40;H3N2 and H1N1&#41; and B&#59; parainfluenza 1&#44;2&#44; 3 e 4&#59; and rhinovirus&#47;enterovirus&#59; Syncytial Respiratory Virus&#59; <span class="elsevierStyleItalic">Bordetella pertussis</span>&#59; <span class="elsevierStyleItalic">Chlamydophila pneumoniae</span> and <span class="elsevierStyleItalic">Mycoplasma pneumoniae&#46;</span></p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">CT image acquisition</span><p id="par0035" class="elsevierStylePara elsevierViewall">Imaging acquisitions were obtained with patients in the supine position during end-inspiration without contrast medium injection&#46; Chest CT was performed on a 16-slice CT &#40;Siemens Emotion 16 Slice CT Scanner&#44; Siemens Healthineers&#44; Forchheim&#44; Germany&#41; and 64-slice CT &#40;Siemens Sensation 64 Slice CT Scanner&#44; Siemens Healthineers&#44; Forchheim&#44; Germany&#41;&#46; The following technical parameters were used for both CT scanners&#58; tube voltage 130&#8239;kV&#59; tube current modulation 100 mAs&#59; spiral pitch factor 1&#46;4&#59; collimation width 0&#46;625&#46; Reconstructions were made with convolution kernel lung and soft tissue at a slice thickness of 1&#46;00&#8239;mm&#46; DICOM data were transferred onto a PACS workstation &#40;Carestream Vue PACS version 12&#46;1&#46;6&#46;1005&#44; Carestream Health&#44; NY&#44; USA&#41;&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">CT image analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">All chest CT images were evaluated independently by two radiologists with two and 10 years of thoracic imaging experience&#46; Both readers evaluated every patient scan twice with a 2-day interval between readout sessions to assess intra and inter-rater agreement&#46; Discordant reports were evaluated by a third thoracic radiologist with 12 years of experience and consensus was reached among the three radiologists&#46; All radiologists were blinded for RT-PCR&#44; clinical and laboratory results&#44; and previous imaging exams&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">CT features were classified as &#34;typical&#44;&#34; &#34;indeterminate&#44;&#34; &#34;atypical&#44;&#34; and &#34;negative&#34; for COVID-19 pneumonia&#34;&#44; according to RSNA expert consensus&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> COVID-19 typical features are peripheral&#44; bilateral and multifocal rounded ground-glass opacities &#40;GGO&#41; with or without consolidation or visible intralobular lines &#40;&#8220;crazy-paving&#8221;&#41;&#46; Reversed halo sign and other findings of organizing pneumonia can be seen later in the disease&#46; Indeterminate features may occur but are nonspecific for COVID-19 pneumonia&#44; such as diffuse&#44; perihilar&#44; or unilateral GGO&#46; All unusual or unreported findings for COVID-19 were classified as atypical &#40;e&#46;g&#46;&#44; centrilobular nodules&#44; tree-in-bud opacities&#44; or lung cavitation&#41;&#46; If no CT suggestive findings of pneumonia were present&#44; a negative classification was assigned&#46; A typical appearance was considered a positive chest CT for COVID-19&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Statistical analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">Statistical analysis was performed using SPSS version 18&#46;0 &#40;2009&#44; PASW Statistics for Windows&#46; SPSS Inc&#46; Chicago&#44; IL&#44; USA&#41;&#46; The association of CT findings and COVID-19 was assessed by univariate analysis using &#967;&#178; or Fisher&#39;s exact test for categorical and Student&#39;s t or Wilcoxon Mann-Whitney tests for continuous variables&#46; Sensitivity&#44; specificity&#44; positive and negative likelihood ratio of a positive CT for COVID-19 pneumonia were calculated&#46; Intra- and inter-rater classification agreement beyond chance &#40;appearance and each specific CT findings&#41; and internal consistency reliability were evaluated with Cohen&#39;s kappa and Cronbach&#39;s alpha coefficients&#44; respectively&#46; Kappa coefficients of 0&#8722;0&#46;20&#44; 0&#46;21&#8722;0&#46;40&#44; 0&#46;41&#8722;0&#46;60&#44; 0&#46;61&#8722;0&#46;80&#44; and 0&#46;81&#8211;1&#46;00 were considered to indicate none to slight&#44; fair&#44; moderate&#44; substantial&#44; and almost perfect agreement&#44; respectively&#44; and Cronbach&#8217;s alpha higher than 0&#46;70 reflects internal consistency&#46;<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20&#44;21</span></a> Positive predictive value &#40;PPV&#41; and negative predictive value &#40;NPV&#41; of the classification according to distinct COVID-19 prevalence were also estimated&#46; A <span class="elsevierStyleItalic">p</span>&#8239;&#60;&#8239;0&#46;05 was considered statistically significant&#46;</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Patient population and clinical data</span><p id="par0055" class="elsevierStylePara elsevierViewall">A total of 1176 patients underwent clinical evaluation for respiratory symptoms&#46; In 443 &#40;37&#46;6&#37;&#41; RT-PCR for SARS-CoV-2 was collected&#46; Of these&#44; a chest CT with suspected pneumonia was reported for 163&#44; four &#40;2&#46;4&#37;&#41; were excluded&#44; and 159 &#40;mean age&#44; 57&#46;9&#8239;&#177;&#8239;18&#46;0 years&#59; 88 &#91;55&#46;3&#37;&#93; males&#41; were included in the study&#58; 86 &#40;54&#46;1&#37;&#41; COVID-19 and 73 &#40;45&#46;9&#37;&#41; non-COVID-19 patients &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; Out of 36 &#40;22&#46;6&#37;&#41; patients admitted to the intensive care unit during hospitalization&#44; 24 &#40;66&#46;7&#37;&#41; were COVID-19 and 12 were &#40;33&#46;3&#37;&#41; non-COVID-19 patients&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">Baseline&#44; clinical and laboratory characteristics of patients were generally similar between COVID-19 and non-COVID-19 groups &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; Age and sex were not significantly different between both groups&#46; Anosmia was significantly more frequent in COVID-19 group&#46; The non-COVID group had a shorter median duration of symptoms before attendance at emergency&#46; COVID-19 patients had significantly lower oxygen saturation at emergency admission&#44; lower leukocyte&#44; lymphocyte&#44; and platelets counts&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0065" class="elsevierStylePara elsevierViewall">The median time between collecting nasal and oropharyngeal swabs and performing chest CT was 3&#46;6&#8239;h &#40;IQR&#44; 1&#46;6&#8211;8&#46;3&#41;&#44; and the median time from onset of symptoms to undergoing CT was seven days &#40;IQR&#44; 3&#8211;9&#41;&#46; Eighty &#40;93&#46;0&#37;&#41; COVID-19 patients had their diagnosis confirmed in the first RT-PCR for SARS-CoV-2&#44; while in 6 &#40;7&#46;0&#37;&#41; the first test was negative but the second was positive&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Chest CT standards accuracy for COVID-19</span><p id="par0070" class="elsevierStylePara elsevierViewall">Chest CT features were classified as typical in 80 &#40;50&#46;3&#37;&#41; patients&#44; as indeterminate in 30 &#40;18&#46;9&#37;&#41;&#44; as atypical in 17 &#40;10&#46;7&#37;&#41; and as negative for COVID-19 pneumonia in 32 &#40;20&#46;1&#37;&#41;&#46; The sensitivity&#44; specificity&#44; accuracy&#44; positive and negative likelihood ratio of typical appearance were 88&#46;3&#37; &#40;95&#37;CI 79&#46;9-93&#46;5&#37;&#41;&#44; 94&#46;5&#37; &#40;95&#37;CI 86&#46;7-97&#46;8&#37;&#41;&#44; 91&#46;1&#37; &#40;95&#37;CI 85&#46;7-94&#46;6&#37;&#41;&#44; 16&#46;1 &#40;95&#37;CI 9&#46;8-26&#46;4&#41; and 0&#46;12 &#40;95&#37;CI 0&#46;10&#8722;0&#46;14&#41;&#44; respectively&#46; The PPV and NPV of typical appearance were 95&#46;0&#37; &#40;95&#37;CI&#44; 88&#46;0&#37;-98&#46;0&#37;&#41; and 87&#46;3&#37; &#40;95&#37;CI&#44; 79&#46;4&#37; - 92&#46;5&#37;&#41;&#44; respectively&#46; PPV and NPV according to distinct expected prevalence of COVID-19 among patients with respiratory symptoms are displayed in <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Only four patients presented a typical appearance and were not confirmed as COVID-19 in two RT-PCR exams&#59; an alternative diagnosis could not established in two cases and were considered as possible COVID-19 pneumonia by the attending physicians&#46; Of the remaining two patients&#44; one had pulmonary thromboembolism with pulmonary infarction diagnosed through magnetic resonance angiography performed three days after chest CT and the other patient had bacterial community-acquired pneumonia&#46; The typical finding in these latter two patients was peripheral and bilateral rounded GGO with consolidation&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">Commonly typical features reported in COVID-19 pneumonia were multifocal&#44; rounded and peripheral GGO displaying a sensitivity of 95&#46;3&#37; &#40;95&#37;CI 88&#46;5-98&#46;7&#41;&#44; 82&#46;5&#37; &#40;95&#37;CI 72&#46;8-89&#46;9&#41; and 81&#46;7&#37; &#40;95&#37;CI 71&#46;6-89&#46;3&#41;&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#59; <a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; All patients with atypical appearance &#40;n&#8239;&#61;&#8239;17&#41; on chest CT were not diagnosed with COVID-19 by RT-PCR&#46; Of these&#44; according to their attendant physician&#44; 13 had the final diagnosis of bacterial pneumonia&#44; one had decompensated heart failure and three had no confirmed alternative diagnosis&#46; The most common findings among these patients were centrilobular nodules &#40;n&#8239;&#61;&#8239;15&#41; and tree-in-bud opacities &#40;n&#8239;&#61;&#8239;7&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>&#41;&#46; Among patients with indeterminate appearance &#40;n&#8239;&#61;&#8239;30&#41;&#44; seven had a positive RT-PCR for SARS-CoV-2&#46; In this group&#44; common findings were very few and non-rounded GGO &#40;n&#8239;&#61;&#8239;4&#41;&#44; diffuse GGO &#40;n&#8239;&#61;&#8239;2&#41;&#44; and unilateral features &#40;n&#8239;&#61;&#8239;1&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46; One of them also had radiological features of pulmonary fibrosis&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Other respiratory pathogens</span><p id="par0085" class="elsevierStylePara elsevierViewall">A total of 33 &#40;41&#46;2&#37;&#41; patients with typical findings were tested for influenza by molecular methods &#40;three of them for all other pathogens described in Methods&#59; two were patients with negative SARS-CoV-2 RT-PCR&#41; and none had positive results&#46; Molecular tests for influenza were negative in other five &#40;16&#46;7&#37;&#59; one also negative for other pathogens&#41;&#44; three &#40;17&#46;6&#37;&#41; and five &#40;15&#46;6&#37;&#59; one also negative for other pathogens&#41; patients with indeterminate&#44; atypical&#44; and negative CT findings&#44; respectively&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Chest CT standards intra- and inter-rater reliability</span><p id="par0090" class="elsevierStylePara elsevierViewall">Intra-rater agreement in assigned classification was seen in 282 &#40;88&#46;7&#37;&#41; of 318 observations&#46; Regarding intra-rater agreement&#44; Cohen&#8217;s kappa of observer one was 0&#46;847 &#40;<span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;&#46;13&#41;&#44; and observer two was 0&#46;924 &#40;<span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;&#46;06&#41;&#46; Inter-rater agreement ranged from 0&#46;725 &#40;<span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;&#46;001&#41; to 0&#46;772 &#40;<span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;&#46;05&#41; between two radiologists &#40;see Tables S1 and S2&#41;&#46; The agreement coefficients of selected typical findings are shown in Table S3&#46;</p></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Discussion</span><p id="par0095" class="elsevierStylePara elsevierViewall">Although Brazil is currently the second most affected country worldwide in number of cases and deaths&#44;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> there is little data regarding chest CT evaluation of COVID-19 pneumonia in the country&#44; as well as in South-american population&#46; Evaluation of a diagnostic method in distinct populations is of paramount importance to ensure reproducibility of the method in different epidemiological scenarios&#44; including potentially distinct baseline clinical characteristics and circulating viruses&#46; Our study demonstrated that typical appearance on chest CT had high specificity for COVID-19 pneumonia in a Brazilian population&#46; The likelihood of COVID-19 pneumonia diagnosis in patients with a typical CT pattern was substantially higher &#40;PLR&#8239;&#61;&#8239;16&#46;1&#41; than in patients with non-typical findings&#46; Two other studies have assessed the accuracy of the RSNA criteria in Brazilian patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">22&#44;23</span></a> In the study of Santos et al&#46; both sensitivity &#40;83&#37;&#41; and specificity &#40;97&#37;&#41; were similar to our results&#46; Barbosa et al&#46; evaluated oncologic patients and found lower sensitivity &#40;64&#46;0&#37;&#41; and specificity &#40;84&#46;8&#37;&#41; rates in that specific population&#46; These results are comparable to those demonstrated in a recent study evaluating Italian patients&#44; in which the authors used the same radiological criteria and found that a typical pattern had an specificity of 91&#46;6&#37; for COVID-19 pneumonia&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> Other Chinese and Italian studies performed in the early COVID-19 pandemic showed much lower specificity rates &#40;25&#46;0&#37; to 56&#46;0&#37;&#41; for chest CT&#59;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#44;25</span></a> However&#44; those studies have not addressed the chest CT criteria proposed by RSNA&#44; which may have affected their results owing to the lack of standards in CT interpretation&#46;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#44;25</span></a> Finally&#44; a recent meta-analysis found a pooled specificity of 37&#46;0&#37; for chest CT&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> However&#44; as considered by the authors&#44; there was significant heterogeneity among the studies&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> We believe that it was mostly caused by the fact that studies using non-standardized criteria for interpretation were included in the analysis&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Only four patients with typical CT findings were not diagnosed with COVID-19 by RT-PCR&#46; Although all had negative RT-PCRs&#44; this diagnosis could not be ruled out in at least two of them&#44; who had no alternative diagnosis during hospitalization &#40;<a class="elsevierStyleCrossRef" href="#fig0030">Fig&#46; 6</a>&#41;&#46; Additionally&#44; one patient had pulmonary embolism&#44; which is a possible complication described in COVID-19 patients&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> Other studies also showed similar findings related to some false negative RT-PCR results with typical chest CT appearance&#46;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">28&#8211;31</span></a></p><elsevierMultimedia ident="fig0030"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">A previous study has assessed the RSNA classification inter-rater reliability&#44; with moderate to substantial agreement results&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">32</span></a> Our study reinforces these findings&#44; demonstrating an almost perfect intra-rater and substantial inter-rater agreements&#46; These are encouraging outcomes&#44; suggesting that the classification may be useful for clinicians to accurately estimate their suspicion for COVID-19 pneumonia before RT-PCR results become available and increase the confidence in imaging classification&#44; especially in settings where molecular tests are restricted or unavailable&#46; Actually&#44; in pandemic scenarios where the expected COVID-19 prevalence in patients with respiratory symptoms is above 30&#37;&#44; the PPV of typical CT appearance was higher than 80&#37;&#46; Moreover&#44; it was higher than 90&#37; when the prevalence was above 40&#37;&#44; making imaging classification a reliable tool to identify highly suspicious cases of SARS-CoV-2 pneumonia&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Even though typical appearance sensitivity was near 90&#37;&#44; it is not possible to rule out the diagnosis with a non-typical appearance&#44; particularly in the high prevalence scenario&#46; Previous studies suggested a high sensitivity for CT&#59; however&#44; the lack of clear definitions for positive CT findings impairs the generalizability of those findings&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">25&#44;26&#44;33</span></a> On the other hand&#44; it is important to highlight that the diagnosis of COVID-19 pneumonia was correctly excluded in all patients classified as atypical&#44; suggesting that this classification may be useful to discourage the diagnosis of COVID-19 pneumonia&#46; Seven of 86 &#40;8&#46;1&#37;&#41; COVID-19 patients presented an indeterminate CT classification&#46; This means that the diagnosis of COVID-19 pneumonia cannot be confirmed or ruled out in patients with an indeterminate CT&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">Among typical findings&#44; the most frequent were multifocal and rounded GGO&#44; crazy-paving&#44; and perilobular pattern&#44; usually peripheral and bilateral&#46; Interestingly&#44; despite discordance among readers regarding some isolated typical CT signs&#44; there was agreement in the final standard&#46; It is noteworthy that each radiological finding should not be considered individually&#44; considering that these features are not uniquely related to COVID-19 pneumonia&#46; Even noninfectious diseases may present findings that might overlap with CT features related to SARS-CoV-2 infection&#44; such as pulmonary edema&#44; organizing pneumonia&#44; drug-related toxicity&#44; pulmonary infarcts&#44; and interstitial lung diseases&#46;<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">34&#8211;37</span></a> Furthermore&#44; coinfection with other viruses cannot be ruled out using only chest CT&#46; However&#44; it is noteworthy that the study was conducted in a period before the influenza season in our region and&#44; in addition to our data on molecular tests for influenza&#44; it should be highlighted that&#44; during the study period&#44; only one case of severe acute respiratory syndrome caused by influenza was reported to the Municipal Health Secretary&#44; in mid March and from another institution &#40;<a href="https://opendatasus.saude.gov.br/dataset/bd-srag-2020">https&#58;&#47;&#47;opendatasus&#46;saude&#46;gov&#46;br&#47;dataset&#47;bd-srag-2020</a>&#41;&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">Our study has limitations and must be interpreted accordingly&#46; First&#44; there was not a previously defined criteria for ordering RT-PCR and chest CT and&#44; during the study period&#44; RT-PCR was mostly collected from patients showing signs of moderate or severe disease&#46; Therefore&#44; COVID-19 patients presenting with mild disease and pneumonia could have been discharged with no further imaging and laboratory investigations&#46; Second&#44; it was a single-center experience with thorax-experienced radiologists&#44; and scans readings may be less precise when evaluated by general radiologists&#46; Third&#44; our findings are applicable to patients with acute moderate and severe respiratory symptoms performing chest CT during a COVID-19 epidemic period&#46; Finally&#44; alternative diagnoses for non-COVID-19 patients were not fully evaluated in all patients&#46; However&#44; as discussed above&#44; two of the four patients with &#34;typical&#34; appearance and negative RT-PCR were considered as non-laboratory confirmed COVID-19 by attendant physicians before hospital discharge&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">In conclusion&#44; in patients with suspected COVID-19 pneumonia&#44; chest CT categorical classification of COVID-19 findings is reproducible and demonstrates high agreement with clinical and RT-PCR diagnosis of COVID-19&#46; Our study reinforces the role of tomographic standards to improve accuracy of radiological reports and to help physicians diagnosing COVID-19 pneumonia&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Funding sources</span><p id="par0130" class="elsevierStylePara elsevierViewall">This research did not receive any specific grant from funding agencies in the public&#44; commercial&#44; or not-for-profit sectors&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Disclosures</span><p id="par0135" class="elsevierStylePara elsevierViewall">RDG&#44; VBB&#44; APZ&#44; FTH&#44; LCAJ&#44; JFPS&#44; GSG and MBG&#58; none&#46;</p><p id="par0140" class="elsevierStylePara elsevierViewall">APZ&#42; is a research fellow of the National Council for Scientific and Technological Development &#40;CNPq&#41;&#44; Ministry of Science and Technology&#44; Brazil and has received a research grant from Pfizer not related to this work&#46;</p></span></span>"
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              "titulo" => "Patient population and clinical data"
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              "titulo" => "Chest CT standards accuracy for COVID-19"
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              "titulo" => "Other respiratory pathogens"
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          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1307182"
          "palabras" => array:4 [
            0 => "Coronavirus disease 2019"
            1 => "Viral pneumonia"
            2 => "CT"
            3 => "Diagnosis&#46;"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:1 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">COVID-19 is a new disease and the most common complication is pneumonia&#46; The Radiological Society of North America &#40;RSNA&#41; proposed an expert consensus for imaging classification for COVID-19 pneumonia&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objective</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">To evaluate sensitivity&#44; specificity&#44; accuracy&#44; and reproducibility of chest CT standards in the beginning of the Brazilian COVID-19 outbreak&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Methods</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Cross-sectional study performed from March 1st to April 14th&#44; 2020&#46; Patients with suspected COVID-19 pneumonia submitted to RT-PCR test and chest computed tomography &#40;CT&#41; were included&#46; Two thoracic radiologists blinded for RT-PCR and clinical and laboratory results classified every patient scan according to the RSNA expert consensus&#46; A third thoracic radiologist also evaluated in case of discordance&#44; and consensus was reached among the three radiologists&#46; A typical appearance was considered a positive chest CT for COVID-19 pneumonia&#46; Sensitivity&#44; specificity&#44; positive and negative predictive values were calculated&#46; Cohen&#8217;s kappa coefficient was used to evaluate intra- and inter-rater agreements&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">A total of 159 patients were included &#40;mean age 57&#46;9&#8239;&#177;&#8239;18&#46;0 years&#59; 88 &#91;55&#46;3&#37;&#93; males&#41;&#58; 86 &#40;54&#46;1&#37;&#41; COVID-19 and 73 &#40;45&#46;9&#37;&#41; non-COVID-19 patients&#46; Eighty &#40;50&#46;3&#37;&#41; patients had a positive CT for COVID-19 pneumonia&#46; Sensitivity and specificity of typical appearance were 88&#46;3&#37; &#40;95&#37;CI&#44; 79&#46;9&#8211;93&#46;5&#41; and 94&#46;5&#37; &#40;95&#37;CI&#44; 86&#46;7&#8211;97&#46;8&#41;&#44; respectively&#46; Intra- and inter-rater agreement were assessed &#40;Cohen&#8217;s kappa&#8239;&#61;&#8239;0&#46;924&#44; <span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;0&#46;06&#59; Cohen&#8217;s kappa&#61;0&#46;772&#44; <span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;0&#46;05&#44; respectively&#41;&#46;</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Chest CT categorical classification of COVID-19 findings is reproducible and demonstrates high level of agreement with clinical and RT-PCR diagnosis of COVID-19&#46; In RT-PCR scarcity scenarios or in equivocal cases&#44; it may be useful for attending physicians in the evaluation of suspected COVID-19 pneumonia patients attended at the emergency unit&#46;</p></span>"
        "secciones" => array:5 [
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      0 => array:3 [
        "etiqueta" => "1"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">These authors contributed equally to this work and are co-senior authors&#46;</p>"
        "identificador" => "fn0005"
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      0 => array:1 [
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          0 => array:4 [
            "apendice" => "<p id="par0155" class="elsevierStylePara elsevierViewall">The following are Supplementary data to this article&#58;<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>"
            "etiqueta" => "Appendix A"
            "titulo" => "Supplementary data"
            "identificador" => "sec0085"
          ]
        ]
      ]
    ]
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      0 => array:8 [
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        "etiqueta" => "Fig&#46; 1"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Fow diagram of study participants&#46; Abbreviations&#58; RT-PCR&#44; Reverse Transcriptase Polymerase Chain Reaction&#59; SARS-CoV-2&#44; Severe Acute Respiratory Syndrome Coronavirus 2&#59; COVID-19&#44; coronavirus disease 2019&#59; CT&#44; computed tomography&#46;</p>"
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      1 => array:8 [
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        "etiqueta" => "Fig&#46; 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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        "figura" => array:1 [
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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Positive and negative predictive values of a positive chest computed tomography &#40;CT&#41; according to distinct prevalences of COVID-19&#46; A positive chest CT was defined as a typical appearance&#46; Error bars indicate 95&#37; confidence intervals &#40;CI&#41;&#46;</p> <p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Positive predictive values &#40;&#37;&#41; and 95&#37; CI according to each estimated prevalence &#40;P&#41;&#58; P 10&#37; - 63&#46;6 &#40;40&#46;8-81&#46;9&#41;&#59; P 20&#37; - 80&#46;0 &#40;62&#46;5-90&#46;9&#41;&#59; P 30&#37; - 87&#46;5 &#40;74&#46;0-94&#46;8&#41;&#59; P 40&#37; - 91&#46;8 &#40;81&#46;1-96&#46;9&#41;&#59; P 50&#37; - 94&#46;6 &#40;86&#46;0-98&#46;2&#41;&#59; P 60&#37; - 96&#46;5 &#40;89&#46;5-99&#46;1&#41;&#59; P 70&#37; - 98&#46;0 &#40;92&#46;2-99&#46;6&#41;&#59; P 80&#37; - 98&#46;2 &#40;93&#46;1-99&#46;7&#41;&#59; P 90&#37; - 99&#46;2 &#40;95&#46;0-99&#46;9&#41;&#46;</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Negative predictive values &#40;&#37;&#41; and 95&#37; CI according to each estimated prevalence &#40;P&#41;&#58; P 10&#37; - 98&#46;5 &#40;94&#46;3-99&#46;7&#41;&#59; P 20&#37; - 96&#46;7 &#40;91&#46;4 - 98&#46;9&#41;&#59; P 30&#37; - 94&#46;6 &#40;88&#46;1-97&#46;7&#41;&#59; P 40&#37; - 92&#46;7 &#40;85&#46;2-96&#46;8&#41;&#59; P 50&#37; - 89&#46;3 &#40;80&#46;1-94&#46;6&#41;&#59; P 60&#37; - 84&#46;5 &#40;73&#46;5-91&#46;6&#41;&#59; P 70&#37; - 77&#46;6 &#40;64&#46;4-87&#46;0&#41;&#59; P 80&#37; - 66&#46;6 &#40;50&#46;9-79&#46;5&#41;&#59; P 90&#37; - 46&#46;8 &#40;29&#46;5-64&#46;9&#41;&#46;</p>"
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        "etiqueta" => "Fig&#46; 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
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            "imagen" => "gr3.jpeg"
            "Alto" => 1141
            "Ancho" => 1500
            "Tamanyo" => 257528
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          0 => array:3 [
            "identificador" => "at0015"
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          "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Nonenhanced high-resolution chest CT of different patients with confirmed COVID-19 pneumonia and typical findings&#46; <span class="elsevierStyleBold">A&#44;</span> 74-year-old man presented with 7-day history of fever and cough&#46; Axial CT shows multifocal&#44; peripheral and rounded ground glass opacities &#40;GGO&#41;&#46; <span class="elsevierStyleBold">B&#44;</span> 47-year-old man presented with 10-day history of moderate breathlessness and fever&#46; Axial CT shows reversed halo sign&#46; <span class="elsevierStyleBold">C&#44;</span> 70-year-old woman presented with 9-day history of mild dyspnea and COVID-19 exposure&#46; Axial CT shows GGO with a perilobular pattern&#46; <span class="elsevierStyleBold">D&#44;</span> 36-year-old man presented with 5-day history of fever&#44; cough and myalgia&#46; Axial CT shows bilateral areas of crazy-paving pattern&#46;</p>"
        ]
      ]
      3 => array:8 [
        "identificador" => "fig0020"
        "etiqueta" => "Fig&#46; 4"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr4.jpeg"
            "Alto" => 1142
            "Ancho" => 1500
            "Tamanyo" => 244476
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        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0020"
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          "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Nonenhanced high-resolution chest CT of different patients with atypical findings&#46; <span class="elsevierStyleBold">A&#44;</span> 52-year-old man presented with 3-day history of fever&#44; cough and adynamia&#46; Axial chest CT shows centrilobular nodules&#44; tree-in-bud opacities and bronchial mucocele&#46; The patient was diagnosed with pulmonary tuberculosis&#46; <span class="elsevierStyleBold">B&#44;</span> 26-year-old woman presented with 10-day history of cough&#44; sputum&#44; fever and dyspnea&#46; Axial chest CT shows lobar consolidation&#46; The patient was diagnosed with bacterial acquired community pneumonia&#46; <span class="elsevierStyleBold">C&#44;</span> 47-year-old woman presented with 30-day history of headache&#44; adynamia&#44; cough and chest pain&#46; Axial chest CT shows pulmonary cavitation with satellite centrilobular opacities&#46; The patient was diagnosed with central nervous system and pulmonary cryptococcosis&#46; <span class="elsevierStyleBold">D&#44;</span> 55-year-old man presented with 3-day history of orthopnea&#44; precordial pain and cough&#46; Axial chest CT shows bilateral pleural effusion&#44; interlobular septal thickening&#44; and centrilobular ground glass opacities&#46; The patient was diagnosed with congestive heart failure due to myocardial infarction&#46;</p>"
        ]
      ]
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        "identificador" => "fig0025"
        "etiqueta" => "Fig&#46; 5"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr5.jpeg"
            "Alto" => 580
            "Ancho" => 1250
            "Tamanyo" => 127596
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        ]
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0025"
            "detalle" => "Fig&#46; "
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          "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Nonenhanced high-resolution chest CT of different patients with indeterminate findings&#46; <span class="elsevierStyleBold">A&#44;</span> 40-year-old man presented with 5-day history of worsening of chronic cough&#44; dyspnea and fever&#46; Axial CT shows diffuse and bilateral ground glass opacities&#46; The patient was diagnosed with acquired immunodeficiency syndrome and <span class="elsevierStyleItalic">Pneumocystis</span> pneumonia&#46; <span class="elsevierStyleBold">B&#44;</span> 55-year-old man presented with 3-day history of cough and mild breathlessness&#46; Axial CT shows unilobar&#44; rounded and peribroncovascular ground glass opacity&#46; COVID-19 pneumonia was confirmed&#46;</p>"
        ]
      ]
      5 => array:8 [
        "identificador" => "fig0030"
        "etiqueta" => "Fig&#46; 6"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr6.jpeg"
            "Alto" => 453
            "Ancho" => 1500
            "Tamanyo" => 116839
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        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0030"
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          "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Nonenhanced high-resolution chest CT of a 79-year-old man presented with 7-day history of dyspnea&#44; adynamia and COVID-19 exposure &#40;wife and job colleague diagnosed with SARS-CoV-2 pneumonia&#41;&#46; A and B&#44; axial&#44; C&#44; sagittal chest CT shows a typical appearance&#44; with bilateral and rounded ground-glass opacities with predominant peripheral distribution&#46; The diagnosis of COVID-19 pneumonia couldn&#39;t be ruled out&#44; even though with two negative RT-PCR&#46; The patient had no alternative diagnosis during hospitalization and he obtained complete resolution mptoms and CT findings in a 6-month follow-up visit&#46;</p>"
        ]
      ]
      6 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
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          "leyenda" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Abbreviations&#58; COVID-19&#44; coronavirus disease 2019&#59; SD&#44; standard deviation&#59; BMI&#44; body mass index&#59; IQR&#44; interquartile range&#46;</p><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Please note&#44; subtitles rows do not have data&#46;</p>"
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            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">COVID-19 Diagnosis</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total patients &#40;n&#8239;&#61;&#8239;159&#41;&#44; No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Yes&#40;n&#8239;&#61;&#8239;86&#41;&#44; No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#40;n&#8239;&#61;&#8239;73&#41;&#44; No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span>-value&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Demographic Information</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Age&#44; mean &#40;SD&#41;&#44; y&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">57&#46;9 &#40;18&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">60&#46;0 &#40;15&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">55&#46;4 &#40;20&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Male&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">88 &#40;55&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">53 &#40;61&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">35 &#40;47&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Comorbidities</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">103 &#40;64&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">58 &#40;67&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">45 &#40;61&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;40&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Cancer&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11 &#40;6&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6 &#40;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#62;&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Hypertension&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">52 &#40;32&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">31 &#40;36&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">21 &#40;28&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;31&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Coronary artery disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;3&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Congestive heart failure&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;1&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;4&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Diabetes&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">20 &#40;12&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13 &#40;15&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;9&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;38&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Hematologic disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;1&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;1&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;1&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#62;&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Immunosuppression&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;3&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Liver disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;1&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;2&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Obesity &#40;BMI&#8239;&#8805;&#8239;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">97 &#40;61&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">56 &#40;65&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">41 &#40;56&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pulmonary disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">33 &#40;20&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14 &#40;16&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;26&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;21&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Smoker&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;4&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;2&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;33&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Signs and symptoms</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Anosmia&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9 &#40;5&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9 &#40;10&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Chest pain&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;11&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;5&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14 &#40;19&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;02&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Cough&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">114 &#40;71&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">67 &#40;77&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">47 &#40;64&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;06&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Diarrhea&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;0&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;1&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Dyspnea&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">86 &#40;54&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">49 &#40;57&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">37 &#40;50&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;42&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Fatigue&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82 &#40;51&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">29 &#40;57&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">33 &#40;45&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Headache&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">41 &#40;25&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;22&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">22 &#40;30&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;35&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Myalgia&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">55 &#40;34&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">35 &#40;40&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">20 &#40;27&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;09&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Rhinorrhea&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">36 &#40;22&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18 &#40;20&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18 &#40;24&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;74&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Temperature &#8805; 37&#46;8&#8239;&#176;C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">35 &#40;22&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">23 &#40;26&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12 &#40;16&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Oxygen saturation &#8804;93&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">31 &#40;19&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">23 &#40;26&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;11&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;006&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Initial laboratory measures</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Leukocytes&#44; median &#40;IQR&#41;&#44; &#47;mm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6820 &#40;4915&#8722;9540&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5930 &#40;4460&#8722;7510&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9230 &#40;6760&#8722;11480&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Lymphocyte&#44; median &#40;IQR&#41;&#44; &#47;mm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1290 &#40;880&#8722;1785&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1165 &#40;850&#8722;1510&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1610 &#40;970&#8722;2150&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;005&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Platelets&#44; median &#40;IQR&#41;&#44; &#47;mm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">188&#46;000 &#40;253&#46;000&#8722;144&#46;500&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">166&#46;000 &#40;130&#46;000&#8722;204&#46;000&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">218&#46;000 &#40;179&#46;000&#8722;273&#46;000&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">C-reactive protein&#44; median &#40;IQR&#41;&#44; mg&#47;dL&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;75 &#40;1&#46;10&#8722;7&#46;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;00 &#40;1&#46;80&#8722;7&#46;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;50 &#40;0&#46;60&#8722;7&#46;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;22&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Creatinine&#44; mg&#47;dL&#44; median &#40;IQR&#41;&#44; mg&#47;dL&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t">0&#46;90 &#40;0&#46;70&#8722;1&#46;05&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">&#46;86&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">512&#46;0 &#40;349&#46;0&#8722;795&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">512&#46;0 &#40;286&#46;5&#8722;773&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">479&#46;0 &#40;336&#46;0&#8722;1256&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="\n
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                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">COVID-19 Diagnosis</th><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"></th></tr><tr title="table-row"><th class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">CT findings&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Patients &#40;n&#8239;&#61;&#8239;159&#41; No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Yes &#40;n&#8239;&#61;&#8239;86&#41;No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No &#40;n&#8239;&#61;&#8239;73&#41;No&#46; &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span>-value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sensitivity &#37;&#40;95&#37; CI&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Specificity &#37;&#40;95&#37; CI&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Multifocal GGO&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">107&#40;67&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82&#40;95&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">25&#40;34&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">95&#46;3&#40;88&#46;5&#8722;98&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">65&#46;7&#40;53&#46;7&#8722;76&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Rounded GGO&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82&#40;51&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">71&#40;82&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11&#40;15&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82&#46;5&#40;72&#46;8&#8722;89&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">84&#46;9&#40;74&#46;6&#8722;92&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">GGO&#8239;&#43;&#8239;consolidation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">72&#40;45&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">47&#40;54&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">25&#40;34&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">54&#46;6&#40;43&#46;5&#8722;65&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">65&#46;7&#40;53&#46;7&#8722;76&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Crazy-paving pattern&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">75&#40;47&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">60&#40;69&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">15&#40;20&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">69&#46;7&#40;58&#46;9&#8722;79&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">79&#46;4&#40;68&#46;3&#8722;88&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Perilobular pattern<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">58&#40;36&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">56&#40;65&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#40;2&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">65&#46;1&#40;54&#46;0&#8722;75&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">97&#46;2&#40;90&#46;4&#8722;99&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Reversed halo sign<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">28&#40;17&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">27&#40;31&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#40;1&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">31&#46;4&#40;21&#46;8&#8722;42&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">98&#46;6&#40;92&#46;6&#8722;99&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t">87&#46;6&#40;77&#46;8&#8722;94&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">42&#46;9&#40;27&#46;7&#8722;59&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Lower predominance&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#46;11&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">51&#46;8&#40;40&#46;4&#8722;63&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">43&#46;5&#40;27&#46;8&#8722;60&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Peripheral &#40;any finding&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#60;&#46;001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">52&#46;7&#40;35&#46;4&#8722;69&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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        "texto" => "<p id="par0145" class="elsevierStylePara elsevierViewall">We would like to thank research consultants Aline da Cunha and C&#225;ssia Pagano&#44; and the statistician Charles Ferreira from &#8220;N&#250;cleo de Apoio &#224; Pesquisa do Hospital Moinhos de Vento&#8221;&#46;</p>"
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