was read the article
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Medina Gamero" "autores" => array:1 [ 0 => array:2 [ "nombre" => "A." 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Sedation and local anaesthesia. Needles (10–13 G) guided by CT or fluoroscopy. Strict asepsis. Sometimes a hammer or drill is necessary to perforate the cortex, if it is not possible to do so by hand. Anterolateral access (to avoid the rectus femoris tendon). After mixing PMMA cement + tantalum (radiopaque) + antibiotic (gentamicin 2 g), there are approximately three minutes before it consolidates. Image-guided monitoring can rule out leakage and proximal progression.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "X. Tomas Batlle, J.C. Soler-Perromat, J. Blasco Andaluz, J.A. Fernández-Valencia" "autores" => array:4 [ 0 => array:2 [ "nombre" => "X." "apellidos" => "Tomas Batlle" ] 1 => array:2 [ "nombre" => "J.C." "apellidos" => "Soler-Perromat" ] 2 => array:2 [ "nombre" => "J." "apellidos" => "Blasco Andaluz" ] 3 => array:2 [ "nombre" => "J.A." 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García-Villar, J.M. Plasencia-Martínez, M.T. Gutiérrez-Amares, J.M. García-Santos" "autores" => array:4 [ 0 => array:4 [ "nombre" => "C." "apellidos" => "García-Villar" "email" => array:1 [ 0 => "cristina.garcia.villar@gmail.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "J.M." "apellidos" => "Plasencia-Martínez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "M.T." "apellidos" => "Gutiérrez-Amares" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "J.M." "apellidos" => "García-Santos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Unidad de Radiodiagnóstico, Hospital Universitario Puerta del Mar, Cádiz, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Servicio de Radiología, Hospital General Universitario Morales Meseguer, Murcia, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Departamento Materno-Infantil y Radiología, Universidad de Cádiz, Cádiz, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Concordancia interobservador de los niveles de evidencia en artículos radiológicos" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1304 "Ancho" => 2177 "Tamanyo" => 191310 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Types of article included and excluded in the final analysis.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Evidence-based radiology (EBR) involves selecting the most appropriate imaging modality according to the best available research, and combining it with the physician’s experience and the patient’s expectations.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Knowing the Level of Evidence (LE) assigned to an article provides important information for clinical decision making.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> LEs form a hierarchical classification of studies according to their design and suggest a greater or lesser likelihood of bias.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The first evidence grading system was developed by the Canadian Task Force on Preventive Health Care (CTFPHC) in 1976.<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> Among the LE classification systems that have proliferated ever since, the following stand out: Oxford Centre for Evidence-Based Medicine (OCEBM),<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> the Scottish Intercollegiate Guidelines Network (SIGN),<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> the National Institute for Health and Clinical Excellence (NICE)<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> and the National Health and Medical Research Council (NHMRC) of Australia.<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> There is considerable variation between these grading scales. This departs from the principles of EBR which ultimately aims to standardise clinical practice.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">The aim of our study is to discover which LE classification system produces the best interobserver agreement for radiology articles, and thus is the simplest to reproduce and interpret.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Material and method</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Selection of journals</span><p id="par0025" class="elsevierStylePara elsevierViewall">All selected journals feature in the 2020 Journal Citation Report (JCR) in the category ‘Radiology, Nuclear Medicine & Medical Imaging’ dated 1 June 2020. Those specific to ‘radiation oncology’, ‘optics’, ‘molecular imaging’ and ‘preclinical radiation physics and biology’ were excluded along with journals that focus solely on one specific area or one specific imaging technique as our aim was to obtain articles from a wide range of areas. The following 12 journals, from all four quartile rankings, were included:<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">•</span><p id="par0030" class="elsevierStylePara elsevierViewall">Q1: Radiology; European Radiology; Korean Journal of Radiology; Radiographics.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">•</span><p id="par0035" class="elsevierStylePara elsevierViewall">Q2: American Journal of Roentgenology; European Journal of Radiology; Academic Radiology.</p></li><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">•</span><p id="par0040" class="elsevierStylePara elsevierViewall">Q3: Clinical Radiology; British Journal of Radiology; Acta Radiológica; Japanese Journal of Radiology.</p></li><li class="elsevierStyleListItem" id="lsti0020"><span class="elsevierStyleLabel">•</span><p id="par0045" class="elsevierStylePara elsevierViewall">Q4: La Radiología Medica.</p></li></ul></p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Selection of articles</span><p id="par0050" class="elsevierStylePara elsevierViewall">The aim was to obtain a diverse sample that included different topics (for this reason, the search period was dated prior to the COVID-19 pandemic in order to achieve a greater diversity of subjects) and varied methodologies so that a range of LEs would need to be assigned. Twenty original articles were randomly selected from each journal.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Selection of evidence scales</span><p id="par0055" class="elsevierStylePara elsevierViewall">Only the following four LE scales currently include the category of diagnosis: Sakett,<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> OCEBM,<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> NICE<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> and NHMRC.<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,11</span></a> Of these four, we selected the two that examine articles from more categories so more articles could be assessed. The two selected scales were the 2011 version of OCEBM<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> and the 2009 version of NHMRC.<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Statistical analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">Interobserver agreement on the LE of the articles was established through the assessment of the abstract by two blinded radiologists (CGV and JMPM). Both observers had 10 years of experience with EBR methodology. In order to address any potential queries that could surface in the classification process, a training session was carried out in which both scales were used to assess 10 original articles that differed from the ones included in the study.</p><p id="par0065" class="elsevierStylePara elsevierViewall">During the abstract analysis, the observers were blinded to the names of the journals, authors or any affiliation data that could influence the classification of the articles. The anonymisation process was carried out by a third researcher.</p><p id="par0070" class="elsevierStylePara elsevierViewall">At times, the abstracts did not include all the information required to decide between one level or another. In these cases, the lowest level was chosen. The articles included in the sample were then analysed in an independent and blinded manner.</p><p id="par0075" class="elsevierStylePara elsevierViewall">To estimate the degree of interobserver agreement, we used the Cohen's Kappa coefficient, which represents the absolute agreement of the ratings, and Kendall's Tau-b coefficient. The Kappa index treats all misclassifications equally, while Kendall's Tau-b takes into account the magnitude of the difference. The level of agreement was set as poor (<0.20), fair (0.21−0.40), moderate (0.41−0.60), good (0.61−0.80), and excellent (>0.80).</p><p id="par0080" class="elsevierStylePara elsevierViewall">Contingency tables were used for bivariate analysis. The Kappa and Kendall's Tau-b coefficients were calculated with a corresponding confidence interval of 95%. In all these inferential statistical tests, differences were considered significant when <span class="elsevierStyleItalic">P</span> < .05 and highly significant when <span class="elsevierStyleItalic">P</span> < .01.</p><p id="par0085" class="elsevierStylePara elsevierViewall">All parameters were analysed using IBM-SPSS Statistics version 25 (reference: IBM Corp. Released 2017. IBM SPSS Statistics v 25.0 for Windows; Armonk. NY. USA).</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Results</span><p id="par0090" class="elsevierStylePara elsevierViewall">A total of 240 articles were obtained, of which the LE could be determined for 106, thus excluding a total of 134 articles (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). The decision to exclude one adverse effects article was made by consensus, as it was only possible to establish its LE with the Oxford classification and not with the NHMRC. Therefore, a total of 105 articles were finally included.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">Of the 105 articles included, 96 were diagnostic articles, 6 were articles on treatment and 3 on screening.</p><p id="par0100" class="elsevierStylePara elsevierViewall">With the OCEBM scale, interobserver agreement on LE based on the abstracts was good (K = 0.679; Tau-b = 0.717). The agreement values were lower with the NHMRC scale (K = 0.577 -moderate-; Tau-b = 0.673 -good-). All differences were statistically significant (<span class="elsevierStyleItalic">P</span> < .000).</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">Determining the LE of an article is fundamental to ensuring that our clinical decisions are based on the best available evidence.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> More than 100 LE classifications have been created,<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> which use different hierarchies and terms, thereby limiting their applicability. However, no previous study has explored interobserver agreement.</p><p id="par0110" class="elsevierStylePara elsevierViewall">In our analysis, the degree of interobserver agreement (K) was higher with the OCEBM scale (good) than with the NHMRC (moderate). This is probably due to the fact that the former scale has no subdivisions.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> Both scales use a lot of technical language and statistical terms, although both try to mitigate this difficulty by adding a glossary of terms and footnotes to make them easier to understand. An initial analysis suggests that the Oxford classification is easier to interpret than the Australian classification, as the degree of agreement was higher.</p><p id="par0115" class="elsevierStylePara elsevierViewall">As for medical imaging, Insights Into Imaging has recently published the first LE classification specifically designed for radiology journals.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> One of its main advantages is that it avoids sub-classifications as it classifies the LEs into high, moderate and low. It also uses less technical language. Furthermore, it also includes the category of review articles (such as narrative reviews, updates or imaging reviews), classifying them with low LEs. All the articles that we excluded from our analysis could be classified in this category. The main drawback is that it does not differentiate between different study designs, which is why it has not been included in this paper.</p><p id="par0120" class="elsevierStylePara elsevierViewall">This study has several limitations. The first is that the interobserver agreement was determined using the LEs assigned by the observers after reading only the abstracts of the articles, not the full texts. Nevertheless, the aim of this study was to find out whether the existing LE classifications are reproducible or not.</p><p id="par0125" class="elsevierStylePara elsevierViewall">Another limitation is that the study compared agreement on the LEs but not the Grades of Recommendation (GR). However, the complicated part is determining the LE, since once assigned, it is directly related to the GR.</p><p id="par0130" class="elsevierStylePara elsevierViewall">In conclusion, there are many LE scales, and they are highly heterogeneous. Of the two scales analysed (OCEBM and NHMRC), the one with the best interobserver agreement is the OCEBM. This is probably due to the fact that it avoids subdividing the evidence levels.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Author contributions</span><p id="par0135" class="elsevierStylePara elsevierViewall"><ul class="elsevierStyleList" id="lis0010"><li class="elsevierStyleListItem" id="lsti0025"><span class="elsevierStyleLabel">1</span><p id="par0140" class="elsevierStylePara elsevierViewall">Research coordinators: CGV, JMPM, MTGA, JMGS</p></li><li class="elsevierStyleListItem" id="lsti0030"><span class="elsevierStyleLabel">2</span><p id="par0145" class="elsevierStylePara elsevierViewall">Development of study concept: CGV, JMGS</p></li><li class="elsevierStyleListItem" id="lsti0035"><span class="elsevierStyleLabel">3</span><p id="par0150" class="elsevierStylePara elsevierViewall">Study design: CGV, JMPM, MTGA, JMGS</p></li><li class="elsevierStyleListItem" id="lsti0040"><span class="elsevierStyleLabel">4</span><p id="par0155" class="elsevierStylePara elsevierViewall">Data collection: CGV, JMPM</p></li><li class="elsevierStyleListItem" id="lsti0045"><span class="elsevierStyleLabel">5</span><p id="par0160" class="elsevierStylePara elsevierViewall">Data analysis and interpretation: CGV, MTGA, JMGS</p></li><li class="elsevierStyleListItem" id="lsti0050"><span class="elsevierStyleLabel">6</span><p id="par0165" class="elsevierStylePara elsevierViewall">Data processing: CGV, JMPM</p></li><li class="elsevierStyleListItem" id="lsti0055"><span class="elsevierStyleLabel">7</span><p id="par0170" class="elsevierStylePara elsevierViewall">Literature search: CGV</p></li><li class="elsevierStyleListItem" id="lsti0060"><span class="elsevierStyleLabel">8</span><p id="par0175" class="elsevierStylePara elsevierViewall">Writing of article: CGV, JMGS</p></li><li class="elsevierStyleListItem" id="lsti0065"><span class="elsevierStyleLabel">9</span><p id="par0180" class="elsevierStylePara elsevierViewall">Critical review of the manuscript with intelectually relevant contributions: JMPM, MTGA</p></li><li class="elsevierStyleListItem" id="lsti0070"><span class="elsevierStyleLabel">10</span><p id="par0185" class="elsevierStylePara elsevierViewall">Approval of the final version: CGV, JMPM, MTGA, JMGS</p></li></ul></p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Conflicts of interest</span><p id="par0190" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres2079431" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1773971" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres2079430" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1773972" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and method" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Selection of journals" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Selection of articles" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Selection of evidence scales" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0040" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0045" "titulo" => "Author contributions" ] 9 => array:2 [ "identificador" => "sec0050" "titulo" => "Conflicts of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2023-06-18" "fechaAceptado" => "2023-08-31" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1773971" "palabras" => array:5 [ 0 => "Evidence-based medicine" 1 => "Evidence-based radiology" 2 => "Radiology" 3 => "Level of evidence" 4 => "Grades of recommendation" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1773972" "palabras" => array:6 [ 0 => "Medicina basada en la evidencia" 1 => "Radiología basada en la evidencia" 2 => "Concordancia interobservador" 3 => "Radiología" 4 => "Niveles de evidencia" 5 => "Grados de recomendación" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Levels of evidence (LE) are established through a hierarchical classification of studies according to their design. At present, there are many heterogeneous LE classifications, and this hampers their applicability. Our study aims to identify which LE classification has the best interobserver concordance for radiology articles. For this purpose, an interobserver agreement analysis were performed on 105 original articles applying two NE scales (Oxford Center of Evidence Based Medicine (OCEBM) y National Health and Medical Research Council (NHMRC)). The inter-rater agreement of the LE assigned after reading the abstracts was good when using the OCEBM scale (<span class="elsevierStyleItalic">K</span> = 0.679), and somewhat lower with the NHMRC (<span class="elsevierStyleItalic">K</span> = 0.577 -moderate-). All differences were statistically significant (<span class="elsevierStyleItalic">P</span> < .000). So, in conclusion, of the two scales analysed (OCEBM and NHMRC), the OCEBM led to the strongest level of inter-rater agreement.</p></span>" ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Los niveles de evidencia (NEs) son una clasificación jerárquica de los estudios atendiendo a su diseño. Actualmente existen muchas clasificaciones de NEs que son muy heterogéneas dificultando su aplicabilidad. Nuestro estudio tiene como objetivo conocer qué clasificación de NE tiene mayor concordancia interobservador en artículos radiológicos. Para ello, se realizó un análisis de concordancia a 105 artículos originales aplicando dos escalas de NE (Oxford Center of Evidence Based Medicine (OCEBM) y National Health and Medical Research Council (NHMRC)). La concordancia interobservador del NE de los abstracts fue buena con la escala OCEBM (<span class="elsevierStyleItalic">K</span> = 0,679), siendo algo inferior con la NHMRC (<span class="elsevierStyleItalic">K</span> = 0,577 -moderada). Todas las diferencias fueron estadísticamente significativas (<span class="elsevierStyleItalic">P</span> < .000). Por tanto, de las dos escalas analizadas la que mejor concordancia interobservador presenta es la OCEBM.</p></span>" ] ] "multimedia" => array:1 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1304 "Ancho" => 2177 "Tamanyo" => 191310 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Types of article included and excluded in the final analysis.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:12 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Evidence-based radiology for diagnostic imaging: what is and how to practice it" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "C. 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