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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Coronavirus disease 2019 &#40;COVID-19&#41; is an ongoing pandemic that has already affected millions of people worldwide and is associated with significant morbidity and mortality&#46; It is caused by severe acute respiratory syndrome coronavirus 2 &#40;SARS-CoV-2&#41; infection and first occurred in Wuhan in December 2019&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">1</span></a> On January 30&#44; 2020&#44; the World Health Organization &#40;WHO&#41; declared COVID-19 a Public Health Emergency of International Concern and on March 11 declared it a pandemic&#46; As of May 6&#44; a total of 3 588 773 people in 208 countries were reported to have COVID-19&#44; leading to more than 247 500 deaths&#46; Early reports from China and Italy indicate that SARS-CoV-2 causes illness of varying degrees of severity&#46;<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">2&#44;3</span></a> It has a wide clinical spectrum&#44; including asymptomatic infection&#44; mild respiratory disease&#44; severe pneumonia with acute respiratory failure and even death&#46; An excessive inflammatory response to SARS-CoV-2 is thought to be one of the major causes of disease severity and death in patients with COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">4</span></a> Evidence suggests that cytokine release syndrome &#40;CRS&#41; can play a major role in severe COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">5</span></a> Inflammatory cytokines and chemokines including interleukin-6 &#40;IL-6&#41;&#44; interleukin-1 beta &#40;IL-1&#946;&#41;&#44; induced protein 10 and monocyte chemoattractant protein-1 &#40;MCP-1&#41; are significantly elevated in COVID-19 patients&#44; and some were more commonly seen in severe than in nonsevere patients&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Epicardial adipose tissue &#40;EAT&#41; is a fat storage tissue located beneath the pericardium&#44; representing approximately 15&#37; of the cardiac weight&#46;<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">6&#44;7</span></a> It is a visceral fat that secretes inflammatory cytokines and mediators like MCP-1&#44; IL-6&#44; and tumor necrosis factor alpha &#40;TNF-&#945;&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">8</span></a> It can be measured with different imaging techniques&#58; transthoracic echocardiography&#44; multislice computed tomography &#40;MSCT&#41; and magnetic resonance imaging&#46;<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">9&#44;10</span></a> Computed tomography &#40;CT&#41; is a reliable and reproducible method for quantification of epicardial fat volume &#40;EFV&#41; independent of cardiac cycle phase&#46;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">11&#44;12</span></a> Chest CT is a cornerstone in the assessment of patients diagnosed with COVID-19&#46; Among recent developments in non-invasive imaging methods&#44; non-gated chest CT was shown to correlate with values measured by coronary CT angiography&#46;<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">2&#44;13</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">C-reactive protein &#40;CRP&#41;&#44; procalcitonin &#40;PCT&#41;&#44; ferritin and IL-6 are known inflammatory biomarkers and their levels have previously been reported to correlate with disease severity in COVID-19 patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">14&#44;15</span></a> However&#44; there are no data about the association between EFV and disease severity&#44; nor on the correlation with these inflammatory biomarkers&#46; Recently&#44; Zhao emphasized the role of epicardial fat in overweight patients&#44; who have worse prognosis during COVID-19 infection&#46;<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">16</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Early diagnosis of serious illness is critical to early classification and improvement of patients&#8217; prognosis&#46; Additionally&#44; the early identification of patients who will become severely ill could facilitate the allocation of limited medical resources to patients in need of aggressive treatment&#46; Therefore&#44; further research is urgently needed on early diagnosis and prognosis&#46; In this paper&#44; we aimed to assess the association between EFV &#40;measured by a 128-slice MSCT scanner&#41;&#44; inflammatory biomarkers and prognosis of COVID-19 patients&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Study design and participants</span><p id="par0025" class="elsevierStylePara elsevierViewall">In this retrospective&#44; single-center study&#44; a total of 101 consecutive patients were enrolled who were diagnosed with COVID-19&#46; The hospital in which the study was conducted is a designated&#44; large-volume hospital capable of receiving severe COVID-19 patients&#46; The diagnosis of COVID-19 was made according to WHO interim guidance and confirmed by RNA detection of SARS-CoV-2 in an on-site clinical laboratory&#46;<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">17</span></a> In accordance with the report of the WHO-China Joint Mission on COVID-19&#44;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">18</span></a> patients with COVID-19 were divided into mild &#40;laboratory confirmed&#44; without pneumonia&#41;&#44; moderate &#40;laboratory confirmed and with pneumonia&#41;&#44; severe &#40;dyspnea&#44; respiratory frequency &#8805;30&#47;min&#44; blood oxygen saturation &#8804;93&#37;&#44; PaO<span class="elsevierStyleInf">2</span>&#47;FiO<span class="elsevierStyleInf">2</span> ratio &#60;300&#44; and&#47;or lung infiltrates &#62;50&#37; of the lung field within 24-48 h&#41; and critical &#40;respiratory failure requiring mechanical ventilation&#44; shock or other organ failure that requires intensive care&#41;&#46; Severe and critical patients were admitted to the intensive care unit &#40;ICU&#41;&#44; whereas patients in the mild to moderate group were admitted to the ward&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">18</span></a> A combination of hydroxychloroquine &#40;HCQ&#41;&#44; azitromycin and favipiravir was used for the treatment of severe COVID-19 cases&#44; whereas only HCQ was used for mild to moderate cases&#46; The study was approved by the hospital&#39;s ethics committee&#44; which waived the requirement for written informed consent&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Data collection and analysis</span><p id="par0030" class="elsevierStylePara elsevierViewall">A doctor and a nurse were responsible for data entry into a computerized database and tracked these data daily&#46; The data were also reviewed by a team of physicians who treat patients with COVID-19&#46; Demographic characteristics &#40;gender and age&#41;&#44; comorbidities &#40;chronic obstructive pulmonary disease &#91;COPD&#93;&#44; hypertension&#44; diabetes&#44; coronary artery disease &#91;CAD&#93;&#44; cerebrovascular disease and chronic kidney disease&#41;&#44; clinical manifestations&#44; laboratory findings&#44; treatment and outcomes &#40;discharge&#47;death&#41; were extracted from electronic medical records using a standardized data collection form&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Routine blood examinations included complete blood count &#40;CBC&#41;&#44; coagulation profile&#44; serum biochemical tests &#40;including renal and liver function&#44; creatine kinase&#44; lactate dehydrogenase and electrolytes&#41;&#44; myocardial enzymes&#44; CRP&#44; PCT&#44; serum ferritin&#44; IL-6&#44; D-dimer and arterial blood gases &#40;lactate and PaO<span class="elsevierStyleInf">2</span>&#47;FiO<span class="elsevierStyleInf">2</span> ratio&#41; were collected at admission&#46; Peripheral venous blood samples were obtained from a large antecubital vein on admission&#46; Total CBC &#40;Sysmex K-1000&#44; Sysmex Corporation&#44; Kobe&#44; Japan&#41; and blood chemistry parameters &#40;Roche Diagnostics&#44; Tokyo&#44; Japan&#41; were determined at the hospital&#39;s biochemistry laboratory&#46; Blood samples were placed in standardized EDTA-containing tubes for total CBC tests and measurements were performed immediately after blood sampling&#46; Serum CRP levels were measured by immune nephelometry &#40;NFL BN-II&#59; Siemens Dade Behring&#41;&#46; PCT was determined using a Biom&#233;rieux Mini VIDAS automatic fluorescence immunoanalyzer&#46; Serum ferritin levels were detected by electrochemiluminescence &#40;Cobas E601&#44; Roche&#41;&#44; as was IL-6&#44; using the corresponding reagent&#46; D-dimer was quantitatively determined using a Sysmax CS-5100 coagulation analyzer&#46; Chest radiographs and CT scans were also performed for all inpatients&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Data on all treatment measures&#44; including antibiotic&#44; antivirus&#44; glucocorticoid and intravenous immunoglobulin therapy and respiratory support&#44; were acquired during hospitalization&#46; Throat swab samples were collected from all suspected patients at admission and laboratory confirmation of SARS-CoV-2 was performed using real-time reverse transcription polymerase chain reaction according to the manufacturer&#39;s protocol &#40;Beijing Genomics Institute and GeneoDx Biotechnology Co&#46; Ltd&#46;&#41;&#46; Repeated tests for SARS-CoV-2 were performed in confirmed patients to verify viral clearance before hospital discharge&#46; The criteria for discharge were absence of fever for at least three days&#44; clinical improvement of respiratory symptoms and two throat swab samples negative for SARS-CoV-2 RNA obtained at least 24 h apart&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Analysis of epicardial fat volume by computed tomography</span><p id="par0045" class="elsevierStylePara elsevierViewall">For patients referred to the hospital with suspected COVID-19&#44; MSCT examination was carried out at the time of admission&#46; All imaging was performed using a 128-slice scanner &#40;GE Revolution Evo&#44; USA&#41; in supine position during end-inspiration&#46; A low-dose CT protocol was applied with the following scanning parameters&#58; gantry rotation time 0&#46;4 s&#44; pitch 0&#46;98&#44; table speed 39&#46;3 mm&#47;rotation&#44; 20 mA&#44; 120 kVp&#44; and a 300&#215;300 matrix&#46; CARE Dose 4D and CARE kV scanning parameters were off&#46; A 1&#46;25 mm slice thickness and 1&#46;2 mm reconstruction interval were used for sagittal and coronal image reconstruction&#46; After each CT&#44; passive air ventilation was performed for at least 30 min and machine surfaces were disinfected with ethanol and didecyldimethylammonium chloride&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">DICOM data were transferred to a picture archiving and communicating system&#46; Then&#44; two expert radiologists independently interpreted the images and a final decision was reached by consensus&#46; Both radiologists were blinded to laboratory data&#44; clinical features&#44; and patients&#8217; diagnosis&#46; In the event of disagreement&#44; the opinion of a third radiologist was used&#46; All CT images were viewed in axial&#44; sagittal and coronal planes&#46; EFV was measured with a quantitative semi-automated procedure using the postprocessing software Advantage Workstation 4&#46;7 &#40;GE Healthcare Revolution&#44; USA&#41;&#46; Epicardial boundaries were manually traced to segment fat in the epicardium on axial images obtained from the pulmonary artery bifurcation to the lowest slice with a detectable pericardium &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>&#41;&#46; A CT attenuation threshold between -200 and -30 Hounsfield units was used to isolate epicardial fat&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">All analyses were carried out using IBM SPSS Statistics for Macintosh&#44; version 24&#46;0 &#40;IBM Corp&#46;&#44; Armonk&#44; New York&#44; USA&#41;&#46; The one-sample Kolmogorov-Smirnov test was used to assess the distribution of numerical variables&#46; Categorical data were presented as counts &#40;percentages&#41;&#44; while continuous data were presented as mean &#177; standard deviation and median &#40;interquartile range&#41;&#46; The Student&#39;s t test was applied to numerical data that conformed to a normal distribution&#44; and the Mann-Whitney U test was applied for skewed distributed variables&#46; The chi-square test was used for categorical variables&#46; For correlation analyses regarding EFV&#44; Pearson&#39;s and Spearman&#39;s correlation analysis was used for data with normal and skewed distribution&#44; respectively&#46; Receiver operating characteristic &#40;ROC&#41; curve analysis was conducted to determine the cut-off values for the sensitivity and specificity of EFV in predicting ICU admission&#46; Independent predictors of clinically severe COVID-19 were determined using logistic regression analysis&#46; Variables that might be confounding factors or established risk factors for ICU admission in patients with COVID-19 such as diabetes&#44; HT&#44; CAD&#44; COPD and EFV were included in logistic regression analyses&#46; The effect of each variable on ICU admission was measured in univariate and multivariate analyses&#46; A two-tailed p value of &#60;0&#46;05 was defined as statistically significant&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Baseline characteristics</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of 101 patients infected with SARS-CoV-2 were retrospectively enrolled in our study&#46; The primary composite endpoint &#40;admission to the ICU or death&#41; was reached in 26 &#40;25&#46;1&#37;&#41; patients&#46; Patients&#8217; demographic and baseline clinical features are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; According to these features&#44; participants were divided into two groups&#58; those admitted to the ICU and those admitted to the ward&#46; Patients in the ICU were significantly older &#40;64&#46;8&#177;14&#46;8 vs&#46; 50&#46;6&#177;15&#46;8 years&#44; p&#60;0&#46;001&#41; and had more comorbidities &#8211; hypertension &#40;46&#37; vs&#46; 20&#37;&#44; p&#61;0&#46;009&#41;&#44; CAD &#40;23&#37; vs&#46; 5&#37;&#44; p&#61;0&#46;009&#41; and COPD &#40;19&#37; vs&#46; 3&#37;&#44; p&#61;0&#46;004&#41; &#8211; than those admitted to the ward&#46; Other characteristics including gender&#44; body mass index&#44; smoking and diabetes showed no significant differences between the two groups&#46; A total of 10 &#40;38&#37;&#41; deaths occurred among the ICU patients&#46; The mean age of patients who died was 71&#46;9&#177;14&#46;3 years &#40;range 44-90 years&#41; and most were male &#40;n&#61;6&#41;&#46; However&#44; death was not observed among the 75 patients admitted to the ward&#46; In the ICU&#44; noninvasive ventilation was used in 15 patients &#40;57&#37;&#41; and 11 patients &#40;42&#37;&#41; were intubated&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Laboratory findings</span><p id="par0065" class="elsevierStylePara elsevierViewall">At admission&#44; patients admitted to the ICU had significantly lower levels of total protein and albumin&#44; hematocrit and lymphocyte count&#44; but higher glucose&#44; urea&#44; aspartate aminotransferase&#44; troponin I&#44; D-dimer levels and white blood cell and neutrophil count compared with those admitted to the ward &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; When inflammatory biomarkers were analyzed&#44; CRP &#40;133 vs&#46; 12&#46;4 g&#47;l&#44; p&#60;0&#46;001&#41;&#44; IL-6 &#40;45&#46;4 vs&#46; 8&#46;8 pg&#47;ml&#44; p&#60;0&#46;001&#41;&#44; PCT &#40;0&#46;14 vs&#46; 0&#46;05 &#956;g&#47;l&#44; p&#61;0&#46;001&#41; and ferritin &#40;432 vs&#46; 172 &#956;g&#47;l&#44; p&#60;0&#46;001&#41; levels were also significantly higher in patients admitted to the ICU than those in the ward&#46; Moreover&#44; patients admitted to the ICU had significantly larger EFV &#40;115&#46;1&#177;44&#46;0 vs&#46; 94&#46;3&#177;45&#46;5 cm<span class="elsevierStyleSup">3</span>&#44; p&#61;0&#46;037&#41; than those admitted to the ward &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Figure 2</a>&#41;&#46; <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the correlation between EFV and inflammatory biomarkers including CRP&#44; PCT&#44; ferritin and IL-6 in all COVID-19 patients&#46; A statistically significant positive correlation was detected between EFV and CRP &#40;r&#58; 0&#46;494&#44; p&#60;0&#46;001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Figure 3</a>&#41;&#44; IL-6 &#40;r&#58; 0&#46;311&#44; p&#61;0&#46;005&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Figure 4</a>&#41;&#44; PCT &#40;r&#58; 0&#46;287&#44; p&#61;0&#46;05&#41; and ferritin &#40;r&#58; 0&#46;265&#44; p&#61;0&#46;010&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Receiver operating characteristic analysis of epicardial fat volume and inflammatory biomarkers on admission</span><p id="par0070" class="elsevierStylePara elsevierViewall">ROC analysis was performed to assess clinical and laboratory biomarkers at the first visit for prediction of COVID-19 severity&#46; This demonstrated that the area under the curve &#40;AUC&#41; of CRP&#44; IL-6&#44; PCT&#44; ferritin and EFV for predicting severe COVID-19 was 0&#46;90 &#40;95&#37; confidence interval &#91;CI&#93;&#58; 0&#46;84-0&#46;96&#41;&#44; 0&#46;73 &#40;95&#37; CI&#58; 0&#46;60-0&#46;87&#41;&#44; 0&#46;74 &#40;95&#37; CI&#58; 0&#46;63-0&#46;85&#41;&#44; 0&#46;85 &#40;95&#37; CI&#58; 0&#46;74-0&#46;96&#41; and 0&#46;86 &#40;95&#37; CI&#58; 0&#46;74-0&#46;96&#41;&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; ROC analysis also demonstrated that at a cut-off of 46 mg&#47;l&#44; the sensitivity&#44; specificity&#44; positive predictive value &#40;PPV&#41; and negative predictive value &#40;NPV&#41; of CRP was 82&#37;&#44; 81&#37;&#44; 57&#37;&#44; and 93&#37;&#44; respectively&#59; at a cut-off of 25 pg&#47;ml&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of IL-6 were 83&#37;&#44; 80&#37;&#44; 55&#37;&#44; and 94&#37;&#44; respectively&#59; and at a cut-off of 0&#46;07 &#956;g&#47;l&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of PCT were 73&#37;&#44; 67&#37;&#44; 41&#37;&#44; and 89&#37;&#44; respectively&#46; Moreover&#44; at a cut-off of 202 &#956;g&#47;l&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of ferritin were 80&#37;&#44; 60&#37;&#44; 42&#37;&#44; and 89&#37; respectively&#46; Lastly&#44; at a cut-off of 102 cm<span class="elsevierStyleSup">3</span>&#44; the sensitivity&#44; specificity&#44; PPV and NPV of EFV were 82&#37;&#44; 80&#37;&#44; 58&#37;&#44; and 94&#37; respectively&#46; ROC analysis also showed that the AUC of CRP and EFV to predict disease severity was higher than that of other inflammatory biomarkers&#44; which demonstrated the excellent predictive power of these parameters for severity of COVID-19&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Univariate regression analysis was performed in order to assess the relationship between clinical characteristics and ICU admission &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#44; which showed that age &#40;odds ratio &#91;OR&#93;&#58; 1&#46;07&#44; 95&#37; CI&#58; 1&#46;03-1&#46;11&#44; p&#60;0&#46;001&#41;&#44; hypertension &#40;OR&#58; 2&#46;90&#44; 95&#37; CI&#58; 1&#46;13-7&#46;42&#44; p&#61;0&#46;026&#41; and EFV &#40;OR&#58; 1&#46;03&#44; 95&#37; CI&#58; 1&#46;01-1&#46;04&#44; p&#60;0&#46;001&#41; were associated with ICU admission&#46; Multivariate regression analysis was then performed to detect independent predictors of admission to the ICU&#46; Both age and EFV independently predicted ICU admission at a significant level &#40;OR&#58; 1&#46;05&#44; 95&#37; CI&#58; 1&#46;01-1&#46;10&#44; p&#61;0&#46;013 and OR&#58; 1&#46;02&#44; 95&#37; CI&#58; 1&#46;01-1&#46;03&#44; p&#61;0&#46;025&#44; respectively&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">To date&#44; the global COVID-19 pandemic has imposed severe burdens on medical systems&#46; It is critical to identify COVID-19 patients who may become severely ill at the first hospital admission in order to facilitate control of the disease and to improve patients&#8217; prognosis in a context of limited medical resources&#46; To our knowledge this is the first study to report an association between EFV and clinical severity of COVID-19&#46; This retrospective cohort study identified several predictors of poor prognosis in adults hospitalized with COVID-19&#46; In particular&#44; older age&#44; presence of comorbid diseases and elevated levels of inflammatory biomarkers including CRP&#44; PCT&#44; ferritin and IL-6 on admission were more commonly seen in severe COVID-19 illness&#46; Furthermore&#44; EFV as measured by MSCT was also demonstrated to be related to the clinical severity of these patients and was also positively correlated with the above-mentioned inflammatory biomarkers&#46; Moreover&#44; in multivariate logistic regression analysis both age and EFV independently predicted admission to the ICU&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">EAT is a visceral fat deposit and as such has the capacity to secrete a number of cytokines and chemokines&#44; together known as adipokines&#46; These are biologically active molecules that are secreted by mature adipocytes themselves as well as stromal preadipocytes&#44; macrophages&#44; fibroblasts&#44; mast cells and lymphocytes that are located within the adipose tissue&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">19</span></a> IL-6&#44; -8&#44; -10 and IL-1&#946;&#44; TNF-&#945;&#44; MCP-1&#44; adiponectin&#44; leptin and plasminogen activator inhibitor 1 are all examples of adipokines&#46;<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">20</span></a> In normal quantities&#44; EAT has various putative physiological functions&#46; However&#44; many changes occur as EAT volumes increase&#46; These changes are often characterized by hypertrophy&#44; failure to store triglycerides&#44; increased lipolysis and inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">21</span></a> As EAT expands&#44; it becomes hypoxic and dysfunctional and is invaded by increasing numbers of macrophages and T lymphocytes&#44; resulting in a shift in its metabolic profile&#46;<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">22</span></a> The result is increased secretion of proinflammatory cytokines such as IL-6&#44; TNF-&#945;&#44; MCP-1 and many others that contribute to the inflammatory environment&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">8</span></a> In this setting&#44; the beneficial paracrine effects of EAT are lost&#46; Shimabukuro et al&#46; showed that EFV was positively correlated with the expression of inflammatory cytokines in EAT&#44; but was negatively correlated with adiponectin expression&#46;<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">23</span></a> Malavazos et al&#46; studied the association between EAT thickness and plasma cytokine levels in severe patients with obesity&#46; They reported that EAT thickness was positively correlated with cytokine levels &#40;i&#46;e&#46; MCP-1 and the serum IL-6&#47;IL-6 complex&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">24</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">The inflammatory response plays a critical role in COVID-19&#44; and inflammatory cytokine storm increases the severity of COVID-19&#46;<a class="elsevierStyleCrossRefs" href="#bib0350"><span class="elsevierStyleSup">25&#44;26</span></a> Wang et al&#46; found that the inflammatory response is crucial to the progression of COVID-19 and cytokine storm can lead to severe complications and death&#46;<a class="elsevierStyleCrossRef" href="#bib0360"><span class="elsevierStyleSup">27</span></a> The fifth edition of the Chinese Diagnosis and Treatment Protocols for COVID-19 recommends monitoring cytokine levels to improve treatment efficacy and reduce mortality&#44;<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">28</span></a> while the seventh edition of this guideline points out that peripheral blood inflammatory factors such as IL-6 may increase during COVID-19 infection&#46;<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">29</span></a></p><p id="par0095" class="elsevierStylePara elsevierViewall">Cytokine releasing syndrome &#40;CRS&#41; occurs in most patients with severe COVID-19 and is known to be an important cause of death&#46; It is a systemic inflammatory response that can be caused by infectious diseases&#44; certain drugs and other factors&#44; and is characterized by a sharp increase in the level of several proinflammatory cytokines&#46;<a class="elsevierStyleCrossRefs" href="#bib0375"><span class="elsevierStyleSup">30&#8211;32</span></a> SARS-CoV-2 binds to alveolar epithelial cells&#44; activates the innate and adaptive immune systems and thus leads to the release of large quantities of cytokines&#44; including IL-6&#44; which is the key molecule involved in CRS&#46; IL-6 is an important member of the cytokine network and plays a central role in acute inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0390"><span class="elsevierStyleSup">33</span></a> It has both anti-inflammatory and proinflammatory effects&#46; Liu et al&#46; showed an increase in inflammatory cytokines &#40;IL-6&#44; IL-10&#44; IL-2 and interferon gamma&#41; in the peripheral blood in severe COVID-19 cases&#46;<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">34</span></a> Zhang et al&#46; also found a relationship between higher IL-6 and CRP levels and disease progression in hospitalized COVID-19 patients&#46;<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">35</span></a> The present study likewise showed increased IL-6 levels in severe COVID-19 patients&#46; In addition to this finding&#44; a statistically significant positive correlation was detected between EFV and IL-6 level in this study&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Besides direct attack from the virus&#44; progressive inflammatory injury has been suggested as a possible mechanism in COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">1</span></a> CRP is a downstream acute phase protein in the innate immune response&#46;<a class="elsevierStyleCrossRef" href="#bib0405"><span class="elsevierStyleSup">36</span></a> It is produced following the increased synthesis of proinflammatory cytokines to activate the immune response&#46;<a class="elsevierStyleCrossRef" href="#bib0410"><span class="elsevierStyleSup">37</span></a> Serum CRP level has therefore often been used as a laboratory marker of inflammation&#46;<a class="elsevierStyleCrossRefs" href="#bib0405"><span class="elsevierStyleSup">36&#44;37</span></a> Zhang et al&#46; reported CRP as a predictor of the progression of COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">35</span></a> Similarly&#44; we found significantly higher CRP levels at admission in severe cases of COVID-19 compared to mild cases&#46; Moreover&#44; we also demonstrated a positive correlation between CRP level and EFV&#46; Eslami et al&#46; investigated the association of CT-measured EAT thickness and density with clinical outcome in 87 patients with COVID-19 and found that mean EAT density was markedly lower in deceased patients compared with survivors&#44; although this significant difference was not observed across the two groups in terms of EAT thickness&#46;<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">38</span></a> In the present study&#44; we measured EFV in COVID-19 patients&#44; rather than EAT thickness and density&#46; Higher EFV was observed in severe patients compared to milder cases&#46; Wei et al&#46; studied EFV as a potential risk factor for myocardial injury in 400 laboratory-confirmed COVID-19 patients and&#44; similarly to our result&#44; found an association between increased EFV on admission chest CT scan and increased myocardial injury and mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0420"><span class="elsevierStyleSup">39</span></a> They therefore suggested that assessment of EFV by chest CT scan on admission may provide a potentially useful threshold for predicting cardiovascular complications of COVID-19&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">PCT is a glycoprotein without hormonal activity that is the precursor of calcitonin&#46;<a class="elsevierStyleCrossRefs" href="#bib0425"><span class="elsevierStyleSup">40&#44;41</span></a> Serum PCT levels are usually low or undetectable<a class="elsevierStyleCrossRef" href="#bib0435"><span class="elsevierStyleSup">42</span></a> but are increased by bacterial infections and relatively low in viral infections&#44; and can therefore be used to distinguish between bacterial and viral infections&#46;<a class="elsevierStyleCrossRef" href="#bib0440"><span class="elsevierStyleSup">43</span></a> Higher PCT levels detected in patients with severe COVID-19 usually suggest the presence of concomitant bacterial infection&#46; Liu et al&#46;<a class="elsevierStyleCrossRef" href="#bib0445"><span class="elsevierStyleSup">44</span></a> recently studied PCT&#44; CRP and IL-6 levels in COVID-19 patients&#44; dividing them into two groups&#58; with severe disease or with mild disease&#46; They found significantly higher PCT&#44; CRP and IL-6 levels in the severe group compared to the mild group&#46; In addition&#44; they identified all of these inflammatory biomarkers as independent factors predicting the severity of COVID-19&#46; Our results also demonstrated higher levels of admission PCT&#44; CRP and IL-6 levels in severe COVID-19 patients&#46; Furthermore&#44; we showed a positive correlation between these inflammatory biomarkers and EFV&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Serum ferritin can be elevated during infection and inflammation&#46; High ferritin levels due to secondary hemophagocytic lymphohistiocytosis and CRS have been reported in severe COVID-19 patients&#46; Velavan et al&#46; recommended the use of serum ferritin&#44; CRP and IL-6 levels in risk stratification of COVID-19 patients to predict severe and fatal COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0450"><span class="elsevierStyleSup">45</span></a> In our study&#44; we also showed significantly elevated ferritin levels in severe COVID-19 cases and a positive correlation of ferritin with EFV&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">There are some limitations in this study&#46; First of all&#44; it is a single-center study with a relatively small sample size&#46; Secondly&#44; it is retrospective in nature&#44; and the results need to be further verified by prospective studies&#46; Thirdly&#44; we aimed to analyze the risk factors that determine prognosis&#44; but the poor prognosis group was small and we were therefore unable to analyze the differences in clinical characteristics of patients in this group&#46; Fourthly&#44; we did not include asymptomatic and mild cases managed at home&#44; and hence our cohort may represent a more severe COVID-19 population&#46; Fifthly&#44; the treatment of these patients was clinically driven and did not follow a unified standard&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conclusion</span><p id="par0120" class="elsevierStylePara elsevierViewall">Epicardial fat volume and serum CRP&#44; IL-6&#44; PCT and ferritin levels show a significant correlation with the severity of COVID-19&#46; In hospitalized patients&#44; clinicians should consider EFV in addition to serum levels of the above inflammatory biomarkers in risk stratification of patients to predict severe and fatal COVID-19&#46; Our findings could help facilitate the early identification of severe COVID-19 patients and thus enable early treatment and intervention&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Funding</span><p id="par0125" 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="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Conflicts of interest</span><p id="par0130" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Epicardial adipose tissue serves as a source of inflammatory cytokines and mediators&#46; Cytokine storm is an important cause of morbidity and mortality in coronavirus disease 2019 &#40;COVID-19&#41;&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objectives</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">To investigate the association between epicardial fat volume &#40;EFV&#41;&#44; inflammatory biomarkers and clinical severity of COVID-19&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">This retrospective study included 101 patients who were infected with COVID-19&#46; Serum inflammatory biomarkers including C-reactive protein &#40;CRP&#41;&#44; interleukin-6 &#40;IL-6&#41;&#44; procalcitonin &#40;PCT&#41; and ferritin levels were measured&#46; Computed tomography images were analyzed and semi-automated measurements for EFV were obtained&#46; The primary composite endpoint was admission to the intensive care unit &#40;ICU&#41; or death&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The primary composite endpoint occurred in 25&#46;1&#37; &#40;n&#61;26&#41; of patients &#40;mean age 64&#46;8&#177;14&#46;8 years&#44; 14 male&#41;&#46; A total of 10 patients died&#46; EFV&#44; CRP&#44; PCT&#44; ferritin and IL-6 levels were significantly higher in ICU patients&#46; Moreover&#44; a positive correlation was determined between EFV and CRP &#40;r&#58; 0&#46;494&#44; p&#60;0&#46;001&#41;&#44; PCT &#40;r&#58; 0&#46;287&#44; p&#61;0&#46;005&#41;&#44; ferritin &#40;r&#58; 0&#46;265&#44; p&#61;0&#46;01&#41; and IL-6 &#40;r&#58; 0&#46;311&#44; p&#61;0&#46;005&#41;&#46; On receiver operating characteristic analysis&#44; patients with EFV &#62;102 cm<span class="elsevierStyleSup">3</span> were more likely to have severe complications&#46; In multivariate logistic regression analysis&#44; EFV independently predicted admission to the ICU at a significant level &#40;OR&#58; 1&#46;02&#44; 95&#37; CI&#58; 1&#46;01-1&#46;03&#44; p&#61;0&#46;025&#41;&#46;</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">EFV and serum CRP&#44; IL-6&#44; PCT and ferritin levels can effectively assess disease severity and predict the outcome in patients with COVID-19&#46; EFV is an independent predictor of admission to the ICU in hospitalized COVID-19 patients&#46;</p></span>"
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        "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introdu&#231;&#227;o</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">O tecido adiposo epic&#225;rdico &#233; fonte de citocinas inflamat&#243;rias e mediadores&#46; A tempestade de citocinas &#233; uma importante causa de morbilidade e mortalidade na doen&#231;a coronav&#237;rus 2019 &#40;COVID-19&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Objetivos</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Investigar a associa&#231;&#227;o entre volume adiposo epic&#225;rdico &#40;VAE&#41;&#44; biomarcadores inflamat&#243;rios e gravidade cl&#237;nica da COVID-19&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">M&#233;todos</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Este estudo retrospetivo incluiu 101 doentes infetados com COVID-19&#46; Foram avaliados biomarcadores inflamat&#243;rios s&#233;ricos&#44; incluindo os n&#237;veis de prote&#237;na C-reativa &#40;PCR&#41;&#44; de interleucina-6 &#40;IL-6&#41;&#44; de procalcitonina &#40;PCT&#41; e de ferritina&#46; Foram analisadas imagens de tomografia computorizada &#40;TC&#41; e foram obtidas medi&#231;&#245;es semi-autom&#225;ticas do VAE&#46; O <span class="elsevierStyleItalic">endpoint</span> prim&#225;rio composto foi a admiss&#227;o na unidade de cuidados intensivos &#40;UCI&#41; ou morte&#46;</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Resultados</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">O <span class="elsevierStyleItalic">endpoint</span> prim&#225;rio ocorreu em 25&#44;1&#37; &#40;n&#61;26&#41; dos doentes &#40;idade m&#233;dia 64&#44;8&#177;14&#44;8 anos&#44; 14 homens&#41;&#46; Um total de 10 doentes morreu&#46; Os n&#237;veis de VAE&#44; PCR&#44; PCT&#44; ferritina e IL-6 foram significativamente superiores nos doentes internados na UCI&#46; Al&#233;m disso&#44; verificou-se uma correla&#231;&#227;o positiva entre o VAE e a PCR &#40;r&#58; 0&#44;494&#44; p&#60;0&#44;001&#41;&#44; PCT &#40;r&#58; 0&#44;287&#44; p&#61;0&#44;005&#41;&#44; ferritina &#40;r&#58; 0&#44;265&#44; p&#61;0&#44;01&#41; e IL-6 &#40;r&#58; 0&#44;311&#44; p&#61;0&#44;005&#41;&#46; Na an&#225;lise de regress&#227;o logistica multivariada&#44; os doentes com VAE&#62;102 cm<span class="elsevierStyleSup">3</span> tinham maior probabilidade de ter complica&#231;&#245;es graves&#46;</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Conclus&#227;o</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">O VAE e os n&#237;veis s&#233;ricos de PCR&#44; IL-6&#44; PCT e ferritina podem avaliar a gravidade da doen&#231;a e prever o resultado em doentes com COVID-19&#46; O VAE constitui um fator preditivo na admiss&#227;o dos doentes hospitalizados com COVID-19 numa UCI&#46;</p></span>"
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          "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">BMI&#58; body mass index&#59; CAD&#58; coronary artery disease&#59; COPD&#58; chronic obstructive pulmonary disease&#59; ICU&#58; intensive care unit&#46;</p>"
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Ward &#40;n&#61;75&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">ICU &#40;n&#61;26&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p&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">Age&#44; years&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">50&#46;6&#177;15&#46;8&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">64&#46;8&#177;14&#46;8&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">&#60;0&#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
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                  \t\t\t\t">Male&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">45 &#40;60&#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
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                  \t\t\t\t">14 &#40;54&#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
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                  \t\t\t\t">0&#46;583&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">BMI&#44; kg&#47;m<span class="elsevierStyleSup">2</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">27&#46;1&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">26&#46;7&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&#46;810&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&#44; n &#40;&#37;&#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">17 &#40;23&#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;27&#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&#46;660&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&#44; n &#40;&#37;&#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;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">12 &#40;46&#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&#46;009&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">CAD&#44; n &#40;&#37;&#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 &#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">6 &#40;23&#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&#46;009&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">COPD&#44; n &#40;&#37;&#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;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;19&#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&#46;004&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">Smoking n &#40;&#37;&#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;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">1 &#40;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">0&#46;472&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">ICU stay&#44; days&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">-&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&#46;5 &#40;5-13&#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">-&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">Discharge time&#44; days&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;9-15&#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">17&#46;5 &#40;12-25&#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;0&#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">Intubated&#44; n &#40;&#37;&#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">11 &#40;42&#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;0&#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">Mortality&#44; n &#40;&#37;&#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">9 &#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">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Parameters are mean &#177; standard deviation or median &#40;interquartile range&#41;&#46;</p><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">ALT&#58; alanine transaminase&#59; AST&#58; aspartate transaminase&#59; CRP&#58; C-reactive protein&#59; EFV&#58; epicardial fat volume&#59; IL-6&#58; interleukin-6&#59; LMR&#58; lymphocyte to monocyte ratio&#59; NLR&#58; neutrophil to lymphocyte ratio&#59; WBC&#58; white blood cells&#46;</p>"
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                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" style="border-bottom: 2px solid black">Variable&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" style="border-bottom: 2px solid black">Ward &#40;n&#61;75&#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="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">ICU &#40;n&#61;26&#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="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p&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">Glucose&#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">110&#177;32&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">129&#177;39&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&#46;035&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">Urea&#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">30 &#40;24-37&#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;30-54&#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&#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">Creatinine&#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">0&#46;88 &#40;0&#46;75-1&#46;04&#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&#46;01 &#40;0&#46;82-1&#46;15&#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&#46;101&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">AST&#44; U&#47;l&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;16-34&#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">42&#40;23-67&#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;0&#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">ALT&#44; U&#47;l&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;19-38&#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">28 &#40;20-52&#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&#46;273&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">Total protein&#44; g&#47;l&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&#46;0 &#40;6&#46;5-7&#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">6&#46;3 &#40;5&#46;8-6&#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">&#60;0&#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">Albumin&#44; g&#47;l&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;3&#177;0&#46;4&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;9&#177;0&#46;5&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;0&#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">Troponin I&#44; ng&#47;l&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;0 &#40;0-6&#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">10&#46;0 &#40;6&#46;0-22&#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;0&#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">D-dimer&#44; mg&#47;l&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&#46;50 &#40;0&#46;29-0&#46;82&#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&#46;01 &#40;0&#46;53-2&#46;68&#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;0&#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">WBC&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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&#46;31&#40;4&#46;48-6&#46;19&#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&#46;01 &#40;5&#46;29-9&#46;34&#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&#46;002&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">Neutrophils&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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;16 &#40;2&#46;65-4&#46;26&#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;87 &#40;4&#46;06-8&#46;13&#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;0&#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
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">0&#46;085&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NLR&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&#46;52 &#40;1&#46;77-3&#46;68&#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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;17 &#40;4&#46;27-15&#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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#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">CRP&#44; g&#47;l&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&#46;4 &#40;3&#46;1-37&#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
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                  \t\t\t\t">133 &#40;59&#46;8-189&#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
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                  \t\t\t\t">&#60;0&#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">IL-6&#44; pg&#47;ml&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">8&#46;8 &#40;4&#46;0-24&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">45&#46;4 &#40;27&#46;2-89&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Procalcitonin&#44; &#956;g&#47;l&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Ferritin&#44; &#956;g&#47;l&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">EFV&#44; cm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col">Covariates&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Il-6&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">PCT&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">Ferritin&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">0&#46;010&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">NLR&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#46;070&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">AUC &#40;95&#37; CI&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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">Sensitivity&#44; &#37;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \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">NLR&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">CRP&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&#46;0&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&#46;904 &#40;0&#46;843-0&#46;965&#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&#46;6&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \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\ttop\n
                  \t\t\t\t">93&#46;7&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">IL-6&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;857 &#40;0&#46;745-0&#46;969&#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">83&#46;3&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">55&#46;5&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">4&#46;22&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;21&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">PCT&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#46;075&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;739 &#40;0&#46;606-0&#46;872&#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">73&#46;9&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">67&#46;1&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\ttop\n
                  \t\t\t\t">41&#46;4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">89&#46;09&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">2&#46;24&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">0&#46;39&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 ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Ferritin&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;740 &#40;0&#46;630-0&#46;851&#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">80&#46;0&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</td><td class="td" title="\n
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                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  """
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          "leyenda" => "<p id="spar0125" class="elsevierStyleSimplePara elsevierViewall">Multivariate logistic regression model&#39;s Nagelkerke R square&#61;0&#46;338&#59; -2 log likelihood&#61;92&#46;2&#59; p&#60;0&#46;001&#46;</p><p id="spar0130" class="elsevierStyleSimplePara elsevierViewall">Hosmer-Lemeshow test&#39;s chi-square value&#61;9&#46;1&#59; p&#61;0&#46;331&#46;</p><p id="spar0135" class="elsevierStyleSimplePara elsevierViewall">CAD&#58; coronary artery disease&#59; CI&#58; confidence interval&#59; COPD&#58; chronic obstructive pulmonary disease&#59; EFV&#58; epicardial fat volume&#59; OR&#58; odds ratio&#46;</p>"
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Original Article
The predictive value of epicardial fat volume for clinical severity of COVID-19
Valor preditivo do volume de gordura epicárdica em relação à gravidade clínica da COVID-19
Mehmet Akif Erdöla,
Autor para correspondência
akiferdol@gmail.com

Corresponding author.
, Fatma Civelek Eserb, Abdullah Nabi Aslana, Mehmet Erdoğana, Adalet Altunsoy Aypakb, Muhammed Said Beşlerc, Ayşe Kaya Kalemb, Ahmet Göktuğ Ertema, Hatice Rahmet Günerb
a Cardiology Unit; Ministry of Health, Ankara City Hospital, Turkey
b Department of Infectious Diseases and Clinical Microbiology, Ankara Yildirim Beyazit University, Faculty of Medicine, Turkey
c Radiology Unit, Ministry of Health, Ankara City Hospital, Turkey
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          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Correlation between epicardial fat volume and interleukin-6 level&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Coronavirus disease 2019 &#40;COVID-19&#41; is an ongoing pandemic that has already affected millions of people worldwide and is associated with significant morbidity and mortality&#46; It is caused by severe acute respiratory syndrome coronavirus 2 &#40;SARS-CoV-2&#41; infection and first occurred in Wuhan in December 2019&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">1</span></a> On January 30&#44; 2020&#44; the World Health Organization &#40;WHO&#41; declared COVID-19 a Public Health Emergency of International Concern and on March 11 declared it a pandemic&#46; As of May 6&#44; a total of 3 588 773 people in 208 countries were reported to have COVID-19&#44; leading to more than 247 500 deaths&#46; Early reports from China and Italy indicate that SARS-CoV-2 causes illness of varying degrees of severity&#46;<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">2&#44;3</span></a> It has a wide clinical spectrum&#44; including asymptomatic infection&#44; mild respiratory disease&#44; severe pneumonia with acute respiratory failure and even death&#46; An excessive inflammatory response to SARS-CoV-2 is thought to be one of the major causes of disease severity and death in patients with COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">4</span></a> Evidence suggests that cytokine release syndrome &#40;CRS&#41; can play a major role in severe COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">5</span></a> Inflammatory cytokines and chemokines including interleukin-6 &#40;IL-6&#41;&#44; interleukin-1 beta &#40;IL-1&#946;&#41;&#44; induced protein 10 and monocyte chemoattractant protein-1 &#40;MCP-1&#41; are significantly elevated in COVID-19 patients&#44; and some were more commonly seen in severe than in nonsevere patients&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Epicardial adipose tissue &#40;EAT&#41; is a fat storage tissue located beneath the pericardium&#44; representing approximately 15&#37; of the cardiac weight&#46;<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">6&#44;7</span></a> It is a visceral fat that secretes inflammatory cytokines and mediators like MCP-1&#44; IL-6&#44; and tumor necrosis factor alpha &#40;TNF-&#945;&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">8</span></a> It can be measured with different imaging techniques&#58; transthoracic echocardiography&#44; multislice computed tomography &#40;MSCT&#41; and magnetic resonance imaging&#46;<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">9&#44;10</span></a> Computed tomography &#40;CT&#41; is a reliable and reproducible method for quantification of epicardial fat volume &#40;EFV&#41; independent of cardiac cycle phase&#46;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">11&#44;12</span></a> Chest CT is a cornerstone in the assessment of patients diagnosed with COVID-19&#46; Among recent developments in non-invasive imaging methods&#44; non-gated chest CT was shown to correlate with values measured by coronary CT angiography&#46;<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">2&#44;13</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">C-reactive protein &#40;CRP&#41;&#44; procalcitonin &#40;PCT&#41;&#44; ferritin and IL-6 are known inflammatory biomarkers and their levels have previously been reported to correlate with disease severity in COVID-19 patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">14&#44;15</span></a> However&#44; there are no data about the association between EFV and disease severity&#44; nor on the correlation with these inflammatory biomarkers&#46; Recently&#44; Zhao emphasized the role of epicardial fat in overweight patients&#44; who have worse prognosis during COVID-19 infection&#46;<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">16</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Early diagnosis of serious illness is critical to early classification and improvement of patients&#8217; prognosis&#46; Additionally&#44; the early identification of patients who will become severely ill could facilitate the allocation of limited medical resources to patients in need of aggressive treatment&#46; Therefore&#44; further research is urgently needed on early diagnosis and prognosis&#46; In this paper&#44; we aimed to assess the association between EFV &#40;measured by a 128-slice MSCT scanner&#41;&#44; inflammatory biomarkers and prognosis of COVID-19 patients&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Study design and participants</span><p id="par0025" class="elsevierStylePara elsevierViewall">In this retrospective&#44; single-center study&#44; a total of 101 consecutive patients were enrolled who were diagnosed with COVID-19&#46; The hospital in which the study was conducted is a designated&#44; large-volume hospital capable of receiving severe COVID-19 patients&#46; The diagnosis of COVID-19 was made according to WHO interim guidance and confirmed by RNA detection of SARS-CoV-2 in an on-site clinical laboratory&#46;<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">17</span></a> In accordance with the report of the WHO-China Joint Mission on COVID-19&#44;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">18</span></a> patients with COVID-19 were divided into mild &#40;laboratory confirmed&#44; without pneumonia&#41;&#44; moderate &#40;laboratory confirmed and with pneumonia&#41;&#44; severe &#40;dyspnea&#44; respiratory frequency &#8805;30&#47;min&#44; blood oxygen saturation &#8804;93&#37;&#44; PaO<span class="elsevierStyleInf">2</span>&#47;FiO<span class="elsevierStyleInf">2</span> ratio &#60;300&#44; and&#47;or lung infiltrates &#62;50&#37; of the lung field within 24-48 h&#41; and critical &#40;respiratory failure requiring mechanical ventilation&#44; shock or other organ failure that requires intensive care&#41;&#46; Severe and critical patients were admitted to the intensive care unit &#40;ICU&#41;&#44; whereas patients in the mild to moderate group were admitted to the ward&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">18</span></a> A combination of hydroxychloroquine &#40;HCQ&#41;&#44; azitromycin and favipiravir was used for the treatment of severe COVID-19 cases&#44; whereas only HCQ was used for mild to moderate cases&#46; The study was approved by the hospital&#39;s ethics committee&#44; which waived the requirement for written informed consent&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Data collection and analysis</span><p id="par0030" class="elsevierStylePara elsevierViewall">A doctor and a nurse were responsible for data entry into a computerized database and tracked these data daily&#46; The data were also reviewed by a team of physicians who treat patients with COVID-19&#46; Demographic characteristics &#40;gender and age&#41;&#44; comorbidities &#40;chronic obstructive pulmonary disease &#91;COPD&#93;&#44; hypertension&#44; diabetes&#44; coronary artery disease &#91;CAD&#93;&#44; cerebrovascular disease and chronic kidney disease&#41;&#44; clinical manifestations&#44; laboratory findings&#44; treatment and outcomes &#40;discharge&#47;death&#41; were extracted from electronic medical records using a standardized data collection form&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Routine blood examinations included complete blood count &#40;CBC&#41;&#44; coagulation profile&#44; serum biochemical tests &#40;including renal and liver function&#44; creatine kinase&#44; lactate dehydrogenase and electrolytes&#41;&#44; myocardial enzymes&#44; CRP&#44; PCT&#44; serum ferritin&#44; IL-6&#44; D-dimer and arterial blood gases &#40;lactate and PaO<span class="elsevierStyleInf">2</span>&#47;FiO<span class="elsevierStyleInf">2</span> ratio&#41; were collected at admission&#46; Peripheral venous blood samples were obtained from a large antecubital vein on admission&#46; Total CBC &#40;Sysmex K-1000&#44; Sysmex Corporation&#44; Kobe&#44; Japan&#41; and blood chemistry parameters &#40;Roche Diagnostics&#44; Tokyo&#44; Japan&#41; were determined at the hospital&#39;s biochemistry laboratory&#46; Blood samples were placed in standardized EDTA-containing tubes for total CBC tests and measurements were performed immediately after blood sampling&#46; Serum CRP levels were measured by immune nephelometry &#40;NFL BN-II&#59; Siemens Dade Behring&#41;&#46; PCT was determined using a Biom&#233;rieux Mini VIDAS automatic fluorescence immunoanalyzer&#46; Serum ferritin levels were detected by electrochemiluminescence &#40;Cobas E601&#44; Roche&#41;&#44; as was IL-6&#44; using the corresponding reagent&#46; D-dimer was quantitatively determined using a Sysmax CS-5100 coagulation analyzer&#46; Chest radiographs and CT scans were also performed for all inpatients&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Data on all treatment measures&#44; including antibiotic&#44; antivirus&#44; glucocorticoid and intravenous immunoglobulin therapy and respiratory support&#44; were acquired during hospitalization&#46; Throat swab samples were collected from all suspected patients at admission and laboratory confirmation of SARS-CoV-2 was performed using real-time reverse transcription polymerase chain reaction according to the manufacturer&#39;s protocol &#40;Beijing Genomics Institute and GeneoDx Biotechnology Co&#46; Ltd&#46;&#41;&#46; Repeated tests for SARS-CoV-2 were performed in confirmed patients to verify viral clearance before hospital discharge&#46; The criteria for discharge were absence of fever for at least three days&#44; clinical improvement of respiratory symptoms and two throat swab samples negative for SARS-CoV-2 RNA obtained at least 24 h apart&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Analysis of epicardial fat volume by computed tomography</span><p id="par0045" class="elsevierStylePara elsevierViewall">For patients referred to the hospital with suspected COVID-19&#44; MSCT examination was carried out at the time of admission&#46; All imaging was performed using a 128-slice scanner &#40;GE Revolution Evo&#44; USA&#41; in supine position during end-inspiration&#46; A low-dose CT protocol was applied with the following scanning parameters&#58; gantry rotation time 0&#46;4 s&#44; pitch 0&#46;98&#44; table speed 39&#46;3 mm&#47;rotation&#44; 20 mA&#44; 120 kVp&#44; and a 300&#215;300 matrix&#46; CARE Dose 4D and CARE kV scanning parameters were off&#46; A 1&#46;25 mm slice thickness and 1&#46;2 mm reconstruction interval were used for sagittal and coronal image reconstruction&#46; After each CT&#44; passive air ventilation was performed for at least 30 min and machine surfaces were disinfected with ethanol and didecyldimethylammonium chloride&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">DICOM data were transferred to a picture archiving and communicating system&#46; Then&#44; two expert radiologists independently interpreted the images and a final decision was reached by consensus&#46; Both radiologists were blinded to laboratory data&#44; clinical features&#44; and patients&#8217; diagnosis&#46; In the event of disagreement&#44; the opinion of a third radiologist was used&#46; All CT images were viewed in axial&#44; sagittal and coronal planes&#46; EFV was measured with a quantitative semi-automated procedure using the postprocessing software Advantage Workstation 4&#46;7 &#40;GE Healthcare Revolution&#44; USA&#41;&#46; Epicardial boundaries were manually traced to segment fat in the epicardium on axial images obtained from the pulmonary artery bifurcation to the lowest slice with a detectable pericardium &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>&#41;&#46; A CT attenuation threshold between -200 and -30 Hounsfield units was used to isolate epicardial fat&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">All analyses were carried out using IBM SPSS Statistics for Macintosh&#44; version 24&#46;0 &#40;IBM Corp&#46;&#44; Armonk&#44; New York&#44; USA&#41;&#46; The one-sample Kolmogorov-Smirnov test was used to assess the distribution of numerical variables&#46; Categorical data were presented as counts &#40;percentages&#41;&#44; while continuous data were presented as mean &#177; standard deviation and median &#40;interquartile range&#41;&#46; The Student&#39;s t test was applied to numerical data that conformed to a normal distribution&#44; and the Mann-Whitney U test was applied for skewed distributed variables&#46; The chi-square test was used for categorical variables&#46; For correlation analyses regarding EFV&#44; Pearson&#39;s and Spearman&#39;s correlation analysis was used for data with normal and skewed distribution&#44; respectively&#46; Receiver operating characteristic &#40;ROC&#41; curve analysis was conducted to determine the cut-off values for the sensitivity and specificity of EFV in predicting ICU admission&#46; Independent predictors of clinically severe COVID-19 were determined using logistic regression analysis&#46; Variables that might be confounding factors or established risk factors for ICU admission in patients with COVID-19 such as diabetes&#44; HT&#44; CAD&#44; COPD and EFV were included in logistic regression analyses&#46; The effect of each variable on ICU admission was measured in univariate and multivariate analyses&#46; A two-tailed p value of &#60;0&#46;05 was defined as statistically significant&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Baseline characteristics</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of 101 patients infected with SARS-CoV-2 were retrospectively enrolled in our study&#46; The primary composite endpoint &#40;admission to the ICU or death&#41; was reached in 26 &#40;25&#46;1&#37;&#41; patients&#46; Patients&#8217; demographic and baseline clinical features are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; According to these features&#44; participants were divided into two groups&#58; those admitted to the ICU and those admitted to the ward&#46; Patients in the ICU were significantly older &#40;64&#46;8&#177;14&#46;8 vs&#46; 50&#46;6&#177;15&#46;8 years&#44; p&#60;0&#46;001&#41; and had more comorbidities &#8211; hypertension &#40;46&#37; vs&#46; 20&#37;&#44; p&#61;0&#46;009&#41;&#44; CAD &#40;23&#37; vs&#46; 5&#37;&#44; p&#61;0&#46;009&#41; and COPD &#40;19&#37; vs&#46; 3&#37;&#44; p&#61;0&#46;004&#41; &#8211; than those admitted to the ward&#46; Other characteristics including gender&#44; body mass index&#44; smoking and diabetes showed no significant differences between the two groups&#46; A total of 10 &#40;38&#37;&#41; deaths occurred among the ICU patients&#46; The mean age of patients who died was 71&#46;9&#177;14&#46;3 years &#40;range 44-90 years&#41; and most were male &#40;n&#61;6&#41;&#46; However&#44; death was not observed among the 75 patients admitted to the ward&#46; In the ICU&#44; noninvasive ventilation was used in 15 patients &#40;57&#37;&#41; and 11 patients &#40;42&#37;&#41; were intubated&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Laboratory findings</span><p id="par0065" class="elsevierStylePara elsevierViewall">At admission&#44; patients admitted to the ICU had significantly lower levels of total protein and albumin&#44; hematocrit and lymphocyte count&#44; but higher glucose&#44; urea&#44; aspartate aminotransferase&#44; troponin I&#44; D-dimer levels and white blood cell and neutrophil count compared with those admitted to the ward &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; When inflammatory biomarkers were analyzed&#44; CRP &#40;133 vs&#46; 12&#46;4 g&#47;l&#44; p&#60;0&#46;001&#41;&#44; IL-6 &#40;45&#46;4 vs&#46; 8&#46;8 pg&#47;ml&#44; p&#60;0&#46;001&#41;&#44; PCT &#40;0&#46;14 vs&#46; 0&#46;05 &#956;g&#47;l&#44; p&#61;0&#46;001&#41; and ferritin &#40;432 vs&#46; 172 &#956;g&#47;l&#44; p&#60;0&#46;001&#41; levels were also significantly higher in patients admitted to the ICU than those in the ward&#46; Moreover&#44; patients admitted to the ICU had significantly larger EFV &#40;115&#46;1&#177;44&#46;0 vs&#46; 94&#46;3&#177;45&#46;5 cm<span class="elsevierStyleSup">3</span>&#44; p&#61;0&#46;037&#41; than those admitted to the ward &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Figure 2</a>&#41;&#46; <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the correlation between EFV and inflammatory biomarkers including CRP&#44; PCT&#44; ferritin and IL-6 in all COVID-19 patients&#46; A statistically significant positive correlation was detected between EFV and CRP &#40;r&#58; 0&#46;494&#44; p&#60;0&#46;001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Figure 3</a>&#41;&#44; IL-6 &#40;r&#58; 0&#46;311&#44; p&#61;0&#46;005&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Figure 4</a>&#41;&#44; PCT &#40;r&#58; 0&#46;287&#44; p&#61;0&#46;05&#41; and ferritin &#40;r&#58; 0&#46;265&#44; p&#61;0&#46;010&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Receiver operating characteristic analysis of epicardial fat volume and inflammatory biomarkers on admission</span><p id="par0070" class="elsevierStylePara elsevierViewall">ROC analysis was performed to assess clinical and laboratory biomarkers at the first visit for prediction of COVID-19 severity&#46; This demonstrated that the area under the curve &#40;AUC&#41; of CRP&#44; IL-6&#44; PCT&#44; ferritin and EFV for predicting severe COVID-19 was 0&#46;90 &#40;95&#37; confidence interval &#91;CI&#93;&#58; 0&#46;84-0&#46;96&#41;&#44; 0&#46;73 &#40;95&#37; CI&#58; 0&#46;60-0&#46;87&#41;&#44; 0&#46;74 &#40;95&#37; CI&#58; 0&#46;63-0&#46;85&#41;&#44; 0&#46;85 &#40;95&#37; CI&#58; 0&#46;74-0&#46;96&#41; and 0&#46;86 &#40;95&#37; CI&#58; 0&#46;74-0&#46;96&#41;&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; ROC analysis also demonstrated that at a cut-off of 46 mg&#47;l&#44; the sensitivity&#44; specificity&#44; positive predictive value &#40;PPV&#41; and negative predictive value &#40;NPV&#41; of CRP was 82&#37;&#44; 81&#37;&#44; 57&#37;&#44; and 93&#37;&#44; respectively&#59; at a cut-off of 25 pg&#47;ml&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of IL-6 were 83&#37;&#44; 80&#37;&#44; 55&#37;&#44; and 94&#37;&#44; respectively&#59; and at a cut-off of 0&#46;07 &#956;g&#47;l&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of PCT were 73&#37;&#44; 67&#37;&#44; 41&#37;&#44; and 89&#37;&#44; respectively&#46; Moreover&#44; at a cut-off of 202 &#956;g&#47;l&#44; the sensitivity&#44; specificity&#44; PPV&#44; and NPV of ferritin were 80&#37;&#44; 60&#37;&#44; 42&#37;&#44; and 89&#37; respectively&#46; Lastly&#44; at a cut-off of 102 cm<span class="elsevierStyleSup">3</span>&#44; the sensitivity&#44; specificity&#44; PPV and NPV of EFV were 82&#37;&#44; 80&#37;&#44; 58&#37;&#44; and 94&#37; respectively&#46; ROC analysis also showed that the AUC of CRP and EFV to predict disease severity was higher than that of other inflammatory biomarkers&#44; which demonstrated the excellent predictive power of these parameters for severity of COVID-19&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">Univariate regression analysis was performed in order to assess the relationship between clinical characteristics and ICU admission &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#44; which showed that age &#40;odds ratio &#91;OR&#93;&#58; 1&#46;07&#44; 95&#37; CI&#58; 1&#46;03-1&#46;11&#44; p&#60;0&#46;001&#41;&#44; hypertension &#40;OR&#58; 2&#46;90&#44; 95&#37; CI&#58; 1&#46;13-7&#46;42&#44; p&#61;0&#46;026&#41; and EFV &#40;OR&#58; 1&#46;03&#44; 95&#37; CI&#58; 1&#46;01-1&#46;04&#44; p&#60;0&#46;001&#41; were associated with ICU admission&#46; Multivariate regression analysis was then performed to detect independent predictors of admission to the ICU&#46; Both age and EFV independently predicted ICU admission at a significant level &#40;OR&#58; 1&#46;05&#44; 95&#37; CI&#58; 1&#46;01-1&#46;10&#44; p&#61;0&#46;013 and OR&#58; 1&#46;02&#44; 95&#37; CI&#58; 1&#46;01-1&#46;03&#44; p&#61;0&#46;025&#44; respectively&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">To date&#44; the global COVID-19 pandemic has imposed severe burdens on medical systems&#46; It is critical to identify COVID-19 patients who may become severely ill at the first hospital admission in order to facilitate control of the disease and to improve patients&#8217; prognosis in a context of limited medical resources&#46; To our knowledge this is the first study to report an association between EFV and clinical severity of COVID-19&#46; This retrospective cohort study identified several predictors of poor prognosis in adults hospitalized with COVID-19&#46; In particular&#44; older age&#44; presence of comorbid diseases and elevated levels of inflammatory biomarkers including CRP&#44; PCT&#44; ferritin and IL-6 on admission were more commonly seen in severe COVID-19 illness&#46; Furthermore&#44; EFV as measured by MSCT was also demonstrated to be related to the clinical severity of these patients and was also positively correlated with the above-mentioned inflammatory biomarkers&#46; Moreover&#44; in multivariate logistic regression analysis both age and EFV independently predicted admission to the ICU&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">EAT is a visceral fat deposit and as such has the capacity to secrete a number of cytokines and chemokines&#44; together known as adipokines&#46; These are biologically active molecules that are secreted by mature adipocytes themselves as well as stromal preadipocytes&#44; macrophages&#44; fibroblasts&#44; mast cells and lymphocytes that are located within the adipose tissue&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">19</span></a> IL-6&#44; -8&#44; -10 and IL-1&#946;&#44; TNF-&#945;&#44; MCP-1&#44; adiponectin&#44; leptin and plasminogen activator inhibitor 1 are all examples of adipokines&#46;<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">20</span></a> In normal quantities&#44; EAT has various putative physiological functions&#46; However&#44; many changes occur as EAT volumes increase&#46; These changes are often characterized by hypertrophy&#44; failure to store triglycerides&#44; increased lipolysis and inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">21</span></a> As EAT expands&#44; it becomes hypoxic and dysfunctional and is invaded by increasing numbers of macrophages and T lymphocytes&#44; resulting in a shift in its metabolic profile&#46;<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">22</span></a> The result is increased secretion of proinflammatory cytokines such as IL-6&#44; TNF-&#945;&#44; MCP-1 and many others that contribute to the inflammatory environment&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">8</span></a> In this setting&#44; the beneficial paracrine effects of EAT are lost&#46; Shimabukuro et al&#46; showed that EFV was positively correlated with the expression of inflammatory cytokines in EAT&#44; but was negatively correlated with adiponectin expression&#46;<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">23</span></a> Malavazos et al&#46; studied the association between EAT thickness and plasma cytokine levels in severe patients with obesity&#46; They reported that EAT thickness was positively correlated with cytokine levels &#40;i&#46;e&#46; MCP-1 and the serum IL-6&#47;IL-6 complex&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">24</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">The inflammatory response plays a critical role in COVID-19&#44; and inflammatory cytokine storm increases the severity of COVID-19&#46;<a class="elsevierStyleCrossRefs" href="#bib0350"><span class="elsevierStyleSup">25&#44;26</span></a> Wang et al&#46; found that the inflammatory response is crucial to the progression of COVID-19 and cytokine storm can lead to severe complications and death&#46;<a class="elsevierStyleCrossRef" href="#bib0360"><span class="elsevierStyleSup">27</span></a> The fifth edition of the Chinese Diagnosis and Treatment Protocols for COVID-19 recommends monitoring cytokine levels to improve treatment efficacy and reduce mortality&#44;<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">28</span></a> while the seventh edition of this guideline points out that peripheral blood inflammatory factors such as IL-6 may increase during COVID-19 infection&#46;<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">29</span></a></p><p id="par0095" class="elsevierStylePara elsevierViewall">Cytokine releasing syndrome &#40;CRS&#41; occurs in most patients with severe COVID-19 and is known to be an important cause of death&#46; It is a systemic inflammatory response that can be caused by infectious diseases&#44; certain drugs and other factors&#44; and is characterized by a sharp increase in the level of several proinflammatory cytokines&#46;<a class="elsevierStyleCrossRefs" href="#bib0375"><span class="elsevierStyleSup">30&#8211;32</span></a> SARS-CoV-2 binds to alveolar epithelial cells&#44; activates the innate and adaptive immune systems and thus leads to the release of large quantities of cytokines&#44; including IL-6&#44; which is the key molecule involved in CRS&#46; IL-6 is an important member of the cytokine network and plays a central role in acute inflammation&#46;<a class="elsevierStyleCrossRef" href="#bib0390"><span class="elsevierStyleSup">33</span></a> It has both anti-inflammatory and proinflammatory effects&#46; Liu et al&#46; showed an increase in inflammatory cytokines &#40;IL-6&#44; IL-10&#44; IL-2 and interferon gamma&#41; in the peripheral blood in severe COVID-19 cases&#46;<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">34</span></a> Zhang et al&#46; also found a relationship between higher IL-6 and CRP levels and disease progression in hospitalized COVID-19 patients&#46;<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">35</span></a> The present study likewise showed increased IL-6 levels in severe COVID-19 patients&#46; In addition to this finding&#44; a statistically significant positive correlation was detected between EFV and IL-6 level in this study&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Besides direct attack from the virus&#44; progressive inflammatory injury has been suggested as a possible mechanism in COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">1</span></a> CRP is a downstream acute phase protein in the innate immune response&#46;<a class="elsevierStyleCrossRef" href="#bib0405"><span class="elsevierStyleSup">36</span></a> It is produced following the increased synthesis of proinflammatory cytokines to activate the immune response&#46;<a class="elsevierStyleCrossRef" href="#bib0410"><span class="elsevierStyleSup">37</span></a> Serum CRP level has therefore often been used as a laboratory marker of inflammation&#46;<a class="elsevierStyleCrossRefs" href="#bib0405"><span class="elsevierStyleSup">36&#44;37</span></a> Zhang et al&#46; reported CRP as a predictor of the progression of COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">35</span></a> Similarly&#44; we found significantly higher CRP levels at admission in severe cases of COVID-19 compared to mild cases&#46; Moreover&#44; we also demonstrated a positive correlation between CRP level and EFV&#46; Eslami et al&#46; investigated the association of CT-measured EAT thickness and density with clinical outcome in 87 patients with COVID-19 and found that mean EAT density was markedly lower in deceased patients compared with survivors&#44; although this significant difference was not observed across the two groups in terms of EAT thickness&#46;<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">38</span></a> In the present study&#44; we measured EFV in COVID-19 patients&#44; rather than EAT thickness and density&#46; Higher EFV was observed in severe patients compared to milder cases&#46; Wei et al&#46; studied EFV as a potential risk factor for myocardial injury in 400 laboratory-confirmed COVID-19 patients and&#44; similarly to our result&#44; found an association between increased EFV on admission chest CT scan and increased myocardial injury and mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0420"><span class="elsevierStyleSup">39</span></a> They therefore suggested that assessment of EFV by chest CT scan on admission may provide a potentially useful threshold for predicting cardiovascular complications of COVID-19&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">PCT is a glycoprotein without hormonal activity that is the precursor of calcitonin&#46;<a class="elsevierStyleCrossRefs" href="#bib0425"><span class="elsevierStyleSup">40&#44;41</span></a> Serum PCT levels are usually low or undetectable<a class="elsevierStyleCrossRef" href="#bib0435"><span class="elsevierStyleSup">42</span></a> but are increased by bacterial infections and relatively low in viral infections&#44; and can therefore be used to distinguish between bacterial and viral infections&#46;<a class="elsevierStyleCrossRef" href="#bib0440"><span class="elsevierStyleSup">43</span></a> Higher PCT levels detected in patients with severe COVID-19 usually suggest the presence of concomitant bacterial infection&#46; Liu et al&#46;<a class="elsevierStyleCrossRef" href="#bib0445"><span class="elsevierStyleSup">44</span></a> recently studied PCT&#44; CRP and IL-6 levels in COVID-19 patients&#44; dividing them into two groups&#58; with severe disease or with mild disease&#46; They found significantly higher PCT&#44; CRP and IL-6 levels in the severe group compared to the mild group&#46; In addition&#44; they identified all of these inflammatory biomarkers as independent factors predicting the severity of COVID-19&#46; Our results also demonstrated higher levels of admission PCT&#44; CRP and IL-6 levels in severe COVID-19 patients&#46; Furthermore&#44; we showed a positive correlation between these inflammatory biomarkers and EFV&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Serum ferritin can be elevated during infection and inflammation&#46; High ferritin levels due to secondary hemophagocytic lymphohistiocytosis and CRS have been reported in severe COVID-19 patients&#46; Velavan et al&#46; recommended the use of serum ferritin&#44; CRP and IL-6 levels in risk stratification of COVID-19 patients to predict severe and fatal COVID-19&#46;<a class="elsevierStyleCrossRef" href="#bib0450"><span class="elsevierStyleSup">45</span></a> In our study&#44; we also showed significantly elevated ferritin levels in severe COVID-19 cases and a positive correlation of ferritin with EFV&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">There are some limitations in this study&#46; First of all&#44; it is a single-center study with a relatively small sample size&#46; Secondly&#44; it is retrospective in nature&#44; and the results need to be further verified by prospective studies&#46; Thirdly&#44; we aimed to analyze the risk factors that determine prognosis&#44; but the poor prognosis group was small and we were therefore unable to analyze the differences in clinical characteristics of patients in this group&#46; Fourthly&#44; we did not include asymptomatic and mild cases managed at home&#44; and hence our cohort may represent a more severe COVID-19 population&#46; Fifthly&#44; the treatment of these patients was clinically driven and did not follow a unified standard&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conclusion</span><p id="par0120" class="elsevierStylePara elsevierViewall">Epicardial fat volume and serum CRP&#44; IL-6&#44; PCT and ferritin levels show a significant correlation with the severity of COVID-19&#46; In hospitalized patients&#44; clinicians should consider EFV in addition to serum levels of the above inflammatory biomarkers in risk stratification of patients to predict severe and fatal COVID-19&#46; Our findings could help facilitate the early identification of severe COVID-19 patients and thus enable early treatment and intervention&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Funding</span><p id="par0125" 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="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Conflicts of interest</span><p id="par0130" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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            1 => "Volume adiposo epic&#225;rdico"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Epicardial adipose tissue serves as a source of inflammatory cytokines and mediators&#46; Cytokine storm is an important cause of morbidity and mortality in coronavirus disease 2019 &#40;COVID-19&#41;&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objectives</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">To investigate the association between epicardial fat volume &#40;EFV&#41;&#44; inflammatory biomarkers and clinical severity of COVID-19&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">This retrospective study included 101 patients who were infected with COVID-19&#46; Serum inflammatory biomarkers including C-reactive protein &#40;CRP&#41;&#44; interleukin-6 &#40;IL-6&#41;&#44; procalcitonin &#40;PCT&#41; and ferritin levels were measured&#46; Computed tomography images were analyzed and semi-automated measurements for EFV were obtained&#46; The primary composite endpoint was admission to the intensive care unit &#40;ICU&#41; or death&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The primary composite endpoint occurred in 25&#46;1&#37; &#40;n&#61;26&#41; of patients &#40;mean age 64&#46;8&#177;14&#46;8 years&#44; 14 male&#41;&#46; A total of 10 patients died&#46; EFV&#44; CRP&#44; PCT&#44; ferritin and IL-6 levels were significantly higher in ICU patients&#46; Moreover&#44; a positive correlation was determined between EFV and CRP &#40;r&#58; 0&#46;494&#44; p&#60;0&#46;001&#41;&#44; PCT &#40;r&#58; 0&#46;287&#44; p&#61;0&#46;005&#41;&#44; ferritin &#40;r&#58; 0&#46;265&#44; p&#61;0&#46;01&#41; and IL-6 &#40;r&#58; 0&#46;311&#44; p&#61;0&#46;005&#41;&#46; On receiver operating characteristic analysis&#44; patients with EFV &#62;102 cm<span class="elsevierStyleSup">3</span> were more likely to have severe complications&#46; In multivariate logistic regression analysis&#44; EFV independently predicted admission to the ICU at a significant level &#40;OR&#58; 1&#46;02&#44; 95&#37; CI&#58; 1&#46;01-1&#46;03&#44; p&#61;0&#46;025&#41;&#46;</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">EFV and serum CRP&#44; IL-6&#44; PCT and ferritin levels can effectively assess disease severity and predict the outcome in patients with COVID-19&#46; EFV is an independent predictor of admission to the ICU in hospitalized COVID-19 patients&#46;</p></span>"
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            "titulo" => "Introduction"
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          1 => array:2 [
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          2 => array:2 [
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        "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introdu&#231;&#227;o</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">O tecido adiposo epic&#225;rdico &#233; fonte de citocinas inflamat&#243;rias e mediadores&#46; A tempestade de citocinas &#233; uma importante causa de morbilidade e mortalidade na doen&#231;a coronav&#237;rus 2019 &#40;COVID-19&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Objetivos</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Investigar a associa&#231;&#227;o entre volume adiposo epic&#225;rdico &#40;VAE&#41;&#44; biomarcadores inflamat&#243;rios e gravidade cl&#237;nica da COVID-19&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">M&#233;todos</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Este estudo retrospetivo incluiu 101 doentes infetados com COVID-19&#46; Foram avaliados biomarcadores inflamat&#243;rios s&#233;ricos&#44; incluindo os n&#237;veis de prote&#237;na C-reativa &#40;PCR&#41;&#44; de interleucina-6 &#40;IL-6&#41;&#44; de procalcitonina &#40;PCT&#41; e de ferritina&#46; Foram analisadas imagens de tomografia computorizada &#40;TC&#41; e foram obtidas medi&#231;&#245;es semi-autom&#225;ticas do VAE&#46; O <span class="elsevierStyleItalic">endpoint</span> prim&#225;rio composto foi a admiss&#227;o na unidade de cuidados intensivos &#40;UCI&#41; ou morte&#46;</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Resultados</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">O <span class="elsevierStyleItalic">endpoint</span> prim&#225;rio ocorreu em 25&#44;1&#37; &#40;n&#61;26&#41; dos doentes &#40;idade m&#233;dia 64&#44;8&#177;14&#44;8 anos&#44; 14 homens&#41;&#46; Um total de 10 doentes morreu&#46; Os n&#237;veis de VAE&#44; PCR&#44; PCT&#44; ferritina e IL-6 foram significativamente superiores nos doentes internados na UCI&#46; Al&#233;m disso&#44; verificou-se uma correla&#231;&#227;o positiva entre o VAE e a PCR &#40;r&#58; 0&#44;494&#44; p&#60;0&#44;001&#41;&#44; PCT &#40;r&#58; 0&#44;287&#44; p&#61;0&#44;005&#41;&#44; ferritina &#40;r&#58; 0&#44;265&#44; p&#61;0&#44;01&#41; e IL-6 &#40;r&#58; 0&#44;311&#44; p&#61;0&#44;005&#41;&#46; Na an&#225;lise de regress&#227;o logistica multivariada&#44; os doentes com VAE&#62;102 cm<span class="elsevierStyleSup">3</span> tinham maior probabilidade de ter complica&#231;&#245;es graves&#46;</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Conclus&#227;o</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">O VAE e os n&#237;veis s&#233;ricos de PCR&#44; IL-6&#44; PCT e ferritina podem avaliar a gravidade da doen&#231;a e prever o resultado em doentes com COVID-19&#46; O VAE constitui um fator preditivo na admiss&#227;o dos doentes hospitalizados com COVID-19 numa UCI&#46;</p></span>"
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Comparison of epicardial fat volume in patients admitted to the intensive care unit and to the ward&#46;</p>"
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        "tipo" => "MULTIMEDIAFIGURA"
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          0 => array:4 [
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        "identificador" => "fig0020"
        "etiqueta" => "Figure 4"
        "tipo" => "MULTIMEDIAFIGURA"
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            0 => array:1 [
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                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" style="border-bottom: 2px solid black">Variable&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" style="border-bottom: 2px solid black">Ward &#40;n&#61;75&#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="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">ICU &#40;n&#61;26&#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="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p&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">Age&#44; years&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">50&#46;6&#177;15&#46;8&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">64&#46;8&#177;14&#46;8&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;0&#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">Male&#44; n &#40;&#37;&#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;60&#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;54&#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&#46;583&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">BMI&#44; kg&#47;m<span class="elsevierStyleSup">2</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">27&#46;1&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">26&#46;7&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&#46;810&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&#44; n &#40;&#37;&#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">17 &#40;23&#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;27&#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&#46;660&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&#44; n &#40;&#37;&#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;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">12 &#40;46&#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&#46;009&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">CAD&#44; n &#40;&#37;&#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 &#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">6 &#40;23&#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&#46;009&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">COPD&#44; n &#40;&#37;&#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;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;19&#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&#46;004&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">Smoking n &#40;&#37;&#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;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">1 &#40;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">0&#46;472&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">ICU stay&#44; days&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">-&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&#46;5 &#40;5-13&#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">-&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">Discharge time&#44; days&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;9-15&#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">17&#46;5 &#40;12-25&#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;0&#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">Intubated&#44; n &#40;&#37;&#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">11 &#40;42&#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;0&#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">Mortality&#44; n &#40;&#37;&#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">9 &#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">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Parameters are mean &#177; standard deviation or median &#40;interquartile range&#41;&#46;</p><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">ALT&#58; alanine transaminase&#59; AST&#58; aspartate transaminase&#59; CRP&#58; C-reactive protein&#59; EFV&#58; epicardial fat volume&#59; IL-6&#58; interleukin-6&#59; LMR&#58; lymphocyte to monocyte ratio&#59; NLR&#58; neutrophil to lymphocyte ratio&#59; WBC&#58; white blood cells&#46;</p>"
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                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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \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">Ward &#40;n&#61;75&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">ICU &#40;n&#61;26&#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="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Glucose&#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">110&#177;32&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">129&#177;39&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&#46;035&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">Urea&#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">30 &#40;24-37&#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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">37 &#40;30-54&#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&#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">Creatinine&#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">0&#46;88 &#40;0&#46;75-1&#46;04&#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&#46;01 &#40;0&#46;82-1&#46;15&#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&#46;101&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">AST&#44; U&#47;l&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;16-34&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">42&#40;23-67&#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;0&#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">ALT&#44; U&#47;l&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;19-38&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">28 &#40;20-52&#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&#46;273&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">Total protein&#44; g&#47;l&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&#46;0 &#40;6&#46;5-7&#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">6&#46;3 &#40;5&#46;8-6&#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">&#60;0&#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">Albumin&#44; g&#47;l&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;3&#177;0&#46;4&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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;9&#177;0&#46;5&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;0&#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">Troponin I&#44; ng&#47;l&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;0 &#40;0-6&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">10&#46;0 &#40;6&#46;0-22&#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;0&#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">D-dimer&#44; mg&#47;l&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&#46;50 &#40;0&#46;29-0&#46;82&#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
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                  \t\t\t\t">1&#46;01 &#40;0&#46;53-2&#46;68&#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;0&#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">WBC&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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&#46;31&#40;4&#46;48-6&#46;19&#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&#46;01 &#40;5&#46;29-9&#46;34&#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&#46;002&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">Neutrophils&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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;16 &#40;2&#46;65-4&#46;26&#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;87 &#40;4&#46;06-8&#46;13&#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;0&#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">Lymphocytes&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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&#46;27 &#40;0&#46;93-1&#46;62&#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
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                  \t\t\t\t">0&#46;78 &#40;0&#46;54-1&#46;14&#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;0&#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">Platelets&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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">211&#46;0 &#40;163&#46;0-238&#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">197&#46;5 &#40;168&#46;7-262&#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">0&#46;741&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">Monocytes&#44; &#215;10<span class="elsevierStyleSup">9</span>&#47;l&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&#46;33 &#40;0&#46;25-0&#46;50&#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
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                  \t\t\t\t">0&#46;24 &#40;0&#46;18-0&#46;46&#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&#46;085&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">NLR&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&#46;52 &#40;1&#46;77-3&#46;68&#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&#46;17 &#40;4&#46;27-15&#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;0&#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">CRP&#44; g&#47;l&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&#46;4 &#40;3&#46;1-37&#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">133 &#40;59&#46;8-189&#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;0&#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">IL-6&#44; pg&#47;ml&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&#46;8 &#40;4&#46;0-24&#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">45&#46;4 &#40;27&#46;2-89&#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;0&#46;001&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">Procalcitonin&#44; &#956;g&#47;l&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
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                  \t\t\t\t\ttop\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">Ferritin&#44; &#956;g&#47;l&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">172 &#40;60-296&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">432 &#40;208-646&#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">&#60;0&#46;001&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">EFV&#44; cm<span class="elsevierStyleSup">3</span>&nbsp;\t\t\t\t\t\t\n
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                  \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">94&#46;3&#177;45&#46;5&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">115&#46;1&#177;44&#46;0&nbsp;\t\t\t\t\t\t\n
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                  \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&#46;037&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Comparison of laboratory findings of COVID-19 patients admitted to the ward and to the intensive care unit&#46;</p>"
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Covariates&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t">0&#46;494&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</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">Il-6&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">0&#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">PCT&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">Ferritin&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;265&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">NLR&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\tvoid\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttable-head\n
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                  \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">PLR&nbsp;\t\t\t\t\t\t\n
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                  \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">NLR&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">CRP&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&#46;0&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&#46;904 &#40;0&#46;843-0&#46;965&#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&#46;6&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">81&#46;1&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;5&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">93&#46;7&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;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">0&#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">IL-6&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&#46;65&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&#46;857 &#40;0&#46;745-0&#46;969&#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">83&#46;3&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">80&#46;3&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;5&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">94&#46;3&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;22&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&#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">PCT&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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