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Absence of relevant clinical effects of SARS-COV-2 on the affinity of hemoglobin for O2 in patients with COVID-19
Ausencia de efectos clínicos destacables del SARS-CoV-2 sobre la afinidad de la hemoglobina por el O2 en pacientes con COVID-19
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(b) After 1<span class="elsevierStyleHsp" style=""></span>h of iNO therapy at 10<span class="elsevierStyleHsp" style=""></span>ppm: increase in perfusion in the RL lobe with an improvement in the ventilation–perfusion ratio.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Anna Sánchez-Corral, Marina García-de-Acilu, Manel Santafè, Oriol Roca" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Anna" "apellidos" => "Sánchez-Corral" ] 1 => array:2 [ "nombre" => "Marina" "apellidos" => "García-de-Acilu" ] 2 => array:2 [ "nombre" => "Manel" "apellidos" => "Santafè" ] 3 => array:2 [ "nombre" => "Oriol" "apellidos" => "Roca" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1579212921004079?idApp=UINPBA00003Z" "url" => "/15792129/0000005700000012/v3_202201080532/S1579212921004079/v3_202201080532/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S1579212921003797" "issn" => "15792129" "doi" => "10.1016/j.arbr.2021.10.005" "estado" => "S300" "fechaPublicacion" => "2021-12-01" "aid" => "2756" "copyright" => "SEPAR" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Arch Bronconeumol. 2021;57:750-6" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "VATS lobectomy morbidity and mortality is lower in patients with the same ppoDLCO: Analysis of the database of the Spanish Video-Assisted Thoracic Surgery Group" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "750" "paginaFinal" => "756" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "La lobectomía VATS tiene una menor morbimortalidad para una misma ppoDLCO: análisis de base de datos del Grupo Español de Cirugía Torácica Video-asistida" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2309 "Ancho" => 3159 "Tamanyo" => 438527 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Proportions of the different morbidities obtained after calculating the centered moving average with a range of ±5 values. 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The stars highlight intervals where significant differences are observed between the thoracotomy and VATS patient groups.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Borja Aguinagalde, Asier Insausti, Iker Lopez, Laura Sanchez, Sergio Bolufer, Raul Embun" "autores" => array:7 [ 0 => array:2 [ "nombre" => "Borja" "apellidos" => "Aguinagalde" ] 1 => array:2 [ "nombre" => "Asier" "apellidos" => "Insausti" ] 2 => array:2 [ "nombre" => "Iker" "apellidos" => "Lopez" ] 3 => array:2 [ "nombre" => "Laura" "apellidos" => "Sanchez" ] 4 => array:2 [ "nombre" => "Sergio" "apellidos" => "Bolufer" ] 5 => array:2 [ "nombre" => "Raul" "apellidos" => "Embun" ] 6 => array:1 [ "colaborador" => "en representación del Grupo Español de Cirugía Torácica Video-asistida" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0300289621000557" "doi" => "10.1016/j.arbres.2021.01.030" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0300289621000557?idApp=UINPBA00003Z" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1579212921003797?idApp=UINPBA00003Z" "url" => "/15792129/0000005700000012/v3_202201080532/S1579212921003797/v3_202201080532/en/main.assets" ] "en" => array:22 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Absence of relevant clinical effects of SARS-COV-2 on the affinity of hemoglobin for O<span class="elsevierStyleInf">2</span> in patients with COVID-19" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "757" "paginaFinal" => "763" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Sergi Pascual-Guàrdia, Antoni Ferrer, Óscar Díaz, Antonio O. Caguana, Elvira Tejedor, Salomé Bellido-Calduch, Diego A. Rodríguez-Chiaradia, Joaquim Gea" "autores" => array:8 [ 0 => array:3 [ "nombre" => "Sergi" "apellidos" => "Pascual-Guàrdia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "Antoni" "apellidos" => "Ferrer" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Óscar" "apellidos" => "Díaz" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "Antonio O." 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"apellidos" => "Rodríguez-Chiaradia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 7 => array:4 [ "nombre" => "Joaquim" "apellidos" => "Gea" "email" => array:1 [ 0 => "quim.gea@upf.edu" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Servicio de Neumología, Hospital del Mar-IMIM, DCEXS, Universitat Pompeu Fabra, CIBERES, ISCIII, BRN, Barcelona, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Laboratorio de Referencia de Cataluña, El Prat de Llobregat, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Ausencia de efectos clínicos destacables del SARS-CoV-2 sobre la afinidad de la hemoglobina por el O<span class="elsevierStyleInf">2</span> en pacientes con COVID-19" ] ] "resumenGrafico" => array:2 [ "original" => 1 "multimedia" => array:5 [ "identificador" => "fig0015" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 739 "Ancho" => 1333 "Tamanyo" => 81752 ] ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">SARS-CoV-2, a virus that manifests clinically as a disease called Covid-19, is causing a serious worldwide pandemic<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,2</span></a>. Although this disease can affect various organs, the main target is the lung, where it can cause both pneumonia with reactive tissue inflammation and also vascular and blood disorders<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2,3</span></a>. As a result, many cases present respiratory failure that can become very serious if it develops into acute respiratory distress syndrome (ARDS). The clinical management of these processes requires pulmonary gas exchange monitoring, determined preferably by arterial blood gas tests, although oximetry is often performed to reduce the invasiveness of the procedure. The variable most widely used to assess the severity of hypoxemia and the clinical course is partial oxygen pressure (PaO<span class="elsevierStyleInf">2</span>) and its ratio to the concentration of gas delivered (fraction of inspired oxygen [FiO<span class="elsevierStyleInf">2</span>]), a variable known as PaFi (PaO<span class="elsevierStyleInf">2</span>/FiO<span class="elsevierStyleInf">2</span>)<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a>. PaO<span class="elsevierStyleInf">2</span> is important for determining the total oxygen content delivered to the tissues from arterial blood (CaO<span class="elsevierStyleInf">2</span>), as it is an indicator of both the amount of gas bound to hemoglobin and the amount dissolved in plasma<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a>. The first is far more important (95% of CaO<span class="elsevierStyleInf">2</span>), and is expressed by percentage oxygen saturation (SaO<span class="elsevierStyleInf">2</span>). However, a recent <span class="elsevierStyleItalic">in silico</span> study reported that some SARS-CoV-2 proteins (e.g., ORF8)<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,7</span></a> might inhibit the binding of hemoglobin with oxygen and even destroy hemoglobin molecules<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,7</span></a>. An even more recent study, conducted on red blood cells from Covid-19 patients using proteomic and lipidomic determinations, also suggested that the affinity between oxygen and hemoglobin in these patients may be reduced<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a>. The clinical consequences of these 2 studies could be significant, as they would limit the usefulness of PaO<span class="elsevierStyleInf">2</span> and PaFi in assessing the real oxygenation status of Covid-19 patients<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a>. Since numerous validated equations can be used to calculate the oxygen saturation that corresponds to a particular partial oxygen pressure while taking into account the other main factors involved, the difference between the estimated oxygen saturation and the patient’s real saturation status will help determine whether the affinity of oxygen for the hemoglobin molecule is affected by the virus. The objective of this study was to analyze the concordance between measured SaO<span class="elsevierStyleInf">2</span> and SaO<span class="elsevierStyleInf">2</span> calculated from PaO<span class="elsevierStyleInf">2</span>, in order to assess whether the infection actually does impact the affinity of oxygen for hemoglobin.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Method</span><p id="par0010" class="elsevierStylePara elsevierViewall">This study was performed by analyzing all arterial and venous blood gas samples obtained from Covid-19 patients (confirmation by polymerase chain reaction [PCR] in nasal or pharyngeal smears) received by our center’s central laboratory between March and April 2020. A total of 549 arterial blood samples were collected from 139 patients, and 544 venous blood samples were collected from 215 patients. Other blood gas determinations that were collected and processed in other healthcare facilities with slightly different instrument calibration and maintenance criteria were excluded. We also studied blood gas determinations from 2 control groups: the first comprising patients tested synchronously during the same period as the experimental group who presented febrile symptoms but radiology not suggestive of SARS-CoV-2 and PCR negative for this virus (251 arterial samples from 73 patients and 1069 venous samples from 379 patients), and the second comprising subjects admitted for non-parenchymal lung disease in the 2 months prior to the detection of the first cases of SARS-CoV-2 infection (2614 arterial samples from 1089 patients and 3098 venous samples from 1461 patients). We included arterial and venous samples because we were interested in analyzing oxygen affinity for hemoglobin over a wide range of arterial oxygen pressures. In line with the requirements of the institution’s clinical research ethics committee, patients initially gave verbal consent for the inclusion of their clinical and analytical data, an approach that was subsequently approved within the framework of a study on patients with severe Covid-19 (ref. 2020/9458).</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Techniques</span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Arterial and venous blood gas analyses</span><p id="par0015" class="elsevierStylePara elsevierViewall">Arterial blood samples were obtained by puncture of the radial artery, following the recommended procedure of the Spanish Society of Pulmonology and Thoracic Surgery (SEPAR) for the collection and preservation of the sample<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>, while the venous blood samples were obtained by venipuncture, usually from the cubital vein, but also from the cephalic or the basilic veins.</p><p id="par0020" class="elsevierStylePara elsevierViewall">The above-mentioned gases were analyzed using Rapidpoint 405 gas measurement systems (Siemens, Munich, Germany), equipped with cooximetry for the measurement of oxygen saturation, either in arterial (SaO<span class="elsevierStyleInf">2</span>) or systemic venous blood (SvO<span class="elsevierStyleInf">2</span>). Standard blood gas parameters were also obtained. Quality controls were calibrated as recommended by the suppliers, with 3 liquid calibration runs daily. Results of these variables in each of the groups were compared with results obtained using the equations of Kelman, Severinghaus, and Siggaard-Andersen<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10–12</span></a>, which estimate values mainly from the measurement of PaO<span class="elsevierStyleInf">2</span>, while taking into account deviations from the saturation curve. Blood hemoglobin was also available at the time of puncture, as it is provided by the same gas analyzer (normal values in our laboratory, 12.0–17.0 g/dL). General blood tests in Covid-19 patients also include ferritin in blood (normal values in our laboratory, 30–400 ng/mL) evaluated by sandwich electrochemiluminescent immunoassay (ECLIA)(Cobas 8000 e801 analyzer, Roche, Basel, Switzerland).</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0025" class="elsevierStylePara elsevierViewall">After confirming the normality of distribution, the values of the variables were displayed as mean and standard deviation from the mean. The measured and calculated values of SaO<span class="elsevierStyleInf">2</span> and SvO<span class="elsevierStyleInf">2</span> for the same group were compared with 2-way random ANOVA, with intra-class correlation (ICC) to express consistency. The same approach was used for comparisons between the three groups. The relationship between variables was analyzed with Pearson's coefficient and linear regression. A concordance analysis was also performed using the Bland-Altman plot, based on the mean of the differences<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>. Since a plateau effect can occur in SaO<span class="elsevierStyleInf">2</span> at PaO<span class="elsevierStyleInf">2</span> levels over 100 mmHg, an additional post-hoc analysis was performed censoring these values. A p-value of <0.05 was considered significant in all tests.</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><p id="par0030" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the most relevant general and clinical characteristics of patients, while <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows mean arterial and venous blood gases for each of the 3 groups. In the Covid-19 group, SaO<span class="elsevierStyleInf">2</span> measured by cooximetry was almost identical to the results calculated using the different equations (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). The results were similar in venous blood. The correlation between measured and calculated SaO<span class="elsevierStyleInf">2</span> and between measured and calculated SvO<span class="elsevierStyleInf">2</span> was also very high, with the regression line very close to the identity line (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a> of the manuscript and figure A(a) of the online supplement <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>); these results were also corroborated by the consistency analysis, in which ICC values were always higher than 0.98 (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). This is also shown in the Bland-Altman plot (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). The patients showed mean partial pressure of carbon dioxide (PCO<span class="elsevierStyleInf">2</span>) and pH within normal ranges in both arterial and venous blood. There were no relationships of interest between clinical variables and the differences between measured and calculated saturations.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">The results did not differ substantially in either control group, nor did the synchronous group of patients with negative PCR for SARS-CoV-2 show differences between measured saturation and saturation calculated with the different equations in either arterial or venous blood. The same was true of the group of patients without infectious disease who had gas analysis performed in the months before the pandemic. In these 2 cases, correlations and ICC were also highly significant. Hemoglobin and ferritin were somewhat higher in the Covid-19 group compared with both control groups.</p><p id="par0040" class="elsevierStylePara elsevierViewall">In the post-hoc analysis, which excluded measurements with PaO<span class="elsevierStyleInf">2</span> values greater than 100 mmHg, no differences were observed between measured SaO<span class="elsevierStyleInf">2</span> and SaO<span class="elsevierStyleInf">2</span> values calculated using any of the 3 equations and for any of the 3 study groups (Appendix <a class="elsevierStyleCrossRef" href="#sec0055">B</a> Tables A and B, and Figure A of the online supplement).</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Discussion</span><p id="par0045" class="elsevierStylePara elsevierViewall">The main finding of this study is that active SARS-CoV-2 infection does not substantially change the PaO<span class="elsevierStyleInf">2</span>:SaO<span class="elsevierStyleInf">2</span> relationship. This is of particular importance in the clinical management of patients with pulmonary involvement due to Covid-19. Furthermore, there was no impairment of oxygen affinity for hemoglobin in venous blood, nor was this molecule reduced by infection.</p><p id="par0050" class="elsevierStylePara elsevierViewall">A recent <span class="elsevierStyleItalic">in silico</span> study suggested that various viral surface proteins (such as ORF8 and perhaps some other glycoprotein) might inhibit binding between the iron of the hemoglobin molecule and oxygen<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,14</span></a>, thus impeding the transport of oxygen to tissue, despite adequate PaO<span class="elsevierStyleInf">2</span> being maintained. This would also mean that PaO<span class="elsevierStyleInf">2</span> is only of relative use in the management of patients, since it does not reflect their real oxygenation status<a class="elsevierStyleCrossRefs" href="#bib0035"><span class="elsevierStyleSup">7,14</span></a>. More recently, another group using omic techniques described protein and lipid alterations that affect the membrane of the red blood cell, a situation that could also reduce the affinity of oxygen for hemoglobin at a certain partial pressure of oxygen<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a>. Under normal circumstances, this pressure helps predict hemoglobin saturation with acceptable accuracy, since both variables maintain a known relationship, similar to an italic S. At high or very low oxygen pressures, saturation changes secondary to PaO<span class="elsevierStyleInf">2</span> modifications are relatively small; however, when the oxygen pressure falls below 60 mmHg, saturation declines dramatically<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5,15</span></a>. Of course, certain factors can modify the relationship between both variables, shifting the curve to the left or right. The most important of these are temperature, PaCO<span class="elsevierStyleInf">2</span>, pH and concentration of 2–3-diphosphoglycerate<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a>, as well as the presence of abnormal hemoglobins, as would be the case in SARS-CoV-2 infection. In clinical circumstances, these shifts are not usually taken into account, but they are used to calculate saturation when it cannot be determined directly. This is no longer common because most current gas analyzers include cooximetry. However, as this technique was not widely available until relatively recently, various equations for predicting saturation were developed; of these, Kelman, Severinghaus, and Siggaard-Andersen offer the best concordance with the measured saturation<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10–12,16</span></a>. In our study, these equations predicted the saturation that would correspond to a certain oxygen pressure, taking into account the other factors mentioned, in both arterial and venous blood, in a large sample of patients and blood samples. Our results indicate that saturation calculated using any of the foregoing equations shows no clinically significant difference with saturation measured by cooximetry, strongly undermining in real-world practice the hypothesis that SARS-CoV-2 infection significantly alters the affinity of oxygen for hemoglobin. Very recently, a British group also suggested that this hypothesis could be misleading after a small pilot study of 14 arterial blood gas samples from patients with Covid-19<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a>. Although they used a different methodology based on the calculation of P<span class="elsevierStyleInf">50</span>, their results are consistent with ours. However, the real situation regarding oxygen affinity for hemoglobin in these patients is still under discussion<a class="elsevierStyleCrossRefs" href="#bib0090"><span class="elsevierStyleSup">18,19</span></a>. Our results also remind us of the enormous gap between <span class="elsevierStyleItalic">in silico</span> or <span class="elsevierStyleItalic">in vitro</span> estimates and real-world practice.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The above-mentioned <span class="elsevierStyleItalic">in silico</span> study suggested that other viral proteins, such as orf1ab, ORF3a and ORF10, might denature the structure of the hemoglobin molecule, releasing iron and transforming the preexisting hemo groups to simple porphyrins that lack the capacity to carry oxygen<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a>. This would affect CaO<span class="elsevierStyleInf">2</span> levels, which depend predominantly on hemoglobin-bound oxygen, decreasing supply to the tissues<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a>. Our results do not support this hypothesis, since we found that blood hemoglobin values in patients with Covid-19 were even slightly higher than those of the control groups. However, some studies have reported lower hemoglobin levels in these patients<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20–22</span></a>. In general, these studies have not included control groups of patients with severe disease, in whom blood collection and reduced hemoglobin are very common. However, like us, other authors have reported increases in serum ferritin in patients with Covid-19<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a>, possibly related to this molecule’s role in buffering iron released by hemoglobin<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a>. Iron is essential for viral replication, and this might explain why several viruses can interfere in iron homeostasis<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a>. However, it is not yet known whether this could also be the case with SARS-CoV-2. Macrophages also play an important role in the regulation of iron homeostasis, as they prevent the release of hemoglobin molecules by red blood cells<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a>. However, an excess of hemo groups can also help activate the innate immune system, triggering proinflammatory macrophage orientation<a class="elsevierStyleCrossRefs" href="#bib0130"><span class="elsevierStyleSup">26,27</span></a>, which appears to be a key trigger of the Covid-19 cytokine storm<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a>.</p><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Study limitations</span><p id="par0060" class="elsevierStylePara elsevierViewall">We should point out that some patients in our SARS-CoV-2 PCR-negative control group may have had Covid-19, since the sensitivity of this test is not 100%, and some may have been in a low viral replication phase. For this reason, we added a second control group of patients who were hospitalized before Covid-19 cases were detected in our setting.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Furthermore, some samples reported as arterial blood may in reality have been venous samples, although this possibility was minimized as far as possible. However, in these cases the similarity between measured and calculated saturation would also support the study premise, despite the minimum distortion of the overall values of samples classified as arterial or venous. There is also some degree of uncertainty regarding the actual shift in the hemoglobin saturation curve, since some minor factors influencing this shift were unavailable. Nevertheless, all the most relevant components were included in the equations.</p><p id="par0070" class="elsevierStylePara elsevierViewall">It is important to note that hemoglobin levels in patients in our Covid-19 group were slightly higher than in the other 2 groups, unlike some results reported in the literature (mainly in patients with severe disease or comorbidities)<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,21–23</span></a>, and suggested in one of the two above mentioned articles that analyzed the mechanisms behind hemoglobin denaturation<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a>. This also meant that a somewhat higher blood oxygen content was found in the Covid-19 group. We believe that hemoglobin levels were maintained in patients with Covid-19 because during the pandemic blood extractions were strictly limited, even for purely medical sampling. For studies, a single sample was obtained, which was stored in the Spanish National Biobank Network. In addition, our series includes patients with moderate levels of severity.</p><p id="par0075" class="elsevierStylePara elsevierViewall">Finally, it would have been useful to have P<span class="elsevierStyleInf">50</span> determination (PaO<span class="elsevierStyleInf">2</span> corresponding to a SaO<span class="elsevierStyleInf">2</span> of 50%) as a complement to the equations for predicting SaO<span class="elsevierStyleInf">2</span>, but the particularly dramatic circumstances of the Covid-19 pandemic did not allow such an approach. The equations used provide a sufficiently accurate estimate of the relationship between PaO<span class="elsevierStyleInf">2</span> and SaO<span class="elsevierStyleInf">2</span><span class="elsevierStyleSup">165</span>.</p><p id="par0080" class="elsevierStylePara elsevierViewall">In conclusion, our study is a reliable representation of real-world clinical practice, and shows that the SARS-CoV-2 virus does not appear to significantly affect the affinity of oxygen for the hemoglobin molecule or denature the hemo group. Therefore, the use of PaO<span class="elsevierStyleInf">2</span> to assess oxygenation status remains valid in Covid-19 patients</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Funding</span><p id="par0085" class="elsevierStylePara elsevierViewall">Funded by an unrestricted grant from <span class="elsevierStyleGrantSponsor" id="gs0005">Boehringer-Ingelheim</span> and the <span class="elsevierStyleGrantSponsor" id="gs0010">Catalan Foundation for Respiratory Medicine (FUCAP)</span>.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1642739" "titulo" => "Graphical abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:3 [ "identificador" => "xres1642740" "titulo" => "Abstract" "secciones" => array:5 [ 0 => array:1 [ "identificador" => "abst0010" ] 1 => array:2 [ "identificador" => "abst0015" "titulo" => "Objective" ] 2 => array:2 [ "identificador" => "abst0020" "titulo" => "Methods" ] 3 => array:2 [ "identificador" => "abst0025" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0030" "titulo" => "Conclusion" ] ] ] 2 => array:2 [ "identificador" => "xpalclavsec1464378" "titulo" => "Keywords" ] 3 => array:3 [ "identificador" => "xres1642738" "titulo" => "Resumen" "secciones" => array:5 [ 0 => array:1 [ "identificador" => "abst0035" ] 1 => array:2 [ "identificador" => "abst0040" "titulo" => "Objetivo" ] 2 => array:2 [ "identificador" => "abst0045" "titulo" => "Métodos" ] 3 => array:2 [ "identificador" => "abst0050" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0055" "titulo" => "Conclusiones" ] ] ] 4 => array:2 [ "identificador" => "xpalclavsec1464379" "titulo" => "Palabras clave" ] 5 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 6 => array:3 [ "identificador" => "sec0010" "titulo" => "Method" "secciones" => array:2 [ 0 => array:3 [ "identificador" => "sec0015" "titulo" => "Techniques" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0020" "titulo" => "Arterial and venous blood gas analyses" ] ] ] 1 => array:2 [ "identificador" => "sec0025" "titulo" => "Statistical analysis" ] ] ] 7 => array:2 [ "identificador" => "sec0030" "titulo" => "Results" ] 8 => array:3 [ "identificador" => "sec0035" "titulo" => "Discussion" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Study limitations" ] ] ] 9 => array:2 [ "identificador" => "sec0045" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "xack579985" "titulo" => "Acknowledgements" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2020-08-06" "fechaAceptado" => "2021-03-17" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1464378" "palabras" => array:4 [ 0 => "COVID-19" 1 => "Hemoglobin" 2 => "Oxygen" 3 => "SARS-CoV-2" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1464379" "palabras" => array:4 [ 0 => "COVID-19" 1 => "Hemoglobina" 2 => "Oxígeno" 3 => "SARS-CoV-2" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Pulmonary involvement in COVID-19 is frequently associated with alterations in oxygenation. The arterial partial pressure of oxygen (PaO<span class="elsevierStyleInf">2</span>) is the most clinically used variable to assess such oxygenation, since it decisively influences the oxygen transported by hemoglobin (expressed by its percentage of saturation, SaO<span class="elsevierStyleInf">2</span>). However, two recent studies conducted respectively <span class="elsevierStyleItalic">in silico</span> and using omic techniques in red blood cells of COVID-19 patients have suggested that SARS-CoV-2 could decrease the affinity of oxygen for the hemoglobin (which would imply that PaO<span class="elsevierStyleInf">2</span> would overestimate SaO<span class="elsevierStyleInf">2</span>), and also reduce the amount of this carrier molecule.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objective</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">To evaluate this hypothesis in blood samples from COVID-19 patients.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Methods</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Blood gases of all COVID-19 patients performed in our laboratory in two months were included, as well as those from two control groups: synchronous patients with negative PCR for SARS-CoV-2 (SCG) and a historical group (HCG). Both SaO<span class="elsevierStyleInf">2</span> and venous saturations (SvO<span class="elsevierStyleInf">2</span>) measured by cooximetry (COX) were compared separately with those calculated using the Kelman (K), Severinghaus (SV) and Siggaard-Andersen (SA) equations in each group.</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Measured and calculated SaO<span class="elsevierStyleInf">2</span> and SvO<span class="elsevierStyleInf">2</span> were practically equivalent in all groups. Intraclass correlation coefficients (ICC) for SaO<span class="elsevierStyleInf">2</span> in COVID-19 were 0.993 for COX-K and 0.992 for both COX-SV and COX-SA; being 0.995 for SvO<span class="elsevierStyleInf">2</span> for either COX-K, COX-SV or COX-SA. Hemoglobin and ferritin were slightly higher in COVID-19 compared to SCG and HCG (hemoglobin, p < 0.001 for both; ferritin, p < 0.05 for SCG and p < 0.001 for HCG).</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Under clinical conditions SARS-CoV-2 does not have an appreciable influence on the affinity of oxygen for the hemoglobin, nor on the levels of this carrier molecule. Therefore, PaO<span class="elsevierStyleInf">2</span> is a good marker of blood oxygenation also in COVID-19.</p></span>" "secciones" => array:5 [ 0 => array:1 [ "identificador" => "abst0010" ] 1 => array:2 [ "identificador" => "abst0015" "titulo" => "Objective" ] 2 => array:2 [ "identificador" => "abst0020" "titulo" => "Methods" ] 3 => array:2 [ "identificador" => "abst0025" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0030" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0035" class="elsevierStyleSection elsevierViewall"><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">La afectación pulmonar por COVID-19 se asocia frecuentemente con alteraciones en la oxigenación. La presión parcial arterial de oxígeno (PaO<span class="elsevierStyleInf">2</span>) es la variable más utilizada clínicamente para valorar dicha oxigenación, ya que influye decisivamente en el oxígeno transportado por la hemoglobina (expresado por porcentaje de saturación, SaO<span class="elsevierStyleInf">2</span>). Sin embargo, dos estudios recientes realizados respectivamente <span class="elsevierStyleItalic">in silico</span> y mediante técnicas ómicas en hematíes de pacientes han sugerido que SARS-CoV-2 podría disminuir la afinidad del oxígeno por la hemoglobina (lo que implicaría que la PaO<span class="elsevierStyleInf">2</span> sobrevaloraría la SaO<span class="elsevierStyleInf">2</span> real), e incluso reduciría la cantidad de esta molécula transportadora.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Objetivo</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Evaluar dicha hipótesis en muestras gasométricas de pacientes con COVID-19.</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Métodos</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron las gasometrías de todos los pacientes con COVID-19 realizadas en nuestro laboratorio, así como las de dos grupos control: pacientes sincrónicos con PCR negativa (GCS) y grupo histórico (GCH). Se compararon por separado las SaO<span class="elsevierStyleInf">2</span> y saturaciones venosas (SvO<span class="elsevierStyleInf">2</span>), medidas por cooximetría (COX) con las calculadas mediante las ecuaciones de Kelman (K), Severinghaus (SV) y Siggaard-Andersen (SA) en cada grupo.</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Resultados</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">Las cifras de SaO<span class="elsevierStyleInf">2</span> y SvO<span class="elsevierStyleInf">2</span> medidas y calculadas fueron prácticamente superponibles en todos los grupos. Así, los coeficientes de correlación intraclase (CCI) en COVID-19 para SaO<span class="elsevierStyleInf">2</span> fueron 0,993 en COX-K y 0,992 en COX-SV y COX-SA; siendo 0,995 para SvO<span class="elsevierStyleInf">2</span> tanto en COX-K como en COX-SV y COX-SA. La hemoglobina y la ferritina resultaron algo superiores en el grupo COVID-19 respecto de GCS y GCH (hemoglobina, p < 0,001 en ambos; ferritina, p < 0,05 para GCS y p < 0,001 para GCH).</p></span> <span id="abst0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conclusiones</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">En condiciones clínicas, el SARS-CoV-2 no influye de forma apreciable en la afinidad del oxígeno por la hemoglobina, ni tampoco en los niveles de esta última. Por tanto, la PaO<span class="elsevierStyleInf">2</span> es un buen marcador de oxigenación sanguínea también en COVID-19.</p></span>" "secciones" => array:5 [ 0 => array:1 [ "identificador" => "abst0035" ] 1 => array:2 [ "identificador" => "abst0040" "titulo" => "Objetivo" ] 2 => array:2 [ "identificador" => "abst0045" "titulo" => "Métodos" ] 3 => array:2 [ "identificador" => "abst0050" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0055" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Pascual-Guàrdia S, Ferrer A, Díaz Ó, Caguana AO, Tejedor E, Bellido-Calduch S, et al. Ausencia de efectos clínicos destacables del SARS-CoV-2 sobre la afinidad de la hemoglobina por el O<span class="elsevierStyleInf">2</span> en pacientes con COVID-19. Arch Bronconeumol. 2021;57:757–763.</p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0100" class="elsevierStylePara elsevierViewall">The following is Supplementary data to this article:<elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0055" ] ] ] ] "multimedia" => array:7 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1810 "Ancho" => 3333 "Tamanyo" => 380155 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Relationships between saturation measured by cooximetry and saturation calculated using the equations of (a) Kelman, (b) Severinghaus, and (c) Siggaard-Andersen for arterial blood, and for venous blood (d), (e), and (f), respectively.</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1790 "Ancho" => 3333 "Tamanyo" => 419806 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Bland-Altman plots for the differences between measured saturation and saturation calculated by the three equations used in the study, for both arterial blood (a), (b), and (c), and systemic venous blood (d), (e) and (f). The solid line represents the mean between the measured and calculated values. Dashed lines represent the mean ± 1.96 x standard deviation (95% confidence interval).</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Rx: Plain radiology; ARDS: acute respiratory distress syndrome; AHT: arterial hypertension; COPD: chronic obstructive pulmonary disease.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \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">Arterial blood \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">Venous blood \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \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">n = 139 \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">n = 215 \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 " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">General data</span></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 ± 17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 ± 13 \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">Women (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 \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">Active smoker (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Former smoker (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 \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">Alcohol intake > 100 g/d (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Body mass index (kg/m<span class="elsevierStyleSup">2</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22.3 ± 3.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.3 ± 10 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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 " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">Clinical presentation</span></span></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">Fever > 38 °C (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cough (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Dyspnea (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76 \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">Asthenia (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Anorexia (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \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">Tachycardia > 100 beats/min (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 \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">Tachypnea > 20 breaths/min (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">No radiological involvement (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 \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">Unilateral Rx involvement (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 \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">Bilateral Rx involvement (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 \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">ARDS (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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">Multiorgan failure (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \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">Death during admission (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Relevant comorbidities (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68 \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">AHT (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Dyslipidemia (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Chronic renal disease (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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 mellitus (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \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 (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Bronchial asthma (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Sleep apnea (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \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">Heart failure (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Obesity (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cancer (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2798302.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">General and clinical data of Covid-19 patients included in the study.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">BE: base excess; Bic.: bicarbonate; CaO<span class="elsevierStyleInf">2</span>: oxygen in arterial blood; COVID-19: coronavirus disease of 2019; CvO<span class="elsevierStyleInf">2</span>: oxygen in venous blood; PaO<span class="elsevierStyleInf">2</span>: partial pressure of oxygen in arterial blood; PaCO<span class="elsevierStyleInf">2</span>: partial pressure of carbon dioxide in arterial blood; pH: potential of hydrogen; PvCO<span class="elsevierStyleInf">2</span>: partial pressure of carbon dioxide in venous blood; PvO<span class="elsevierStyleInf">2</span>: partial pressure of oxygen in venous blood.</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Significance levels between historical control and Covid-19 patients:</p><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">* p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001.</p><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Significance levels between synchronous controls and Covid-19 patients: <span class="elsevierStyleSup">+</span> p ≤ 0.05; <span class="elsevierStyleSup">++</span> p ≤ 0.01; <span class="elsevierStyleSup">+++</span> p ≤ 0.001.</p>" "tablatextoimagen" => array:2 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"><span class="elsevierStyleBold">a) Arterial blood</span> \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">Historical control group \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">Synchronous control group \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">Covid-19 patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \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">n = 1089 \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">n = 73 \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">n = 139 \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 (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">69 ± 18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 ± 18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 ± 17 \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">Women (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 \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">Number of blood gas analyses (n) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2614 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">251 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">549 \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">PaO<span class="elsevierStyleInf">2</span> (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87 ± 46 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 ± 28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 ± 33 \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">CaO<span class="elsevierStyleInf">2</span> (ml/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.2 ± 4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.5 ± 3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.5 ± 3.2***<span class="elsevierStyleSup">+++</span> \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">PaCO<span class="elsevierStyleInf">2</span> (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43.5 ± 12.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42.0 ± 12.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39.4 ± 10.5***<span class="elsevierStyleSup">++</span> \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">pH \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 ± 0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.41 ± 0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.42 ± 0.08*** \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">Bic. Standard (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.4 ± 5.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.8 ± 7.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24.6 ± 4.0***<span class="elsevierStyleSup">+</span> \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">BE (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.7 ± 4.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3 ± 4.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.7 ± 3.9***<span class="elsevierStyleSup">++</span> \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">Hb (g/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.4 ± 2.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.8 ± 2.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13.3 ± 1.8***<span class="elsevierStyleSup">+++</span> \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">Ferritin (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">553 ± 690 (NR<span class="elsevierStyleSup">1</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">725 ± 687 (NR<span class="elsevierStyleSup">2</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1280 ± 1628***<span class="elsevierStyleSup">+</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2798303.png" ] ] 1 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"><span class="elsevierStyleBold">b) Venous blood</span> \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">Historical control group \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">Synchronous control group \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">Covid-19 patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \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">n = 1461 \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">n = 379 \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">n = 215 \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 (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 ± 23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 ± 22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 ± 18 \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">Sex (women, %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 \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">Number of blood gas analyses (n) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3098 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1069 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">544 \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">PvO<span class="elsevierStyleInf">2</span> (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 ± 9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 ± 9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 ± 9 \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">PvCO<span class="elsevierStyleInf">2</span> (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.7 ± 10.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.8 ± 10.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.8 ± 9.2*<span class="elsevierStyleSup">+</span> \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">CvO<span class="elsevierStyleInf">2</span> (ml/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.3 ± 5.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.8 ± 5.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.2 ± 5.2*<span class="elsevierStyleSup">++</span> \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">pH \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.37 ± 0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.36 ± 0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.38 ± 0.06***<span class="elsevierStyleSup">+++</span> \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">Bic. Standard (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24.0 ± 4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.8 ± 5.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24.4 ± 4.0*<span class="elsevierStyleSup">++</span> \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">BE (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3 ± 4.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.2 ± 4.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 4.1***<span class="elsevierStyleSup">+++</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2798301.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Arterial and venous blood gases in the different patient groups.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">ICC: intraclass correlation coefficient; SaO<span class="elsevierStyleInf">2</span>: oxygen saturation in arterial blood; SvO<span class="elsevierStyleInf">2</span>: oxygen saturation in venous blood.</p>" "tablatextoimagen" => array:2 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">a) Arterial blood</span> \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">Historical control group \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">Synchronous control group \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">Covid-19 patients \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">Measured SaO<span class="elsevierStyleInf">2</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.4 ± 4.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.8 ± 4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.0 ± 3.9 \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">SaO<span class="elsevierStyleInf">2</span> Kelman (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.5 ± 5.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.9 ± 4.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.0 ± 3.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs. Measured SaO<span class="elsevierStyleInf">2</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.989 [0.988−0.990] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.991 [0.988−0.993] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.993 [0.991−0.994] \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">SaO<span class="elsevierStyleInf">2</span> Kelman (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.5 ± 5.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.0 ± 4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.0 ± 4.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs. Measured SaO<span class="elsevierStyleInf">2</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.987 [0.986−0.988] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.990 [0.987−0.993] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.992 [0.991−0.993] \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">SaO<span class="elsevierStyleInf">2</span> Siggaard-Andersen (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.4 ± 5.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.8 ± 4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.8 ± 3.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs. Measured SaO<span class="elsevierStyleInf">2</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.987 [0.986−0.988] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.991 [0.988−0.993] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.992 [0.990−0.994] \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2798305.png" ] ] 1 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">b) Venous blood</span> \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">Historical control group \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">Synchronous control group \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">Covid-19 patients \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">Measured SaO<span class="elsevierStyleInf">2</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.3 ± 17.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.1 ± 18.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.6 ± 18.8 \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">SaO<span class="elsevierStyleInf">2</span> Kelman (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 ± 17.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.5 ± 17.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.1 ± 18.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs. measured SaO<span class="elsevierStyleInf">2</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.991 [0.990−0.991] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.990 [0.988−0.991] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.995 [0.994−0.996] \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">SaO<span class="elsevierStyleInf">2</span> Severinghaus (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.1 ± 18.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.6 ± 18.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.4 ± 19.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs.</span> measured SvO<span class="elsevierStyleInf">2</span> SvO<span class="elsevierStyleInf">2</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.990 [0.989−0.990] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.989 [0.987−0.990] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.995 [0.994−0.996] \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">Siggaard-Andersen (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.2 ± 18.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.6 ± 18.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.4 ± 19.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">ICC vs. measured SaO<span class="elsevierStyleInf">2</span></span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.990 [0.989−0.990] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.989 [0.987−0.990] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.995 [0.994−0.996] \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2798304.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Comparison between hemoglobin saturation measured by oximetry and calculated with the different prediction equations.</p>" ] ] 5 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.pdf" "ficheroTamanyo" => 242412 ] ] 6 => array:5 [ "identificador" => "fig0015" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 739 "Ancho" => 1333 "Tamanyo" => 81752 ] ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:28 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 12 | 4 | 16 |
| 2024 October | 76 | 23 | 99 |
| 2024 September | 50 | 20 | 70 |
| 2024 August | 80 | 43 | 123 |
| 2024 July | 135 | 28 | 163 |
| 2024 June | 61 | 25 | 86 |
| 2024 May | 82 | 25 | 107 |
| 2024 April | 50 | 22 | 72 |
| 2024 March | 57 | 18 | 75 |
| 2024 February | 58 | 26 | 84 |
| 2024 January | 54 | 28 | 82 |
| 2023 December | 71 | 28 | 99 |
| 2023 November | 48 | 19 | 67 |
| 2023 October | 113 | 30 | 143 |
| 2023 September | 74 | 33 | 107 |
| 2023 August | 58 | 29 | 87 |
| 2023 July | 66 | 30 | 96 |
| 2023 June | 51 | 15 | 66 |
| 2023 May | 87 | 15 | 102 |
| 2023 April | 72 | 28 | 100 |
| 2023 March | 125 | 19 | 144 |
| 2023 February | 65 | 21 | 86 |
| 2023 January | 61 | 38 | 99 |
| 2022 December | 109 | 34 | 143 |
| 2022 November | 108 | 51 | 159 |
| 2022 October | 99 | 37 | 136 |
| 2022 September | 87 | 32 | 119 |
| 2022 August | 76 | 44 | 120 |
| 2022 July | 73 | 52 | 125 |
| 2022 June | 182 | 49 | 231 |
| 2022 May | 75 | 36 | 111 |
| 2022 April | 90 | 44 | 134 |
| 2022 March | 136 | 64 | 200 |
| 2022 February | 54 | 27 | 81 |
| 2022 January | 212 | 0 | 212 |
| 2021 December | 338 | 5 | 343 |
| 2021 November | 27 | 6 | 33 |
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