Original article
Lung injury prediction scores: Clinical validation and C-reactive protein involvement in high risk patients
Escalas de predicción de la lesión pulmonar: validación clínica e implicación de la proteína C reactiva en pacientes de alto riesgo
Read
3833
Timeswas read the article
1824
Total PDF
2009
Total HTML
Share statistics
array:23 [ "pii" => "S2173572720301004" "issn" => "21735727" "doi" => "10.1016/j.medine.2019.02.014" "estado" => "S300" "fechaPublicacion" => "2020-06-01" "aid" => "1325" "copyright" => "Elsevier España, S.L.U. and SEMICYUC" "copyrightAnyo" => "2019" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Intensiva. 2020;44:267-74" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "itemSiguiente" => array:18 [ "pii" => "S2173572720300990" "issn" => "21735727" "doi" => "10.1016/j.medine.2019.02.013" "estado" => "S300" "fechaPublicacion" => "2020-06-01" "aid" => "1324" "copyright" => "Elsevier España, S.L.U. y SEMICYUC" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Med Intensiva. 2020;44:275-82" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original</span>" "titulo" => "C-reactive protein at ICU admission as a marker of early graft dysfunction after liver transplant. A prospective, single-center cohort study" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "275" "paginaFinal" => "282" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Proteína C reactiva al ingreso en UCI como marcador de disfunción temprana del injerto tras trasplante hepático. Estudio unicéntrico, prospectivo y de cohortes" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 837 "Ancho" => 2083 "Tamanyo" => 83171 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">ROC curve depicting relationship between CRP against in-hospital mortality. AuC: ROC area under curve; CRP: C reactive protein. CRP values depicted as 1/CRP.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "G. Seller-Pérez, J.E. Barrueco-Francioni, R. Lozano-Sáez, M.M. Arrebola-Ramírez, M.J. Diez-de-los-Ríos, G. Quesada-García, M.E. Herrera-Gutiérrez" "autores" => array:7 [ 0 => array:2 [ "nombre" => "G." "apellidos" => "Seller-Pérez" ] 1 => array:2 [ "nombre" => "J.E." "apellidos" => "Barrueco-Francioni" ] 2 => array:2 [ "nombre" => "R." "apellidos" => "Lozano-Sáez" ] 3 => array:2 [ "nombre" => "M.M." "apellidos" => "Arrebola-Ramírez" ] 4 => array:2 [ "nombre" => "M.J." "apellidos" => "Diez-de-los-Ríos" ] 5 => array:2 [ "nombre" => "G." "apellidos" => "Quesada-García" ] 6 => array:2 [ "nombre" => "M.E." "apellidos" => "Herrera-Gutiérrez" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572720300990?idApp=WMIE" "url" => "/21735727/0000004400000005/v1_202006090711/S2173572720300990/v1_202006090711/en/main.assets" ] "itemAnterior" => array:18 [ "pii" => "S2173572720301041" "issn" => "21735727" "doi" => "10.1016/j.medine.2019.12.012" "estado" => "S300" "fechaPublicacion" => "2020-06-01" "aid" => "1440" "copyright" => "Elsevier España, S.L.U. and SEMICYUC" "documento" => "article" "crossmark" => 1 "subdocumento" => "sco" "cita" => "Med Intensiva. 2020;44:265-6" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Editorial</span>" "titulo" => "Adequate antibiotic monitoring to improve what needs to be improved" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "265" "paginaFinal" => "266" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Monitorización adecuada de antibióticos para mejorar lo que necesita mejorarse" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "R. Amaya-Villar" "autores" => array:1 [ 0 => array:2 [ "nombre" => "R." "apellidos" => "Amaya-Villar" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572720301041?idApp=WMIE" "url" => "/21735727/0000004400000005/v1_202006090711/S2173572720301041/v1_202006090711/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Lung injury prediction scores: Clinical validation and C-reactive protein involvement in high risk patients" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "267" "paginaFinal" => "274" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "M.E.-H. Ahmed, G. Hamed, S. Fawzy, K.M. Taema" "autores" => array:4 [ 0 => array:3 [ "nombre" => "M.E.-H." "apellidos" => "Ahmed" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "G." "apellidos" => "Hamed" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "S." "apellidos" => "Fawzy" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:4 [ "nombre" => "K.M." "apellidos" => "Taema" "email" => array:1 [ 0 => "Khaled.toaima@kasralainy.edu.eg" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Critical Care Medicine Department, Al-Haram Hospital, Cairo, Egypt" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Critical Care Medicine Department, Cairo University, Cairo, Egypt" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Escalas de predicción de la lesión pulmonar: validación clínica e implicación de la proteína C reactiva en pacientes de alto riesgo" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1983 "Ancho" => 1583 "Tamanyo" => 150342 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">The ROC curve for the LIPS-N and LIPS-2011 scores in predicting ARDS.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">The acute respiratory distress syndrome (ARDS) represents a well-known public health problem that was reported in 190,600 cases each year in the United States and to be associated with 74,500 deaths and 3.6 million hospital days.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Despite advances in ARDS management, mortality rates remain high<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">1,2</span></a> especially if associated with diffuse alveolar damage (DAD).<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">3</span></a> Patients who even survive ARDS are at risk of diminished functional capacity, mental illness, and decreased quality of life.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">4</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Until now, there are limited specific therapeutic options for ARDS.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">5</span></a> This lack of effective management strategies had directed the research to early identify patients at risk for the evaluation of preventive strategies before ARDS development.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">6</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Early recognition of patients at high risk of ARDS is a prerequisite for conduction of these prevention studies. In the attempts for identifying patients at risk for ARDS, many investigators had derived and validated a lung injury prediction scores (LIPS).<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">7,8</span></a> Despite using similar risk factors and risk modifiers, LIPS scores derived by Cartin-Ceba et al.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">7</span></a> and by Trillo-Alvarez et al.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">8</span></a> used different weights for every risk factors and risk modifiers present in the enrolled patients. Both scores were seen to be significantly higher in patients who subsequently develop ARDS.</p><p id="par0025" class="elsevierStylePara elsevierViewall">Most of studies that evaluated these scores involved ED and ward patients with very low incidence of developing ARDS.<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">7,9,10</span></a> Patients admitted to the ICU with higher APACHE-II scores had higher incidence of developing ARDS.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">10</span></a> Identifying patients at risk of ARDS development from those critically ill patients might help in structuring preventive studies.</p><p id="par0030" class="elsevierStylePara elsevierViewall">This study was intended to validate and compare between two different lung injury prediction scores in predicting the occurrence of ARDS in high risk ICU patients and to improve the score accuracy by involving the serum CRP level.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Patients and methods</span><p id="par0035" class="elsevierStylePara elsevierViewall">This study was done as a prospective observational cohort study including all patients older than 18 years old who were admitted to critical care department at AL-Haram hospital, Egypt with APACHE-II score ≥15 and at least one of the predisposing risk factors or risk modifiers of ARDS within 6<span class="elsevierStyleHsp" style=""></span>h from ICU admission during the period from January 2016 to May 2017. We used standardized definitions for the risk factors (Sepsis,<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">11</span></a> Shock,<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">12</span></a> shock index,<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">13</span></a> High risk trauma,<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">14</span></a> Pneumonia,<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">14</span></a> Aspiration,<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">14</span></a> Pancreatitis,<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">15</span></a> and high risk surgery<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">16</span></a>) and risk modifiers (alcohol abuse,<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">17</span></a> smoking,<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">17</span></a> hypoalbuminemia,<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">14</span></a> Diabetes,<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">18</span></a> Chemotherapy use,<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">19</span></a> Interstitial lung disease (ILD),<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">20</span></a> and tachypnoea<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">14</span></a>). Patients with ARDS on admission, supposed cardiac cause for hypoxemia, and those with hospital readmission (within 7 days) were excluded from the study.</p><p id="par0040" class="elsevierStylePara elsevierViewall">All included patients were subjected to complete history taking and clinical examination with special emphasis on risk factors and risk modifiers of ARDS, routine laboratory investigations included: complete blood count (CBC), serum sodium, serum potassium, serum creatinine, blood urea, random blood sugar, total protein, serum albumin, serum bilirubin, Chest X-ray on admission, every 24<span class="elsevierStyleHsp" style=""></span>h and when needed, arterial blood gas analysis through direct arterial puncture or inserted arterial line for measurement of PaO<span class="elsevierStyleInf">2</span> to calculate (PaO<span class="elsevierStyleInf">2</span>/FiO<span class="elsevierStyleInf">2</span> ratio), hemodynamic parameters including hourly monitoring of heart rate and non-invasive measurement of systolic and diastolic blood pressures (SBP and DBP) using bedside monitor. The Shock index was calculated as heart rate/systolic blood pressure.<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">13</span></a></p><p id="par0045" class="elsevierStylePara elsevierViewall">Sampling for CRP levels on admission (CRP-0) and 48<span class="elsevierStyleHsp" style=""></span>h thereafter (CRP-48) were taken. The change in CRP (ΔCRP) was estimated as (CRP-48<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>CRP-0).</p><p id="par0050" class="elsevierStylePara elsevierViewall">Six hours after admission, LIPS was calculated according to two different calculation formulas that use different weights for the variables; Cartin-Ceba et al. (2009)<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">7</span></a> that will be referred in the text as LIPS-2009 and Trillo-Alvarez et al. (2011),<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">8</span></a> that will be referred as LIPS-2011.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The outcome of interest was the development of ARDS according to Berlin definition (2012).<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">21</span></a> The development of ARDS was determined by two independent experts who were blinded to the LIPS scores.</p><p id="par0060" class="elsevierStylePara elsevierViewall">The study protocol was approved by the institutional review board at Cairo University together with representatives of study conduction site. Informed consent was obtained from patients or first degree relative.</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Statistical analysis</span><p id="par0065" class="elsevierStylePara elsevierViewall">Data were prospectively collected and coded using the statistical package of social science (SPSS version 22). Normal distribution of different dependent variables in relation to their independent variables was studied. A variable was considered normally distributed if the Shapiro–Wilk's test had a <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05<a class="elsevierStyleCrossRefs" href="#bib0330"><span class="elsevierStyleSup">22,23</span></a> and <span class="elsevierStyleItalic">z</span>-value of skewness and kurtosis between −1.96 and +1.96.<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">24</span></a> Apart from LIPS-2011, all other variables were non-normally distributed. Continuous variables were accordingly expressed as median (25th–75th) percentiles [Median (<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">1</span>–<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">3</span>)]. Categorical variables were expressed as frequency and proportion. When two groups were studied, non-parametric test (Mann–Whitney <span class="elsevierStyleItalic">U</span> test) was used for comparison between two groups as regard quantitative variables. The confidence intervals of median difference across groups were derived by the Hodges–Lehmann estimate. Chi-Square Test (<span class="elsevierStyleItalic">x</span><span class="elsevierStyleSup">2</span>) was used for comparison between two groups regarding qualitative data. Exact test was used instead when the expected frequency is less than 5. Receiver operator characteristic (ROC) analysis was performed to define a cut-off value of a variable. We identified three cut-off values; one with a 100% sensitivity, one with a 100% specificity and the third with the best matched sensitivity and specificity according to the highest Youden index. Comparisons between the different area under curves (AUC) were done using the <span class="elsevierStyleItalic">Z</span> statistics calculation according to DeLong et al.<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">25</span></a> MedCalc Statistical Software version 18.11 (MedCalc Software bvba, Ostend, Belgium; <a href="http://www.medcalc.org;/">http://www.medcalc.org;</a> 2018) was used for its calculation as it cannot be calculated using the SPSS.</p><p id="par0070" class="elsevierStylePara elsevierViewall">New model was built using multivariate binary logistic regression analysis. The model contained only LIPS-2011 and ΔCRP which were associated with the ARDS prediction. The strength of the association was measured as the odds ratio (OR) and the 95% confidence interval (CI). The <span class="elsevierStyleItalic">β</span>-coefficient of different variables was estimated to formulate an equation of a new score (LIPS-N) that included constant value added to the sum of the variables multiplied by their <span class="elsevierStyleItalic">β</span>-coefficient. The AUC for the new model was compared with the LIPS-2011 by the DeLong test.<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">25</span></a> The regression model and the odds ratio of the LIPS-N derived by univariate regression were validated using bootstrapping of 1000 sample.</p><p id="par0075" class="elsevierStylePara elsevierViewall">Results were considered statistically significant if <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>≤<span class="elsevierStyleHsp" style=""></span>0.05.</p></span></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results</span><p id="par0080" class="elsevierStylePara elsevierViewall">We initially enrolled 280 patients in the study, 80 were subsequently excluded; 47 patients with cardiac cause of hypoxia, 25 with ARDS on admission and 8 patients had a history of previous admission. The remaining 200 patients represented the study population.</p><p id="par0085" class="elsevierStylePara elsevierViewall">Eighty-eight of the study population (44%) developed ARDS during their ICU stay while 112 patients (56%) did not develop ARDS. ARDS developed after a median (<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">1</span>–<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">3</span>) of 2.5 (1.3–6.8) days.</p><p id="par0090" class="elsevierStylePara elsevierViewall">The demographic data, co-morbidities, risk factors, risk modifiers, LIPS scores and CRP measures of our study are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">The LIPS-2009, LIPS-2011, CRP-48 and ΔCRP but not CRP-0 were found to be significantly higher in patients who developed ARDS compared to non-ARDS patients (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><p id="par0100" class="elsevierStylePara elsevierViewall">ROC analysis was used to evaluate the predictive value of the LIPS scores and CRP-48 for the prediction of ARDS development. The AUC was 0.74 [95% CI: 0.67–0.81)] for LIPS-2011 compared to 0.738 [95% CI: 0.67–0.81)] and 0.730 [95% CI: 0.67–0.8)] for LIPS-2009 and CRP-48 respectively. These AUCs were statistically significant when compared to the AUC of 0.5 (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000 for the three AUCs) while comparing those AUCs together revealed a non-significant difference (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.9, 0.9, 0.8 for pairwise comparison of different ROC curves) (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows the cut-off values of the different variables with their sensitivity, specificity, positive likelihood ratio (LR+) and negative likelihood ratio (LR−).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">A multivariate binary logistic regression model involving the ΔCRP and LIPS-2011 was studied. The odds ratio (95% CI) of LIPS-2011 was 1.5 (1.3–1.8) and that of Δ CRP was 1.02 (1–1.02). Using their <span class="elsevierStyleItalic">β</span>-coefficient, the following equation was derived: −2.416<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(0.41<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>LIPS-2011)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(0.016<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>ΔCRP). The new score was estimated according to this equation and was termed as LIPS-N. The LIPS-N was 0.31 (−0.37–1.4) in ARDS patients compared to −0.99 (−1.7–0.2) in non-ARDS patients [<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000, 95% CI for Hodges–Lehmann median difference −1.4 (−1.8,−1.1)]. We compared the new LIPS-N and LIPS-2011 scores using ROC analysis to evaluate their AUC. The AUC of the LIPS-N was 0.8 [95% CI (0.74–0.86)] which is significantly higher than AUC of 0.5 (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.000). The AUC of LIPS-N was seen to be significantly higher than that of LIPS-2011 (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). The cut-off of the LIPS-N and their sensitivity, specificity, LR+ and LR− are seen in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The odds ratio (95% CI) of patients with LIPS-N more than −0.418 compared to those with less LIPS-N was 7.989 (4.2–15.3).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Discussion</span><p id="par0110" class="elsevierStylePara elsevierViewall">We found in this study that the risk of progression to ARDS may be ascertained using the LIPS scores; either derived by Cartin-Ceba et al.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">7</span></a> (LIPS-2009) or by Trillo-Alvarez et al.<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">8</span></a> (LIPS-2011) early in the course of illness. Both LIPS scores are significantly higher in patients who developed ARDS. We evaluated the accuracy of the LIPS for predicting ARDS using ROC curve. The AUC was 0.740 for LIPS-2011 compared to 0.738 for LIPS-2009 which is statistically insignificant. LIPS-2011 score of 3.5 was 75% sensitive and 62% specific for predicting ARDS while a LIPS-2009 score of 2 was found to have a sensitivity of 92% and specificity of 53%. In their derivation cohort for the LIPS-2009, Cartin-Ceba et al.<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">7</span></a> found higher AUC of 0.85 for predicting ARDS in a population of 1431 patients which is nearly similar to the AUC derived by Trillo-Alvarez and colleagues<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">8</span></a> which was 0.84 in their retrospective derivation and prospective validation cohorts using the LIPS-2011 score with a cut-off value of 3 to have 69% sensitive and 84% specific.</p><p id="par0115" class="elsevierStylePara elsevierViewall">In surgically ventilated patients, Bauman et al. found that LIPS is predictive for ARDS with AUC of 0.79<a class="elsevierStyleCrossRef" href="#bib0350"><span class="elsevierStyleSup">26</span></a> with 50% increase in the development of ARDS for every one-unit increase in LIPS. They however, used LIPS derived by Gajic et al.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">10</span></a> which we did not use in our study. In their study on 5584 patients, Gajic et al.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">10</span></a> derived their score on 2500 patients and validated it on the remaining 3084 patients. They identified AUC for the LIPS of 0.8 for predicting ARDS development in both the derivation and validation cohorts. They identified an optimum cut-off value of 4 to be 69% sensitive and 78% specific. Using this score in ICU patients, Soto et al.<a class="elsevierStyleCrossRef" href="#bib0355"><span class="elsevierStyleSup">27</span></a> showed 31% increase in the likelihood of ARDS development for every point increase in LIPS with AUC of 0.7 which is close to ours; with a cut-off value of 4 to be 90% sensitive and 31% specific. Due to the higher mortality of ARDS patients with DAD, Lorente et al. derived a regression model including PaO<span class="elsevierStyleInf">2</span>/FiO<span class="elsevierStyleInf">2</span> ratio, dynamic compliance and age to predict DAD within ARDS patients. The AUC for their model was 0.74 in derivation cohort and 0.73 in the validation cohort.<a class="elsevierStyleCrossRef" href="#bib0360"><span class="elsevierStyleSup">28</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">The notion of using a biomarker reflecting the severity and course of alveolocapillary inflammation and increased permeability characterizing the ARDS is enthusiastic. Theoretically, the ideal biomarker would be involved in the disease pathogenesis, easy to measure, rapid results availability, and highly sensitive and specific in predicting the required outcome.<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">29</span></a> Many biomarkers related to DAD and its association with distal airway pathologic changes characterizing ARDS might be seen of value<a class="elsevierStyleCrossRefs" href="#bib0370"><span class="elsevierStyleSup">30,31</span></a> and even, too specific biomarker at the molecular level had been studied.<a class="elsevierStyleCrossRef" href="#bib0380"><span class="elsevierStyleSup">32</span></a> Many of these biomarkers are not commonly used in clinical practice. Despite being non-specific, C-reactive protein is a biomarker in common clinical use to delineate the activity of host inflammatory conditions such as sepsis, cardiovascular disease and rheumatological disorders.<a class="elsevierStyleCrossRef" href="#bib0385"><span class="elsevierStyleSup">33</span></a> Patients with sepsis-induced ARDS have elevated levels of CRP in both plasma and the broncho-alveolar lavage.<a class="elsevierStyleCrossRef" href="#bib0390"><span class="elsevierStyleSup">34</span></a> We measured the admission and 48<span class="elsevierStyleHsp" style=""></span>h CRP levels in our study population.</p><p id="par0125" class="elsevierStylePara elsevierViewall">In this study, CRP-48 and the change of the CRP over the first 48<span class="elsevierStyleHsp" style=""></span>h following ICU admission were significantly higher in patients who developed ARDS. CRP-48 had an AUC of 0.730 for predicting patients who developed ARDS. The CRP-48 of 48<span class="elsevierStyleHsp" style=""></span>mg/L was seen to be 76% sensitive and 62% specific. This was concordant with Zheng et al.<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">35</span></a> who showed that the CRP can predict the occurrence of ARDS in trauma patients. Contrary to these results, In a study on community acquired pneumonia, Lee et al. concluded that the CRP does not predict patients who required mechanical ventilation and accordingly cannot predict ARDS development.<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">36</span></a> Another study conducted by Komiya et al. showed that the CRP had an AUC of 0.831 for discriminating patients with ARDS compared to those with cardiogenic pulmonary edema and that this AUC was increased to 0.931 when CRP was added to the brain natriuretic peptide.<a class="elsevierStyleCrossRef" href="#bib0405"><span class="elsevierStyleSup">37</span></a> This study was however used in patients admitted by respiratory failure for the diagnosis rather than for predicting ARDS as we intended to evaluate. Despite the specificity of 62% that we had for CRP-48, it is well-known that the CRP might be elevated in numerous inflammatory disorders and lack a specificity for the ARDS development.<a class="elsevierStyleCrossRef" href="#bib0385"><span class="elsevierStyleSup">33</span></a></p><p id="par0130" class="elsevierStylePara elsevierViewall">We incorporated the ΔCRP with the LIPS-2011 in a new score using binary logistic regression model forming the LIPS-N. This score was estimated by the formula of [−2.416<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(0.41<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>LIPS-2011)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(0.016<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>ΔCRP)]. The AUC of this score was 0.803 which was significantly higher than that of LIPS-2011 alone. A result of this score of −0.418 was found to be 78% sensitive and 69% specific for predicting ARDS. This score however needs to be validated in another sample.</p><p id="par0135" class="elsevierStylePara elsevierViewall">It is important to mention that the incidence of ARDS in this study was very high (44%) compared to other previous studies where the incidence did not exceed 20%<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">8,38–40</span></a> and this could be due to using a sample population with APACHE-II score ≥15 representing high risk population who are admitted to the ICU rather than ED or ward admission. In Trillo-Alvarez's study,<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">8</span></a> they found ARDS incidence to be 17% in their retrospective derivation cohort of ICU patients compared to 7% in the prospective validation cohort of all hospitalized patients.</p><p id="par0140" class="elsevierStylePara elsevierViewall">Both previously derived LIPS scores were seen to be similarly functioning in terms of ARDS prediction. Both include readily available clinical information known to be associated with ARDS. They identify at-risk patients early during illness with fair sensitivity and specificity. Accordingly, both may be beneficial for segregating subsets of high-risk patients for enrollment in prevention strategies. Adding biomarker may, however, improve the score accuracy.</p><p id="par0145" class="elsevierStylePara elsevierViewall">The lack of optimum sensitivity and specificity of these scores might be attributed to the absence of some well-known risk modifiers for ARDS; large volume transfusion of packed red blood cells and fluid balance are examples of these risk modifiers that was seen by many investigators to affect ARDS risk.<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">14,41</span></a> The predictive value of these scoring systems could be accordingly improved using more additional variables including more risk modifiers in all patients. In addition, the exposure to risk factors and risk modifiers is a dynamic process that might develop during the hospital course rather than on admission and so, any predictive tool needs to be dynamic on daily bases. Adding more additional information and data that are unavailable on admission might however affect the simplicity of using these scores in real practice.</p><p id="par0150" class="elsevierStylePara elsevierViewall">Our study is limited by the relatively small sample size that used for the validation of the LIPS and that it is a single center study. We recruited high risk ICU patients with high APACH-II score having higher incidence of ARDS that may explain the needed smaller sample. One of the important factors that should be considered during planning for a preventive study for ARDS is that many of those patients expose to their risk factors prior to their ICU admission. Despite being more difficult, the enrollment of all hospitalized patients might be more practical, yet the authors intended here to validate the LIPS scores in the more critically ICU patients. One of the draw-backs of this study is the validation of the new score derived from the study on the same study sample. The LIPS-N score should be validated in another ICU patients’ sample. The authors used bootstrapping for validation of the regression model.</p><p id="par0155" class="elsevierStylePara elsevierViewall">Despite that the Berlin definition represents the gold standard for ARDS diagnosis, many of its items, like interpretation of portable chest X-ray, remain clinician dependent. Some authors concluded limited experts’ ability to accurately differentiate between ARDS and other causes of respiratory failure.<a class="elsevierStyleCrossRef" href="#bib0430"><span class="elsevierStyleSup">42</span></a> On the histopathologic level, many of the clinically diagnosed ARDS patients showed subsequently normal lung after open lung biopsy or autopsy.<a class="elsevierStyleCrossRefs" href="#bib0360"><span class="elsevierStyleSup">28,43,44</span></a> Finally, many scores with different weighting power for the risk factors are established that limit the ability to compare different studies.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conclusions</span><p id="par0160" class="elsevierStylePara elsevierViewall">This study concludes that both LIPS scores derived by Cartin-Ceba et al. on 2009 and Trillo-Alvarez et al. on 2011 are equally effective in predicting ARDS in risky ICU patients. The incorporation of change of CRP over the first 48<span class="elsevierStyleHsp" style=""></span>h of ICU admission with the LIPS-2011 score may increase its accuracy in ARDS prediction.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Funding</span><p id="par0165" class="elsevierStylePara elsevierViewall">The study is self-funded.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Author's contribution</span><p id="par0170" class="elsevierStylePara elsevierViewall">Concept: MEHA, KMT, SF, GH.</p><p id="par0175" class="elsevierStylePara elsevierViewall">Design: MEHA, KMT, GH.</p><p id="par0180" class="elsevierStylePara elsevierViewall">Definition of intellectual content: KMT, SF, GH.</p><p id="par0185" class="elsevierStylePara elsevierViewall">Literature search: MEHA, KMT.</p><p id="par0190" class="elsevierStylePara elsevierViewall">Data acquisition: MEHA, SF.</p><p id="par0195" class="elsevierStylePara elsevierViewall">Data analysis and statistical analysis: KMT.</p><p id="par0200" class="elsevierStylePara elsevierViewall">Manuscript preparation: KMT.</p><p id="par0205" class="elsevierStylePara elsevierViewall">Manuscript editing: KMT.</p><p id="par0210" class="elsevierStylePara elsevierViewall">Manuscript review: SF, GH.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflict of interest</span><p id="par0215" class="elsevierStylePara elsevierViewall">The authors do not have a conflict of interest to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:13 [ 0 => array:3 [ "identificador" => "xres1345911" "titulo" => "Abstract" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Design" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Patients" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Interventions" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Main variables of interest" ] 5 => array:2 [ "identificador" => "abst0030" "titulo" => "Results" ] 6 => array:2 [ "identificador" => "abst0035" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1238399" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1345910" "titulo" => "Resumen" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "abst0040" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0045" "titulo" => "Diseño" ] 2 => array:2 [ "identificador" => "abst0050" "titulo" => "Pacientes" ] 3 => array:2 [ "identificador" => "abst0055" "titulo" => "Intervenciones" ] 4 => array:2 [ "identificador" => "abst0060" "titulo" => "Principales variables de interés" ] 5 => array:2 [ "identificador" => "abst0065" "titulo" => "Resultados" ] 6 => array:2 [ "identificador" => "abst0070" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1238398" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0020" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0025" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0030" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "sec0035" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0040" "titulo" => "Author's contribution" ] 11 => array:2 [ "identificador" => "sec0045" "titulo" => "Conflict of interest" ] 12 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-12-06" "fechaAceptado" => "2019-02-15" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1238399" "palabras" => array:4 [ 0 => "ARDS" 1 => "LIPS" 2 => "Lung injury prediction score" 3 => "ARDS prediction" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1238398" "palabras" => array:4 [ 0 => "ARDS" 1 => "LIPS" 2 => "Puntaje de predicción de la lesión pulmonar" 3 => "Predicción del ARDS" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">A study was made to validate two previously derived lung injury prediction scores (LIPS) for the prediction of acute respiratory distress syndrome (ARDS) in high risk intensive care patients, with the incorporation of C-reactive protein (CRP) for improving score accuracy.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Design</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A prospective, observational cohort study was carried out.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Patients</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">A total of 200 patients with APACHE II score ≥15 and at least one ARDS risk factor upon ICU admission were included.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Interventions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Calculation of LIPS using formulas developed by Cartin-Ceba et al. (2009) and Trillo-Alvarez et al. (2011) (LIPS-2009 and LIPS-2011). C-reactive protein was measured upon admission (CRP-0) and after 48<span class="elsevierStyleHsp" style=""></span>h (CRP-48).</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Main variables of interest</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Independent variables: LIPS-2009, LIPS-2011 and CRP values. Dependent variable: development of ARDS.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Results</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Eighty-eight patients (44%) developed ARDS after a median (<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">1</span>–<span class="elsevierStyleItalic">Q</span><span class="elsevierStyleInf">3</span>) of 2.5 (1.3–6.8) days. The LIPS-2009 and LIPS-2011 scores were 4 (3–6) and 5 (3.6–6.5) in ARDS patients compared to 2 (1–4) and 3.5 (1.5–4.5) in non-ARDS patients (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). CRP-48 was 96 (67.5–150.3)<span class="elsevierStyleHsp" style=""></span>mg/L and 48 (24–96)<span class="elsevierStyleHsp" style=""></span>mg/L in the two groups, respectively (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). ΔCRP (i.e., CRP-48 minus CRP-0) was significantly higher in the ARDS patients (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001). The AUC was 0.740 and 0.738 for LIPS-2011 and LIPS-2009, respectively – the difference being nonsignificant (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.9, 0.9 and 0.8 for pairwise comparison of the different ROC curves). Integrating ΔCRP with LIPS-2011 using binary logistic regression analysis identified a new score (LIPS-N) with AUC 0.803, which was significantly higher than the AUC of LIPS-2011 (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.01).</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Conclusions</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Both LIPS scores are equally effective in predicting ARDS in high risk ICU patients. Integrating the change in CRP within the score might improve its accuracy.</p></span>" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Design" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Patients" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Interventions" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Main variables of interest" ] 5 => array:2 [ "identificador" => "abst0030" "titulo" => "Results" ] 6 => array:2 [ "identificador" => "abst0035" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Objetivo</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Se llevó a cabo un estudio para validar 2 puntuaciones de predicción de la lesión pulmonar (LIPS) previamente obtenidas para la predicción del síndrome de dificultad respiratoria aguda (SDRA) en pacientes de alto riesgo ingresados en la unidad de cuidados intensivos, con la incorporación de la proteína C reactiva (PCR) para aumentar la precisión de la puntuación.</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Diseño</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Se llevó a cabo un estudio prospectivo y observacional de cohortes.</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Pacientes</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Se incluyó un total de 200 pacientes con una puntuación APACHE II<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>15 y al menos un factor de riesgo de SDRA en el momento de su ingreso en la UCI.</p></span> <span id="abst0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Intervenciones</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Se calcularon las puntuaciones por medio de las fórmulas desarrolladas por Cartin-Ceba et al. (2009) y Trillo-Alvarez et al. (2011) (LIPS-2009 y LIPS-2011). La concentración de PCR se midió en el momento del ingreso (PCR-0) y al cabo de 48<span class="elsevierStyleHsp" style=""></span>horas (PCR-48).</p></span> <span id="abst0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Principales variables de interés</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Variables independientes<span class="elsevierStyleUnderline">:</span> LIPS-2009, LIPS-2011 y valores de PCR. Variable dependiente: desarrollo de SDRA.</p></span> <span id="abst0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Resultados</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Ochenta y ocho pacientes (44%) desarrollaron SDRA tras una mediana (Q<span class="elsevierStyleInf">1</span>-Q<span class="elsevierStyleInf">3</span>) de 2,5 (1,3-6,8) días. Las puntuaciones LIPS-2009 y LIPS-2011 fueron 4 (3-6) y 5 (3,6-6,5) en los pacientes con SDRA, frente a 2 (1-4) y 3,5 (1,5-4,5) en pacientes sin SDRA (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,001). El valor de PCR-48 fue 96<span class="elsevierStyleHsp" style=""></span>mg/l (67,5-150,3) y 48<span class="elsevierStyleHsp" style=""></span>mg/l (24-96) en los 2 grupos respectivamente (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,001). ΔPCR (esto es, RCR-48 menos PCR-0) fue significativamente mayor en los pacientes con SDRA (p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,001). El AUC fue 0,740 y 0,738 para LIPS-2011 y LIPS-2009 respectivamente y la diferencia no fue significativa (p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,9, 0,9 y 0,8 para la comparación por parejas de las distintas curvas ROC). La integración de ΔPCR con LIPS-2011 mediante un análisis de regresión logística binaria identificó una nueva puntuación (LIPS-N) con un AUC 0,803, el cual era significativamente mayor que el AUC de LIPS-2011 (p<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,01).</p></span> <span id="abst0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Conclusiones</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Ambas puntuaciones LIPS resultan igualmente eficaces en cuanto a la predicción del SDRA en pacientes de alto riesgo ingresados en la UCI. La integración en esta puntuación del cambio en la PCR podría aumentar su precisión.</p></span>" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "abst0040" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0045" "titulo" => "Diseño" ] 2 => array:2 [ "identificador" => "abst0050" "titulo" => "Pacientes" ] 3 => array:2 [ "identificador" => "abst0055" "titulo" => "Intervenciones" ] 4 => array:2 [ "identificador" => "abst0060" "titulo" => "Principales variables de interés" ] 5 => array:2 [ "identificador" => "abst0065" "titulo" => "Resultados" ] 6 => array:2 [ "identificador" => "abst0070" "titulo" => "Conclusiones" ] ] ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1838 "Ancho" => 1500 "Tamanyo" => 184716 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">The ROC curve for the LIPS-2009, LIPS-2011 scores and CRP-48 in predicting ARDS.</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" => 1983 "Ancho" => 1583 "Tamanyo" => 150342 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">The ROC curve for the LIPS-N and LIPS-2011 scores in predicting ARDS.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">SBP: systolic blood pressure, HR: heart rate, LIPS: lung injury prediction score, CRP-0: C-reactive protein on admission, CRP-48: C-reactive protein 48<span class="elsevierStyleHsp" style=""></span>h after admission, ΔCRP: CRP-48<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>CRP-0.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Risk factors and risk modifiers \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">The whole population(200 patients) \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">ARDS patients(88 patients) \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">Non-ARDS patients(112 patients) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">Age (years old) [(median (</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Q</span></span><span class="elsevierStyleInf"><span class="elsevierStyleBold">1</span></span><span class="elsevierStyleBold">–</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Q</span></span><span class="elsevierStyleInf"><span class="elsevierStyleBold">3</span></span><span class="elsevierStyleBold">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 (43–70) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 (44–70) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 (43–70) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.983 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">Male gender [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">120 (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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51 (58%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">69 (61.6%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.352 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">APACHE II score [(median (</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Q</span></span><span class="elsevierStyleInf"><span class="elsevierStyleBold">1</span></span><span class="elsevierStyleBold">–</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Q</span></span><span class="elsevierStyleInf"><span class="elsevierStyleBold">3</span></span><span class="elsevierStyleBold">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (18–24) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (18–24) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (18–22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.004</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">Risk modifiers</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Alcohol abuse [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (1.5%) \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="char" 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (2.7%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.17 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Smoking [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80 (40%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (37.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">47 (42%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.31 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Hypoalbuminemia [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">129 (64.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68 (77.3%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61 (54.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Diabetes [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82 (41%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38 (43.2%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44 (39.3%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.34 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Chemotherapy [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (7.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (7.9%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (7.1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.52 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Tachypnea [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76 (38%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 (62.9%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (18%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Interstitial lung disease [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (2.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (2.3%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (2.7%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.613 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">Risk factors</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Sepsis [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">99 (49.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 (63.6%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 (38.4%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SBP (mmHg) [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 (80–120) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90 (73–120) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 (90–120) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.003</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HR (bpm) [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">105 (90–110) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 (100–120) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 (90–110) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Shock index [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (0.8–1.5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.2 (0.9–1.8) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9 (0.7–1.2) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Shock index score [No. (%)]</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span><1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">108 (54%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30 (34.1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 (69.6%) \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 " rowspan="3" align="char" valign="middle"><<span class="elsevierStyleBold">0.001</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>1–1.5 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 (25%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (37.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (15.2%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>>1.5 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 (21%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 (28.4%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (15.2%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">High risk trauma [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 (25%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 (26.1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 (24.1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.42 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Pneumonia [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80 (40%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">47 (53.4%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (29.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Aspiration [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 (24.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (31.8%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (18.8%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.02</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Pancreatitis [No. (%)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (1%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (1.8%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.31 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">High risk surgery [No. (%)]</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Elective \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 (12.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (5.7%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (17.9%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="char" valign="middle"><span class="elsevierStyleBold">0.03</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Emergent \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (13%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (15.9%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (10.7%) \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"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51 (25.5%) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (22%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (28.6%) \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"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">LIPS-2009 [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (2–5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (3–6) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (1–4) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">LIPS-2011 [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (2.5–5.5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (3.6–6.5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.5 (1.5–4.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CRP-0, mg/L [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (24–48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (24–48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (24–48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.4 \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"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CRP-48, mg/L [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96 (48–96) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96 (67.5–150.3) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (24–96) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">ΔCRP, mg/L [(median (Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">1</span></span><span class="elsevierStyleItalic">–Q</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">3</span></span><span class="elsevierStyleItalic">)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 (0–61.5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (19.5–83.5) \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0–48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2309087.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">The demographic data, co-morbidities, risk factors, risk modifiers, LIPS scores and CRP measures in the study groups.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">LIPS: lung injury prediction score, CRP: C-reactive protein, CI: confidence interval, LR+: positive likelihood ratio, LR−: negative likelihood ratio.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \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">Cut-off value \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sensitivity \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">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">Specificity \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">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">LR+ \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">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">LR− \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">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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LIPS-2009</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.9–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0–3.2 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–1 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">92 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84–97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43–62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.6–2.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07–0.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0–4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96.8–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LIPS-2011</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.9–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0–3.2 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–1 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65–84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52–71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.5–2.5 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3–0.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.5 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.9–12.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96.8–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9–1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CRP-48 (mg/L)</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.9–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.1–23.2 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.1–1.3 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" 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><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66–85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52–71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.5–2.6 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3–0.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">317 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0–4.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96.8–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LIPS-N</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−2.9 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.9–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–9 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1–1.1 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.418 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68–87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59–77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.5 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.9–3.4 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.2–0.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.8 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.9–26.6 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96.8–100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.83 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.8–0.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2309086.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">The cut-off values of the different variables with their sensitivity, specificity, LR+, and LR−.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:44 [ 0 => array:3 [ "identificador" => "bib0225" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Incidence and outcomes of acute lung injury" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "G.D. Rubenfeld" 1 => "E. Caldwell" 2 => "E. Peabody" 3 => "J. Weaver" 4 => "D.P. Martin" 5 => "M. Neff" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1056/NEJMoa050333" "Revista" => array:5 [ "tituloSerie" => "N Engl J Med" "fecha" => "2005" "volumen" => "353" "paginaInicial" => "1685" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/16236739" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0230" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Identification of patients with acute lung injury. Predictors of mortality" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "R.L. Doyle" 1 => "N. Szaflarski" 2 => "G.W. Modin" 3 => "J.P. Wiener-Kronish" 4 => "M.A. Matthay" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1164/ajrccm.152.6.8520742" "Revista" => array:6 [ "tituloSerie" => "Am J Respir Crit Care Med" "fecha" => "1995" "volumen" => "152" "paginaInicial" => "1818" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/8520742" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673612616894" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0235" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The presence of diffuse alveolar damage on open lung biopsy is associated with mortality in patients with acute respiratory distress syndrome: a systematic review and meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "P. Cardinal-Fernandez" 1 => "E.K. Bajwa" 2 => "A. Dominguez-Calvo" 3 => "J.M. Menendez" 4 => "L. Papazian" 5 => "B.T. Thompson" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.chest.2016.02.635" "Revista" => array:6 [ "tituloSerie" => "Chest" "fecha" => "2016" "volumen" => "149" "paginaInicial" => "1155" "paginaFinal" => "1164" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26896701" "web" => "Medline" ] ] ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0240" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Two-year outcomes, health care use, and costs of survivors of acute respiratory distress syndrome" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A.M. Cheung" 1 => "C.M. Tansey" 2 => "G. Tomlinson" 3 => "N. Diaz-Granados" 4 => "A. Matte" 5 => "A. Barr" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1164/rccm.200505-693OC" "Revista" => array:6 [ "tituloSerie" => "Am J Respir Crit Care Med" "fecha" => "2006" "volumen" => "174" "paginaInicial" => "538" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/16763220" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0165032717322826" "estado" => "S300" "issn" => "01650327" ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0245" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pharmacological treatments for acute respiratory distress syndrome: systematic review" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "A. Duggal" 1 => "A. Ganapathy" 2 => "M.A.N. Ratnapalan" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/MCC.0b013e328334b151" "Revista" => array:5 [ "tituloSerie" => "Minerva Anestesiol" "fecha" => "2015" "volumen" => "81" "paginaInicial" => "567" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24937499" "web" => "Medline" ] ] ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0250" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Beyond mortality: future clinical research in acute lung injury" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R.G. Spragg" 1 => "G.R. Bernard" 2 => "W. Checkley" 3 => "J.R. Curtis" 4 => "O. Gajic" 5 => "G. Guyatt" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1164/rccm.201001-0024WS" "Revista" => array:5 [ "tituloSerie" => "Am J Respir Crit Care Med" "fecha" => "2010" "volumen" => "181" "paginaInicial" => "1121" "itemHostRev" => array:3 [ "pii" => "S0920996415001826" "estado" => "S300" "issn" => "09209964" ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0255" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Derivation of a lung injury prediction score (LIPS) to identify patients at high risk of ARDS at the time of hospital admission" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R. Cartin-Ceba" 1 => "C. Trillo-Alvarez" 2 => "G. Li" 3 => "R. Kashyap" 4 => "M. Kojicic" 5 => "Y. Dong" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1164/ajrccm-conference.2009.179.1_MeetingAbstracts.A4653" "Revista" => array:3 [ "tituloSerie" => "Am J Respir Crit Care Med" "fecha" => "2009" "paginaInicial" => "A4653" ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0260" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Acute lung injury prediction score: derivation and validation in a population-based sample" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. Trillo-Alvarez" 1 => "R. Cartin-Ceba" 2 => "D.J. Kor" 3 => "M. Kojicic" 4 => "R. Kashyap" 5 => "S. Thakur" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1183/09031936.00036810" "Revista" => array:5 [ "tituloSerie" => "Eur Respir J" "fecha" => "2011" "volumen" => "37" "paginaInicial" => "604" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20562130" "web" => "Medline" ] ] ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0265" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Towards the prevention of acute lung injury: a population based cohort study protocol" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.J. Thakur" 1 => "C.A. Trillo-Alvarez" 2 => "M.M. Malinchoc" 3 => "R. Kashyap" 4 => "L. Thakur" 5 => "A. Ahmed" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/1471-227X-10-8" "Revista" => array:5 [ "tituloSerie" => "BMC Emerg Med" "fecha" => "2010" "volumen" => "10" "paginaInicial" => "8" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20420711" "web" => "Medline" ] ] ] ] ] ] ] ] 9 => array:3 [ "identificador" => "bib0270" "etiqueta" => "10" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Early identification of patients at risk of acute lung injury: evaluation of lung injury prediction score in a multicenter cohort study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "O. Gajic" 1 => "O. Dabbagh" 2 => "P.K. Park" 3 => "A. Adesanya" 4 => "S.Y. Chang" 5 => "P. Hou" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1164/rccm.201004-05490C" "Revista" => array:5 [ "tituloSerie" => "Am J Respir Crit Care Med" "fecha" => "2011" "volumen" => "183" "paginaInicial" => "462" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20802164" "web" => "Medline" ] ] ] ] ] ] ] ] 10 => array:3 [ "identificador" => "bib0275" "etiqueta" => "11" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M.M. Levy" 1 => "M.P. Fink" 2 => "J.C. Marshall" 3 => "E. Abraham" 4 => "D. Angus" 5 => "D. Cook" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-003-1662-x" "Revista" => array:5 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2003" "volumen" => "29" "paginaInicial" => "530" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/12664219" "web" => "Medline" ] ] ] ] ] ] ] ] 11 => array:3 [ "identificador" => "bib0280" "etiqueta" => "12" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Hemodynamic monitoring in shock and implications for management" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Antonelli" 1 => "M. Levy" 2 => "P.J.D. Andrews" 3 => "J. Chastre" 4 => "L.D. Hudson" 5 => "C. Manthous" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-007-0531-4" "Revista" => array:5 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2007" "volumen" => "33" "paginaInicial" => "575" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/17285286" "web" => "Medline" ] ] ] ] ] ] ] ] 12 => array:3 [ "identificador" => "bib0285" "etiqueta" => "13" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Shock index and early recognition of sepsis in the emergency department: pilot study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "T. Berger" 1 => "J. Green" 2 => "T. Horeczko" 3 => "Y. Hagar" 4 => "N. Garg" 5 => "A. Suarez" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.5811/westjem.2012.8.11546" "Revista" => array:5 [ "tituloSerie" => "West J Emerg Med" "fecha" => "2013" "volumen" => "14" "paginaInicial" => "168" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/23599863" "web" => "Medline" ] ] ] ] ] ] ] ] 13 => array:3 [ "identificador" => "bib0290" "etiqueta" => "14" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Clinical predictors of and mortality in acute respiratory distress syndrome: potential role of red cell transfusion" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "M.N. Gong" 1 => "B.T. Thompson" 2 => "P. Williams" 3 => "L. Pothier" 4 => "P.D. Boyce" 5 => "D.C. Christiani" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/01.CCM. 0000165566.82925.14" "Revista" => array:5 [ "tituloSerie" => "Crit Care Med" "fecha" => "2005" "volumen" => "33" "paginaInicial" => "1191" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/15942330" "web" => "Medline" ] ] ] ] ] ] ] ] 14 => array:3 [ "identificador" => "bib0295" "etiqueta" => "15" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "American College of Gastroenterology Guideline: management of acute pancreatitis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "S. Tenner" 1 => "J. Baillie" 2 => "J. DeWitt" 3 => "S.S. Vege" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/ajg.2013.218" "Revista" => array:6 [ "tituloSerie" => "Am J Gastroenterol" "fecha" => "2013" "volumen" => "108" "paginaInicial" => "1400" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/23896955" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0034745013700088" "estado" => "S300" "issn" => "00347450" ] ] ] ] ] ] ] 15 => array:3 [ "identificador" => "bib0300" "etiqueta" => "16" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Multifactorial risk index for predicting postoperative respiratory failure in men after major noncardiac surgery" "autores" => array:1 [ 0 => array:3 [ "colaboracion" => "Program NVASQI" "etal" => false "autores" => array:4 [ 0 => "A.M. Arozullah" 1 => "J. Daley" 2 => "W.G. Henderson" 3 => "S.F. Khuri" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/00000658-200008000-00015" "Revista" => array:5 [ "tituloSerie" => "Ann Surg" "fecha" => "2000" "volumen" => "232" "paginaInicial" => "242" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/10903604" "web" => "Medline" ] ] ] ] ] ] ] ] 16 => array:3 [ "identificador" => "bib0305" "etiqueta" => "17" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Cigarette smoking, alcohol consumption, and risk of ARDS: a 15-year cohort study in a managed care setting" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "C. Iribarren" 1 => "D.R. Jacobs Jr." 2 => "S. Sidney" 3 => "M.D. Gross" 4 => "M.D. Eisner" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1378/chest.117.1.163" "Revista" => array:6 [ "tituloSerie" => "Chest" "fecha" => "2000" "volumen" => "117" "paginaInicial" => "163" "paginaFinal" => "168" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/10631215" "web" => "Medline" ] ] ] ] ] ] ] ] 17 => array:3 [ "identificador" => "bib0310" "etiqueta" => "18" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Diabetic patients have a decreased incidence of acute respiratory distress syndrome" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Moss" 1 => "D.M. Guidot" 2 => "K.P. Steinberg" 3 => "G.F. Duhon" 4 => "P. Treece" 5 => "R. Wolken" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/00003246-200007000-00001" "Revista" => array:5 [ "tituloSerie" => "Crit Care Med" "fecha" => "2000" "volumen" => "28" "paginaInicial" => "2187" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/10921539" "web" => "Medline" ] ] ] ] ] ] ] ] 18 => array:3 [ "identificador" => "bib0315" "etiqueta" => "19" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Risk factors for the development of acute lung injury in patients with septic shock: an observational cohort study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R. Iscimen" 1 => "R. Cartin-Ceba" 2 => "M. Yilmaz" 3 => "H. Khan" 4 => "R.D. Hubmayr" 5 => "B. Afessa" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/CCM.0b013e31816fc2c0" "Revista" => array:6 [ "tituloSerie" => "Crit Care Med" "fecha" => "2008" "volumen" => "36" "paginaInicial" => "1518" "paginaFinal" => "1522" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18434908" "web" => "Medline" ] ] ] ] ] ] ] ] 19 => array:3 [ "identificador" => "bib0320" "etiqueta" => "20" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Interstitial lung disease guideline: the British Thoracic Society in collaboration with the Thoracic Society of Australia and New Zealand and the Irish Thoracic Society" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B. Bradley" 1 => "H.M. Branley" 2 => "J.J. Egan" 3 => "M.S. Greaves" 4 => "D.M. Hansell" 5 => "N.K. Harrison" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1136/thx.2008.101691" "Revista" => array:7 [ "tituloSerie" => "Thorax" "fecha" => "2008" "volumen" => "63" "numero" => "Suppl. 5" "paginaInicial" => "v1" "paginaFinal" => "v58" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18757459" "web" => "Medline" ] ] ] ] ] ] ] ] 20 => array:3 [ "identificador" => "bib0325" "etiqueta" => "21" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Acute respiratory distress syndrome: the Berlin definition" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "Force* TADT" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1001/jama.2012.5669" "Revista" => array:5 [ "tituloSerie" => "JAMA" "fecha" => "2012" "volumen" => "307" "paginaInicial" => "2526" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/22797452" "web" => "Medline" ] ] ] ] ] ] ] ] 21 => array:3 [ "identificador" => "bib0330" "etiqueta" => "22" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "An analysis of variance test for normality (complete samples)" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "S.S. Shapiro" 1 => "M.B. Wilk" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1093/biomet/52.3-4.591" "Revista" => array:5 [ "tituloSerie" => "Biometrika" "fecha" => "1965" "volumen" => "52" "paginaInicial" => "591" "itemHostRev" => array:3 [ "pii" => "S2215036614703074" "estado" => "S300" "issn" => "22150366" ] ] ] ] ] ] ] 22 => array:3 [ "identificador" => "bib0335" "etiqueta" => "23" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, Lilliefors and Anderson–Darling tests" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "N.M. Razali" 1 => "Y.B. Wah" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "J Stat Model Anal" "fecha" => "2011" "volumen" => "2" "paginaInicial" => "21" "itemHostRev" => array:3 [ "pii" => "S0924933815006951" "estado" => "S300" "issn" => "09249338" ] ] ] ] ] ] ] 23 => array:3 [ "identificador" => "bib0340" "etiqueta" => "24" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Measuring skewness: a forgotten statistic" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "D.P. Doane" 1 => "L.E. Seward" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:4 [ "tituloSerie" => "J Stat Educ" "fecha" => "2011" "volumen" => "19" "paginaInicial" => "1" ] ] ] ] ] ] 24 => array:3 [ "identificador" => "bib0345" "etiqueta" => "25" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "E.R. DeLong" 1 => "D.M. DeLong" 2 => "D.L. Clarke-Pearson" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2307/2531595" "Revista" => array:5 [ "tituloSerie" => "Biometrics" "fecha" => "1988" "volumen" => "44" "paginaInicial" => "837" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/3203132" "web" => "Medline" ] ] ] ] ] ] ] ] 25 => array:3 [ "identificador" => "bib0350" "etiqueta" => "26" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lung injury prediction score is useful in predicting acute respiratory distress syndrome and mortality in surgical critical care patients" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "Z.M. Bauman" 1 => "M.Y. Gassner" 2 => "M.A. Coughlin" 3 => "M. Mahan" 4 => "J. Watras" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1155/2015/157408" "Revista" => array:3 [ "tituloSerie" => "Crit Care Res Pract" "fecha" => "2015" "paginaInicial" => "157408" ] ] ] ] ] ] 26 => array:3 [ "identificador" => "bib0355" "etiqueta" => "27" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lung injury prediction score in hospitalized patients at risk of acute respiratory distress syndrome" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "G.J. Soto" 1 => "D.J. Kor" 2 => "P.K. Park" 3 => "P.C. Hou" 4 => "D.A. Kaufman" 5 => "M. Kim" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/CCM. 0000000000002001" "Revista" => array:6 [ "tituloSerie" => "Crit Care Med" "fecha" => "2016" "volumen" => "44" "paginaInicial" => "2182" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27513358" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0920996416304996" "estado" => "S300" "issn" => "09209964" ] ] ] ] ] ] ] 27 => array:3 [ "identificador" => "bib0360" "etiqueta" => "28" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Acute respiratory distress syndrome in patients with and without diffuse alveolar damage: an autopsy study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.A. Lorente" 1 => "P. Cardinal-Fernandez" 2 => "D. Munoz" 3 => "F. Frutos-Vivar" 4 => "A.W. Thille" 5 => "C. Jaramillo" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-015-4046-0" "Revista" => array:7 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2015" "volumen" => "41" "paginaInicial" => "1921" "paginaFinal" => "1930" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26385863" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673618319482" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 28 => array:3 [ "identificador" => "bib0365" "etiqueta" => "29" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The utility of biomarkers in sorting out the complex patient" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "C. Moriates" 1 => "A. Maisel" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.amjmed.2009.07.034" "Revista" => array:5 [ "tituloSerie" => "Am J Med" "fecha" => "2010" "volumen" => "123" "paginaInicial" => "393" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20399312" "web" => "Medline" ] ] ] ] ] ] ] ] 29 => array:3 [ "identificador" => "bib0370" "etiqueta" => "30" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Biomarkers in acute respiratory distress syndrome: from pathobiology to improving patient care" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "J.M. Walter" 1 => "J. Wilson" 2 => "L.B. Ware" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1586/17476348.2014.924073" "Revista" => array:5 [ "tituloSerie" => "Expert Rev Respir Med" "fecha" => "2014" "volumen" => "8" "paginaInicial" => "573" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24875533" "web" => "Medline" ] ] ] ] ] ] ] ] 30 => array:3 [ "identificador" => "bib0375" "etiqueta" => "31" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Airway pathological alterations selectively associated with acute respiratory distress syndrome and diffuse alveolar damage – narrative review" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "G. Ortiz" 1 => "M. Garay" 2 => "V. Capelozzi" 3 => "P. Cardinal-Fernández" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.arbres.2018.03.006" "Revista" => array:5 [ "tituloSerie" => "Arch Bronconeumol" "fecha" => "2019" "volumen" => "55" "paginaInicial" => "31" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29853259" "web" => "Medline" ] ] ] ] ] ] ] ] 31 => array:3 [ "identificador" => "bib0380" "etiqueta" => "32" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Characteristics of microRNAs and their potential relevance for the diagnosis and therapy of the acute respiratory distress syndrome: from bench to bedside" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "P. Cardinal-Fernandez" 1 => "A. Ferruelo" 2 => "A. Esteban" 3 => "J.A. Lorente" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.trsl.2015.11.004" "Revista" => array:6 [ "tituloSerie" => "Transl Res" "fecha" => "2016" "volumen" => "169" "paginaInicial" => "102" "paginaFinal" => "111" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26687392" "web" => "Medline" ] ] ] ] ] ] ] ] 32 => array:3 [ "identificador" => "bib0385" "etiqueta" => "33" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "C-reactive protein: a critical update" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "M.B. Pepys" 1 => "G.M. Hirschfield" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1172/JCI200318921" "Revista" => array:5 [ "tituloSerie" => "J Clin Investig" "fecha" => "2003" "volumen" => "111" "paginaInicial" => "1805" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/12813013" "web" => "Medline" ] ] ] ] ] ] ] ] 33 => array:3 [ "identificador" => "bib0390" "etiqueta" => "34" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Impact of C-reactive protein (CRP) on surfactant function" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.J. Li" 1 => "R.L. Sanders" 2 => "K.P.W.J. Mcadam" 3 => "C.A. Hales" 4 => "B.T. Thompson" 5 => "J.A. Gelfand" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:4 [ "tituloSerie" => "J Trauma Acute Care Surg" "fecha" => "1989" "volumen" => "29" "paginaInicial" => "1690" ] ] ] ] ] ] 34 => array:3 [ "identificador" => "bib0395" "etiqueta" => "35" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Observation on CRP levels in severe trauma patients with ARDS and its significance" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "Y. Zheng" 1 => "X. Huang" 2 => "H. Liang" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:4 [ "tituloSerie" => "J Trauma Surg" "fecha" => "2005" "volumen" => "4" "paginaInicial" => "274" ] ] ] ] ] ] 35 => array:3 [ "identificador" => "bib0400" "etiqueta" => "36" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Albumin and C-reactive protein have prognostic significance in patients with community-acquired pneumonia" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.H. Lee" 1 => "J. Kim" 2 => "K. Kim" 3 => "Y.H. Jo" 4 => "J.E. Rhee" 5 => "T.Y. Kim" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.jcrc.2010.10.007" "Revista" => array:5 [ "tituloSerie" => "J Crit Care" "fecha" => "2011" "volumen" => "26" "paginaInicial" => "287" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/21129911" "web" => "Medline" ] ] ] ] ] ] ] ] 36 => array:3 [ "identificador" => "bib0405" "etiqueta" => "37" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Diagnostic utility of C-reactive protein combined with brain natriuretic peptide in acute pulmonary edema: a cross sectional study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "K. Komiya" 1 => "H. Ishii" 2 => "S. Teramoto" 3 => "O. Takahashi" 4 => "N. Eshima" 5 => "O. Yamaguchi" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/1465-9921-12-83" "Revista" => array:5 [ "tituloSerie" => "Respir Res" "fecha" => "2011" "volumen" => "12" "paginaInicial" => "83" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/21696613" "web" => "Medline" ] ] ] ] ] ] ] ] 37 => array:3 [ "identificador" => "bib0410" "etiqueta" => "38" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Management of acute lung injury and acute respiratory distress syndrome in children" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "A.G. Randolph" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/CCM.0b013e3181aee5dd" "Revista" => array:6 [ "tituloSerie" => "Crit Care Med" "fecha" => "2009" "volumen" => "37" "paginaInicial" => "2448" "paginaFinal" => "2454" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/19531940" "web" => "Medline" ] ] ] ] ] ] ] ] 38 => array:3 [ "identificador" => "bib0415" "etiqueta" => "39" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Incidence, clinical course, and outcome in 217 patients with acute respiratory distress syndrome" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "E. Estenssoro" 1 => "A. Dubin" 2 => "E. Laffaire" 3 => "H. Canales" 4 => "G. Sáenz" 5 => "M. Moseinco" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/00003246-200211000-00008" "Revista" => array:5 [ "tituloSerie" => "Crit Care Med" "fecha" => "2002" "volumen" => "30" "paginaInicial" => "2450" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/12441753" "web" => "Medline" ] ] ] ] ] ] ] ] 39 => array:3 [ "identificador" => "bib0420" "etiqueta" => "40" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Developing prevention model of acute lung injury: validity of lung injury prediction score and risk panel" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "M.S. Atta" 1 => "A.A.A. Mahrous" 2 => "A.A. Hassanien" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ejcdt.2013.08.014" "Revista" => array:4 [ "tituloSerie" => "Egypt J Chest Dis Tuberc" "fecha" => "2013" "volumen" => "62" "paginaInicial" => "675" ] ] ] ] ] ] 40 => array:3 [ "identificador" => "bib0425" "etiqueta" => "41" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comparison of two fluid-management strategies in acute lung injury" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "H.P. Wiedemann" 1 => "A.P. Wheeler" 2 => "G.R. Bernard" 3 => "B.T. Thompson" 4 => "D. Hayden" 5 => "B. DeBoisblanc" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1056/NEJMoa062200" "Revista" => array:5 [ "tituloSerie" => "N Engl J Med" "fecha" => "2006" "volumen" => "354" "paginaInicial" => "2564" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/16714767" "web" => "Medline" ] ] ] ] ] ] ] ] 41 => array:3 [ "identificador" => "bib0430" "etiqueta" => "42" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Interobserver variability in applying a radiographic definition for ARDS" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "G.D. Rubenfeld" 1 => "E. Caldwell" 2 => "J. Granton" 3 => "L.D. Hudson" 4 => "M.A. Matthay" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1378/chest.116.5.1347" "Revista" => array:4 [ "tituloSerie" => "CHEST J" "fecha" => "1999" "volumen" => "116" "paginaInicial" => "1347" ] ] ] ] ] ] 42 => array:3 [ "identificador" => "bib0435" "etiqueta" => "43" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Impact and safety of open lung biopsy in patients with acute respiratory distress syndrome (ARDS)" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "G. Ortiz" 1 => "M. Garay" 2 => "D. Mendoza" 3 => "P. Cardinal-Fernandez" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.medin.2018.01.007" "Revista" => array:2 [ "tituloSerie" => "Med Intensiva" "fecha" => "2018" ] ] ] ] ] ] 43 => array:3 [ "identificador" => "bib0440" "etiqueta" => "44" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Acute Respiratory Distress: from syndrome to disease" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "P. Cardinal-Fernandez" 1 => "E. Correger" 2 => "J. Villanueva" 3 => "F. Rios" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.medin.2015.11.006" "Revista" => array:7 [ "tituloSerie" => "Med Intensiva" "fecha" => "2016" "volumen" => "40" "paginaInicial" => "169" "paginaFinal" => "175" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26754207" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S016503271830805X" "estado" => "S300" "issn" => "01650327" ] ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/21735727/0000004400000005/v1_202006090711/S2173572720301004/v1_202006090711/en/main.assets" "Apartado" => array:4 [ "identificador" => "411" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/21735727/0000004400000005/v1_202006090711/S2173572720301004/v1_202006090711/en/main.pdf?idApp=WMIE&text.app=https://medintensiva.org/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572720301004?idApp=WMIE" ]
| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 3 | 5 | 8 |
| 2024 October | 99 | 50 | 149 |
| 2024 September | 109 | 40 | 149 |
| 2024 August | 81 | 54 | 135 |
| 2024 July | 52 | 37 | 89 |
| 2024 June | 62 | 49 | 111 |
| 2024 May | 50 | 39 | 89 |
| 2024 April | 41 | 33 | 74 |
| 2024 March | 49 | 20 | 69 |
| 2024 February | 38 | 36 | 74 |
| 2024 January | 30 | 28 | 58 |
| 2023 December | 21 | 40 | 61 |
| 2023 November | 38 | 39 | 77 |
| 2023 October | 26 | 26 | 52 |
| 2023 September | 20 | 38 | 58 |
| 2023 August | 16 | 23 | 39 |
| 2023 July | 23 | 27 | 50 |
| 2023 June | 24 | 23 | 47 |
| 2023 May | 37 | 32 | 69 |
| 2023 April | 25 | 28 | 53 |
| 2023 March | 59 | 38 | 97 |
| 2023 February | 47 | 33 | 80 |
| 2023 January | 21 | 31 | 52 |
| 2022 December | 74 | 44 | 118 |
| 2022 November | 48 | 55 | 103 |
| 2022 October | 79 | 28 | 107 |
| 2022 September | 29 | 47 | 76 |
| 2022 August | 27 | 52 | 79 |
| 2022 July | 26 | 53 | 79 |
| 2022 June | 24 | 31 | 55 |
| 2022 May | 28 | 34 | 62 |
| 2022 April | 22 | 43 | 65 |
| 2022 March | 33 | 43 | 76 |
| 2022 February | 28 | 35 | 63 |
| 2022 January | 26 | 21 | 47 |
| 2021 December | 39 | 42 | 81 |
| 2021 November | 22 | 34 | 56 |
| 2021 October | 39 | 67 | 106 |
| 2021 September | 17 | 30 | 47 |
| 2021 August | 17 | 38 | 55 |
| 2021 July | 12 | 21 | 33 |
| 2021 June | 24 | 18 | 42 |
| 2021 May | 34 | 50 | 84 |
| 2021 April | 83 | 83 | 166 |
| 2021 March | 26 | 33 | 59 |
| 2021 February | 29 | 26 | 55 |
| 2021 January | 21 | 20 | 41 |
| 2020 December | 28 | 21 | 49 |
| 2020 November | 23 | 24 | 47 |
| 2020 October | 19 | 13 | 32 |
| 2020 July | 64 | 19 | 83 |
| 2020 June | 97 | 30 | 127 |
Show all
