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array:24 [ "pii" => "S2173511516300185" "issn" => "21735115" "doi" => "10.1016/j.rppnen.2016.03.012" "estado" => "S300" "fechaPublicacion" => "2016-11-01" "aid" => "1163" "copyright" => "Sociedade Portuguesa de Pneumologia" "copyrightAnyo" => "2016" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "Rev Port Pneumol. 2016;22:308-14" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1379 "formatos" => array:3 [ "EPUB" => 199 "HTML" => 629 "PDF" => 551 ] ] "itemSiguiente" => array:19 [ "pii" => "S2173511516300410" "issn" => "21735115" "doi" => "10.1016/j.rppnen.2016.05.005" "estado" => "S300" "fechaPublicacion" => "2016-11-01" "aid" => "1176" "copyright" => "Sociedade Portuguesa de Pneumologia" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "Rev Port Pneumol. 2016;22:315-22" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1545 "formatos" => array:3 [ "EPUB" => 217 "HTML" => 787 "PDF" => 541 ] ] "en" => array:12 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Acute exercise amplifies inflammation in obese patients with COPD" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "315" "paginaFinal" => "322" ] ] "contieneResumen" => array:1 [ "en" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 394 "Ancho" => 2271 "Tamanyo" => 27976 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Blood sampling scheme and maximal exercise test.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "F. Rodrigues, A.L. Papoila, D. Ligeiro, M.J.M. Gomes, H. Trindade" "autores" => array:5 [ 0 => array:2 [ "nombre" => "F." "apellidos" => "Rodrigues" ] 1 => array:2 [ "nombre" => "A.L." "apellidos" => "Papoila" ] 2 => array:2 [ "nombre" => "D." "apellidos" => "Ligeiro" ] 3 => array:2 [ "nombre" => "M.J.M." "apellidos" => "Gomes" ] 4 => array:2 [ "nombre" => "H." "apellidos" => "Trindade" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173511516300410?idApp=UINPBA00004E" "url" => "/21735115/0000002200000006/v1_201612110145/S2173511516300410/v1_201612110145/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S2173511516301324" "issn" => "21735115" "doi" => "10.1016/j.rppnen.2016.11.004" "estado" => "S300" "fechaPublicacion" => "2016-11-01" "aid" => "1204" "copyright" => "Sociedade Portuguesa de Pneumologia" "documento" => "simple-article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "edi" "cita" => "Rev Port Pneumol. 2016;22:305-7" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1471 "formatos" => array:3 [ "EPUB" => 217 "HTML" => 788 "PDF" => 466 ] ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Editorial</span>" "titulo" => "IMPACT FACTOR 1,35Once again; what should and could we do about it?" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "305" "paginaFinal" => "307" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 852 "Ancho" => 1649 "Tamanyo" => 69447 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">PJP impact factor evolution in the last five years.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "A. Morais" "autores" => array:1 [ 0 => array:2 [ "nombre" => "A." "apellidos" => "Morais" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173511516301324?idApp=UINPBA00004E" "url" => "/21735115/0000002200000006/v1_201612110145/S2173511516301324/v1_201612110145/en/main.assets" ] "en" => array:18 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Mid-regional proadrenomedullin: An early marker of response in critically ill patients with severe community-acquired pneumonia?" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "308" "paginaFinal" => "314" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "J.M. Pereira, A. Azevedo, C. Basílio, C. Sousa-Dias, P. Mergulhão, J.A. Paiva" "autores" => array:6 [ 0 => array:4 [ "nombre" => "J.M." "apellidos" => "Pereira" "email" => array:1 [ 0 => "jmcrpereira@yahoo.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "A." "apellidos" => "Azevedo" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 2 => array:3 [ "nombre" => "C." "apellidos" => "Basílio" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "C." "apellidos" => "Sousa-Dias" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "P." "apellidos" => "Mergulhão" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 5 => array:3 [ "nombre" => "J.A." "apellidos" => "Paiva" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Emergency and Intensive Care Department, Centro Hospitalar São João EPE, Porto, Portugal" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Medicine, University of Porto Medical School, Porto, Portugal" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Hospital Epidemiology Centre, Centro Hospitalar São João EPE, Porto, Portugal" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Portugal" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "EPIUnit – Institute of Public Health, University of Porto, Portugal" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1091 "Ancho" => 1519 "Tamanyo" => 74926 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Discrimination of mid-regional proadrenomedullin kinetics in the first 48<span class="elsevierStyleHsp" style=""></span>h after antibiotic therapy, as measured by the percent decrease from baseline, to predict hospital mortality (aROC 0.80; 95% CI 0.47–1.00).</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Community-acquired pneumonia (CAP) remains a major cause of morbidity, mortality and healthcare costs.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">1–3</span></a> In 9–16% of cases, ICU admission is needed, due to severe respiratory failure, severe sepsis or septic shock.<a class="elsevierStyleCrossRefs" href="#bib0175"><span class="elsevierStyleSup">4–6</span></a> In these patients, mortality is high, reaching 50% in those patients requiring vasopressor support.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">7</span></a> Inadequate initial antibiotic therapy is a poor prognostic factor.<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">8–10</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Severity assessment and outcome prediction are fundamental in the management of CAP patients, both to allocate the most appropriate site of care and to select empirical antibiotic and adjuvant therapy. Response assessment is also paramount. Early identification of responders and non-responders could help reduce antibiotic consumption or allow earlier rescue antibiotic therapy. However, there is no standard definition for clinical response in severe CAP.</p><p id="par0015" class="elsevierStylePara elsevierViewall">Efforts have been made to study the usefulness of biomarkers, as a complement to clinical judgment, in the diagnosis, severity assessment, treatment, prognosis and follow-up of CAP. In recent years, promising data regarding the role of adrenomedullin (ADM) in the management of CAP have been published.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">11–13</span></a> This hormone, a peptide with 52 aminoacids, is a potent vasodilator agent with immune modulating and metabolic properties and bactericidal activity that increases in sepsis.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">14</span></a> It is produced by multiple tissue types but, unfortunately, its serum levels are difficult to measure, since it is rapidly cleared from the circulation.<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">15–17</span></a> However, the more stable mid-region fragment of proadrenomedullin (MR-proADM) directly reflects levels of ADM.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">18</span></a> This biomarker may be as good as validated pneumonia-specific severity scores at detecting patients with severe CAP and is probably better than other biomarkers, such as procalcitonin.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">11,12</span></a> MR-proADM serum level correlate well with mortality (both short and long term)<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">19</span></a> and its addition to clinical scoring systems improves their discriminatory power.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">11–13</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">The purpose of our study was to evaluate the value of MR-proADM at ICU admission for further severity stratification and outcome prediction and to assess its kinetics as an early marker of response in SCAP patients.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Study design</span><p id="par0025" class="elsevierStylePara elsevierViewall">This was a single-center, observational, prospective cohort study of 19 patients with severe CAP admitted to the Intensive Care Department of a tertiary care university hospital in Portugal between March 2012 and January 2013. The study was approved by the local ethics committee. Written informed consent was obtained from every patient or patient representative prior to inclusion in the study.</p><p id="par0030" class="elsevierStylePara elsevierViewall">CAP was diagnosed when, in addition to suggestive clinical features (e.g. cough, fever, sputum production, pleuritic chest pain), a demonstrable infiltrate by chest radiograph or CT scan was present. Severe CAP was defined according to the Infectious Diseases Society of America/American Thoracic Society criteria (IDSA/ATS).<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">20</span></a> In order to be included into this study, patients had to be older than 18 years old and have MR-proADM measured within 12<span class="elsevierStyleHsp" style=""></span>h after the first antibiotic dose.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Data collection</span><p id="par0035" class="elsevierStylePara elsevierViewall">The following parameters were registered by the investigators in a specifically created database at the moment or within the first 24<span class="elsevierStyleHsp" style=""></span>h of ICU admission: age, sex, co-morbidities, corticosteroids use, existence or development of septic shock and/or acute respiratory distress syndrome and empiric antibiotic therapy. The duration of mechanical ventilation, length of hospital and ICU stay and mortality (ICU, hospital and 1-year) were also recorded. Simplified Acute Physiology Score (SAPS) II<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">21</span></a>, Sepsis-related Organ Failure Assessment (SOFA) score<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">22</span></a>, Pneumonia Severity Index (PSI)<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">6</span></a> and PIRO-CAP<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">23</span></a> were calculated.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Proadrenomedullin determination</span><p id="par0040" class="elsevierStylePara elsevierViewall">Within 12<span class="elsevierStyleHsp" style=""></span>h of the first antibiotic dose, a blood sample was withdrawn for the determination of MR-proADM and the process was repeated 48<span class="elsevierStyleHsp" style=""></span>h later except for one patient.</p><p id="par0045" class="elsevierStylePara elsevierViewall">MR-proADM concentrations (normal<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.52<span class="elsevierStyleHsp" style=""></span>nmol/l) were measured at the Clinical Biochemistry Laboratory of Hospital Universitario Central de Asturias (Oviedo, Spain) in an automated Kryptor analyzer, using TRACE technology (Kryptor; BRAHMS, Hennigsdorf, Germany), without any pre-analytical treatments (i.e., extraction or derivatization). Analytical characteristics of the assay and reference values for the healthy adult population have already been described.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">24</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Microbiologic evaluation</span><p id="par0050" class="elsevierStylePara elsevierViewall">At the point of inclusion into the study, two pairs of blood cultures were collected. Blood cultures were processed using an automated microbiology growth and detection system (BACTEC). If there was bacterial growth, samples were Gram stained and subcultured. A bacteremic episode was defined as growth of a typical organism for CAP in at least one of four collected blood cultures.</p><p id="par0055" class="elsevierStylePara elsevierViewall">Tracheal aspirate was taken from every patient whenever possible to test for bacteria according to standard procedures. Representative sputum originating from the lower respiratory tract was validated by the criteria of >25 granulocytes and <10 epithelial cells per low power field (total magnification<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>100).</p><p id="par0060" class="elsevierStylePara elsevierViewall">Urine samples were collected and tested whenever possible for <span class="elsevierStyleItalic">Legionella pneumophila</span> and <span class="elsevierStyleItalic">Streptococcus pneumoniae</span> with an antigen test. Real-time polymerase chain reaction was used to evaluate the presence of respiratory virus in nasopharyngeal swab and bronchoalveolar lavage when clinically and epidemiologically indicated. Pleural fluid when available was also collected.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Identification of microorganisms and susceptibility testing was performed according to standard methods.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">Categorical variables are described as counts and percentages and continuous variables as the median and interquartile range (IQR). MR-proADM kinetics was quantified as the percent change from baseline according to: (100*(MR-proADM[48<span class="elsevierStyleHsp" style=""></span>h]<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>MR-proADM[baseline])/MR-proADM[baseline]. Spearman's correlations were used to quantify the association between MR-proADM and severity scores. Median MD-proADM levels were compared across subgroups using the Kruskal–Wallis test. The area under the receiver operating characteristics (ROC) curves was estimated to quantify the discrimination of MR-proADM in predicting death at different times. The association between the change in MR-proADM and death was assessed by odds ratios (OR) estimated by logistic regression, adjusting for severity scores.</p><p id="par0075" class="elsevierStylePara elsevierViewall">Statistical analysis was performed using the statistical package Stata version 11.1 for Windows (StataCorp LP, College Station, TX).</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Demographic and clinical characteristics of patients</span><p id="par0080" class="elsevierStylePara elsevierViewall">The median age of the overall cohort was 68 years (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>64–82), 58% were male and 89.5% of the cases were in high-risk PSI classes IV and V. Median SAPS II and SOFA score were 55 (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>41–61) and 9 (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>8–12), respectively. <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows global baseline characteristics at hospital admission.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">SCAP was microbiologically documented in 58% cases and <span class="elsevierStyleItalic">S. pneumoniae</span> (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>6) was the leading pathogen followed by <span class="elsevierStyleItalic">L. pneumophila</span> (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3). All patients received antibiotic therapy concordant with IDSA/ATS guidelines.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">20</span></a></p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Proadrenomedullin at ICU admission and severity scores</span><p id="par0090" class="elsevierStylePara elsevierViewall">Median MR-proADM at ICU admission was 3.58<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.83–10.00). In this cohort, no significant association was found between MR-proADM serum levels at admission and severity assessed by SAPS II (Spearman's correlation<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.24; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.31) (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). MR-proADM serum levels were higher in patients with SOFA score ≥10, but this difference did not reach statistical significance (SOFA score<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>10: 3.90<span class="elsevierStyleHsp" style=""></span>nmol/l vs. SOFA score<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>10: 3.45<span class="elsevierStyleHsp" style=""></span>nmol/l; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.74) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">As for SOFA score, patients with higher pneumonia-specific severity scores, such as PSI (class III and IV: 2.78<span class="elsevierStyleHsp" style=""></span>nmol/l vs. class V: 3.74<span class="elsevierStyleHsp" style=""></span>nmol/l; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.29) and PIRO CAP (mild risk: 2.53<span class="elsevierStyleHsp" style=""></span>nmol/l vs. high risk: 4.93<span class="elsevierStyleHsp" style=""></span>nmol/l vs. very high risk: 3.89; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.23), had higher MR-proADM serum levels but the differences were not statistically significant.</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Proadrenomedullin at ICU admission and outcome</span><p id="par0100" class="elsevierStylePara elsevierViewall">ICU, hospital and one-year mortality were 16%, 26% and 32%, respectively. Median MR-proADM serum levels were similar, in survivors and non-survivors regarding hospital [survivors 3.51<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.60–13.00) vs. non-survivors 3.89<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.10–8.10); <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.89] and 1-year mortality [survivors 3.58<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>2.40–13.00) vs. non-survivors 3.67<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.30–7.20); <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.0]. Receiver operating characteristic (ROC) curve analysis showed that this biomarker at ICU admission had a bad discriminatory power to predict hospital [aROC 0.53; 95% confidence interval (CI) 0.26–0.79] and 1-year mortality (aROC 0.51; 95% CI 0.25–0.78) (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>).</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Proadrenomedullin kinetics and outcome</span><p id="par0105" class="elsevierStylePara elsevierViewall">After 48<span class="elsevierStyleHsp" style=""></span>h of antibiotic therapy, MR-proADM serum levels decreased in all but 5 patients (median −20%; IQR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−56% to +0.1%). MR-proADM kinetics measured by the percent change from baseline was a good predictor of hospital mortality (aROC 0.80; 95% CI: 0.47–1.00) (<a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>).</p><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">The best discrimination was achieved by classifying patients according to MR-proADM decreasing (one patient died out of 13) or not (4 out of 5 died) within 48<span class="elsevierStyleHsp" style=""></span>h of antibiotic therapy. The absence of reduction in this biomarker significantly increased the chances of dying in the hospital independently of general severity [SAPS II-adjusted odds ratio (OR) 174; 95% CI: 2–15,422; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.024].</p></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0115" class="elsevierStylePara elsevierViewall">In our study MR-proADM at ICU admission and within 12<span class="elsevierStyleHsp" style=""></span>h of first antibiotic dose did not further stratify severity in patients with SCAP. Furthermore, serum MR-proADM at this stage did not perform well as a predictor of both short- (ICU and hospital) and long-term (one-year) mortality. Nevertheless, MR-proADM kinetics in the first 48<span class="elsevierStyleHsp" style=""></span>h after antibiotic therapy was a good tool to predict hospital mortality.</p><p id="par0120" class="elsevierStylePara elsevierViewall">Considering the morbidity and mortality associated with CAP, early identification of high risk patients is of paramount importance. Several papers demonstrate an association between this biomarker's serum levels and severity assessed by pneumonia specific scores such as PSI. Christ-Cain et al. and Huang DT et al.,<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">11,12</span></a> reported that MR-proADM levels consistently rise as PSI class increases (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). In 49 patients with severe sepsis/septic shock due to CAP admitted to the ICU, MR-proADM consistently rose as PSI advanced from II to V (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.02).<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">25</span></a> Yet, our results, like those of Akpinar et al.,<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">26</span></a>, do not support this finding. Although patients in PSI class V presented higher MR-proADM serum levels, we did not observe any significant difference across different risk classes of this score. Besides the sample size, differences in study cohort, namely the fact that only severe CAP patients were included, may explain these different results.</p><p id="par0125" class="elsevierStylePara elsevierViewall">We also did not find a significant association with severity assessed by SAPS II or SOFA score. In contrast, Marino et al.,<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">27</span></a>, in a prospective observational study in patients with suspected sepsis presenting to the Emergency Department, observed a moderate association of MR-proADM with severity of disease evaluated by APACHE II score (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.46; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). This correlation was also described by Travaglino et al.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">28</span></a> In a Swiss study with 101 critically ill patients, MR-proADM levels on ICU admission exhibited correlation with APACHE II score (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.42; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001) and SAPS II score (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.5; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001).<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">29</span></a> These differences may be explained by the different types of population studied. Indeed, our study was the first to include only critically ill patients with severe sepsis or septic shock, a significant proportion of them (68%) needing vasopressors at ICU admission. The fact that MR-proADM serum levels are higher in these groups of patients<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">27,29</span></a> may explain the lack of relationship between this biomarker and severity scores in our study.</p><p id="par0130" class="elsevierStylePara elsevierViewall">In the emergency department, MR-proADM seems to be a very good prognostic tool to predict both short and long-term outcome in patients with lower respiratory tract infections.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">19</span></a> However, when the analysis is restricted to the most severe patients, conflicting results have been published. According to Christ-Crain study,<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">29</span></a> the prognostic accuracy for ICU mortality of this biomarker on admission, in septic critically ill patients, is good (AUC 0.81), similar to severity scores such as APACHE II and SAPS II score and significantly better than other biomarkers such as C-reactive protein. Huang's study<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">12</span></a> showed that, within PSI classes IV/V (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>546), subjects with MR-proADM higher than 1.45<span class="elsevierStyleHsp" style=""></span>nmol/l had a higher 30-day mortality rate (23% vs. 9%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). In a subgroup of patients (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>61) with high risk PSI scores (classes IV and V), Courtais et al.,<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">30</span></a> showed that, in univariate logistic regression analysis, MR-proADM levels significantly predicted 30-day mortality risk (OR 4.68; 95% CI: 1.66–20.22) with an aROC curve of 0.81 (95% CI: 0.65–0.96). Nevertheless, only 24 of these patients were admitted to the ICU.</p><p id="par0135" class="elsevierStylePara elsevierViewall">Like other studies, we observed a low discriminatory power of MR-proADM to predict hospital and one-year mortality. Apkinar<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">26</span></a> reported that this biomarker had a bad discriminatory power to predict 4- (AUC 0.505) and 8-week mortality (AUC 0.513) and Marino et al.<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">27</span></a> showed a poor performance to predict 28 day-mortality (AUC 0.60). Despite being slightly better than previously reported, in Suberviola's study the discriminatory power of this pro-hormone to predict hospital mortality was only moderate (AUC 0.72).<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">25</span></a></p><p id="par0140" class="elsevierStylePara elsevierViewall">Until now, there have been no published data regarding the value of MR-proADM kinetics in the management of SCAP patients. In our cohort, we found that after 48<span class="elsevierStyleHsp" style=""></span>h of antibiotic therapy, the percent change from baseline was a good predictor of hospital mortality. Indeed, the absence of decrease in serum levels was an independent risk factor for hospital mortality. Similar findings were described in other groups of patients. For instance, in febrile patients with hematologic malignancies,<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">31</span></a> serum MR-proADM levels dropped in patients who responded to therapy whereas in patients who did not respond there was no significant change between initial (at fever onset) and follow-up levels (4–7 days later). Furthermore, septic patients admitted to the emergency department with high plasma ADM (>70<span class="elsevierStyleHsp" style=""></span>pg/ml) that present a decrease in serum levels in the first 4 days of therapy have a higher survival rate than those patients whose levels remain above that threshold (100% vs. 36%).<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">27</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">The fact that this biomarker was collected within 12<span class="elsevierStyleHsp" style=""></span>h after the first antibiotic dose in patients without prior antibiotic use and that all patients were prospectively enrolled are two of the strengths of this study. However, some limitations also merit consideration, namely the fact that it was a single center study and that the generalizability of our findings is limited by the small sample size (only 19 patients). Therefore, these results should be validated in a large multicenter study.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Conclusions</span><p id="par0150" class="elsevierStylePara elsevierViewall">We concluded that, in SCAP patients, MR-proADM on ICU admission is not useful for further severity stratification and to predict both short- and long-term outcome. However, its kinetics in the first 48<span class="elsevierStyleHsp" style=""></span>h after antibiotic therapy may be a helpful tool to assist clinicians in identifying patients with a better clinical outcome. Moreover, although further studies are needed, decreasing levels of this biomarker, as a sign of early response to therapy, may lead to shorter duration of antibiotic therapy and play a role in antibiotic stewardship.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Authors’ contributions</span><p id="par0155" class="elsevierStylePara elsevierViewall">All authors have made substantial contribution to the conception and design of the study as well as in the drafting, revising and final approval of the version to be published. JMP and AA performed statistical analysis.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Ethical disclosures</span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Protection of human and animal subjects</span><p id="par0160" class="elsevierStylePara elsevierViewall">The authors declare that no experiments were performed on humans or animals for this study.</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Confidentiality of data</span><p id="par0165" class="elsevierStylePara elsevierViewall">The authors declare that they have followed the protocols of their work center on the publication of patient data.</p></span><span id="sec0095" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Right to privacy and informed consent</span><p id="par0170" class="elsevierStylePara elsevierViewall">The authors declare that the procedures followed were in accordance with the regulations of the relevant clinical research ethics committee and with those of the Code of Ethics of the World Medical Association (Declaration of Helsinki). The authors have obtained the written informed consent of the patients included in this study. The corresponding author is in possession of this document.</p></span></span><span id="sec0100" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Conflict of interest</span><p id="par0175" class="elsevierStylePara elsevierViewall">The authors declare that they have no competing interests.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres771337" "titulo" => "Abstract" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Purpose" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Materials and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec772524" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xpalclavsec772523" "titulo" => "Abbreviations" ] 3 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 4 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study design" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Data collection" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Proadrenomedullin determination" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Microbiologic evaluation" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Statistical analysis" ] ] ] 5 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Demographic and clinical characteristics of patients" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "Proadrenomedullin at ICU admission and severity scores" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Proadrenomedullin at ICU admission and outcome" ] 3 => array:2 [ "identificador" => "sec0060" "titulo" => "Proadrenomedullin kinetics and outcome" ] ] ] 6 => array:2 [ "identificador" => "sec0065" "titulo" => "Discussion" ] 7 => array:2 [ "identificador" => "sec0070" "titulo" => "Conclusions" ] 8 => array:2 [ "identificador" => "sec0075" "titulo" => "Authors’ contributions" ] 9 => array:3 [ "identificador" => "sec0080" "titulo" => "Ethical disclosures" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0085" "titulo" => "Protection of human and animal subjects" ] 1 => array:2 [ "identificador" => "sec0090" "titulo" => "Confidentiality of data" ] 2 => array:2 [ "identificador" => "sec0095" "titulo" => "Right to privacy and informed consent" ] ] ] 10 => array:2 [ "identificador" => "sec0100" "titulo" => "Conflict of interest" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-02-07" "fechaAceptado" => "2016-03-09" "PalabrasClave" => array:1 [ "en" => array:2 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec772524" "palabras" => array:5 [ 0 => "Proadrenomedullin" 1 => "Biomarkers" 2 => "Severe community acquired pneumonia" 3 => "Outcome" 4 => "Critically ill patients" ] ] 1 => array:4 [ "clase" => "abr" "titulo" => "Abbreviations" "identificador" => "xpalclavsec772523" "palabras" => array:12 [ 0 => "CAP" 1 => "ICU" 2 => "COPD" 3 => "SAPS" 4 => "PIRO" 5 => "SOFA" 6 => "PSI" 7 => "MR-proADM" 8 => "SD" 9 => "IQR" 10 => "ROC" 11 => "aROC" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Mid-regional proadrenomedullin (MR-proADM) is a novel biomarker with potential prognostic utility in patients with community-acquired pneumonia (CAP).</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Purpose</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">To evaluate the value of MR-proADM levels at ICU admission for further severity stratification and outcome prediction, and its kinetics as an early predictor of response in severe CAP (SCAP).</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Materials and methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Prospective, single-center, cohort study of 19 SCAP patients admitted to the ICU within 12<span class="elsevierStyleHsp" style=""></span>h after the first antibiotic dose.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">At ICU admission median MR-proADM was 3.58<span class="elsevierStyleHsp" style=""></span>nmol/l (IQR: 2.83–10.00). No significant association was found between its serum levels at admission and severity assessed by SAPS II (Spearman's correlation<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.24, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.31) or SOFA score (SOFA<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>10: <3.45<span class="elsevierStyleHsp" style=""></span>nmol/l vs. SOFA<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>10: 3.90<span class="elsevierStyleHsp" style=""></span>nmol/l, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.74). Hospital and one-year mortality were 26% and 32%, respectively. No significant difference in median MR-proADM serum levels was found between survivors and non-survivors and its accuracy to predict hospital mortality was bad (aROC 0.53). After 48<span class="elsevierStyleHsp" style=""></span>h of antibiotic therapy, MR-proADM decreased in all but 5 patients (median −20%; IQR −56% to +0.1%). Its kinetics measured by the percent change from baseline was a good predictor of clinical response (aROC 0.80). The best discrimination was achieved by classifying patients according to whether MR-proADM decreased or not within 48<span class="elsevierStyleHsp" style=""></span>h. No decrease in MR-proADM serum levels significantly increased the chances of dying independently of general severity (SAPS II-adjusted OR 174; 95% CI 2–15,422; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.024).</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusions</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">In SCAP patients, a decrease in MR-proADM serum levels in the first 48<span class="elsevierStyleHsp" style=""></span>h after ICU admission was a good predictor of clinical response and better outcome.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Purpose" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Materials and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1152 "Ancho" => 1583 "Tamanyo" => 52412 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Serum mid-regional proadrenomedullin levels according to SAPS II score.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1151 "Ancho" => 1583 "Tamanyo" => 57168 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Serum mid-regional proadrenomedullin levels according to SOFA score.</p>" ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1078 "Ancho" => 3015 "Tamanyo" => 156154 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Discrimination of serum mid-regional proadrenomedullin levels at day 1 to predict hospital (aROC 0.53; 95% CI 0.26–0.79) and one-year mortality (aROC 0.51; 95% CI 0.25–0.78).</p>" ] ] 3 => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1091 "Ancho" => 1519 "Tamanyo" => 74926 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Discrimination of mid-regional proadrenomedullin kinetics in the first 48<span class="elsevierStyleHsp" style=""></span>h after antibiotic therapy, as measured by the percent decrease from baseline, to predict hospital mortality (aROC 0.80; 95% CI 0.47–1.00).</p>" ] ] 4 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">SAPS: Simplified Acute Physiology Score; PSI: Pneumonia Severity Index; PIRO-CAP: Predisposition, Infection, Response, Organ dysfunction-Community-acquired pneumonia; SOFA; Sepsis-related Organ Failure Assessment; COPD: Chronic Obstructive Pulmonary Disease; IDSA/ATS: Infectious Diseases Society of America/American Thoracic Society; ICU: Intensive Care Unit; LOS: Length of stay.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="middle" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">n</span> (%)<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Age (years)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">68 (64–82) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Male sex \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">11 (58) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">SAPS II score<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">51 (41–61) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">PSI<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">5 (4–5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle">PIRO-CAP</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Mild-risk \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">6 (32) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>High-risk \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">10 (52) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Very high-risk \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">3 (16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">SOFA score<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">9 (8–12) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Co-morbidities \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">14 (74) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">7 (37) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>COPD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">6 (32) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Chronic renal failure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">2 (11) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Alchool abuse \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Congestive heart failure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Cancer \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Microbiological documentation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">11 (58) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle">Microorganisms</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Streptococcus pneumoniae</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">6 (32) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Legionella pneumophila</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">3 (16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Haemophilus influenza</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Klebsiella pneumoniae</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Streptococcus mitis</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">1 (5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Secondary bacteremia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">5 (26) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Appropriate antibiotic therapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">11 (100) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Median time to first antibiotic dose (min)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">129 (78–160) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Duration of mechanical ventilation (days)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">8 (6–10) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Vasopressors use \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">13 (68%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">ICU LOS (days)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">11 (9–14) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle">Hospital LOS (days)<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">17 (13–24) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="middle">Mortality</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>ICU \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">3 (16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>Hospital \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">5 (26) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>28-day \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">5 (26) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="middle"><span class="elsevierStyleHsp" style=""></span>One-year \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="middle">6 (32) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1276928.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Unless otherwise specified.</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Data presented as median (IQR).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Main demographic and clinical characteristics of the study sample (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>19).</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:31 [ 0 => array:3 [ "identificador" => "bib0160" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prognosis and outcomes of patients with community-acquired pneumonia: a meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M.J. 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