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array:22 [ "pii" => "S0025775321005285" "issn" => "00257753" "doi" => "10.1016/j.medcli.2021.08.003" "estado" => "S300" "fechaPublicacion" => "2022-07-22" "aid" => "5808" "copyright" => "Elsevier España, S.L.U.. All rights reserved" "copyrightAnyo" => "2021" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2022;159:59-64" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "itemSiguiente" => array:19 [ "pii" => "S0025775321006473" "issn" => "00257753" "doi" => "10.1016/j.medcli.2021.09.031" "estado" => "S300" "fechaPublicacion" => "2022-07-22" "aid" => "5848" "copyright" => "Elsevier España, S.L.U." "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Clin. 2022;159:65-72" "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" => "Benefits of SGLT2 inhibitors combining with renin–angiotensin-system blockers on cardiovascular outcomes in chronic kidney disease patients: A systemic review and meta-analysis" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "65" "paginaFinal" => "72" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Beneficios de los inhibidores de SGLT2 combinados con bloqueadores del sistema renina-angiotensina en los resultados cardiovasculares de los pacientes con enfermedad renal crónica: una revisión sistémica y un metaanálisis" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0035" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1860 "Ancho" => 2175 "Tamanyo" => 244414 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Forest plot of meta-analyses comparing renal outcomes of combination therapy with SGLT2 inhibitors and RAS blockers versus placebo.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Ting Liu, Rui Li, Xiaoxia Wang, Xingxing Gao, Xiaodong Zhang" "autores" => array:5 [ 0 => array:2 [ "nombre" => "Ting" "apellidos" => "Liu" ] 1 => array:2 [ "nombre" => "Rui" "apellidos" => "Li" ] 2 => array:2 [ "nombre" => "Xiaoxia" "apellidos" => "Wang" ] 3 => array:2 [ "nombre" => "Xingxing" "apellidos" => "Gao" ] 4 => array:2 [ "nombre" => "Xiaodong" "apellidos" => "Zhang" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2387020622003151" "doi" => "10.1016/j.medcle.2021.09.027" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020622003151?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775321006473?idApp=UINPBA00004N" "url" => "/00257753/0000015900000002/v1_202207080542/S0025775321006473/v1_202207080542/en/main.assets" ] "en" => array:20 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "High-resolution computed tomography (HRCT) analysis in anti-synthase antibody syndrome with organizing pneumonia" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "59" "paginaFinal" => "64" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Xueren Li, Qi Wu, Shouchun Peng, Huarui Zhang, Yuhua Zhang" "autores" => array:5 [ 0 => array:3 [ "nombre" => "Xueren" "apellidos" => "Li" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 1 => array:4 [ "nombre" => "Qi" "apellidos" => "Wu" "email" => array:2 [ 0 => "haiheyywuqi@163.com" 1 => "wq572004@163.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 2 => array:4 [ "nombre" => "Shouchun" "apellidos" => "Peng" "email" => array:1 [ 0 => "pengshouchun@163.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 3 => array:3 [ "nombre" => "Huarui" "apellidos" => "Zhang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 4 => array:3 [ "nombre" => "Yuhua" "apellidos" => "Zhang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Department of Respiratory Medicine, Haihe Clinical College of Tianjin Medical University, Tianjin 300350, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Tianjin Institute of Respiratory Diseases, Tianjin 300350, China" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Department of Emergency, Haihe Hospital, Tianjin University, Tianjin 300350, China" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Department of Respiratory and Critical Care Medicine, Pingjin Hospital, Tianjin 300162, China" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding authors." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Análisis por tomografía computarizada de alta resolución (TCAR) del síndrome de anticuerpos antisintéticos con un patrón de neumonía organizada" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1456 "Ancho" => 2083 "Tamanyo" => 116035 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">The FVC% has a linear relationship with mean lung attenuation of the extracted whole lung volume with attenuation values of the poorly aerated and fibrosis.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Idiopathic inflammatory myositis (IIM) is a subgroup of connective tissue diseases (CTDs) that has both muscular and extramuscular lesions.<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">1,2</span></a> Interstitial pneumonia (IP) is a frequent and challenging issue for IIM patients. Anti-synthase antibody syndrome (ASS) is a specific subtype characterised by IP, inflammatory arthritis, fever, Raynaud's phenomenon, and mechanical hands,<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">3</span></a> and anti-Jo1, PL7, PL12, or EJ antibodies are commonly present. The clinical presentation and course of ASS in patients is similar, regardless of the specific antibody responsible, because this syndrome has similar characteristics and triad feature types across patients.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">4</span></a> High-resolution computed tomography (HRCT) often shows nonspecific interstitial pneumonia (NSIP) or organizing pneumonia (OP) as the major manifestations seen in IIM-IP patients.<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">OP is a histopathological term characterized by polypoid granulation tissue called Masson bodies, which consist of connective tissue components, fibrin, and fibroblasts, deposited in the alveolar ducts and alveoli.<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">6</span></a> Crop organizing pneumonia (COP) is the most common form and can also be secondary to other diseases, such as hypersensitivity pneumonia, connective tissue diseases (CTDs), and eosinophilic pneumonia. An OP pattern often predicts a good prognosis because this condition rapidly improves with glucocorticoid therapy. Recently, HRCT analysis has been widely used with both semiquantitative and quantitative methods. Therefore, we designed a study to investigate two semiquantitative methods using digital imaging and communications in medicine (DICOM) viewers to evaluate and score the OP patterns in ASS patients, and we acquired differently aerated lung compartment quantitative parameters by the workstation for modelling. In addition, this study aimed to assess the value of the different analysis methods to analyse the OP patterns on the HRCT.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Patient</span><p id="par0015" class="elsevierStylePara elsevierViewall">Fourteen patients were enrolled in this study and were admitted to the respiratory department of the Ping Jin Hospital from October 2014 to June 2020. A patient diagnosed with ASS-OP had to meet the criterion of interstitial lung disease guidelines for inclusion in this study: the British Thoracic Society in collaboration with the Thoracic Society of Australia and New Zealand and the Irish Thoracic Society.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">7</span></a> The patients had to meet the criteria proposed by Connors and colleagues to be included in this study: the presence of anti-tRNA plus one or more of the following clinical features: Raynaud's phenomenon, arthritis, interstitial lung disease, fever, and mechanic's hands.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">8,9</span></a> We reviewed and recorded the patients’ basic information, including age, sex, smoking history, laboratory test results, the HRCT findings, the clinical data of patients, especially the symptoms involving the respiratory and rheumatology systems, and the treatment strategies. This study was a retrospective design and was approved by the local Institutional Ethics Committee approval (Registration No: 2019-0007).</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Chest CT imaging data</span><p id="par0020" class="elsevierStylePara elsevierViewall">HRCT imaging was performed with a 16- or 64-section multidetector CT scanner set with the following variables: 120<span class="elsevierStyleHsp" style=""></span>kV with a field of view according to the clinical needs (range, 360–500<span class="elsevierStyleHsp" style=""></span>mm), a reconstruction matrix of 512<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>512, a pitch factor of 0.984–1.375, a collimation of 64<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>0.625<span class="elsevierStyleHsp" style=""></span>mm, and a rotation time of 0.4–0.8<span class="elsevierStyleHsp" style=""></span>s. The DICOM formatted images were obtained and stored for analysis.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">HRCT evaluation</span><p id="par0025" class="elsevierStylePara elsevierViewall">Semiquantitative analysis (SQL) is a form of visual judgement performed by two chest radiologists with 10 years of experience. The OP pattern was characterized by ground-glass opacity (GGO) and consolidation (CO) patterns.<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">10</span></a> The SQL was carried out by two methods. Method-1: To score the interstitial parenchymal disease with the OP pattern, we used the extent of these abnormalities at 3 representing lung levels: (1) the aortic arch; (2) subcarinal area consisting of 2<span class="elsevierStyleHsp" style=""></span>cm; (3) 2<span class="elsevierStyleHsp" style=""></span>cm above the diaphragm, and 3 parts at each level (sternal side, spin side, and central part). Eighteen anatomic locations involving the GGOs and CO patterns were analysed. The extent of these abnormalities and the overall extent of the lesions were determined for each lung using a 3-point scale (0: no involvement, 1: ≤1/3 involvement, 2:1/3 to 2/3 involvement, 3: ≥2/3 involvement).<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">11,12</span></a> Method-2: To evaluate these abnormalities, Method-1 represented the lung levels. A 4-point scale (0: no involvement, 1: 1–25% involvement, 2: 26–50% involvement, 3: 51–75% involvement, and 4: 76–100% involvement) was used. Each lobe score was composed of the GGO and CO pattern scores.<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">13,14</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">Imaging data was inputted and transformed into a commercially available quantitative analysis (QL) workstation. In each slice, the operator manually outlined the lung borders by selecting the whole lung tissue but excluding the heart, the central airways, and the major blood vessels. The total lung volume (TLV) was defined as the lung parenchymal volume excluding the total volume of the bronchus and pulmonary vessels. The TLV and mean lung attenuation (MA) were calculated by the workstation. The attenuation area ranges had to cover the consolidation areas in the HRCT patterns of ASS patients, so they were used to differentially define the aerated lung compartments: non-aerated, −100 to +100 Hounsfield units (Hu), which represented the areas of pulmonary consolidation<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">15</span></a>; poorly aerated and fibrosis (fibrosis), −101 to −500<span class="elsevierStyleHsp" style=""></span>Hu, which represented the areas of ground-glass opacity and reticulation; normally lung aerated (normal), −501 to −900<span class="elsevierStyleHsp" style=""></span>Hu; and hyperinflated (hyper), −901 to −1000<span class="elsevierStyleHsp" style=""></span>Hu.<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">16,17</span></a> The Volume % and weight % of the attenuation area were calculated as percentages of the extracted whole lung volume with attenuation values ranging from 100 to −1000<span class="elsevierStyleHsp" style=""></span>Hu.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">9,11</span></a> A <span class="elsevierStyleItalic">μ</span> value was assigned to each voxel (<span class="elsevierStyleItalic">μ</span> voxel), which was roughly proportional to its density, and was expressed as a CT number standardized to the density of water. Proportional weights were also measured.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">PFTs</span><p id="par0035" class="elsevierStylePara elsevierViewall">PFTs were performed by a spirometer (JAEGER Master Screen) and were used for the diagnosis and monitoring of ARS patients. The PFTs included carbon monoxide diffusion (DLCO), airway obstruction, and restrictive ventilation abnormalities. The following variables were recorded: forced vital capacity (FVC), forced expiratory volume in 1 second (FEV<span class="elsevierStyleInf">1</span>), FEV1/FVC, and DLCO%.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Statistical analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">Patient data were analysed by SPSS 19.0 (IBM Corp., Armonk, NY, USA) and were expressed as the mean (SD), interquartile range, or as a percentage of the relative frequency based on the differences. Categorical data were compared using the <span class="elsevierStyleItalic">χ</span><span class="elsevierStyleSup">2</span> test or Fisher's exact probability test for independence, and the 95% confidence interval (CI) was used. Correlation analysis between different SQL scores and aerated lung compartment quantitative parameters (<span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, MA<span class="elsevierStyleInf">nonaerated</span>, MA<span class="elsevierStyleInf">fibrosis</span>, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%) were performed. <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 was considered statistically significant.</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Baseline clinical characteristics</span><p id="par0045" class="elsevierStylePara elsevierViewall">Baseline clinical characteristics including patient demographic data, patient symptoms, physical examination findings, laboratory test results, and PFTs are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. Eight female patients and six male patients were diagnosed with ASS-OP during the 6 years, the mean age of the patients was 49.34<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.17 years, and the mean disease duration of the patients was 4.90<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.25 months. The majority of patients had dyspnoea (57.14%) and cough (71.43%). The physical examination data revealed that crackles (92.86%) were heard in almost all of the patients, and skin lesions (35.71%), muscle weakness (50%), and mechanical hands (78.57%) were also common symptoms. The prevalence of antibodies against JO-1, PL-12, PL-7, and EJ was 21.43%, 42.86%, 21.42%, and 14.29%, respectively, among these patients. Arterial blood gas analyses revealed hypoxemia (FiO<span class="elsevierStyleInf">2</span> 21%; PaCO<span class="elsevierStyleInf">2</span> 36.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.40<span class="elsevierStyleHsp" style=""></span>mmHg; PaO<span class="elsevierStyleInf">2</span> 78.64<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.14<span class="elsevierStyleHsp" style=""></span>mmHg) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>) in the patients, and the PFTs showed medium restrictive ventilation abnormalities (FVC%, 60.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.91) and mild carbon monoxide diffusion barriers (DLCO%, 41.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.81).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">SQL and QL of HRCT</span><p id="par0050" class="elsevierStylePara elsevierViewall">The CO, GGO and CO plus GGO (CG) scored by the SQL (method -1 and method -2) and QL parameters (<span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">norma</span>l%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">hyper</span>%, MA<span class="elsevierStyleInf">nonaerated</span>, MA<span class="elsevierStyleInf">fibrosis</span>, MA<span class="elsevierStyleInf">normal</span>, MA<span class="elsevierStyleInf">hyper</span>, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>% and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">hyper</span>%) are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. In method-1, the CO score and MA <span class="elsevierStyleInf">fibrosis</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.56, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.04), the GGO score and MA<span class="elsevierStyleInf">nonaerated</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.64, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01), and the CG score and MA<span class="elsevierStyleInf">nonaerated</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.59, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.03) all had linear correlations (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). In method-2, the GGO score and MA<span class="elsevierStyleInf">nonaerated</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.58, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.03) and the CG (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.68, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) score to MA<span class="elsevierStyleInf">nonaerated</span> also had liner correlations (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). The FVC% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.68, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) and FEV<span class="elsevierStyleInf">1</span>% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.64, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) had linear relationships with the MA<span class="elsevierStyleInf">fibrosis</span> (<a class="elsevierStyleCrossRefs" href="#fig0005">Figs. 1 and 2</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Treatment strategies and follow-up</span><p id="par0055" class="elsevierStylePara elsevierViewall">Patients were prescribed glucocorticoids combined with immunosuppressants. Tacrolimus, cyclosporine, azathioprine, and mycophenolate mofetil were used in 7 (50.00%), 3 (21.43%), 2 (14.29%), 1 (7.15%), and 1 (7.15%) patient, respectively. Ten patients were followed up for 3–6 months, and all of their conditions improved. The SQL and QL analysis indicated that the CO score from Method-2 and the <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, MA<span class="elsevierStyleInf">fibrosis</span>, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>% had significant differences compared to the prior treatment (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>).</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0060" class="elsevierStylePara elsevierViewall">The most common imaging findings in patients with OP are CO and GGO, which are bilaterally and peripherally, OP is the second most common finding in ASS patients, it is second only to NSIP.<a class="elsevierStyleCrossRefs" href="#bib0205"><span class="elsevierStyleSup">18,19</span></a> Debray et al found that NSIP or OP patterns accounted for a large proportion, which was present in 15 out of 33 (45%) patients and 7 out of 33 (21%) patients, respectively. Hui Liu et al reported that an NSIP pattern was found in 44 patients (64%) and OP was found in 13 patients (19%).<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">20</span></a> Based on the history, symptoms, signs, immune antibodies, HRCT, and pulmonary pathology, 14 patients were definitively diagnosed with ASS-OP. The presence of mechanical hands (78.57%) may be one of the characteristic extrapulmonary manifestations, but the antibody specificity partially influences the clinical presentation. Anti-Jo1, PL7, PL12, or EJ antibodies were found in this group, and the positive anti-PL12 was present in the highest proportion of patients.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">4</span></a> PFTs and arterial blood gas analyses were not different in the ASS patients compared to patients with other common interstitial lung diseases, because the patients present with limited dysfunction or diffuse dysfunction and with hypoxemia.</p><p id="par0065" class="elsevierStylePara elsevierViewall">The highlight and focus of this study were the SQL and QL analysis of the HRCT. The SQL for the GGO or CO scores were visual subjective judgements based on the interpretations from two radiologists, and these parameters did not correlate with the FVC% or FEV<span class="elsevierStyleInf">1</span>% in the two SQL methods. However, the quantitative index MA<span class="elsevierStyleInf">fibrosis</span> had a good correlation with the FVC% and FEV1%, indicating that the MA<span class="elsevierStyleInf">fibrosis</span> may be a predictive factor for the results of the PFTs. To evaluate the heterogeneity, the correlations between the semiquantitative and quantitative HRCT were analysed, and the results showed that the GGOs and CG scored by the two SQL methods were related to the MA<span class="elsevierStyleInf">nonaerated</span>. This indicates that there was a certain degree of consistency between the SQL and the SQL based on the OP pattern evaluation and that a simple SQL is an alternative method when conditions are limited. Moreover, the CO score and MA<span class="elsevierStyleInf">fibrosis</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.56, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.04) had a linear correlation, and this suggests that the CO score may be more accurate than the score from method 2.</p><p id="par0070" class="elsevierStylePara elsevierViewall">Patients with OP patterns often have a good prognosis. The uses of corticosteroids in patients with OP leads to rapid clinical improvement and lesion absorption on HRCT, relapses are a common problem that arises when stopping or reducing corticosteroids, and immunosuppressants are sometimes necessary to control the disease,<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">19</span></a> especially in CTD-OP. The primary disease and the immunosuppressants that target the lungs should both be considered during the treatment of ASS-OP patients, and previous studies have shown that Tacrolimus may benefit ASS-OP patients, with functional improvement rates of 86.2% and with manageable safety profiles.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">21</span></a> Seven patients were also prescribed tacrolimus in this retrospective study.</p><p id="par0075" class="elsevierStylePara elsevierViewall">In this study, the extent of CO patterns decreased or disappeared after 3–6 months of follow-up, and this finding is similar to previous research.<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">22,23</span></a> Ten patients were followed up for 3–6 months in our research. The reason that the CO or CG patient scores generally decreased but the GGOs did not significantly change may be that the CO pattern can change to the GGO pattern during the treatment course. Even though the GC calculated from the SQL method showed no significant difference, the parameters from the QL infers that the <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>%, and MA<span class="elsevierStyleInf">fibrosis</span> can provide an accurate analysis of the HRCT in the short-term follow-up. Among these valuable QL parameters, the <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>% were the more valuable indexes compared to the other parameters based on the aggregating data from both the aerated lung volume and the mean lung attenuation.</p><p id="par0080" class="elsevierStylePara elsevierViewall">This study has some limitations. First, it was a retrospective and single-centre study with a relatively small sample size. Second, the quantitative analysis indexes cannot completely represent real world situations due to artificial elimination of the heart, the central airways, and the major blood vessels in the analyses. Third, the follow-up period was only 3–6 months, and the data acquired were limited.</p><p id="par0085" class="elsevierStylePara elsevierViewall">In conclusion, the GGO and CO scored by the semiquantitative or quantitative analysis methods was similar. The HRCT QL index had a good correlation with the PFT parameters in ASS-OP patients. The <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>%, and MA<span class="elsevierStyleInf">fibrosis</span> can provide an accurate OP pattern interpretation and may be used as a monitoring and therapeutic indicator for patients with ASS-OP, but these parameters needs further study.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Funding</span><p id="par0090" class="elsevierStylePara elsevierViewall">None declared.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conflict of interest</span><p id="par0095" class="elsevierStylePara elsevierViewall">None declared.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1744711" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1537460" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1744712" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1537459" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Patient" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Chest CT imaging data" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "HRCT evaluation" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "PFTs" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Baseline clinical characteristics" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "SQL and QL of HRCT" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Treatment strategies and follow-up" ] ] ] 7 => array:2 [ "identificador" => "sec0060" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0065" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0070" "titulo" => "Conflict of interest" ] 10 => array:2 [ "identificador" => "xack616019" "titulo" => "Acknowledgements" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2021-05-12" "fechaAceptado" => "2021-08-26" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1537460" "palabras" => array:4 [ 0 => "Anti-synthase antibody syndrome" 1 => "High-resolution computed tomography" 2 => "Quantitative analysis" 3 => "Organizing pneumonia" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1537459" "palabras" => array:4 [ 0 => "Síndrome de anticuerpos antisintasa" 1 => "Tomografía computarizada de alta resolución" 2 => "Análisis cuantitativo" 3 => "Neumonía organizada" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The organizing pneumonia (OP) pattern is the second most common finding in anti-synthase antibody syndrome (ASS), and nonspecific interstitial pneumonia (NSIP) is the most common finding. This study analysed the OP score changes by semiquantitative and quantitative analysis methods and the correlation between the high-resolution computed tomography (HRCT) indexes and the pulmonary function test parameters (PFTs) in ASS patients.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Data from ASS-OP patients admitted to the respiratory department of Ping Jin Hospital from October 2014 to June 2020 were retrospectively reviewed and analysed.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Fourteen ASS-OP patients were recruited for this study. (1) In method-1, the consolidation (CO) score and the mean lung attenuation (MA) of poorly aerated and fibrosis lung fields (MA<span class="elsevierStyleInf">fibrosis</span>) (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.56, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.04), the ground-glass opacity (GGO) score and the MA of non-aerated lung fields (MA<span class="elsevierStyleInf">nonaerated</span>) (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.64, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01), and the CO plus the GGO (CG) score and the MA<span class="elsevierStyleInf">nonaerated</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.59, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.03) of the lung fields had liner correlations. In method-2, the GGO score to the MA<span class="elsevierStyleInf">nonaerated</span> (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.58, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.03), and the CG (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.68, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) score to the MA<span class="elsevierStyleInf">nonaerated</span> had liner correlations. The FVC% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.68, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) and FEV<span class="elsevierStyleInf">1</span>% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.64, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) to the MA<span class="elsevierStyleInf">fibrosis</span> had good linear correlations. (2) Compared to the values before treatment, the CO pattern score, volume and weight percentages of the extracted whole lung volume with attenuation values of the nonaerated area (<span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%), the volume of poorly aerated and fibrosis lung tissue (<span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%), the weight percentages of normal aerated lung (<span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>%), and the MA<span class="elsevierStyleInf">fibrosis</span> exhibited significant differences during the 3–6 month follow-up period.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The GGO and CO scored by the semiquantitative or quantitative analysis methods was similar. The HRCT quantitative analysis parameters showed a good correlation with the PFTs in ASS-OP patients, can provide an accurate OP pattern interpretation, and may be used as a monitoring and therapeutic indicator for ASS-OP patients.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El patrón de neumonía organizada (PNO) es el segundo hallazgo más común en el síndrome de anticuerpos antisintasa (SAA), y la neumonía intersticial inespecífica es el hallazgo más común. Este estudio analizó los cambios en la puntuación de PNO mediante métodos de análisis semicuantitativos y cuantitativos, y la correlación entre los índices de la tomografía computarizada de alta resolución y los parámetros de las pruebas de función pulmonar en pacientes con SAA.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se revisaron y analizaron retrospectivamente los datos de los pacientes SAA-PNO ingresados en el departamento respiratorio del Hospital Ping Jin desde octubre de 2014 hasta junio de 2020.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se reclutaron 14 pacientes SAA-PNO para este estudio. (1) En el método 1, la puntuación de consolidación (PC) y la atenuación pulmonar media (APM) de los campos pulmonares mal aireados y fibrosis (APM<span class="elsevierStyleInf">fibrosis</span>) (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,56; p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,04), la puntuación de la opacidad del vidrio molido (OVM) y la PC de los campos pulmonares no aireados (APM<span class="elsevierStyleInf">noaireado</span>) (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0,64; p <span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,01), y la PC más la puntuación OVM (PV) y el APM<span class="elsevierStyleInf">noaireado</span> de los campos pulmonares tenían correlaciones de revestimiento. En el método 2, la puntuación de OVM para el APM<span class="elsevierStyleInf">noaireado</span> (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0,58; p <span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,03) y la puntuación de PV (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0,68; p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,01) para el APM<span class="elsevierStyleInf">noaireado</span> tenían correlaciones de revestimiento. El FVC% (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,68; p <span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,01) y el FEV<span class="elsevierStyleInf">1</span>% (r<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,64; p <span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,01) a la APM<span class="elsevierStyleInf">fibrosis</span> tuvieron buenas correlaciones lineales. (2) En comparación con los valores anteriores al tratamiento, la puntuación del patrón de PC, los porcentajes de volumen y peso del volumen pulmonar total extraído con los valores de atenuación del área no aireada (V<span class="elsevierStyleInf">noaireado</span>%, P<span class="elsevierStyleInf">noaireado</span>%), el volumen de tejido pulmonar poco aireado y fibroso (V<span class="elsevierStyleInf">fibrosis</span>%, P<span class="elsevierStyleInf">fibrosis</span>%), los porcentajes de peso del pulmón aireado normal (P<span class="elsevierStyleInf">normal</span>%) y la APM<span class="elsevierStyleInf">fibrosis</span> mostraron diferencias significativas durante el período de seguimiento de 3 a 6 meses.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusión</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">El OVM y la PC puntuados por los métodos de análisis semicuantitativo o cuantitativo fue similar. Los parámetros del análisis cuantitativo de la tomografía computarizada de alta resolución mostraron una buena correlación con las pruebas de función pulmonar en los pacientes SAA-PNO, pueden proporcionar una interpretación precisa del PNO y pueden utilizarse como un indicador terapéutico y de seguimiento para los pacientes SAA-PNO.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1456 "Ancho" => 2083 "Tamanyo" => 116035 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">The FVC% has a linear relationship with mean lung attenuation of the extracted whole lung volume with attenuation values of the poorly aerated and fibrosis.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1456 "Ancho" => 2083 "Tamanyo" => 116831 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">The FEV1% has a linear relationship with mean lung attenuation of the extracted whole lung volume with attenuation values of the poorly aerated and fibrosis.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">n</span>, number. SD, standard deviation. FVC, forced vital capacity. FEV<span class="elsevierStyleInf">1</span>, forced expiratory volume in 1 second. DLCO, carbon monoxide diffusion.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><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"><span class="elsevierStyleItalic">Age, median years, mean</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">±</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SD</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49.34<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.17 \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"><span class="elsevierStyleItalic">Disease duration, median (months)</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.90<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.25 \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="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Symptoms, n (%)</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"><span class="elsevierStyleHsp" style=""></span>Dyspnoea \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (57.14%) \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"><span class="elsevierStyleHsp" style=""></span>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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (71.43%) \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"><span class="elsevierStyleHsp" style=""></span>Fever \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (21.43%) \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"><span class="elsevierStyleHsp" style=""></span>Raynaud's phenomenon \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (7.14%) \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="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Physical examination, n (%)</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"><span class="elsevierStyleHsp" style=""></span>skin lesion \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (35.71%) \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="elsevierStyleHsp" style=""></span>Fine crackle \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (92.86%) \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="elsevierStyleHsp" style=""></span>Muscle weakness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (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"><span class="elsevierStyleHsp" style=""></span>Gottron's papules \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (7.14%) \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"><span class="elsevierStyleHsp" style=""></span>Mechanic's hand \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (78.57%) \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="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Antisynthetase antibodie, n (%)</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"><span class="elsevierStyleHsp" style=""></span>Antibodies JO-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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (21.43%) \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"><span class="elsevierStyleHsp" style=""></span>Antibodies PL-12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (42.86%) \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="elsevierStyleHsp" style=""></span>Antibodies PL-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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (21.42%) \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"><span class="elsevierStyleHsp" style=""></span>Antibodies EJ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (14.29%) \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="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Arterial blood gases (FiO</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">21%), mmHg</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"><span class="elsevierStyleHsp" style=""></span>PaCO<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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.40 \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="elsevierStyleHsp" style=""></span>PaO<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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78.64<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.14 \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="2" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Pulmonary function test, mean</span><span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SD</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"><span class="elsevierStyleHsp" style=""></span>FVC%, \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.91 \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="elsevierStyleHsp" style=""></span>FEV<span class="elsevierStyleInf">1</span>%, mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58.94<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>17.14 \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"><span class="elsevierStyleHsp" style=""></span>DLCO%, mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.81 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Baseline clinical characteristics of ASS-OP patients.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">QL, quantitative analysis. SQL, semiquantitative analysis. HRCT, high-resolution computed tomography. CI, the confidence interval. GGO, ground-glass opacity. CO, consolidation. CG, CO plus GGO patterns. MA means lung attenuation. <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">normal</span>%, and <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">hyper</span>%, volume percentages of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated (normal), and the hyperinflated. <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>% and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">hyper</span>%, weight percentages of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated (normal) and hyperinflated.MA, mean lung attenuation. MA<span class="elsevierStyleInf">nonaerated</span>, MA<span class="elsevierStyleInf">fibrosis</span>, MA<span class="elsevierStyleInf">normal</span>, and MA<span class="elsevierStyleInf">hyper</span>, MA of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated, hyperinflated area and outlined total lung area.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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">Method \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">Score or parameter value \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">Mean \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">CI (95%) \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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">SQL</span></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Method-1</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.42–29.08 \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">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.11–8.73 \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">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26.17 \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">18.47–33.87 \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 " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Method-2</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.77–9.51 \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">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.46–4.25 \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">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.01–11.99 \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="4" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">QL</span></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.75–8.60 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.11 to 18.38 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">normal</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.11 \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">55.95–68.28 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">hyper</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.44–26.36 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">nonaerated</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−11.80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−18.24 to −5.37 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">fibrosis</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−321.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−328.94 to −313.29 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">normal</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−763.74 \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">−780.28 to −747.20 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">hyper</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−936.39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−942.42 to −930.37 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.12–22.26 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.01–34.34 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49.39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42.88–55.91 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">hyper</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.23 \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">2.12–6.334 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">SQL and QL analysis of HRCT before treatment.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">QL, quantitative analysis. SQL, semiquantitative analysis. HRCT, high-resolution computed tomography. CI, the confidence interval. GGO, ground-glass opacity. CO, consolidation. CG. CO plus GGO patterns. MA, means lung attenuation. <span class="elsevierStyleItalic">V</span>% or <span class="elsevierStyleItalic">W</span>%, volume or weight percentages of the extracted whole lung volume with attenuation values of some aerated lung compartments. <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>% or <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span>% of the non-aerated area. <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%. <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>% or <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span>% of the poorly aerated and fibrosis. MA, mean lung attenuation. MA<span class="elsevierStyleInf">fibrosis</span>, MA of the extracted whole lung volume with attenuation values of the poorly aerated and fibrosis.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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">Method \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">Patterns \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"><span class="elsevierStyleItalic">r</span> or <span class="elsevierStyleItalic">P</span> value \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"><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</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"><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</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">MA<span class="elsevierStyleInf">nonaerated</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">MA<span class="elsevierStyleInf">fibrosis</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"><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</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"><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>% \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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Method-1</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.24 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.18 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.09 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.83 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.76 \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">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.64 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.20 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.34 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.38 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.16 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.24 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.18 \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">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.16 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.38 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.19 \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 " rowspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Method-2</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.11 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.71 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.33 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.16 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.24 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.40 \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">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">r \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.68 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.18 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.17 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.37 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">P</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.18 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Correlations between SQL and QL analysis of HRCT before treatment.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at4" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">QL, quantitative analysis. SQL, semiquantitative analysis. HRCT, high-resolution computed tomography. CI, the confidence interval. GGO, ground-glass opacity. CO, consolidation. CG. CO plus GGO patterns. MA, means lung attenuation. <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">normal</span>%, and <span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">hyper</span>%, Volume percentages of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated (normal), and the hyperinflated. <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</span>%, <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</span>% and <span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">hyper</span>%, Weight percentages of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated (normal) and hyperinflated. MA, mean lung attenuation. MA<span class="elsevierStyleInf">nonaerated</span>, MA<span class="elsevierStyleInf">fibrosis</span>, MA<span class="elsevierStyleInf">normal</span>, and MA<span class="elsevierStyleInf">hyper</span>, MA of the extracted whole lung volume with attenuation values of the non-aerated area, poorly aerated and fibrosis, normally lung aerated, hyperinflated area and outlined total lung area. Hu, Hounsfield unit. SD, standard deviation.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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">Method \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">Pattern or parameter \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">Before treatment (Mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD) \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">After 3–6 months of treatment (Mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD) \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"><span class="elsevierStyleItalic">P</span> value \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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">SQL</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"><span class="elsevierStyleHsp" style=""></span>Method-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">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.85<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.31<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.22 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.59<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.10 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29.31<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.90<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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"><span class="elsevierStyleHsp" style=""></span>Method-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">GGO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.10<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.63 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.10<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.70<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.16 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.30<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.08 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.80<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.11 \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="5" 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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">QL</span></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">nonaerated</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.85<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.39<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">fibrosis</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.50<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.65 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.08<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">normal</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60.13<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67.15<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.25 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">V</span><span class="elsevierStyleInf">hyper</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.52<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.74 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21.37<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.80 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">nonaerated,Hu</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−12.94<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−17.56<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.43 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">fibrosis,Hu</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−320.01<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−335.09<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>16.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">normal,Hu</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−759.59<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>31.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−777.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>27.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>MA<span class="elsevierStyleInf">hyper,Hu</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−937.48<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−933.88<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.49 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">nonaerated</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.25<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.22 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.03<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">fibrosis</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22.68<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">normal</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48.49<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.59<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.24 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \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 " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">W</span><span class="elsevierStyleInf">hyper</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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.49<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.71<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.31 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.36 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Comparing of HRCT parameters before treatment and after the 3–6 months follow up in ten patients.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" 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We also thank the information technicians, Yuguang Tie and Chunhui Zhang (from the Department of Information, the Affiliated Hospital of Logistics University of Chinese People's Armed Police Force), for the search and abstraction of the data of ASS-OP patients.</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/00257753/0000015900000002/v1_202207080542/S0025775321005285/v1_202207080542/en/main.assets" "Apartado" => array:4 [ "identificador" => "93343" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Originales" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/00257753/0000015900000002/v1_202207080542/S0025775321005285/v1_202207080542/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0025775321005285?idApp=UINPBA00004N" ]
