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array:24 [ "pii" => "S2173510722001379" "issn" => "21735107" "doi" => "10.1016/j.rxeng.2022.03.007" "estado" => "S300" "fechaPublicacion" => "2023-09-01" "aid" => "1389" "copyright" => "SERAM" "copyrightAnyo" => "2022" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Radiologia. 2023;65:423-30" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "Traduccion" => array:1 [ "es" => array:19 [ "pii" => "S0033833822001321" "issn" => "00338338" "doi" => "10.1016/j.rx.2022.03.009" "estado" => "S300" "fechaPublicacion" => "2023-09-01" "aid" => "1389" "copyright" => "SERAM" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Radiologia. 2023;65:423-30" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original</span>" "titulo" => "Mejora en el manejo de la sospecha del síndrome aórtico agudo en urgencias mediante un algoritmo clínico y el estudio de factores predictivos" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "423" "paginaFinal" => "430" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figura 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1504 "Ancho" => 2500 "Tamanyo" => 378609 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Algoritmo para la estratificación del riesgo de SAA y el manejo diagnóstico. Paso 1: puntuación basada en la presencia de factores de riesgo. A cada factor de riesgo existente se le asigna un punto. Se asigna 1 punto al dolor intenso de aparición brusca con cualquiera de las características clásicas descritas (no es necesario que cumpla todos los criterios descriptivos). Se asigna 1 punto, de forma independiente, a cualquier signo de déficit de perfusión, soplo por insuficiencia valvular aórtica de nueva aparición o presencia de hipotensión o choque. Paso 2: estratificación del riesgo. Puntuación de 0: riesgo bajo. Puntuación de 1: riesgo intermedio. Puntuación de 2 o más: riesgo alto. Paso 3: enfoque diagnóstico. Riesgo bajo o intermedio: medir el dímero D (con un valor de corte de 500 ng/ml) y obtener radiografías posteroanterior y lateral de tórax. Si estas sugieren un diagnóstico diferente o son normales, la TC de aorta no está indicada. Si el dímero D es elevado, la radiografía de tórax sugiere una enfermedad aórtica o hay una hipotensión sostenida de causa desconocida, debe realizarse una TC de aorta. Riesgo alto: realizar una TC de aorta urgente como primera línea.</p> <p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Nota: si el médico considera necesario la TC de aorta frente a la indicación del algoritmo, puede indicarlo en las observaciones del formulario de solicitud.</p> <p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">ECG: electrocardiograma; PA: presión arterial; SAA: síndrome aórtico agudo; TC: tomografía computarizada.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "B. Lumbreras-Fernández, A. Vicente Bártulos, B.M. Fernandez-Felix, J. Corres González, J. Zamora, A. Muriel" "autores" => array:6 [ 0 => array:2 [ "nombre" => "B." "apellidos" => "Lumbreras-Fernández" ] 1 => array:2 [ "nombre" => "A." "apellidos" => "Vicente Bártulos" ] 2 => array:2 [ "nombre" => "B.M." "apellidos" => "Fernandez-Felix" ] 3 => array:2 [ "nombre" => "J." "apellidos" => "Corres González" ] 4 => array:2 [ "nombre" => "J." "apellidos" => "Zamora" ] 5 => array:2 [ "nombre" => "A." "apellidos" => "Muriel" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2173510722001379" "doi" => "10.1016/j.rxeng.2022.03.007" "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/S2173510722001379?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0033833822001321?idApp=UINPBA00004N" "url" => "/00338338/0000006500000005/v1_202309081053/S0033833822001321/v1_202309081053/es/main.assets" ] ] "itemSiguiente" => array:19 [ "pii" => "S2173510723000836" "issn" => "21735107" "doi" => "10.1016/j.rxeng.2022.12.005" "estado" => "S300" "fechaPublicacion" => "2023-09-01" "aid" => "1453" "copyright" => "SERAM" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Radiologia. 2023;65:431-46" "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">Update in Radiology</span>" "titulo" => "MRI for detection, staging, and follow-up of prostate cancer: Synthesis of the PI-RADS v2.1, MET-RADS, PRECISE, and PI-RR guidelines" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "431" "paginaFinal" => "446" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Resonancia magnética en la detección, estadificación y seguimiento del cáncer de próstata: síntesis de las guías PI-RADS v2.1, MET-RADS, PRECISE y PI-RR" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 3603 "Ancho" => 2917 "Tamanyo" => 587499 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0235" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Reporting template from the MET-RADS guidelines. The template assesses involvement in 14 predefined regions of the body (primary lesion, seven skeletal regions and three nodal, lungs, liver and other soft-tissue sites) at baseline and on follow-up. The template indicates whether or not the disease is present in each anatomical area (yes/no) and the category of response (primary/secondary). The overall response of the primary tumour, nodal and visceral disease is categorical (no disease, complete response, partial response, stable disease and progressive disease). However, the overall response of the bone is communicated through a scale of 1–5 which indicates the overall likelihood response category: a score of 1 means that it is highly likely to be responding; 2 means it is likely to be responding; 3 means that there is no change in the disease; 4 means it is likely to be progressing; and 5 means it is highly likely to be progressing.</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">SD: stable disease; PD: progressive disease; RAC: response assessment category; CR: complete response; PR: partial response.</p> <p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Adapted from Padhani and Tunariu<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> with permission.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "J.C. Vilanova, V. Catalá-Sventzetzky, J. Hernández-Mancera" "autores" => array:3 [ 0 => array:2 [ "nombre" => "J.C." "apellidos" => "Vilanova" ] 1 => array:2 [ "nombre" => "V." "apellidos" => "Catalá-Sventzetzky" ] 2 => array:2 [ "nombre" => "J." "apellidos" => "Hernández-Mancera" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0033833823000097" "doi" => "10.1016/j.rx.2022.12.005" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0033833823000097?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173510723000836?idApp=UINPBA00004N" "url" => "/21735107/0000006500000005/v1_202309260839/S2173510723000836/v1_202309260839/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S2173510723000988" "issn" => "21735107" "doi" => "10.1016/j.rxeng.2021.12.002" "estado" => "S300" "fechaPublicacion" => "2023-09-01" "aid" => "1349" "copyright" => "SERAM" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Radiologia. 2023;65:414-22" "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 articles</span>" "titulo" => "Radiological predictors of final infarct volume in patients with proximal vascular occlusion" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "414" "paginaFinal" => "422" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Predictores radiológicos del volumen final del infarto cerebral en pacientes con obstrucción vascular proximal" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 596 "Ancho" => 1500 "Tamanyo" => 99519 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0220" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">80-year-old female patient with a history of hypertension, type II diabetes, dyslipidaemia and atrial fibrillation, NIHSS on admission 19 points. She consulted with sudden onset right brachial paresis and dysarthria. This patient did not have mechanical thrombectomy. (A) CT-angiogram of the brain, axial slice, maximum intensity projection (MIP), 120<span class="elsevierStyleHsp" style=""></span>min after the onset of symptoms, showing absence of brain parenchyma enhancement in the territory of the left middle cerebral artery. The leptomeningeal collateral branches have similar lumen and post-contrast filling as those on the healthy side (grade 3). (B) MIP coronal slice CT-angiogram of the brain showing absence of opacification of the left internal carotid artery in its cervical tract (−1 point) and in its supraclinoid portion (−2 points). Clot burden score<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>7 points. (C) Non-contrast CT scan of the brain 48<span class="elsevierStyleHsp" style=""></span>h after symptom onset showed a left frontal hypodense lesion. Volumetric measurement of the infarcted brain parenchyma measuring approximately 75 cc.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "M.J. Rodríguez, A. Graziani, J.S. Seoane, L. Di Napoli, M. Pérez Akly, C. Besada" "autores" => array:6 [ 0 => array:2 [ "nombre" => "M.J." "apellidos" => "Rodríguez" ] 1 => array:2 [ "nombre" => "A." "apellidos" => "Graziani" ] 2 => array:2 [ "nombre" => "J.S." "apellidos" => "Seoane" ] 3 => array:2 [ "nombre" => "L." "apellidos" => "Di Napoli" ] 4 => array:2 [ "nombre" => "M." "apellidos" => "Pérez Akly" ] 5 => array:2 [ "nombre" => "C." "apellidos" => "Besada" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0033833822000017" "doi" => "10.1016/j.rx.2021.12.002" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0033833822000017?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173510723000988?idApp=UINPBA00004N" "url" => "/21735107/0000006500000005/v1_202309260839/S2173510723000988/v1_202309260839/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original articles</span>" "titulo" => "Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "423" "paginaFinal" => "430" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "B. Lumbreras-Fernández, A. Vicente Bártulos, B.M. Fernandez-Felix, J. Corres González, J. Zamora, A. Muriel" "autores" => array:6 [ 0 => array:4 [ "nombre" => "B." "apellidos" => "Lumbreras-Fernández" "email" => array:2 [ 0 => "blancalumfer@gmail.com" 1 => "blanca.lumbreras@salud.madrid.org" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "A." "apellidos" => "Vicente Bártulos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "B.M." "apellidos" => "Fernandez-Felix" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "J." "apellidos" => "Corres González" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "J." "apellidos" => "Zamora" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 5 => array:3 [ "nombre" => "A." "apellidos" => "Muriel" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0030" ] ] ] ] "afiliaciones" => array:6 [ 0 => array:3 [ "entidad" => "Servicio de Radiología, Hospital Universitario Ramón y Cajal, Madrid, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Servicio de Radiología de Urgencias, Hospital Universitario Ramón y Cajal, Madrid, Centro de Investigación Biomédica en Red Enfermedades respiratorias (CIBERES), Madrid, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Unidad de Bioestadística Clínica, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Servicio de Urgencias, Hospital Universitario Ramón y Cajal, Madrid, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Unidad de Bioestadística Clínica, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, España, Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "Unidad de Bioestadística Clínica, Hospital Universitario Ramón y Cajal, IRYCIS, CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Departamento de Enfermería de la Universidad de Alcalá, Madrid, Spain" "etiqueta" => "f" "identificador" => "aff0030" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Mejora en el manejo de la sospecha del síndrome aórtico agudo en urgencias mediante un algoritmo clínico y el estudio de factores predictivos" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1372 "Ancho" => 2500 "Tamanyo" => 164662 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Literature search process.</p> <p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">The Haynes pyramid of the 5S was used, accessing the publications of the highest possible level according to the following order: 5-aid systems for clinical decision making; 4-clinical practice guidelines; 3-critical reviews of articles; 2-systematic reviews. 573 studies were identified; 6 of these were excluded as duplicates and 550 as the articles did not meet the criteria (level 1 studies including original studies, primary sources and case series, studies describing findings and sensitivity of imaging tests, studies not in English or Spanish, or in a pediatric population). Ultimately, the analysis and qualitative synthesis included 17 studies that were used to develop the decision support algorithm.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Acute aortic syndrome (AAS) has an estimated incidence of 2–3.5/100,000 population/year.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> The classical presentation is of sudden onset of intense chest, abdominal, or back pain, although there is great variety in clinical presentation<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> and mimickers.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> Due to its rapid progression and high mortality<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,4,5</span></a> algorithms or clinical decision support systems (CDSS) are essential.</p><p id="par0010" class="elsevierStylePara elsevierViewall">Prior to the use of algorithms, AAS was misdiagnosed in more than 30% of cases.<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,7</span></a> In 2010, the American College of Cardiology Foundation/American Heart Association (ACCF/AHA), along with other North American scientific societies and colleges published an algorithm for its diagnosis and management using a scoring system based on the presence of defined risk factors: the Aortic Dissection Detection Risk Score (ADD-RS).<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> In 2014 the European Society of Cardiology (ESC)<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> and the American College of Radiology (ACR)<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> published guidelines for the diagnosis and treatment of aortic disease and appropriate use of tests.</p><p id="par0015" class="elsevierStylePara elsevierViewall">The main objectives of this study were: <ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">1</span><p id="par0020" class="elsevierStylePara elsevierViewall">To develop a CDSS to improve the appropriateness of computed tomography of the aorta (CTA) when AAS is suspected in the emergency department and to determine the effect of its implementation.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">2</span><p id="par0025" class="elsevierStylePara elsevierViewall">To identify the risk factors (past medical history, presentation, examination findings) associated with a positive diagnosis of AAS on CTA and that could help in developing a clinical prediction rule.</p></li></ul></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Materials and methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">This study forms part of the multicenter project <span class="elsevierStyleItalic">MAPAC-imagen</span> (<span class="elsevierStyleBold"><span class="elsevierStyleItalic">M</span></span><span class="elsevierStyleItalic">ejora de la</span><span class="elsevierStyleBold"><span class="elsevierStyleItalic">A</span></span><span class="elsevierStyleItalic">decuación de la</span><span class="elsevierStyleBold"><span class="elsevierStyleItalic">P</span></span><span class="elsevierStyleItalic">ráctica</span><span class="elsevierStyleBold"><span class="elsevierStyleItalic">A</span></span><span class="elsevierStyleItalic">sistencial y</span><span class="elsevierStyleBold"><span class="elsevierStyleItalic">C</span></span><span class="elsevierStyleItalic">línica</span>, meaning <span class="elsevierStyleItalic">Improvement of Appropriateness of Health Care and Clinical Practice</span>) funded by the ISCIII (Instituto de Salud Carlos III) as part of their <span class="elsevierStyleItalic">Acción Estratégica en Salud</span> (<span class="elsevierStyleItalic">Strategic Health Action</span>) between 2013 and 2016.</p><p id="par0035" class="elsevierStylePara elsevierViewall">The project was approved by the hospital ethics committee.</p><p id="par0040" class="elsevierStylePara elsevierViewall">The study was conducted in the following phases:</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Phase 1: development of the algorithm for radiological management in cases of suspected AAS</span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Literature review</span><p id="par0045" class="elsevierStylePara elsevierViewall">The databases Best Practice, Dynamed, UptoDate, Ovid, MEDLINE and EMBASE were consulted, as well as repositories of clinical practice guidelines, ACR guidelines (ACR appropriateness criteria), guidelines from the ACCF/AHA and the ESC, to identify relevant documents on the diagnostic management and risk factors for AAS (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). A specific search was made by a documentalist looking for clinical prediction rules and validity.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Development of the algorithm, consensus and implementation</span><p id="par0050" class="elsevierStylePara elsevierViewall">The documents identified in the search were screened, and those considered most relevant as a source of evidence were selected to create the decision support algorithm on the use of CTA for diagnosis of AAS. With the selected literature we created a narrative synthesis, to design an algorithm that took into account the risk factors analyzed in these studies. It was performed by a panel of experts (six emergency physicians with 10–25 years of experience; 12 radiologists with 7–20 years of experience, eight methodologists with 5–18 years of experience) using the Delphi panel technique.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The final algorithm (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>) was integrated in the electronic medical record system of our hospital, to generate a pop-up window with questions prompting selection of risk factors when CTA was requested in patients with suspicion of AAS. It stratified the degree of suspicion of AAS, and the system would then indicate whether or not CTA would be appropriate. For imaging findings, the criteria of the ACCF / AHA guidelines<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> have been considered. In appropriate cases, a triphasic CT was performed (unenhanced and postcontrast in arterial and venous phase).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Phase 2: analysis of the outcomes of implementation</span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Design</span><span id="sec0031" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0091">-Impact of implementation of the algorithm</span><p id="par0070" class="elsevierStylePara elsevierViewall">This was a prospective study based on before-and-after observations (6 months pre-implementation and 6 months post-implementation of the CDSS), in which all requests for CTA for suspected AAS were collected. We evaluated the number of requests for CTA for suspected AAS and the diagnostic yield of these (normal study, findings of AAS, or other unrelated findings)</p></span><span id="sec0032" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0092">-Exploration of risk factors associated with radiological findings</span><p id="par0080" class="elsevierStylePara elsevierViewall">All cases of suspected AAS in the 27 successive months after implementation of the algorithm (from March 2016 to June 2018) were studied. We evaluated the association between the factors included in the CDSS and the radiological findings on CTA.</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Statistical analysis</span><p id="par0085" class="elsevierStylePara elsevierViewall">Univariate multinomial regression models were used to evaluate the association between the risk factors included in the algorithm and the radiological findings, with three categories: normal study or irrelevant/nonpathological findings, study diagnostic of AAS, or study with findings of other acute pathologies different from AAS. No multivariate models were used due to the low frequency of positive findings.</p><p id="par0090" class="elsevierStylePara elsevierViewall">P-values <0.05 were considered indicative of statistical significance.</p><p id="par0095" class="elsevierStylePara elsevierViewall">For statistical analysis the program STATA v.15.1 (StataCorp LLC, 4905 Lakeway Drive, College Station, Texas, USA) was used.</p></span></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Literature review</span><p id="par0100" class="elsevierStylePara elsevierViewall">The screening and selection process is shown in <a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>.</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">The included studies were clinical practice guidelines,<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1,4</span></a> imaging appropriateness guidelines,<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5–7</span></a> systematic reviews<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8–12</span></a> and meta-analyses<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> and other studies that evaluated risk factors for AAS.<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">14,15</span></a> No clinical prediction rules were identified.</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Development and application of the algorithm</span><p id="par0110" class="elsevierStylePara elsevierViewall">Based on the algorithm proposed by the ACCF/AHA<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> we created a modified decision support algorithm (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>) by consensus of the panel of experts (through a subsequent telematic survey).</p><p id="par0115" class="elsevierStylePara elsevierViewall">It was designed for use in patients with clinical suspicion of AAS, identifying risk factors and takes into account the presence, or not, of risk factors from the past medical history, clinical presentation, and examination findings.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Analysis of the outcomes of implementation</span><p id="par0120" class="elsevierStylePara elsevierViewall">In the 6-month-periods analyzed, before and after implementation of the CDSS, a similar number of patients were attended the emergency department (69,081 and 72,915, respectively, p = 0.067). The total number of CTs requested was also similar (5081 and 5563, respectively, p = 0.083). After implementation of the CDSS, the number of CTA requested for suspicion of AAS doubled (10 vs 21 requests). In the pre-implementation period, all the tests were negative for AAS; in the post-implantation period, there was one case (5%). Acute pathologies mimicking AAS increased (5 cases, 24% vs no cases registered before).</p><p id="par0125" class="elsevierStylePara elsevierViewall">In the 27-month-post-implementation follow-up period, 130 CTA requests for suspected AAS were recorded; 19 of these (14.6%) were diagnostic of AAS and 34 (26.2%) of other acute pathology. In total, 53 patients (40.8%) benefitted from undergoing urgent CTA because of significant pathological findings.</p><p id="par0130" class="elsevierStylePara elsevierViewall">The most frequent variables classified as risk factors were high-risk pain characteristics (63.2%), past history of aortic aneurysm (AA) (52.6%), known valve disease (36.8%), murmur of aortic regurgitation (26.3%) and hypotension or shock (26.3%) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">Regarding risk stratification, 10 patients (7.7%) were in the low-risk group, 48 (36.9%) were in the intermediate-risk group and 72 (55.4%) were in the high-risk group.</p><p id="par0140" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows the number of CTA that were positive for AAS, and for other serious acute pathologies, grouped according to pretest probability.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0145" class="elsevierStylePara elsevierViewall">The alternative radiological diagnoses in the patients with acute pathology other than AAS were cardiac disease (11 patients, 32.4%), abdominal disease (8 patients, 23.5%), pulmonary thromboembolism (PTE) (3 patients, 8.8%), pulmonary disease non-PTE (7 patients, 20.6%), aortic prosthesis complication (3 patients, 8.8%) and bone fracture (2 patients, 5.9%).</p><p id="par0150" class="elsevierStylePara elsevierViewall">The univariate analysis of the association of the different radiological diagnoses with each of the factors included in the decision support algorithm is shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>. The probability of AAS was 3.4 times higher in patients with known AA (<span class="elsevierStyleItalic">p</span> = 0.021; 95% CI 1.2–9.6) and 5.1 times higher in patients with a new murmur suggestive of aortic regurgitation (<span class="elsevierStyleItalic">p</span> = 0.019; 95% CI 1.3–20.1). The probability of having an alternative acute severe pathology was 3.2 times higher in patients with hypotension or shock (<span class="elsevierStyleItalic">p</span> = 0.02, 95 % CI 1.2–8.5). This variable did not show an increased risk of AAS that reached statistical significance.</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0155" class="elsevierStylePara elsevierViewall">Chest X-ray was performed in 54 patients and provided an alternative diagnosis in 20 of them (37%). When analyzed with Chi-squared test, the probability of having an alternative acute severe pathology was twice as high in patients with abnormalities on chest X-ray including mediastinal widening and aortic and/or cardiac contour anomalies (<span class="elsevierStyleItalic">p</span> = 0.022).</p></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Discussion</span><p id="par0160" class="elsevierStylePara elsevierViewall">Implementation of the CDSS has improved the indication of CTA in suspected AAS, finding more pathologies than in the preimplantation period and, therefore, improving the management of these patients as 14.6% were positive for AAS and 26.2% for other acute pathology (40.8% in total).</p><p id="par0165" class="elsevierStylePara elsevierViewall">The high prevalence of cardiac disease mimicking AAS justifies our recommendation to rule this out with an ECG before applying the algorithm. To perform a chest X-ray in patients with intermediate or low risk provides an alternative diagnosis in 37% of these patients. We added D-dimer measurement in patients who are low or intermediate risk, based on the results of a recent meta-analyses.<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a></p><p id="par0170" class="elsevierStylePara elsevierViewall">In the validation study of ADD-RS applied to the 2011 International Registry of Acute Aortic Dissection (IRAD) database,<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> the results by risk group were similar to ours. However, in our study, all AAS were included in the categories of intermediate and high risk.</p><p id="par0175" class="elsevierStylePara elsevierViewall">The main risk factor for AAS in our series was high-risk pain, the same as in the IRAD database published in 2018.<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> We also found a similar prevalence of hypotension and hypoperfusion. We obtained discordant results for history of AA (24.7% vs 52.6%) and aortic regurgitation murmur (40% vs 26.3%). We also found discrepancies compared with the ADD-RS validation study<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> for known aortic valve disease (11.9% vs 36.8%) and recent aortic manipulation (2.8% vs 21.1%).</p><p id="par0180" class="elsevierStylePara elsevierViewall">Recently, alternative scoring systems have been published, such as the 2020 Canadian guidelines,<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> and the AORTAs score,<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> in which history of AA was associated with a significantly higher probability of AAS. Both algorithms gave greater value to hypotension or shock, while in our series this variable was associated with alternative diagnoses. The great variability in presentation of AAS makes it necessary a sensitive algorithm to avoid underdiagnosis without performing unnecessary investigations in patients with low pretest probability.</p><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Limitations</span><p id="par0185" class="elsevierStylePara elsevierViewall">The differences from other studies based on IRAD must be interpreted with caution, as our study, unlike IRAD, included the whole AAS spectrum taking into account complicated aneurysms and prostheses.</p><p id="par0190" class="elsevierStylePara elsevierViewall">This is a small sample, a fact that explains the wide CI of the RRR of the risk factors studied. Increasing the sample size could reveal a higher and/or significant RRR for risk factors that have not shown statistical significance.</p><p id="par0195" class="elsevierStylePara elsevierViewall">Since the reference test was not carried out for those classified as low risk, the specificity cannot be calculated, nor can it be known how many AAS were not diagnosed for this reason.</p><p id="par0200" class="elsevierStylePara elsevierViewall">The marked increase in CT requests after the implementation of the algorithm could be due to an observational bias and/or a consequence of learning through the algorithm itself about the clinical diagnosis of the AAS and its differential diagnoses.</p><p id="par0205" class="elsevierStylePara elsevierViewall">This CDSS was implemented in a tertiary hospital, so we cannot extrapolate the results to other non-tertiary hospitals. We did not assess the satisfaction of the professionals using the algorithm or the potential difficulties of putting the system into practice.</p><p id="par0210" class="elsevierStylePara elsevierViewall">The study period was very short due to issues with the electronic medical record system at our hospital. The number of observations are insufficient to develop a clinical prediction rule. A prospective validation study of the score with more patients is needed.</p><p id="par0215" class="elsevierStylePara elsevierViewall">As a conclusion, the use of a sensitive algorithm in the emergency department can be useful to optimize the diagnosis of AAS. The implementation at our hospital of this evidence-based pathway for requesting CTA in patients with suspected AAS achieved an improvement in AAS management. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. The existence of hypotension or shock increased the risk of alternative severe acute disease. Further studies are needed to establish a clinical prediction rule.</p></span></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Funding</span><p id="par0220" class="elsevierStylePara elsevierViewall">This study was supported by the Instituto de Salud Carlos III (Plan Estatal de I + D+i 2013–2016) projects (P13/00896, P13/01183, P16/00296, PI16/01786, P16/01828, P16/00558) and cofinanced by the European Development Regional Fund “A way to achieve Europe” (EDRF).</p></span><span id="sec0081" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0141">Authorship</span><p id="par0001" class="elsevierStylePara elsevierViewall">1. Responsible for study integrity: JZ, AVB, JC, and AM.</p><p id="par0002" class="elsevierStylePara elsevierViewall">2. Study conception: JZ, AVB, and JC.</p><p id="par0003" class="elsevierStylePara elsevierViewall">3. Study design: AM and JZ.</p><p id="par0004" class="elsevierStylePara elsevierViewall">4. Data acquisiton: AMBL-F, AVB, and BMF-F.</p><p id="par0006" class="elsevierStylePara elsevierViewall">5. Data analysis and interpretation: BL-F, BMF-F, and AM.</p><p id="par0007" class="elsevierStylePara elsevierViewall">6. Statistical processing: BMF-F and AM.</p><p id="par0008" class="elsevierStylePara elsevierViewall">7. Literature search: JC.</p><p id="par0009" class="elsevierStylePara elsevierViewall">8. Drafting of the manuscript: BL-F and AVB.</p><p id="par0011" class="elsevierStylePara elsevierViewall">9. Critical review of the manuscript with intellectually significant contributions: BL-F, AVB, AM, and JZ.</p><p id="par0012" class="elsevierStylePara elsevierViewall">10. Approval of the final version: BL-F, AVB, and AM.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflicts of interest</span><p id="par0225" class="elsevierStylePara elsevierViewall">None.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1975832" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1699471" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1975833" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1699470" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:2 [ 0 => array:3 [ "identificador" => "sec0015" "titulo" => "Phase 1: development of the algorithm for radiological management in cases of suspected AAS" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0020" "titulo" => "Literature review" ] 1 => array:2 [ "identificador" => "sec0025" "titulo" => "Development of the algorithm, consensus and implementation" ] ] ] 1 => array:3 [ "identificador" => "sec0030" "titulo" => "Phase 2: analysis of the outcomes of implementation" "secciones" => array:2 [ 0 => array:3 [ "identificador" => "sec0035" "titulo" => "Design" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0031" "titulo" => "-Impact of implementation of the algorithm" ] 1 => array:2 [ "identificador" => "sec0032" "titulo" => "-Exploration of risk factors associated with radiological findings" ] ] ] 1 => array:2 [ "identificador" => "sec0040" "titulo" => "Statistical analysis" ] ] ] ] ] 6 => array:3 [ "identificador" => "sec0045" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0050" "titulo" => "Literature review" ] 1 => array:2 [ "identificador" => "sec0055" "titulo" => "Development and application of the algorithm" ] 2 => array:2 [ "identificador" => "sec0060" "titulo" => "Analysis of the outcomes of implementation" ] ] ] 7 => array:3 [ "identificador" => "sec0065" "titulo" => "Discussion" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0070" "titulo" => "Limitations" ] ] ] 8 => array:2 [ "identificador" => "sec0075" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0081" "titulo" => "Authorship" ] 10 => array:2 [ "identificador" => "sec0080" "titulo" => "Conflicts of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2021-11-03" "fechaAceptado" => "2022-03-15" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1699471" "palabras" => array:6 [ 0 => "Acute aortic syndrome" 1 => "Chest pain" 2 => "Thoracic pain" 3 => "Algorithm" 4 => "Aortic CT angiography" 5 => "Clinical decision support system (CDSS)" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1699470" "palabras" => array:6 [ 0 => "Síndrome aórtico agudo" 1 => "Dolor en el pecho" 2 => "Dolor torácico" 3 => "Algoritmo" 4 => "Angiografía aórtica por TAC" 5 => "Sistema de apoyo a las decisiones clínicas (SADC)" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and objective</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm <span class="elsevierStyleItalic">(P</span> = .021, 95% CI 1.2–9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur <span class="elsevierStyleItalic">(P</span> = .019, 95% CI 1.3–20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock <span class="elsevierStyleItalic">(P</span> = .02, 95% CI 1.2–8.5).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and 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">Antecedentes y objetivo</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">El síndrome aórtico agudo (SAA) es poco frecuente y difícil de diagnosticar, con una gran variabilidad en su cuadro clínico inicial. Desarrollar un algoritmo informático, o un sistema de apoyo a las decisiones clínicas (SADC), para el manejo y la solicitud de estudios de diagnóstico por la imagen en el servicio de Urgencias, en concreto de una tomografía axial computarizada (TAC) de la aorta, ante la sospecha de SAA, y determinar el efecto de la implantación de este sistema. Determinar los factores asociados a un diagnóstico radiológico positivo que mejoren la capacidad predictiva de los hallazgos de la TAC de aorta.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y métodos</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Tras desarrollar e implementar un algoritmo basado en la evidencia, se estudiaron presuntos casos de SAA. Se utilizó la prueba de la χ2 para analizar la asociación entre las variables incluidas en el algoritmo y el diagnóstico radiológico, con 3 categorías: sin hallazgos relevantes, positivo para SAA y diagnósticos alternativos.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Resultados</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">Se identificaron 130 solicitudes; 19 (14,6%) tenían SAA y 34 (26,2%) tenían otra enfermedad aguda. De las 19 con SAA, 15 habían sido estratificadas como de alto riesgo y 4 como de riesgo intermedio. La probabilidad de SAA era 3,4 veces mayor en los pacientes con aneurisma aórtico conocido <span class="elsevierStyleItalic">(p</span> = 0,021, IC del 95%: 1,2–9,6) y 5,1 veces mayor en los pacientes con un nuevo soplo por insuficiencia valvular aórtica <span class="elsevierStyleItalic">(p</span> = 0,019, IC del 95 %: 1,3–20,1). La probabilidad de tener una enfermedad aguda grave alternativa fue 3,2 veces mayor en los pacientes con hipotensión o choque <span class="elsevierStyleItalic">(p</span> = 0,02, IC del 95 %: 1,2–8,5).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conclusión</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">El uso de un SADC en el servicio de Urgencias puede ayudar a optimizar el diagnóstico del SAA. Se demostró que la presencia de un aneurisma aórtico conocido y de insuficiencia valvular aórtica de nueva aparición aumentan significativamente la probabilidad de SAA. Se necesitan más estudios para establecer una regla de predicción clínica.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:6 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1003 "Ancho" => 2091 "Tamanyo" => 139929 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Bibliographic search scheme.</p> <p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">For this systematic search we combined search terms associated with the disease (<span class="elsevierStyleItalic">acute aortic syndrome, aortic dissection, acute intramural hematoma, penetrating aortic ulcer, periaortic hematoma, unstable aneurysm, complicated aortic prosthesis</span>), the reason for attendance (<span class="elsevierStyleItalic">acute chest pain, thoracic pain, chest pain, sudden onset excruciating anterior or interscapular</span>), crossing them with terms for the imaging technique and synonyms (<span class="elsevierStyleItalic">aortic CT angiography, CT angiography, contrast enhanced CT),</span> and the study setting <span class="elsevierStyleItalic">(emergency</span>) (supplementary Fig. 3). To restrict the search we used methodological filters for clinical prediction rules including Haynes Broad Filter (HBF) and Teljeur/Murphy Inclusion Filter 26 items (TMIF-26) and exclusion filter (TMEF).</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1501 "Ancho" => 2500 "Tamanyo" => 350592 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Algorithm for AAS risk stratification and diagnostic management.</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Step 1: Scoring based on the presence of risk factors. Each existing condition scores one point. Abrupt-onset, severe pain with any of the classical characteristics described (it need not meet all descriptive criteria) scores 1 point. Any sign of perfusion deficit, new-onset aortic regurgitation murmur or the presence of hypotension or shock each score 1 point, independently.</p> <p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Step 2: Risk stratification. Score 0: low risk. Score 1: Intermediate risk. Score 2 or more: high risk.</p> <p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Step 3: Diagnostic approach. Low or intermediate risk: measure <span class="elsevierStyleSmallCaps">d</span>-dimer (with cutoff of 500 ng/mL) and perform PA and lateral chest X-ray. If these suggest a different diagnosis or are normal, CTA is not indicated. If D-dimer is raised, chest X-ray suggests aortic pathology, or there is unexplained sustained hypotension, CTA should be performed. High risk: perform urgent CTA as a first line.</p> <p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Note: if the physician considers CT necessary against the algorithm's indication, he/she can indicate it in the observations of the application form to be performed.</p> <p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">BP = blood pressure.</p> <p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Observations: figure to be published preferably in color.</p>" ] ] 2 => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1372 "Ancho" => 2500 "Tamanyo" => 164662 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Literature search process.</p> <p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">The Haynes pyramid of the 5S was used, accessing the publications of the highest possible level according to the following order: 5-aid systems for clinical decision making; 4-clinical practice guidelines; 3-critical reviews of articles; 2-systematic reviews. 573 studies were identified; 6 of these were excluded as duplicates and 550 as the articles did not meet the criteria (level 1 studies including original studies, primary sources and case series, studies describing findings and sensitivity of imaging tests, studies not in English or Spanish, or in a pediatric population). Ultimately, the analysis and qualitative synthesis included 17 studies that were used to develop the decision support algorithm.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">No relevant findings \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">AAS \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">Alternative diagnosis \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n = 77 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n = 19 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">n = 34 \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Marfan syndrome \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (8.8%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Connective tissue disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (2.6%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (5.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (8.8%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Family history of aortic disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (6.5%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (5.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (11.8%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Known valve disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (33.8%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (36.8%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (14.7%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Recent aortic manipulation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (7.8%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (21.1%) \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">3 (8.8%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aortic aneurysm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (24.7%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (52.6%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (17.6%) \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">High-risk pain \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (62.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (63.2%) \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">23 (67.6%) \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">Perfusion deficit \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (16.9%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (21.1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (32.4%) \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">Murmur of aortic regurgitation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (6.5%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (26.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (14.7%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypotension or shock \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (13.0%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (26.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (32.4%) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3288941.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Absolute and relative frequencies of each of the positive risk factors recorded on CTA requests according to radiological diagnosis.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Risk category \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">No relevant findings \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">AAS \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">Alternative diagnosis \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">Total \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Low \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (70%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (30%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 \t\t\t\t\t\t\n \t\t\t\t</td></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">Intermediate \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (56.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (8.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (35.4%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 \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">High \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 (59.7%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (20.8%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (19.4%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77 (59.2%) \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">19 (14.6%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 (26.2%) \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">130 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3288942.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Association between risk groups by pretest probability of AAS; absolute and relative frequencies of findings on CTA grouped into no relevant findings, positive findings for AAS and findings associated with other acute processes.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate multinomial logistic regression</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \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">AAS \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">Alternative diagnosis \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">RRR (95% CI) \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">RRR (95% CI) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Marfan syndrome \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Not estimable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Not estimable \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">Connective tissue disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.08 (0.18–24.26) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.63 (0.58–22.79) \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">Family history of aortic disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.80 (0.09–7.28) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.92 (0.48–7.65) \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">Known valve disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.14 (0.40–3.25) \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">0.34 (0.12–0.98) \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">Recent aortic manipulation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.16 (0.79–12.57) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.15 (0.27–4.88) \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">Aortic aneurysm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.39 (1.20–9.59) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.65 (0.24–1.82) \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">High-risk pain \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.04 (0.37–2.93) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.26 (0.54–2.97) \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">Perfusion deficit \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.31 (0.37–4.60) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.35 (0.93–5.99) \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">Murmur of aortic regurgitation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.14 (1.31–20.15) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.48 (0.67–9.22) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypotension or shock \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.39 (0.71–8.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.20 (1.20–8.53) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3288940.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Univariate multinomial logistic regression analysis of the association of the risk factors from the decision support algorithm with findings of AAS or other unrelated findings. 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