array:22 [ "pii" => "S2173572724001383" "issn" => "21735727" "doi" => "10.1016/j.medine.2024.05.015" "estado" => "S200" "fechaPublicacion" => "2024-06-16" "aid" => "2037" "copyright" => "Elsevier España, S.L.U. and SEMICYUC" "copyrightAnyo" => "2024" "documento" => "article" "crossmark" => 0 "subdocumento" => "fla" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "itemSiguiente" => array:17 [ "pii" => "S2173572724001371" "issn" => "21735727" "doi" => "10.1016/j.medine.2024.05.014" "estado" => "S200" "fechaPublicacion" => "2024-06-16" "aid" => "2036" "copyright" => "Elsevier España, S.L.U. and SEMICYUC" "documento" => "article" "crossmark" => 0 "subdocumento" => "sco" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Images in Intensive Medicine</span>" "titulo" => "Horner’s syndrome after chest drain insertion due to pneumothorax" "tienePdf" => "en" "tieneTextoCompleto" => "en" "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Síndrome de Horner tras la inserción de un drenaje torácico por neumotórax" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1917 "Ancho" => 2508 "Tamanyo" => 398300 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Arthur Orieux, Raphaël Birot, Didier Gruson, Renaud Prevel" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Arthur" "apellidos" => "Orieux" ] 1 => array:2 [ "nombre" => "Raphaël" "apellidos" => "Birot" ] 2 => array:2 [ "nombre" => "Didier" "apellidos" => "Gruson" ] 3 => array:2 [ "nombre" => "Renaud" "apellidos" => "Prevel" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572724001371?idApp=WMIE" "url" => "/21735727/unassign/S2173572724001371/v1_202406161028/en/main.assets" ] "itemAnterior" => array:17 [ "pii" => "S2173572724000274" "issn" => "21735727" "doi" => "10.1016/j.medine.2024.02.003" "estado" => "S200" "fechaPublicacion" => "2024-02-25" "aid" => "1976" "copyright" => "Elsevier España, S.L.U. and SEMICYUC" "documento" => "article" "crossmark" => 0 "subdocumento" => "fla" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:12 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Fractional excretion of sodium and potassium and urinary strong ion difference in the evaluation of persistent AKI in sepsis" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Excreción fraccional de sodio y potasio, y brecha aniónica urinaria en la evaluación de la IRA persistente en sepsis" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1448 "Ancho" => 1675 "Tamanyo" => 110835 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0135" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">ROC curve showing the area under de curve of FENa, FEK and uSID.</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">FENa: fractional excretion of sodium; FEK: fractional excretion of potassium; uSID: urinary strong ion difference.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Nicolás Contrera Rolón, Joaquín Cantos, Iván Huespe, Eduardo Prado, Griselda I. Bratti, Carlos Schreck, Sergio Giannasi, Guillermo Rosa Diez, Carlos F. Varela" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Nicolás" "apellidos" => "Contrera Rolón" ] 1 => array:2 [ "nombre" => "Joaquín" "apellidos" => "Cantos" ] 2 => array:2 [ "nombre" => "Iván" "apellidos" => "Huespe" ] 3 => array:2 [ "nombre" => "Eduardo" "apellidos" => "Prado" ] 4 => array:2 [ "nombre" => "Griselda I." "apellidos" => "Bratti" ] 5 => array:2 [ "nombre" => "Carlos" "apellidos" => "Schreck" ] 6 => array:2 [ "nombre" => "Sergio" "apellidos" => "Giannasi" ] 7 => array:2 [ "nombre" => "Guillermo" "apellidos" => "Rosa Diez" ] 8 => array:2 [ "nombre" => "Carlos F." "apellidos" => "Varela" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572724000274?idApp=WMIE" "url" => "/21735727/unassign/S2173572724000274/v1_202402251056/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Mortality prediction model from combined serial lactate, procalcitonin and calprotectin levels in critically ill patients with sepsis: A retrospective study according to Sepsis-3 definition" "tieneTextoCompleto" => true "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Luis García de Guadiana-Romualdo, Lourdes Albert Botella, Carlos Rodríguez Rojas, Angela Puche Candel, Roberto Jimenez Sánchez, Pablo Conesa Zamora, María Dolores Albaladejo-Otón, José Manuel Allegue-Gallego" "autores" => array:8 [ 0 => array:4 [ "nombre" => "Luis" "apellidos" => "García de Guadiana-Romualdo" "email" => array:1 [ 0 => "guadianarom@yahoo.es" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">1</span>" "identificador" => "fn0005" ] 2 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Lourdes Albert" "apellidos" => "Botella" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">1</span>" "identificador" => "fn0005" ] ] ] 2 => array:3 [ "nombre" => "Carlos" "apellidos" => "Rodríguez Rojas" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "Angela" "apellidos" => "Puche Candel" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Roberto" "apellidos" => "Jimenez Sánchez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 5 => array:3 [ "nombre" => "Pablo" "apellidos" => "Conesa Zamora" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "María Dolores" "apellidos" => "Albaladejo-Otón" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 7 => array:3 [ "nombre" => "José Manuel" "apellidos" => "Allegue-Gallego" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Laboratory Medicine Department, Hospital Universitario Santa Lucía, Cartagena, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Laboratory Medicine Department, Hospital Universitario Virgen de la Arrixaca, Murcia, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Critical Care Unit, Hospital Universitario Santa Lucía, Cartagena, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Un modelo de predicción de mortalidad basado en la combinación de lactato, procalcitonina y calprotectina en pacientes críticos con sepsis: un estudio retrospectivo de acuerdo a la definición Sepsis-3" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1033 "Ancho" => 2091 "Tamanyo" => 151642 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Flowchart of patients’ enrollment in the study.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Sepsis is a life-threatening condition caused by a dysregulated host response to infection resulting in multiple organ dysfunction.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Despite significant improvements in care, existing epidemiologic studies suggest that sepsis remains a huge burden across all regions, with a high incidence and mortality.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Therefore, an early diagnosis and identification of high-risk sepsis patients is key, increasing the possibility of initiating early and specific treatments. Severity scoring systems, such as <span class="elsevierStyleItalic">Acute Physiology and Chronic Health Evaluation</span> (APACHE) and <span class="elsevierStyleItalic">Simplified Acute Physiology Score</span> (SAPS) for mortality, or <span class="elsevierStyleItalic">Sequential Organ Failure Assessment</span> (SOFA) to assess and characterize the degree of organ dysfunction, are commonly used in critical care to inform about mortality prediction and risk stratification and optimization of patient outcomes. However, their use to guide decision-making and their applicability in the real-life clinical practice have been questioned.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> An easy-measurable tool for the early identification of high-risk patients, as circulating biochemical markers, would be key in aiding clinical decision-making and optimizing the use of health care resources. Biomarkers such as procalcitonin have been reported as useful tools for diagnosis of bacterial infection in critically ill patients,<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> but its prognostic value is controversial.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> Therefore, an accurate and early evaluation of the prognosis of sepsis is still lacking and the research on new biomarkers is a priority for sepsis.<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> Besides, in view of the complexity of the sepsis pathophysiology, a combination of several biomarkers may be a more effective strategy for diagnosis and prognosis, but this requires further evaluation.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Calprotectin, as part of the innate immune system, has emerged as a promising sepsis biomarker. It is a heterodimeric protein belonging to the family of calcium-binding S100 leucocyte proteins and composed by two calcium binding proteins: S100A8 and S100A9, also called myeloid-related proteins (MRP) 8 and MRP-14. Calprotectin is an abundant cytosolic protein that is constitutively expressed in neutrophils and other immune cells, such as monocytes and activated macrophages.<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,9</span></a> During inflammation and mediated through neutrophil activation, it is released actively and exerts a critical role in regulating the inflammatory response by modulating leukocyte recruitment and inducing cytokine secretion.<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9,10</span></a> In critically ill patients, calprotectin has been reported as a helpful biomarker for early diagnosis of sepsis,<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> but its prognostic value has been scarcely evaluated and results are controversial.<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12–14</span></a> A recent health economic analysis on the predictive use of blood calprotectin concludes that this biomarker helps clinical decision making in sepsis and indicates that it has a cost-saving and life-saving impact on the healthcare system.<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">In this study, we aimed: 1) to evaluate the ability for prognosis of baseline, on 24 h and clearance of serum calprotectin for prognosis of 28-day mortality, in comparison to conventional biomarkers, and 2) to develop a predictive model, based on laboratory tests (lactate, procalcitonin and calprotectin) measured in blood samples collected in the first 24 h of Intensive Care Unit (ICU) stay, for predicting 28-day mortality in patients with sepsis. We hypothesized that a combination of these biomarkers would be better than any single biomarker for this purpose and we tested whether the addition to SOFA score could improve the prediction of mortality in these patients.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Study design and population</span><p id="par0020" class="elsevierStylePara elsevierViewall">We conducted a single-center, retrospective study enrolling consecutive adult (≥ 18 years) patients admitted to the ICU of Santa Lucía University Hospital (Cartagena, Spain) from January 2015 to November 2016 and fulfilling criteria for severe sepsis or septic shock, according to Sepsis-2 definition. For definitive inclusion in the study, only those patients with SOFA ≥ 2 and therefore met criteria for the new Sepsis-3 definition for sepsis were included. Other exclusion criteria were (a) age < 18 years; (b) patients developing sepsis while on ICU but admitted to the ICU for other reasons; (c) lack of blood sample for the measurement of biomarkers; (d) pregnancy; (e) limitation of therapeutic effort; (f) lack of informed consent; and (g) patients transferred from or to other ICUs.</p><p id="par0025" class="elsevierStylePara elsevierViewall">The study protocol was approved by the local Ethics Committee of our hospital (E.O.2013-28 Enm.3 BIOMARCADORES) and was performed in accordance with the Declaration of Helsinki ethical guidelines.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Data collection</span><p id="par0030" class="elsevierStylePara elsevierViewall">For eligible patients, demographic, comorbidities, laboratory and microbiological tests and outcome data were extracted from electronic medical records and laboratory information systems. A database was prepared for register of collected data and all patient identities were coded for blindness.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Outcome measures</span><p id="par0035" class="elsevierStylePara elsevierViewall">All patients were followed-up to 28 days for the outcome of all-cause mortality.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Blood sampling and biomarker testing</span><p id="par0040" class="elsevierStylePara elsevierViewall">In all patients, baseline blood samples were collected on admission to ICU and a second sample was drawn at 24 h of ICU stay. Blood samples were centrifuged at 3000×<span class="elsevierStyleItalic">g</span> for 5 min to obtain serum and analysed for procalcitonin and reported to clinicians within 1 h from collection. Leftover serum for calprotectin was immediately frozen and stored to −80 °C until testing.</p><p id="par0045" class="elsevierStylePara elsevierViewall">Baseline blood lactate levels were measured on ICU by amperometry on an ABL 90 FLEX point-of-care testing analyzer (Radiometer Medical ApS, Brønshøj, Denmark), with a limit of detection of 0.1 mmol/L. Procalcitonin levels were measured by a chemiluminiscent enzyme immunoassay on G600II analyzer (Fujirebio Diagnostics Inc. Japan) and a electrochemiluminescence immunoassay on Cobas e601 and Cobas e401 analyzers (Roche Diagnostics, Switzerland), both with a limit of detection of 0.02 ng/mL and a functional sensitivity of 0.06 ng/mL. Serum calprotectin levels were measured by a particle enhanced turbidimetric immunoassay (PETIA) (Gentian AS, Norway) using a Cobas c702 instrument (Roche Diagnostics, Switzerland). According to manufacturer´s data, limit of quantification is 0.30 mg/L.</p><p id="par0050" class="elsevierStylePara elsevierViewall">Procalcitonin and calprotectin clearance was defined by using the following formula: Clearance<span class="elsevierStyleInf">24 h</span> = 100 × (Biomarker level<span class="elsevierStyleInf">ICU admission</span> − Biomarker level<span class="elsevierStyleInf">24 h</span>)/Biomarker level<span class="elsevierStyleInf">ICU admission</span></p><p id="par0055" class="elsevierStylePara elsevierViewall">A positive value denotes a decrease or clearance of biomarker levels, whereas a negative value denotes an increase in the biomarker after 24 h.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Statistical analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">The normality of continuous variables was tested by Kolmogorov-Smirnov or Shapiro-Wilk and they are reported as median (interquartile range [IQR]) or mean (standard deviation [SD]), as appropriate. Categorical variables are presented as frequency and percentage in each category. Mann–Whitney U and chi-squared or Fisher exact tests, as appropriate, were used to compare continuous and categorical data between groups, respectively.</p><p id="par0065" class="elsevierStylePara elsevierViewall">To evaluate the ability for predicting 28-day mortality of SOFA score, calprotectin and the other tested biomarkers we estimated the area under the curve (AUC) of the receiver operating characteristic (ROC) curves and optimal cut-offs were defined as the value maximizing the Youden index.</p><p id="par0070" class="elsevierStylePara elsevierViewall">In addition, a logistic regression equation was constructed to predict the probability of 28-day mortality. For this, all biomarkers with a univariate significance of <span class="elsevierStyleItalic">p</span>-value < 0.15 as covariates and 28-day all-cause mortality as the dependent variable were included in the multivariate analysis, after testing for collinearity using the variance inflation factor (VIF), using a mixed and forward-backward stepwise variable selection procedure (<span class="elsevierStyleItalic">p</span>-value < 0.05 and <span class="elsevierStyleItalic">p</span>-value > 0.10 respectively). The logistic regression equation for predicting a logit transformation of the probability of 28-day mortality was created using the coefficients generated for each biomarker in the final step of the regression model. Discriminative ability and calibration of the model generated were assessed by the ROC AUC and Hosmer-Lemeshow test, respectively. ROC AUC for combinations of SOFA score and biomarkers or the novel model from regression analysis was calculated by logistic regression analysis. The Delong method was used for comparison of significant ROC AUCs.</p><p id="par0075" class="elsevierStylePara elsevierViewall">We performed analyses using the software packages SPSS 21.0 (SPSS Inc., IL, USA) and MedCalc 15.0 (MedCalc Software, Ostend, Belgium). In all tests, a two-sided p value of < 0.05 was considered significant.</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Baseline characteristics and laboratory findings</span><p id="par0080" class="elsevierStylePara elsevierViewall">During study period, 202 patients with sepsis, according to Sepsis-2 definition, were admitted to ICU. According to exclusion criteria, 29 patients were excluded (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Finally, 173 patients (median age: 67 years [interquartile range: 55−76; (IQR); 109 (63%) male) were included in the study. According to Sepsis-3 definition, 101 patients were diagnosed as sepsis (58.4%) and 72 (41.6%) as septic shock on ICU admission. The most common source of infection was abdominal (42.8%) and infection was microbiologically documented in 132 patients (75.7%). In these cases, Gram-negative bacteria were the main causative agent for infection (<span class="elsevierStyleItalic">n</span> = 69 [39.9%]), followed by polybacterial infection (<span class="elsevierStyleItalic">n</span> = 32 [18.5%]) and Gram-positive bacteria (<span class="elsevierStyleItalic">n</span> = 24 [13.9%]). Blood culture was requested in 145 (83.8%) patients and bacteremia was detected in 68 (39.3%) patients, being <span class="elsevierStyleItalic">Escherichia coli</span> the most frequent isolate (<span class="elsevierStyleItalic">n</span> = 22). The 28-day mortality rate was 15%. Patients’ characteristics according to survival status are presented in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">In the comparison among non-survivors and survivors, SOFA score was higher in the non-survivors (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). Concerning laboratory findings, on ICU admission only lactate levels were significantly higher in non-survivors and differences were not found for procalcitonin and calprotectin levels. On blood samples collected on 24 h, differences between groups were not detected for both biomarkers. However, procalcitonin and calprotectin clearances were significantly lower in non-survivor patients (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Prognostic value of SOFA score and biomarkers for 28-day mortality</span><p id="par0090" class="elsevierStylePara elsevierViewall">The predictive ability of SOFA score and circulating biomarkers and their optimal cutoffs for predicting 28-day mortality were computed (<a class="elsevierStyleCrossRefs" href="#tbl0010">Tables 2 and 3</a>and <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>a–c). On ICU admission, only SOFA score (ROC AUC: 0.736) and lactate levels (ROC AUC: 0.698) achieved a significant accuracy, withouth difference between both (<span class="elsevierStyleItalic">p</span> = 0.495). Serum calprotectin and procalcitonin levels measured on admission and on 24 h did not achieve a significant accuracy for the outcome. The accuracy of SOFA score on ICU admission to predict 28-day mortality did not improve in combination with the biomarkers evaluated in this study (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). The discriminative ability for procalcitonin and calprotectin clearance was statistically significant, achieving ROC AUC of 0.668 and 0.644, respectively, withouth a significant difference between both (<span class="elsevierStyleItalic">p</span> = 0.739).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Association of biomarkers with 28-day mortality: SEPCART score</span><p id="par0095" class="elsevierStylePara elsevierViewall">From multivariate analysis, SOFA score and lactate on ICU admission, chronic kidney injury, procalcitonin clearance and calprotectin clearance in the first 24 h were independent predictors of 28-day mortality (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>).</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">A multivariate logistic regression model using circulating biomarker levels was constructed to predict the 28-day mortality. Combining these three biomarkers (SEPCART score), through a regression equation, the log of probability was converted to the probability of 28-day mortality as follows:<elsevierMultimedia ident="eq0005"></elsevierMultimedia><elsevierMultimedia ident="eq0010"></elsevierMultimedia><elsevierMultimedia ident="eq0015"></elsevierMultimedia></p><p id="par0105" class="elsevierStylePara elsevierViewall">As to goodness of fit, the following pseudo-R<span class="elsevierStyleSup">2</span> indices were obtained: McFadden’s R<span class="elsevierStyleSup">2</span>: 0.151, Cox-Snell R<span class="elsevierStyleSup">2</span>: 0.120 and Nagelkerke R<span class="elsevierStyleSup">2</span>: 0.210. The absence of multicolinearity between predictors was confirmed for all variables (mean VIF = 1.03). The Hosmer–Lemeshow chi-square value was 8.18 (<span class="elsevierStyleItalic">p</span> = 0.416), indicating that the model had a good calibration.</p><p id="par0110" class="elsevierStylePara elsevierViewall">In the ROC curve analysis, SEPCART and SOFA scores achieved a similar AUC in predicting 28-day mortality, without a statistically significant difference between both (0.766 (95% CI: 0.677−0.856) vs. 0.736 (95% CI: 0.635−0.838); <span class="elsevierStyleItalic">p</span> = 0.650) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>d). The optimal cutoff value for the probability of 28-day mortality was 0.151, with a sensitivity, specificity, negative predictive value and positive predictive value of 69.2% (95% CI: 48.2–85.7 %), 71.4% (95%CI: 63.4−78.6%), 92.9% (95% CI: 86<span class="elsevierStyleSmallCaps">.5−96.9%</span>) and 30.5% (95% CI: <span class="elsevierStyleSmallCaps">18.8-</span>43.2%), respectively. The addition of SEPCART score to SOFA score result in a better performance (0.829; 95% CI: 0.765−0.882; <span class="elsevierStyleItalic">p</span> < 0.001), with a trend to statistical significance when both ROC curves were compared (<span class="elsevierStyleItalic">p</span> = 0.055).</p></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0160">Discusion</span><p id="par0115" class="elsevierStylePara elsevierViewall">Sepsis is still a major challenge in critical care. Because it is a time-sensitive condition, its early diagnosis for initiation of antimicrobial therapy, the source control and a close monitoring remain as the cornerstones to decrease the morbidity and mortality related to sepsis.<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> However, the early risk stratification of septic patients still remains an unsolved issue and novel strategies are required.<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> In this sense, canonical blood biochemical markers are useful to help monitor patient response to treatment and guide therapeutic decisions in individual patients,<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> but their ability for risk stratification is controversial.<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> In this sense, novel emergent biomarkers, such as MR-proADM, have been reported as helpful tools to predict the prognosis of critically ill patients with sepsis.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Besides, due to the complex nature of sepsis,<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> in which the host response involves the interplay between different mechanisms, models combining different biochemical markers represent a new and interesting strategy to overcome the limited prognostic performance of single parameters.<a class="elsevierStyleCrossRefs" href="#bib0105"><span class="elsevierStyleSup">21,22</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">This single-center study demonstrated that: 1) procalcitonin and calprotectin levels, measured on ICU admission and on 24 h, did not predict the prognosis of critically ill patients with sepsis; 2) for both biomarkers, clearance on first 24 h achieved a moderate accuracy for predicting 28-day mortality; and 3) a model combining the levels and clearance of two canonical biomarkers widely used for the management of septic patients, lactate and procalcitonin, and an emergent sepsis marker, calprotectin, was valuable for predicting 28-day mortality in ICU patients with sepsis. Although this novel model increased numerically, but without a significant difference, the performance of SOFA score alone, it trended to improve the prognostic value of SOFA score.</p><p id="par0125" class="elsevierStylePara elsevierViewall">Lactate is a well-known indicator of sepsis severity and a marker of resuscitation<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> and its levels are known to be associated with 28-day mortality in patients with sepsis.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> Concerning other conventional biomarkers, a recent review showed that unique baseline and isolated measurement of procalcitonin and CRP are not useful for determining the mortality prognosis among critically ill sepsis patients.<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> A potential strategy to improve this prognostic value is by using serial measurements because their time courses may be more reliable than their absolute levels, but time for collection of blood samples and the optimal clearance cutoff for accurate risk assessment has not been clearly defined.<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> Finally, calprotectin, as signature of neutrophil activation, has recently emerged as sepsis biomarker. In critically ill patients, higher serum calprotectin levels have been reported in patients with sepsis<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12,26</span></a> and it is a helpful marker for early diagnosis of sepsis in these patients.<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> However, its potential as prognostic biomarker is still controversial. In Emergency Department patients, the ROC AUC of calprotectin for predicting 28-day mortality in septic patients was 0.813.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> In critically ill patients, serum calprotectin concentrations predict short-term mortality with a moderate performance (ROC AUC: 0.64) but better than procalcitonin (ROC AUC: 0.56),<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> and in the subgroup of septic patients high calprotectin concentrations on ICU admission predict long-term mortality risk.<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> In patients with septic shock, plasma calprotectin levels were also significantly higher in non-survivors and this biomarker could indicate a higher risk of death and help the stratification for improved care and treatment selection.<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> However, in Lee et al. study, no difference was reported for calprotectin levels in critically ill surgical patients according to survival.<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> Besides, the potential role of serial measurement of calprotectin has not been evaluated yet.</p><p id="par0130" class="elsevierStylePara elsevierViewall">In our study, only ICU admission lactate levels achieved a significant, but moderate, performance for predicting mortality (ROC AUC: 0.698). Baseline procalcitonin levels lacked prognostic value for mortality, finding previously reported by our group<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> and recently by Ríos-Toro et al.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> Concerning procalcitonin clearance, although different studies have reported the prognostic usefulness of variations of procalcitonin levels measured on admission and on fifth day,<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">30,31</span></a> on 72 h<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">32</span></a> and on 48 h,<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">33</span></a> these are too long periods to be used as a predicting time in sepsis, a condition in which prognostic and therapeutic tools must be reinforced earlier to improve the evolution of patients. In our study, procalcitonin clearance in the first 24 h achieved a weak, although statiscally significant, performance (ROC AUC: 0.668), although higher than that reported by Ríos-Toro et al. (ROC AUC: 0.51).<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> Similar findings were found for calprotectin. No differences were observed in calprotectin levels on ICU admission, similarly to Lee et al.,<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> and serial measurements on first 24 h achieved a poor performance to predict mortality (ROC AUC: 0.585).</p><p id="par0135" class="elsevierStylePara elsevierViewall">Similarly to other previous studies, we tested the prognostic ability of combined biomarkers. A model generated from regression analysis combining 3 independent predictors of 28-day mortality (SEPCART score, including baseline lactate and procalcitonin and calprotectin clearance on first 24 h) achieved a significant performance (ROC AUC: 0.766), increasing this accuracy to 0.829 in combination with SOFA score. The performance of this approach was similar than those reported in previous studies combining procalcitonin, lactate, neutrophil-to-white blood cell ratio and IL-6 in Emergency Department patients (ROC AUC: 0.823)<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">34</span></a> or pentraxin-3, procalcitonin, lactate and interleukin-6 (IL-6) in ICU patients (ROC AUC: 0.778).<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> However, conversely to Song et al. study,<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> our novel model combining blood-based biomarkers did not improve significantly the accuracy of SOFA alone, limiting a potential applicability in the real-life clinical practice.</p><p id="par0140" class="elsevierStylePara elsevierViewall">There were some limitations to this study. First, an estimation of sample size was not previously calculated and the final size depended on available reagent provided by manufacturer for measurement of calprotectin levels. Second, serial lactate levels at prefixed timepoints to calculate blood lactate clearance were not available. The observation of a better prognosis with decreasing lactate levels in critically ill patients, including those with sepsis, is consistent throughout the literature,<a class="elsevierStyleCrossRefs" href="#bib0175"><span class="elsevierStyleSup">35–37</span></a> although the optimal or desired rate of lactate clearance is a contentious area.<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">38</span></a> Some authors have hardly criticized the value of lactate clearance in sepsis.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">39</span></a> Recent studies have reported a low accuracy for lactate clearance at 24 h as predictor of mortality in critically ill patients, with a ROC AUC of 0.620,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">40</span></a> or no difference for predicting mortality was reported by Lestari et al. when baseline lactate and lactate clearance were compared.<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">41</span></a> Third, the results for calprotectin are assay- and matrix-dependent and results could vary according to type of sample used.<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">42,43</span></a> In our study, blood tubes for serum were centrifuged within 2 h after blood collection, immediately transferred to the secondary tube, as recommended by the manufacturer, and the samples were stored according to stability results previously reported.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">43</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">In conclusion, both serum calprotectin and procalcitonin, measured on ICU admission baseline and on 24 h, lacked the ability for prognosis of 28-day mortality and only their clearance achieved a significant but moderate accuracy. The combined biomarker approach using baseline lactate and serial measurements of procalcitonin and calprotectin showed good performance in predicting 28-day all-cause mortality among the critically ill patients diagnosed with sepsis as defined by Sepsis-3. Furthermore, the addition of this combination of biomarkers to SOFA score appears promising as tool for risk stratification in ICU septic patients, although more studies including populations with larger sample size are required to confirm this finding.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0165">Author contributions</span><p id="par0150" class="elsevierStylePara elsevierViewall">LGGR and LAB conceived and designed the study and supervised the conduct of the trial and data collection. LAB and APC measured calprotectin in serum samples. RJS and JMAG contributed to the enrollment of patients and clinical data collection. CRR provided statistical advice to analyze the data. LGGR drafted the article, and MDAO and PCZ contributed substantially to its revision. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0170">Funding</span><p id="par0155" class="elsevierStylePara elsevierViewall">This work was supported by <span class="elsevierStyleGrantSponsor" id="gs0005">Gentian AS, Moss, Norway</span>, providing reagents and other materials for measurement of calprotectin. Gentian AS did not participate in the study design, collection and analysis of data.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0175">Disclosure statement</span><p id="par0160" class="elsevierStylePara elsevierViewall">The authors report there are no competing interests to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres2166788" "titulo" => "Abstract" "secciones" => array:8 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Design" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Setting" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Patients or participants" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Interventions" ] 5 => array:2 [ "identificador" => "abst0030" "titulo" => "Main variables of interest" ] 6 => array:2 [ "identificador" => "abst0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1837554" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres2166789" "titulo" => "Resumen" "secciones" => array:8 [ 0 => array:2 [ "identificador" => "abst0045" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0050" "titulo" => "Diseño" ] 2 => array:2 [ "identificador" => "abst0055" "titulo" => "Ámbito" ] 3 => array:2 [ "identificador" => "abst0060" "titulo" => "Pacientes o participantes" ] 4 => array:2 [ "identificador" => "abst0065" "titulo" => "Intervenciones" ] 5 => array:2 [ "identificador" => "abst0070" "titulo" => "Variables de interés principales" ] 6 => array:2 [ "identificador" => "abst0075" "titulo" => "Resultados" ] 7 => array:2 [ "identificador" => "abst0080" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1837553" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study design and population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Data collection" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Outcome measures" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Blood sampling and biomarker testing" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Baseline characteristics and laboratory findings" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "Prognostic value of SOFA score and biomarkers for 28-day mortality" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Association of biomarkers with 28-day mortality: SEPCART score" ] ] ] 7 => array:2 [ "identificador" => "sec0060" "titulo" => "Discusion" ] 8 => array:2 [ "identificador" => "sec0065" "titulo" => "Author contributions" ] 9 => array:2 [ "identificador" => "sec0070" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0075" "titulo" => "Disclosure statement" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2023-11-07" "fechaAceptado" => "2024-05-10" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1837554" "palabras" => array:6 [ 0 => "Sepsis" 1 => "Procalcitonin" 2 => "Calprotectin" 3 => "Lactate" 4 => "SOFA score" 5 => "Mortality" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1837553" "palabras" => array:6 [ 0 => "Sepsis" 1 => "Procalcitonina" 2 => "Calprotectina" 3 => "Lactato" 4 => "Escala SOFA" 5 => "Mortalidad" ] ] ] ] "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="spar0050" class="elsevierStyleSimplePara elsevierViewall">1) To evaluate the ability of baseline and on 24 h serum calprotectin, in comparison to canonical biomarkers (lactate and procalcitonin), for prognosis of 28-day mortality in critically ill septic patients; and 2) To develop a predictive model combining the three biomarkers.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Design</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">A single-center, retrospective study.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Setting</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Intensive Care Unit of a university hospital.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Patients or participants</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">One hundred and seventy three septic pacientes were included.</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Interventions</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Measurement of baseline lactate, procalcitonin and calprotectin level and procalcitonin and calprotectin levels on 24 h.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Main variables of interest</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Demographics and comorbidities, SOFA score on ICU admission, baseline lactate, procalcitonin and calprotectin on admission and on 24 h and 28-day mortality.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Results</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">1) On ICU admission, lactate was the only biomarker achieving a significant accuracy (AUC: 0.698); 2) On 24 h, no differences were found on procalcitonin and calprotectin levels. Procalcitonin and calprotectin clearances were significantly lower in non-survivors and both achieved a moderate performance (AUCs: 0.668 and 0.664, respectively); 3) A biomarker based-model achieved a significant accuracy (AUC: 0.766), trending to increase (AUC: 0.829) to SOFA score alone; y 4) Baseline lactate levels and procalcitonin and calprotectin clearance were independent predictors for the outcome.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Conclusions</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">1) Baseline and on 24 h calprotectina and procalcitonin levels lacked ability in predicting 28-day mortality; 2) Accuracy of clearance of both biomarkers was moderate; and 3) Combination of SOFA score and the predictive biomarker based-model showed a high prognostic accuracy.</p></span>" "secciones" => array:8 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Design" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Setting" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Patients or participants" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Interventions" ] 5 => array:2 [ "identificador" => "abst0030" "titulo" => "Main variables of interest" ] 6 => array:2 [ "identificador" => "abst0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Objetivo</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">1) Valorar en pacientes críticos sépticos la capacidad de la medida basal y a las 24 horas de calprotectina sérica, en comparación con marcadores convencionales (lactato y procalcitonina), para predecir mortalidad a los 28 días; y 2) Generar un modelo predictivo basado en la combinación de biomarcadores.</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Diseño</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Estudio unicéntrico, retrospectivo.</p></span> <span id="abst0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Ámbito</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Unidad de Cuidados Intensivos de un hospital universitario.</p></span> <span id="abst0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Pacientes o participantes</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">173 pacientes sépticos.</p></span> <span id="abst0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Intervenciones</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">Medida de las concentraciones basales de lactato, procalcitonina y calprotectina y de procalcitonina y calprotectina a las 24 horas.</p></span> <span id="abst0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Variables de interés principales</span><p id="spar0115" class="elsevierStyleSimplePara elsevierViewall">Datos demográficos y comorbilidades, escala SOFA al ingreso, lactato al ingreso, y procalcitonina y calprotectina basal y a las 24 horas y mortalidad a los 28 días.</p></span> <span id="abst0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Resultados</span><p id="spar0120" class="elsevierStyleSimplePara elsevierViewall">1) Al ingreso, el lactato fue el único biomarcador con un rendimiento predictivo significativo (AUC: 0,698); 2) A las 24 horas no se observaron diferencias en las concentraciones de procalcitonina y calprotectina sérica, pero sí en el aclaramiento de ambos biomarcadores, que mostraron un rendimiento moderado (AUCs: 0,668 y 0,664); 3) Un modelo combinando biomarcadores bioquímicos alcanzó un rendimiento significativo (AUC: 0,766), con tendencia a incrementar (AUC: 0,829) el de la escala SOFA aislada; y 4) Las concentraciones de lactato basal y el aclaramiento de procalcitonina y calprotectina fueron predictores independientes del evento.</p></span> <span id="abst0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Conclusiones</span><p id="spar0125" class="elsevierStyleSimplePara elsevierViewall">1) Calprotectina y procalcitonina basal y a las 24 horas carecen de valor para predecir mortalidad a los 28 días; 2) El rendimiento del aclaramiento de ambos fue moderado; y 3) La combinación de la escala SOFA y un modelo combinando los biomarcadores sanguíneos mostró un rendimiento pronóstico alto.</p></span>" "secciones" => array:8 [ 0 => array:2 [ "identificador" => "abst0045" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0050" "titulo" => "Diseño" ] 2 => array:2 [ "identificador" => "abst0055" "titulo" => "Ámbito" ] 3 => array:2 [ "identificador" => "abst0060" "titulo" => "Pacientes o participantes" ] 4 => array:2 [ "identificador" => "abst0065" "titulo" => "Intervenciones" ] 5 => array:2 [ "identificador" => "abst0070" "titulo" => "Variables de interés principales" ] 6 => array:2 [ "identificador" => "abst0075" "titulo" => "Resultados" ] 7 => array:2 [ "identificador" => "abst0080" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:3 [ "etiqueta" => "1" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">These authors contributed equally to this work.</p>" "identificador" => "fn0005" ] ] "multimedia" => array:9 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1033 "Ancho" => 2091 "Tamanyo" => 151642 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Flowchart of patients’ enrollment in the study.</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 3007 "Ancho" => 3341 "Tamanyo" => 583229 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleBold">a.</span> Receiver operating characteristic curves of SOFA score and circulating biomarker levels on admission; <span class="elsevierStyleBold">b.</span> Receiver operating characteristic curves of biomarker levels on 24 h; <span class="elsevierStyleBold">c.</span> Receiver operating characteristic curves of biomarker clearances; <span class="elsevierStyleBold">d.</span> Receiver operating characteristic curves of SOFA and SEPCART scores to predict 28-day mortality.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">ICU: Intensive Care Unit; IQR: Interquartile range; SOFA: <span class="elsevierStyleItalic">Sequential Organ Failure Assessment</span>.</p>" "tablatextoimagen" => array:2 [ 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">Variables \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total<span class="elsevierStyleItalic">n</span> = 173 \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">Survivors<span class="elsevierStyleItalic">n</span> = 147 (85%) \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-survivors<span class="elsevierStyleItalic">n</span> = 26 (15%) \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> \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">Age in years; median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 (55−76) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 (54−75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 (70−78) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.101 \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">Gender, male; <span class="elsevierStyleItalic">n</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">109 (63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90 (61.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (73.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.249 \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_colgroup " 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-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">Type of patient; <span class="elsevierStyleItalic">n</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowgroup " rowspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.798</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>Medical \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">109 (63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93 (63.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (61.5) \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>Surgical \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39 (22.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (21.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (26.9) \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>Medical requiring surgery \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 (14.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (11.5) \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">Septic shock; <span class="elsevierStyleItalic">n</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 (41.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 (34) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (84.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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">SOFA score on ICU admission; median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (5−10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (5−9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (8−14) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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_colgroup " 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-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>Infection source; <span class="elsevierStyleItalic">n</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowgroup " rowspan="8" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.612</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>Abdominal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74 (42.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 (42.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (42.3) \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>Respiratory \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (20.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (19.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (30.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Urinary \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (20.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (22.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (11.5) \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>Central nervous system infections \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (1.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (2.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \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>Bacteremia of unknown origin or catheter-related bloodstream infections \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (5.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (6.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Skin and soft tissues \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (7.7) \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>Other \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_colgroup " 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-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">Comorbidities; <span class="elsevierStyleItalic">n</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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>Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64 (37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 (38.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (30.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.476 \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>Hypertension \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">107 (61.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87 (59.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (76.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.086 \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>Inmunosupresión \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (28) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (19.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (26.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.405 \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>Chronic kidney disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (16.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (12.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (38.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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>Chronic obstructive pulmonary disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (10.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (11.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.000 \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>Active cancer \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">48 (27.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38 (25.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (38.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.186 \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>Cardiovascular disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52 (30.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40 (27.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (46.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.052 \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>Chronic liver disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (5.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (4.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (11.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.175 \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">Acute kidney injury on ICU admission; n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">123 (71.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100 (68) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 (88.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.034</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">Need for replacement renal therapy; n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37 (21.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (14.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (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="left" 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">Need for invasive mechanical ventilation; n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84 (48.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60 (40.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 (92.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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">ICU lenght of stay (days) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (3−10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (3−11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (2−10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.834 \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">In-hospital lenght of stay (días) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (15−32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 (11−37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (5−16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" 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 => "xTab3569949.png" ] ] 1 => 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-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Laboratory findings</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 colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">On ICU admission</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">Procalcitonin (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14.2 (4.7−38.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13.5 (4.4−38.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.6 (6.7−27.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.731 \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">Calprotectin (mg/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.6 (4.0−10.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.5 (4.1−10.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.0 (3.1−10.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.768 \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">Lactate (mmol/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.3 (1.4−3.6) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.2 (1.3−2.5) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.0 (2.3−6.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">On 24 h</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">Procalcitonin (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.8 (4.3−33.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.5 (4.2−31.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.4 (6.2−57.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.050 \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">Calprotectin (mg/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.6 (3.5−12.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.1 (3.4−11.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.5 (4.4−14.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.167 \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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clearance biomarkers</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">Procalcitonin (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.1 (−16.8 to 43.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29.5 (−5.1 to 44.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−12.9 (−101.5 to 37.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.006</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">Calprotectin (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (−35.6 to 25.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.8 (−29.2 to 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−27.8 (−50.6 to 15.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.019</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3569947.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Characteristics of patients according to 28-day mortality.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">SOFA: <span class="elsevierStyleItalic">Sequential Organ Failure Assessment</span>; ROC AUC: Receiver Operating Characteristic Area Under Curve; CI: Confidence interval.</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">ROC AUC \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"><span class="elsevierStyleItalic">p</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> (comparison vs. SOFA score) \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 colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">On ICU admission</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">SOFA score \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.736 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.664−0.800 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</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="left" 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-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">Lactate \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.698 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.623−0.765 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.495 \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">Procalcitonin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.521 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.444−0.598 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.727 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.007</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">Calprotectin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.518 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.441−0.595 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.789 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.018</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">SOFA + Lactate \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.750 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.678−0.812 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.217 \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">SOFA + Procalcitonin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.734 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.662−0.798 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.773 \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">SOFA + Calprotectin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.736 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.664−0.800 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold"><0.001</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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.981 \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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">On 24 h</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">Procalcitonin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.621 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.498−0.743 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.054 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\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">Calprotectin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.585 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.455−0.715 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.199 \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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clearance</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">Procalcitonin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.668 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.545−0.790 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.007</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\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">Calprotectin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.644 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.527−0.760 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.016</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3569948.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">ROC curves of biomarker levels to predict 28-day mortality.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">SOFA: Sequential Organ Failure Assessment; S: Sensitivity; Sp: Specificity; PPV: Positive predictive value; NPV: Negative predictive value; CI: Confidence Interval.</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"> \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">Cutoff \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">S (%) 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">Sp (%) 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">PPV (%) 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">NPV (%) 95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SOFA score (ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80.8 (60.6−93.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53.7 (45.3−62.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.6 (15.2−33.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94.0 (86.7−98.0) \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">Lactate (mmol/L) (ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥2.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84 (65.1−95.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52.4 (44.0−60.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.9 (15.6−33.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.1 (87.8−98.6) \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">Procalcitonin clearance (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≤11.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.4 (44.3−82.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">71.4 (63.4−78.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28.8 (17.8−42.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">92.1(85.5−96.3) \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">Calprotectin clearance (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≤−20.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61.5 (40.6−79.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68.0 (59.8−75.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25.4 (15.3−37.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90.9 (83.9−95.6) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3569946.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Optimal cutoffs for biomarkers with a significant accuracy for 28-day mortality.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Variable \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate analysis</th><th class="td-with-role" title="\n \t\t\t\t\ttable-head\n \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Multivariate analysis</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR (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"><span class="elsevierStyleItalic">p</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR (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"><span class="elsevierStyleItalic">p</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-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">Age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.027 (0.994−1.061) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.109 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Gender, male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.719 (0.680−4.348) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.252 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Comorbidities and other variables</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">Diabetes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.722 (0.295−1.771) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.477 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Inmunosupresión \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.499 (0.576−3.904) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.407 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Hypertension \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.299 (0.872−6.063) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.093 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Chronic renal disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.211 (1.669−10.623) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.571 (1.123−11.361) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.031</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">Chronic obstructive pulmonary disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.068 (0.288−3.959) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.922 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Cardiovascular disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.293 (0.978−5.377) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.056 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Chronic liver disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.609 (0.629−10.820) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.186 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Active cancer \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.793 (0.749−4.288) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.190 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Acute kidney injury (on ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.603 (1.030−12.603) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.045 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">SOFA score (on ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.325 (1.159−1.515) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.252 (1.062−1.477) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.008</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_colgroup " 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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead colgroup " colspan="5" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Circulating biomarkers</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">Procalcitonin (on ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.036 (0.763−1.408) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.819 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Calprotectin (on ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.871 (0.530−1.431) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.585 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Lactate (on ICU admission) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.736 (1.470−5.091) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.055 (0.925−4.568) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.077</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">Procalcitonin (on 24 h) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.320 (0.973−1.791) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.074 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Calprotectin (on 24 h) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.280 (0.828−1.979) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.267 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \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">Procalcitonin clearance \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.672 (1.151−2.428) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.007 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.716 (1.090−2.701) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.020</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">Calprotectin clearance \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.372 (1.214−4.633) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.011 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.006 (1.047−3.843) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleBold">0.036</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3569945.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Univariate and multivariate regression analysis for 28-day mortality.</p>" ] ] 6 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:1 [ "Quimica" => "Logit (p) (SEPCART score) = −7.5 + (1.10 × Lactate) + (0.49 × Procalcitonin clearance) + (0.56 × Calprotectin clearance)" ] ] 7 => array:5 [ "identificador" => "eq0010" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:1 [ "Quimica" => "<span class="elsevierStyleItalic">p</span> (probability of 28-day mortality) = [elogit(<span class="elsevierStyleItalic">p</span>)/1 + elogit(<span class="elsevierStyleItalic">p</span>)] (0 < <span class="elsevierStyleItalic">p</span> < 1)" ] ] 8 => array:5 [ "identificador" => "eq0015" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:1 [ "Quimica" => "SEPCART: Sepsis Prognosis Cartagena" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:43 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The third international consensus definitions for sepsis and septic shock (Sepsis-3)" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Singer" 1 => "C.S. Deutschman" 2 => "C.W. Seymour" 3 => "M. Shankar-Hari" 4 => "D. Annane" 5 => "M. Bauer" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1001/jama.2016.0287" "Revista" => array:5 [ "tituloSerie" => "JAMA" "fecha" => "2016" "volumen" => "315" "paginaInicial" => "801" "paginaFinal" => "810" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Incidence and mortality of hospital- and ICU-treated sepsis: results from an updated and expanded systematic review and meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. Fleischmann-Struzek" 1 => "L. Mellhammar" 2 => "N. Rose" 3 => "A. Cassini" 4 => "K.E. Rudd" 5 => "P. Schlattmann" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-020-06151-x" "Revista" => array:6 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2020" "volumen" => "46" "paginaInicial" => "1552" "paginaFinal" => "1562" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32572531" "web" => "Medline" ] ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Intensive care unit scoring systems" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "T.P. Pellathy" 1 => "M.R. Pinsky" 2 => "M. Hravnak" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.4037/ccn2021613" "Revista" => array:6 [ "tituloSerie" => "Crit Care Nurse" "fecha" => "2021" "volumen" => "41" "paginaInicial" => "54" "paginaFinal" => "64" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34333619" "web" => "Medline" ] ] ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Utilidad de la procalcitonina para el diagnóstico de infección en el paciente crítico con cirrosis hepatica [Usefulness of procalcitonin for diagnosing infection in critically ill patients with liver cirrhosis]" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "E. Villarreal" 1 => "K. Vacacela" 2 => "M. Gordon" 3 => "C. Calabuig" 4 => "R. Alonso" 5 => "J. Ruiz" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.medin.2015.02.006" "Revista" => array:7 [ "tituloSerie" => "Med Intensiva" "fecha" => "2016" "volumen" => "40" "numero" => "2" "paginaInicial" => "84" "paginaFinal" => "89" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/25843699" "web" => "Medline" ] ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0025" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "C-reactive protein and procalcitonin during course of sepsis and septic shock" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "T. Schupp" 1 => "K. Weidner" 2 => "J. Rusnak" 3 => "S. Jawhar" 4 => "J. Forner" 5 => "F. Dulatahu" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s11845-023-03385-8" "Revista" => array:5 [ "tituloSerie" => "Ir J Med Sci" "fecha" => "2023" "volumen" => "19" "paginaInicial" => "1" "paginaFinal" => "12" ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0030" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Surviving sepsis campaign: research priorities for sepsis and septic shock" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C.M. Coopersmith" 1 => "D. De Backer" 2 => "C.S. Deutschman" 3 => "R. Ferrer" 4 => "I. Lat" 5 => "F.R. Machado" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-018-5175-z" "Revista" => array:6 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2018" "volumen" => "44" "paginaInicial" => "1400" "paginaFinal" => "1426" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29971592" "web" => "Medline" ] ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0035" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Biomarkers of sepsis: time for a reappraisal" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "C. Pierrakos" 1 => "D. Velissaris" 2 => "M. Bisdorff" 3 => "J.C. Marshall" 4 => "J.L. Vincent" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13054-020-02993-5" "Revista" => array:5 [ "tituloSerie" => "Crit Care" "fecha" => "2020" "volumen" => "24" "paginaInicial" => "287" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32503670" "web" => "Medline" ] ] ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0040" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Identification of p8,14 as a highly abundant heterodimeric calcium binding protein complex of myeloid cells" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "J. Edgeworth" 1 => "M. Gorman" 2 => "R. Bennett" 3 => "P. Freemont" 4 => "N. Hogg" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "J Biol Chem" "fecha" => "1991" "volumen" => "266" "paginaInicial" => "7706" "paginaFinal" => "7713" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/2019594" "web" => "Medline" ] ] ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0045" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Calprotectin: from biomarker to biological function" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "A. Jukic" 1 => "L. Bakiri" 2 => "E.F. Wagner" 3 => "H. Tilg" 4 => "T.E. Adolph" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1136/gutjnl-2021-324855" "Revista" => array:7 [ "tituloSerie" => "Gut" "fecha" => "2021" "volumen" => "70" "numero" => "10" "paginaInicial" => "1978" "paginaFinal" => "1988" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34145045" "web" => "Medline" ] ] ] ] ] ] ] ] 9 => array:3 [ "identificador" => "bib0050" "etiqueta" => "10" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "S100A8/A9 in inflammation" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "S. Wang" 1 => "R. Song" 2 => "Z. Wang" 3 => "Z. Jing" 4 => "S. Wang" 5 => "J. Ma" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3389/fimmu.2018.01298" "Revista" => array:5 [ "tituloSerie" => "Front Immunol" "fecha" => "2018" "volumen" => "9" "paginaInicial" => "1298" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29942307" "web" => "Medline" ] ] ] ] ] ] ] ] 10 => array:3 [ "identificador" => "bib0055" "etiqueta" => "11" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Calprotectin as a diagnostic marker for sepsis: a meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R.Y. Gao" 1 => "H.M. Jia" 2 => "Y.Z. Han" 3 => "B.S. Qian" 4 => "P. You" 5 => "X.K. Zhang" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3389/fcimb.2022.1045636" "Revista" => array:3 [ "tituloSerie" => "Front Cell Infect Microbiol" "fecha" => "2022" "volumen" => "12" ] ] ] ] ] ] 11 => array:3 [ "identificador" => "bib0060" "etiqueta" => "12" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Calprotectin is superior to procalcitonin as a sepsis marker and predictor of 30-day mortality in intensive care patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. Larsson" 1 => "J. Tydén" 2 => "J. Johansson" 3 => "M. Lipcsey" 4 => "M. Bergquist" 5 => "K. Kultima" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1080/00365513.2019.1703216" "Revista" => array:6 [ "tituloSerie" => "Scand J Clin Lab Invest" "fecha" => "2020" "volumen" => "80" "paginaInicial" => "156" "paginaFinal" => "161" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31841042" "web" => "Medline" ] ] ] ] ] ] ] ] 12 => array:3 [ "identificador" => "bib0065" "etiqueta" => "13" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Performance of plasma calprotectin as a biomarker of early sepsis: a pilot study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Simm" 1 => "E. Söderberg" 2 => "A. Larsson" 3 => "M. Castegren" 4 => "T. Nilsen" 5 => "M. Eriksson" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2217/bmm-2016-0032" "Revista" => array:6 [ "tituloSerie" => "Biomark Med" "fecha" => "2016" "volumen" => "10" "paginaInicial" => "811" "paginaFinal" => "818" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27414210" "web" => "Medline" ] ] ] ] ] ] ] ] 13 => array:3 [ "identificador" => "bib0070" "etiqueta" => "14" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A combination of SOFA score and biomarkers gives a better prediction of septic AKI and in-hospital mortality in critically ill surgical patients: a pilot study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C.W. Lee" 1 => "H.W. Kou" 2 => "H.S. Chou" 3 => "H.H. Chou" 4 => "S.F. Huang" 5 => "C.H. Chang" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13017-018-0202-5" "Revista" => array:5 [ "tituloSerie" => "World J Emerg Surg" "fecha" => "2018" "volumen" => "13" "paginaInicial" => "41" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30214469" "web" => "Medline" ] ] ] ] ] ] ] ] 14 => array:3 [ "identificador" => "bib0075" "etiqueta" => "15" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Analysis of calprotectin as an early marker of infections is economically advantageous in intensive care-treated patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. Havelka" 1 => "A.O. Larsson" 2 => "J. Mårtensson" 3 => "M. Bell" 4 => "M. Hultström" 5 => "M. Lipcsey" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3390/biomedicines11082156" "Revista" => array:5 [ "tituloSerie" => "Biomedicines" "fecha" => "2023" "volumen" => "11" "paginaInicial" => "2156" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/37626653" "web" => "Medline" ] ] ] ] ] ] ] ] 15 => array:3 [ "identificador" => "bib0080" "etiqueta" => "16" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. Evans" 1 => "A. Rhodes" 2 => "W. Alhazzani" 3 => "M. Antonelli" 4 => "C.M. Coopersmith" 5 => "C. French" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-021-06506-y" "Revista" => array:6 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2021" "volumen" => "47" "paginaInicial" => "1181" "paginaFinal" => "1247" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34599691" "web" => "Medline" ] ] ] ] ] ] ] ] 16 => array:3 [ "identificador" => "bib0085" "etiqueta" => "17" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "T. Barichello" 1 => "J.S. Generoso" 2 => "M. Singer" 3 => "F. Dal-Pizzol" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13054-021-03862-5" "Revista" => array:4 [ "tituloSerie" => "Crit Care" "fecha" => "2022" "volumen" => "26" "paginaInicial" => "14" ] ] ] ] ] ] 17 => array:3 [ "identificador" => "bib0090" "etiqueta" => "18" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Basal procalcitonin, C-reactive protein, interleukin-6, and presepsin for prediction of mortality in critically ill septic patients: a systematic review and meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "D. Molano-Franco" 1 => "I. Arevalo-Rodriguez" 2 => "A. Muriel" 3 => "L. Del Campo-Albendea" 4 => "S. Fernández-García" 5 => "A. Alvarez-Méndez" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s41512-023-00152-2" "Revista" => array:5 [ "tituloSerie" => "Diagn Progn Res" "fecha" => "2023" "volumen" => "7" "paginaInicial" => "15" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/37537680" "web" => "Medline" ] ] ] ] ] ] ] ] 18 => array:3 [ "identificador" => "bib0095" "etiqueta" => "19" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Assessment of adrenomedullin and proadrenomedullin as predictors of mortality in septic patients: a systematic review and meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "Q. Li" 1 => "B.S. Wang" 2 => "L. Yang" 3 => "C. Peng" 4 => "L.B. Ma" 5 => "C. Chai" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.medin.2017.10.013" "Revista" => array:7 [ "tituloSerie" => "Med Intensiva (Engl Ed)" "fecha" => "2018" "volumen" => "42" "numero" => "7" "paginaInicial" => "416" "paginaFinal" => "424" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29246418" "web" => "Medline" ] ] ] ] ] ] ] ] 19 => array:3 [ "identificador" => "bib0100" "etiqueta" => "20" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Embracing complexity in sepsis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "A.R. Schuurman" 1 => "P.M.A. Sloot" 2 => "W.J. Wiersinga" 3 => "T. van der Poll" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13054-023-04374-0" "Revista" => array:5 [ "tituloSerie" => "Crit Care" "fecha" => "2023" "volumen" => "27" "paginaInicial" => "102" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/36906606" "web" => "Medline" ] ] ] ] ] ] ] ] 20 => array:3 [ "identificador" => "bib0105" "etiqueta" => "21" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Biomarker combination and SOFA score for the prediction of mortality in sepsis and septic shock: a prospective observational study according to the Sepsis-3 definitions" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. Song" 1 => "S. Moon" 2 => "D.W. Park" 3 => "H.J. Cho" 4 => "J.Y. Kim" 5 => "J. Park" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/MD.0000000000020495" "Revista" => array:3 [ "tituloSerie" => "Medicine (Baltimore)" "fecha" => "2020" "volumen" => "99" ] ] ] ] ] ] 21 => array:3 [ "identificador" => "bib0110" "etiqueta" => "22" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "28-day sepsis mortality prediction model from combined serial interleukin-6, lactate, and procalcitonin measurements: a retrospective cohort study" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "Y. Xie" 1 => "D. Zhuang" 2 => "H. Chen" 3 => "S. Zou" 4 => "W. Chen" 5 => "Y. Chen" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s10096-022-04517-1" "Revista" => array:7 [ "tituloSerie" => "Eur J Clin Microbiol Infect Dis" "fecha" => "2023" "volumen" => "42" "numero" => "1" "paginaInicial" => "77" "paginaFinal" => "85" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/36383295" "web" => "Medline" ] ] ] ] ] ] ] ] 22 => array:3 [ "identificador" => "bib0115" "etiqueta" => "23" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lactate, a useful marker for disease mortality and severity but an unreliable marker of tissue hypoxia/hypoperfusion in critically ill patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S. Kushimoto" 1 => "S. Akaishi" 2 => "T. Sato" 3 => "R. Nomura" 4 => "M. Fujita" 5 => "D. Kudo" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1002/ams2.207" "Revista" => array:6 [ "tituloSerie" => "Acute Med Surg" "fecha" => "2016" "volumen" => "3" "paginaInicial" => "293" "paginaFinal" => "297" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29123802" "web" => "Medline" ] ] ] ] ] ] ] ] 23 => array:3 [ "identificador" => "bib0120" "etiqueta" => "24" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prognostic accuracy of the serum lactate level, the SOFA score and the qSOFA score for mortality among adults with Sepsis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "Z. Liu" 1 => "Z. Meng" 2 => "Y. Li" 3 => "J. Zhao" 4 => "S. Wu" 5 => "S. Gou" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13049-019-0609-3" "Revista" => array:5 [ "tituloSerie" => "Scand J Trauma Resusc Emerg Med" "fecha" => "2019" "volumen" => "27" "paginaInicial" => "51" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31039813" "web" => "Medline" ] ] ] ] ] ] ] ] 24 => array:3 [ "identificador" => "bib0125" "etiqueta" => "25" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Should serial monitoring of procalcitonin be done routinely in critically ill patients of ICU: a systematic review and meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "R. Patnaik" 1 => "A. Azim" 2 => "P. Mishra" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.4103/joacp.JOACP_388_19" "Revista" => array:6 [ "tituloSerie" => "J Anaesthesiol Clin Pharmacol" "fecha" => "2020" "volumen" => "36" "paginaInicial" => "458" "paginaFinal" => "464" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33840923" "web" => "Medline" ] ] ] ] ] ] ] ] 25 => array:3 [ "identificador" => "bib0130" "etiqueta" => "26" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Association of serum calprotectin concentrations with mortality in critically ill and septic patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "T.H. Wirtz" 1 => "L. Buendgens" 2 => "R. Weiskirchen" 3 => "S.H. Loosen" 4 => "N. Haehnsen" 5 => "T. Puengel" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3390/diagnostics10110990" "Revista" => array:5 [ "tituloSerie" => "Diagnostics (Basel)" "fecha" => "2020" "volumen" => "10" "paginaInicial" => "990" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33238644" "web" => "Medline" ] ] ] ] ] ] ] ] 26 => array:3 [ "identificador" => "bib0135" "etiqueta" => "27" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Diagnostic and prognostic value of myeloid-related protein complex 8/14 for sepsis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "S. Gao" 1 => "Y. Yang" 2 => "Y. Fu" 3 => "W. Guo" 4 => "G. Liu" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ajem.2015.06.025" "Revista" => array:6 [ "tituloSerie" => "Am J Emerg Med" "fecha" => "2015" "volumen" => "33" "paginaInicial" => "1278" "paginaFinal" => "1282" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26206243" "web" => "Medline" ] ] ] ] ] ] ] ] 27 => array:3 [ "identificador" => "bib0140" "etiqueta" => "28" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "High plasma level of S100A8/S100A9 and S100A12 at admission indicates a higher risk of death in septic shock patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. Dubois" 1 => "D. Marcé" 2 => "V. Faivre" 3 => "A.C. Lukaszewicz" 4 => "C. Junot" 5 => "F. Fenaille" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41598-019-52184-8" "Revista" => array:4 [ "tituloSerie" => "Sci Rep" "fecha" => "2019" "volumen" => "9" "paginaInicial" => "15660" ] ] ] ] ] ] 28 => array:3 [ "identificador" => "bib0145" "etiqueta" => "29" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prognostic performance of pancreatic stone protein in critically ill patients with sepsis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. García de Guadiana-Romualdo" 1 => "M.D. Albaladejo-Otón" 2 => "M. Berger" 3 => "E. Jiménez-Santos" 4 => "R. Jiménez-Sánchez" 5 => "P. Esteban-Torrella" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.2217/bmm-2019-0174" "Revista" => array:6 [ "tituloSerie" => "Biomark Med" "fecha" => "2019" "volumen" => "13" "paginaInicial" => "1469" "paginaFinal" => "1480" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31621373" "web" => "Medline" ] ] ] ] ] ] ] ] 29 => array:3 [ "identificador" => "bib0150" "etiqueta" => "30" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prognostic value of variations in serum biomarkers and prognostic scores values between admission and second day in intensive care unit septic patients" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.J. Rios-Toro" 1 => "M.D. Pola-Gallego de Guzman" 2 => "M. Guerrero-Marin" 3 => "D. Rodriguez-Rubio" 4 => "M.I. Ruiz-Garcia" 5 => "E. Aguilar-Alonso Sr." ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.7759/cureus.16472" "Revista" => array:4 [ "tituloSerie" => "Cureus" "fecha" => "2021" "volumen" => "13" "numero" => "7" ] ] ] ] ] ] 30 => array:3 [ "identificador" => "bib0155" "etiqueta" => "31" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Serial procalcitonin predicts mortality in severe sepsis patients: results from the Multicenter Procalcitonin MOnitoring SEpsis (MOSES) study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "P. Schuetz" 1 => "R. Birkhahn" 2 => "R. Sherwin" 3 => "A.E. Jones" 4 => "A. Singer" 5 => "J.A. Kline" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/CCM.0000000000002321" "Revista" => array:7 [ "tituloSerie" => "Crit Care Med" "fecha" => "2017" "volumen" => "45" "numero" => "5" "paginaInicial" => "781" "paginaFinal" => "789" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28257335" "web" => "Medline" ] ] ] ] ] ] ] ] 31 => array:3 [ "identificador" => "bib0160" "etiqueta" => "32" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Changes in heparin-binding protein, procalcitonin, and C-reactive protein within the first 72 hours predict 28-day mortality in patients admitted to the intensive care unit with septic shock" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "H. Xue" 1 => "F. Yu" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.12659/MSM.938538" "Revista" => array:3 [ "tituloSerie" => "Med Sci Monit" "fecha" => "2023" "volumen" => "29" ] ] ] ] ] ] 32 => array:3 [ "identificador" => "bib0165" "etiqueta" => "33" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prognostic value of lipopolysaccharide binding protein and procalcitonin in patients with severe sepsis and septic shock admitted to intensive care" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L.M. García de Guadiana-Romualdo" 1 => "S. Rebollo-Acebes" 2 => "P. Esteban-Torrella" 3 => "R. Jiménez-Sánchez" 4 => "A. Hernando-Holgado" 5 => "A. Ortín-Freire" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.medin.2014.04.005" "Revista" => array:7 [ "tituloSerie" => "Med Intensiva" "fecha" => "2015" "volumen" => "39" "numero" => "4" "paginaInicial" => "207" "paginaFinal" => "212" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24953001" "web" => "Medline" ] ] ] ] ] ] ] ] 33 => array:3 [ "identificador" => "bib0170" "etiqueta" => "34" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Combining blood-based biomarkers to predict mortality of sepsis at arrival at the emergency department" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "Y. Xie" 1 => "B. Li" 2 => "Y. Lin" 3 => "F. Shi" 4 => "W. Chen" 5 => "W. Wu" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.12659/MSM.929527" "Revista" => array:3 [ "tituloSerie" => "Med Sci Monit" "fecha" => "2021" "volumen" => "27" ] ] ] ] ] ] 34 => array:3 [ "identificador" => "bib0175" "etiqueta" => "35" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The value of blood lactate kinetics in critically ill patients: a systematic review" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "J.L. Vincent" 1 => "A.Q.E. Silva" 2 => "L. Couto Jr." 3 => "F.S. Taccone" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s13054-016-1403-5" "Revista" => array:5 [ "tituloSerie" => "Crit Care" "fecha" => "2016" "volumen" => "20" "paginaInicial" => "257" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27520452" "web" => "Medline" ] ] ] ] ] ] ] ] 35 => array:3 [ "identificador" => "bib0180" "etiqueta" => "36" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lactate level versus lactate clearance for predicting mortality in patients with septic shock defined by sepsis-3" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.M. Ryoo" 1 => "J. Lee" 2 => "Y.S. Lee" 3 => "J.H. Lee" 4 => "K.S. Lim" 5 => "J.W. Huh" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/CCM.0000000000003030" "Revista" => array:7 [ "tituloSerie" => "Crit Care Med" "fecha" => "2018" "volumen" => "46" "numero" => "6" "paginaInicial" => "e489" "paginaFinal" => "e495" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29432347" "web" => "Medline" ] ] ] ] ] ] ] ] 36 => array:3 [ "identificador" => "bib0185" "etiqueta" => "37" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Early lactate clearance-guided therapy in patients with sepsis: a meta-analysis with trial sequential analysis of randomized controlled trials" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "W.J. Gu" 1 => "Z. Zhang" 2 => "J. Bakker" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-015-3955-2" "Revista" => array:7 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2015" "volumen" => "41" "numero" => "10" "paginaInicial" => "1862" "paginaFinal" => "1863" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26154408" "web" => "Medline" ] ] ] ] ] ] ] ] 37 => array:3 [ "identificador" => "bib0190" "etiqueta" => "38" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Relative efficacy and safety of early lactate clearance-guided therapy resuscitation in patients with sepsis: a meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "J. Pan" 1 => "M. Peng" 2 => "C. Liao" 3 => "X. Hu" 4 => "A. Wang" 5 => "X. Li" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/MD.0000000000014453" "Revista" => array:4 [ "tituloSerie" => "Medicine (Baltimore)" "fecha" => "2019" "volumen" => "98" "numero" => "8" ] ] ] ] ] ] 38 => array:3 [ "identificador" => "bib0195" "etiqueta" => "39" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The ten pitfalls of lactate clearance in sepsis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "G. Hernandez" 1 => "R. Bellomo" 2 => "J. Bakker" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1007/s00134-018-5213-x" "Revista" => array:6 [ "tituloSerie" => "Intensive Care Med" "fecha" => "2019" "volumen" => "45" "numero" => "1" "paginaInicial" => "82" "paginaFinal" => "85" ] ] ] ] ] ] 39 => array:3 [ "identificador" => "bib0200" "etiqueta" => "40" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The combination of lactate level, lactate clearance and APACHE II score better predicts short-term outcomes in critically Ill patients: a retrospective cohort study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "Y. Cao" 1 => "S. Yao" 2 => "J. Shang" 3 => "F. Ping" 4 => "Q. Tan" 5 => "Z. Tian" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s12871-022-01878-0" "Revista" => array:5 [ "tituloSerie" => "BMC Anesthesiol" "fecha" => "2022" "volumen" => "22" "paginaInicial" => "382" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/36482299" "web" => "Medline" ] ] ] ] ] ] ] ] 40 => array:3 [ "identificador" => "bib0205" "etiqueta" => "41" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Initial lactate levels versus lactate clearance for predicting mortality in sepsis: a prospective observational analytical study" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "M.I. Lestari" 1 => "R. Sedono" 2 => "Zulkifli" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:6 [ "tituloSerie" => "J Pak Med Assoc" "fecha" => "2021" "volumen" => "71(Suppl 2)" "numero" => "2" "paginaInicial" => "S25" "paginaFinal" => "S29" ] ] ] ] ] ] 41 => array:3 [ "identificador" => "bib0210" "etiqueta" => "42" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pre-analytical and analytical confounders of serum calprotectin as a biomarker in rheumatoid arthritis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "L. Van Hoovels" 1 => "B. Vander Cruyssen" 2 => "L. Bogaert" 3 => "S. Van den Bremt" 4 => "X. Bossuyt" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1515/cclm-2019-0508" "Revista" => array:7 [ "tituloSerie" => "Clin Chem Lab Med" "fecha" => "2019" "volumen" => "58" "numero" => "1" "paginaInicial" => "40" "paginaFinal" => "49" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31665107" "web" => "Medline" ] ] ] ] ] ] ] ] 42 => array:3 [ "identificador" => "bib0215" "etiqueta" => "43" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Circulating calprotectin as biomarker in neutrophil-related inflammation: pre-analytical recommendations and reference values according to sample type" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Mylemans" 1 => "L. Nevejan" 2 => "S. Van Den Bremt" 3 => "M. Stubbe" 4 => "B.V. Cruyssen" 5 => "C. Moulakakis" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.cca.2021.02.022" "Revista" => array:6 [ "tituloSerie" => "Clin Chim Acta" "fecha" => "2021" "volumen" => "517" "paginaInicial" => "149" "paginaFinal" => "155" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33689693" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/21735727/unassign/S2173572724001383/v1_202406161028/en/main.assets" "Apartado" => null "PDF" => "https://static.elsevier.es/multimedia/21735727/unassign/S2173572724001383/v1_202406161028/en/main.pdf?idApp=WMIE&text.app=https://medintensiva.org/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572724001383?idApp=WMIE" ]
Journal Information
Original article
Available online 16 June 2024
Mortality prediction model from combined serial lactate, procalcitonin and calprotectin levels in critically ill patients with sepsis: A retrospective study according to Sepsis-3 definition
Un modelo de predicción de mortalidad basado en la combinación de lactato, procalcitonina y calprotectina en pacientes críticos con sepsis: un estudio retrospectivo de acuerdo a la definición Sepsis-3