- Email: [email protected]
Diagnostic accuracy of sTREM-1 to identify infection in critically ill patients with systemic inflammatory response syndrome
Clinical Biochemistry 43 (2010) 720–724
Contents lists available at ScienceDirect
Clinical Biochemistry j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / c l i n b i o c h e m
Diagnostic accuracy of sTREM-1 to identify infection in critically ill patients with systemic inflammatory response syndrome Jaime Latour-Pérez a,⁎, Adoración Alcalá-López a, Miguel-Ángel García-García b, José F. Sánchez-Hernández c, Carmen Abad-Terrado a, José A. Viedma-Contreras c, Mar Masiá d, Matilde González-Tejera e, David Arizo-León b, María-Jesús Broch Porcar b, Fernando Bonilla-Rovira e, Félix Gutiérrez d a
Hospital General Universitario de Elche, Servicio de Medicina Intensiva, Camí Vell de l´almàssera 11, 03203 Elche, Spain Hospital de Sagunto, Servicio de Medicina Intensiva, Ramón y Cajal, 46, 46520 Sagunto, Spain c Hospital General Universitario de Elche, Servicio de Bioquímica, Camí Vell de l´almàssera 11, 03203 Elche, Spain d Hospital General Universitario de Elche, Unidad de Enfermedades Infecciosas, Camí Vell de l´almàssera 11, 03203 Elche, Spain e Hospital General Universitario de Elche, Departamento de Urgencias, Camí Vell de l´almàssera 11, 03203 Elche, Spain b
a r t i c l e
i n f o
Article history: Received 23 December 2009 Received in revised form 2 March 2010 Accepted 4 March 2010 Available online 17 March 2010 Keywords: Sepsis Systemic inflammatory response syndrome sTREM-1 Soluble triggering receptor expressed on myeloid cells-1 Sensitivity and specificity ROC curve
a b s t r a c t Objectives: To assess the accuracy of plasma levels of soluble Triggering Receptor Expressed on Myeloid cells (sTREM)-1 to diagnose infection in critical patients with systemic inflammatory response syndrome (SIRS). Design and methods: We prospectively studied 114 patients with SIRS criteria. The patients’ plasma levels of sTREM-1 were measured within 24 h of admission to the intensive care unit. The final diagnosis of infection was made independently by two investigators, who were blinded to the levels of sTREM-1. Results: The area under the ROC curve of sTREM-1 for the diagnosis of sepsis was 0.62 (95% confidence interval [95% CI] 0.51–0.72). The diagnostic odds ratio of sTREM-1 after adjusting for the Infection Probability Score and procalcitonin plasma levels was 1.81 (95% CI 0.66–4.98; p = 0.2508). Conclusions: In critical patients admitted with SIRS, sTREM-1 has poor discriminative power to identify patients with infection, and sTREM-1 levels do not add diagnostic information to that provided by other routinely available clinical tests. © 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction The diagnosis of sepsis is based on the presence of systemic inflammatory response syndrome (SIRS) and the clinical suspicion of infection [1]. Unfortunately, microbiological data are late and insensitive, while classic signs of infection (such as fever and leukocytosis) are often present in patients with non-infectious causes of SIRS such as trauma, pancreatitis or stroke. During the last few years, different biological markers (such as Creactive protein [CRP], procalcitonin [PCT], interleukin-6, interleukin8 and C3a) have been proposed for the diagnosis of infection; however, none of them has proved to be sufficiently sensitive and specific [2–4].
Triggering receptor expressed on myeloid cells (TREM)-1 is a recently discovered cell-surface molecule that is present on neutrophils and mature monocytes and is actively expressed in response to infection by bacteria or fungi [5]. This upregulation is accompanied by an increased release of its soluble form (sTREM-1) [6]. The value of plasma levels of sTREM-1 for diagnosing infection has been addressed in several studies, with inconsistent results [6–14]. Moreover, there is much uncertainty about the incremental sensitivity and specificity of sTREM-1 compared with other tests that are more easily performed. It seems appropriate, therefore, to assess the diagnostic accuracy of this biomarker in a representative group of critical patients admitted to the intensive care unit. Methods
⁎ Corresponding author. Fax: +34 966 679 108. E-mail addresses: [email protected] (J. Latour-Pérez), [email protected] (A. Alcalá-López), [email protected] (M.-Á. García-García), [email protected] (J.F. Sánchez-Hernández), [email protected] (C. Abad-Terrado), [email protected] (J.A. Viedma-Contreras), [email protected] (M. Masiá), [email protected] (M. González-Tejera), [email protected] (D. Arizo-León), [email protected] (M.-J.B. Porcar), [email protected] (F. Bonilla-Rovira), [email protected] (F. Gutiérrez).
Objectives The main goal of the study was to estimate the accuracy of sTREM-1 plasma levels in the diagnosis of infection in critical patients with SIRS. The secondary goal was to assess the added value of sTREM-1 to clinical and laboratory data usually available in hospital settings, such as the Infection Probability Score (IPS) [15] or PCT serum levels.
0009-9120/$ – see front matter © 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.clinbiochem.2010.03.001
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
Participants All patients older than 18 years admitted into two general intensive care units through the study period with a diagnosis of SIRS, according to the criteria of the ACCP/SCCM Consensus Conference [1], were suitable for inclusion in the study. However, the ultimate inclusion of patients in the study required the availability of one of the researchers; therefore, the patients included in the study were not strictly consecutive. Daily, one of the clinical investigators reviewed all patients admitted to the Intensive Care Unit using a screening form to identify those patients who met the inclusion criteria. After obtaining informed consent from the patient or his/her relatives, one serum sample was obtained as soon as possible after detection of SIRS, and the sample was frozen at −80 °C until determination of sTREM-1 levels. Patients who did not sign the informed consent form and those from whom a serum sample could not be obtained within the first 24 h after the onset of SIRS were excluded from the study.
721
parametric ROC curve (AUC) along with its 95% confidence intervals. In the case of continuous variables, the sensitivity, specificity and likelihood ratios were calculated at the optimal cutoff point of the ROC curve. Finally, in order to assess the independent diagnostic value of sTREM-1 (i.e., its added value), we built a multiple logistic regression model that included the presence of infection as the outcome variable and sTREM-1 as the main predictor. Thereafter, the routinely available diagnostic tests (e.g., IPS and PCT) were added to the model (one each time) as potential confounding variables, and the crude and adjusted sTREM-1 diagnostic odds ratios were compared. Ethical considerations The study was approved by the corresponding ethics committees. Results Study population
Gold standard The final diagnosis of infection was made by two investigators who had access to all patient clinical data, including microbiological results and diagnostic imaging, but without knowledge of the levels of sTREM-1. The origin of the final infection was established following the criteria of the International Sepsis Forum Consensus Conference on Definitions of Infection in the Intensive Care Unit [16]. Any disagreements between the two investigators were resolved by consensus. Variables In addition to the final diagnosis and sTREM-1 plasma levels, other variables were collected prospectively, including biological data (blood count, CRP, PCT, lactate), the Sepsis-related Organ Failure Assessment (SOFA) score on admission [17], IPS [15], the Simplified Acute Physiological Score-III (SAPS-3) on admission[18], and variables related to the spectrum of patients (age, sex, history of immunodeficiency, and so on).
Due to logistic restrictions (non-availability of reagents), the patients were recruited during two periods, the first from October 2007 to April 2008 and the second from November 2008 to March 2009. During the enrollment period, 144 patients presented SIRS criteria on admission to the ICU. This figure represents 28% of all noncoronary admissions during the study period. Thirty patients were further excluded due to age less than 18 years (5 patients), missing sTREM-1 values during the first 24 h of admission (24 patients) and withdrawal of informed consent (1 patient). Therefore, 114 patients were finally analyzed. Forty-two patients (37% of the study population) were identified as having non-infectious SIRS, 5 (4%) as having sepsis, 24 (21%) as having severe sepsis, and 43 (38%) as having septic shock (Table 1, Fig. 1). Eighty-three percent of sepsis were community acquired, whereas the remaining 17% were classified as nosocomial. The most prevalent source of infection was respiratory (40%), followed by abdominal-pelvic (21%) and urinary (12.5%). The most frequent causes of non-infectious SIRS were acute respiratory failure without signs of infection (29%), post-cardiac arrest status (14%), acute heart failure (12%) and non-septic shock (10%).
Test methods Diagnostic value of sTREM-1 serum levels Plasma levels of sTREM-1 were determined by sandwich type ELISA using a commercial kit (R & D Systems, Inc., Minneapolis, MN). The concentration of sTREM-1 was calculated from the calibration curve of reference standards included in the kit. The range of the assay was 0–4000 pg/mL. Determinations were performed in duplicate, and the results were averaged. The intra- and inter-assay coefficients of variation were 5% and 10%, respectively. An immunochromatographic test was used for the semiquantitative determination of the plasma procalcitonin (BRAHMS PCT-Q, Berlin, Germany); the sensitivity of the method was 0.5 ng/mL. C-Reactive protein levels were measured by an automated particle-enhanced turbidimetric immunoassay using the Olympus CRP latex kit (OSR 6299).
The sTREM-1 levels were higher in patients with infection than in patients with non-infectious SIRS (median 420.5 versus 326.5 pg/mL; p = 0.0406). However, there was a huge overlap between the sTREM1 distributions in patients with infectious and non-infectious SIRS (Fig. 1). This overlap is reflected in the ROC curve, with an AUC of 0.62 (95% CI 0.51 to 0.72). This figure compares disadvantageously with the AUCs of other classical tests, such as CRP, PCT and IPS (Fig. 2, Table 2). The AUC was similar (close to 0.50) in each of the subgroups analyzed (age, sex, clinical suspicion of infection, immunity status or severity of disease). Added diagnostic value of sTREM-1
Statistical analysis Since most of the continuous variables did not follow a normal distribution, the statistical analyses were performed using nonparametric methods (Mann–Whitney, Kruskal–Wallis and nonparametric linear regression). The categorical variables were analyzed using the chi-squared test for 2 × 2 tables. For the ordinal variables with more than two categories, a chi-squared test for trend was performed. All hypothesis tests were two-tailed. The diagnostic accuracy of different variables was assessed by estimating their sensitivity, specificity, and area under the non-
After adjusting by logistic regression analysis to IPS (two categories) and PCT (two categories), the diagnostic odds ratio of sTREM-1 was 1.81 (95% CI 0.66–4.98; p = 0.2508). This result indicates that sTREM-1 levels did not add significant diagnostic information to that offered by these typically available tests (Table 3). Variables associated with sTREM-1 Plasma levels of sTREM-1 were positively correlated with hospital mortality (p = 0.0013) and other severity of illness indexes such as
722
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
Table 1 Study population. Variable
Sepsis (n = 72)
No sepsis (n = 42)
p
Gender: women, n (percent) Age: median (percentile 25–75) Clinical suspicion of infection: n (percent) Fever/hypothermia: n (percent) Tachycardia: n (percent) Tachypnea: n (percent) Leukocytosis/leukopenia: n (percent) Hypo-perfusion: n (percent) Organ failure: n (percent) MODS: n (percent) Shock: n (percent) Hospital mortality: n (percent) SAPS 3: median (percentile 25–75) SOFA: median (percentile 25–75) IPS: median (percentile 25–75) sTREM-1: median (percentile 25–75) PCT: ≤0.5 ng/mL N0.5 b 2 ng/mL N2 b 10 ng/mL N= 10 ng/mL CRP: median (percentile 25–75) mg/mL Lactate: median (percentile 25–75) mmol/L
30 (41.7%) 68 (58–75) 69 (95.8%) 39 (54.2%) 60 (62.5%) 60 (64.5%) 61 (67.8%) 44 (62.0%) 65 (90.3%) 46 (65.7%) 43 (63.2%) 27 (37.5%) 71 (58–84) 8 (5–11) 18 (16–20) 420.5 (265–694.5) 17 (27.4%) 14 (22.6%) 7 (11.3%) 24 (38.7%) 158 (79–313) 2.3 (1.5–4.3)
15 (35.7%) 69.5 (58–76) 16 (38.1%) 11 (26.2%) 12 (66.7%) 12 (57.1%) 10 (43.5%) 17 (44.7%) 27 (65.9%) 14 (34.2%) 4 (10.0%) 15 (35.7%) 63.5 (52–73) 6 (3–8) 14 (10–17) 326.5 (231–453) 30 (88.2%) 3 (8.8%) 1 (2.9%) 0 (0%) 41 (14.5–113) 1.6 (1.1–2.4)
0.5305 0.7576 b 0.0001 0.0037 0.7366 0.5270 0.0314 0.0841 0.0013 0.0013 b 0.0001 0.8488 0.0139 0.0097 0.0003 0.0406 b 0.0001
b 0.0001 0.0031
Abbreviations: CRP, C-reactive protein; IPS, infection probability score; MODS, multi-organ dysfunction syndrome; PCT, procalcitonin; SAPS, simplified acute physiology score; SOFA, sepsis-related organ failure assessment score; sTREM-1, soluble triggering receptor on myeloid cells-1.
PCT, CRP, IPS, lactate, SAPS-3 or SOFA (Table 4). Indeed, sTREM-1 levels showed a moderate discriminative power to identify patients with Multiple Organ Dysfunction Syndrome (AUC 0.77, 95% CI 0.68– 0.86) and patients who did not survive to hospitalization (AUC 0.68, 95% CI 0.58–0.78). The hospital mortality of patients with positive or negative results of sTREM-1 was 50% and 29%, respectively.
probability after a positive test (sTREM-1 greater than 463.2 pg/mL) increases up to 80%, whereas after a negative test this probability is reduced to 53%. Moreover, sTREM-1 levels did not add diagnostic information to that provided by other usually available tests, such as the IPS, CRP or the PCT levels. Consequently, it would probably be of limited usefulness to include sTREM-1 levels in a panel of biomarkers for the diagnosis of sepsis that already included PCT and CRP.
Discussion Validity of the study Summary of results The study results show that in critically ill patients with SIRS, sTREM-1 plasma levels have a low power to discriminate between patients with or without infection. Given the heterogeneity of the sepsis processes and the different evolution times of the included patients, it would not necessarily be expected for a particular biomarker to have perfect sensitivity and specificity. However, our study showed that the sTREM-1 levels had little effect on the probability of sepsis. For example, for a pre-test probability of infection of 63% (similar to our prevalence of infection), the revised
Fig. 1. Study population (Box and whisker plot). The central “box” represents the first and third quartiles with the median between them marked with a diamond, with the minimum as the origin of the leading “whisker” and with the maximum as the limit of the trailing “whisker”.
Our study had some limitations. First of all, an imperfect gold standard (expert criteria) was used for the diagnosis of infection. Consequently, despite efforts to apply explicit criteria for diagnosis [16], some degree of misclassification, and hence a sub-estimation of
Fig. 2. ROC curves for the diagnosis of infection.
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
723
Table 2 Comparative accuracy of diagnostic tests. Variable
AUC (95% CI)
Cutpoint
Sensitivity (95% CI)
Specificity (95% CI)
Positive predictive value (95% CI)
Negative predictive value (95% CI)
sTREM-1 PCT CRP Lactate IPS
0.62 0.83 0.75 0.67 0.70
463.2 pg/mL ≥0.5 ng/mL ≥94.5 mg/L ≥2.21 mmol/L ≥15
0.49 0.73 0.72 0.55 0.82
0.79 0.88 0.73 0.74 0.54
0.80 0.92 0.82 0.80 0.75
0.47 0.64 0.60 0.47 0.63
(0.51–0.72) (0.76–0.91) (0.66–0.85) (0.57–0.78) (0.60–0.81)
(0.37–0.61) (0.60–0.83) (0.60–0.82) (0.43–0.67) (0.71–0.90)
(0.63–0.90) (0.73–0.97) (0.57–0.86) (0.57–0.87) (0.37–0.69)
(0.65–0.90) (0.80–0.98) (0.70–0.91) (0.66–0.90) (0.64–0.84)
(0.35–0.59) (0.49–0.77) (0.45–0.74) (0.34–0.60) (0.45–0.79)
Abbreviations: CRP, C-reactive protein; IPS, infection probability score; PCT, procalcitonin; SAPS, simplified acute physiology score; sTREM-1, soluble triggering receptor on myeloid cells-1.
Table 3 Incremental diagnostic value of sTREM-1.
Consistency with other studies
Variables controlled
Adjusted DOR (95% CI)
p
None (crude odds ratio) CRP (2 categories) IPS (2 categories) PCT (2 categories) IPS + PCT (2 categories) PCT (2 categories) + PCR (2 categories)
3.47 2.11 2.40 2.46 1.81 1.70
0.0051 0.1242 0.0638 0.0655 0.2508 0.3111
(1.45–8.28) (0.81–5.47) (0.95–6.05) (0.94–6.39) (0.66–4.98) (0,61–4.75)
Abbreviations: CRP, C-reactive protein; DOR, diagnostic odds ratio; IPS, infection probability score; PCT, procalcitonin.
the diagnostic accuracy of sTREM-1, could have occurred. Nevertheless, the AUC of other established biomarkers, like PCT or CRP, was similar to that reported in other studies, suggesting that the magnitude of this potential bias was not substantial. Given the non-consecutive recruitment and the low prevalence of sepsis in the study, the issue of selection bias must be considered. However some study findings argue against this possibility. First, the relative prevalence of the infection sources and severity of illness was similar to other epidemiologic studies in sepsis [19–22]. Second, the diagnostic accuracy of other tests such as PCT and PCR was consistent with the published literature [3,4]. Third, recruitment was performed using a prospectively designed screening instrument that required the review of inclusion and exclusion criteria for each patient remaining in ICU, so that the final inclusion in the study was independent of the a priori likelihood of infection. The possibility of ascertainment bias, another important source of error in diagnostic evaluations, can also be disregarded, since the determination of sTREM-1 was deferred so that neither the clinical investigators that established the final diagnostic knew the test results, nor did the researchers that performed the biochemical analyses know the final diagnosis of the patient. Certainly, the researchers responsible for the final diagnosis were not blinded to the levels of other biomarkers such as PCT and PCR. Therefore, it could be argued that the diagnostic accuracy of these biomarkers could have been favored as compared with sTREM-1. This possibility seems, however, unlikely, since—as noted previously—the AUCs of PCT and PCR were similar to those published in other studies.
Table 4 Variables related to sTREM-1. Variables
Kendall's Tau
p
PCT CRP IPS lactate SAPS-3 SOFA
0.2916 0.1985 0.1693 0.2898 0.3554 0.3541
0.0001 0.0019 0.0108 b0.0001 b0.0001 b0.0001
Abbreviations: PCT, procalcitonin; CRP, C-reactive protein; IPS, infection probability score; SAPS-3, simplified acute physiology score-3; SOFA, sepsis-related organ failure assessment score; sTREM-1, soluble triggering receptor on myeloid cells-1.
The accuracy of sTREM-1 plasma levels for the diagnosis of infection has been addressed in several studies [6–14] with conflicting results. The causes of this heterogeneity are not straightforward. Some plausible sources are the use of different laboratory techniques for the measurement of sTREM-1[7], differences in the spectrum of patients and different study designs (case-control versus cohort-transversal design [23]). Furthermore, several previous studies have suggested that sTREM-1 is a marker of the intensity of the SIRS [10,14,24,25]. Indeed, if patients with sepsis included in the study had a higher level of severity, higher sTREM-1 levels would be expected in patients with sepsis, which could be wrongly attributed to infection when in fact it is due to the different severity of SIRS (confounding by severity). Our results support this hypothesis. Conclusions We conclude that in critical patients admitted with SIRS, sTREM-1 levels are positively correlated with disease severity and organ dysfunction. The discriminative power of serum sTREM-1 levels is poor, and sTREM-1 levels do not add diagnostic information to that provided by routine clinical tests. Acknowledgments We are grateful to the medical and nursing staff of the Biochemistry Departments of the participating hospitals for their support in the processing of blood samples. This study was supported by a grant from the Fondo de Investigación Sanitaria (FIS) PI-060457 and by an award from Brahms Inc. and the Spanish Society of Intensive Care Medicine (SEMICYUC). References [1] Bone RC, Sibbald WJ, Sprung CL. The ACCP-SCCM consensus conference on sepsis and organ failure. Chest 1992;101:1481–3. [2] Selberg O, Hecker H, Martin M, Klos A, Bautsch W, Kohl J. Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin6. Crit Care Med 2000;28:2793–8. [3] Tang BM, Eslick GD, Craig JC, McLean AS. Accuracy of procalcitonin for sepsis diagnosis in critically ill patients: systematic review and meta-analysis. Lancet Infect Dis 2007;7:210–7. [4] Uzzan B, Cohen R, Nicolas P, Cucherat M, Perret GY. Procalcitonin as a diagnostic test for sepsis in critically ill adults and after surgery or trauma: a systematic review and meta-analysis. Crit Care Med 2006;34:1996–2003. [5] Bouchon A, Facchetti F, Weigand MA, Colonna M. TREM-1 amplifies inflammation and is a crucial mediator of septic shock. Nature 2001;410:1103–7. [6] Gibot S, Massin F. Soluble form of the triggering receptor expressed on myeloid cells 1: an anti-inflammatory mediator? Intensive Care Med 2006;32:185–7. [7] Gibot S, Kolopp-Sarda MN, Bene MC, Cravoisy A, Levy B, Faure GC, et al . Plasma level of a triggering receptor expressed on myeloid cells-1: its diagnostic accuracy in patients with suspected sepsis. Ann Intern Med 2004;141:9–15. [8] Phua J, Koay ES, Zhang D, Tai LK, Boo XL, Lim KC, et al . Soluble triggering receptor expressed on myeloid cells-1 in acute respiratory infections. Eur Respir J 2006;28: 695–702. [9] Kofoed K, Andersen O, Kronborg G, Tvede M, Petersen J, Eugen-Olsen J, et al . Use of plasma C-reactive protein, procalcitonin, neutrophils, macrophage migration
724
[10]
[11]
[12]
[13]
[14]
[15]
[16] [17]
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724 inhibitory factor, soluble urokinase-type plasminogen activator receptor, and soluble triggering receptor expressed on myeloid cells-1 in combination to diagnose infections: a prospective study. Crit Care 2007;11:R38. Yasuda T, Takeyama Y, Ueda T, Shinzeki M, Sawa H, Takahiro N, et al . Increased levels of soluble triggering receptor expressed on myeloid cells-1 in patients with acute pancreatitis. Crit Care Med 2008;36:2048–53. Bopp C, Hofer S, Bouchon A, Zimmermann JB, Martin E, Weigand MA. Soluble TREM-1 is not suitable for distinguishing between systemic inflammatory response syndrome and sepsis survivors and nonsurvivors in the early stage of acute inflammation. Eur J Anaesthesiol 2009;26:504–7. Carrol ED, Mankhambo LA, Jeffers G, Parker D, Guiver M, Newland P, et al . The diagnostic and prognostic accuracy of five markers of serious bacterial infection in Malawian children with signs of severe infection. PLoS One 2009;4:e6621. Jiyong J, Tiancha H, Wei C, Huahao S. Diagnostic value of the soluble triggering receptor expressed on myeloid cells-1 in bacterial infection: a meta-analysis. Intensive Care Med 2009;35:587–95. Park JJ, Cheon JH, Kim BY, Kim DH, Kim ES, Kim TI, et al . Correlation of serumsoluble triggering receptor expressed on myeloid cells-1 with clinical disease activity in inflammatory bowel disease. Dig Dis Sci 2009;54:1525–31. Peres Bota D, Melot C, Lopes Ferreira F, Vincent JL. Infection probability score (IPS): a method to help assess the probability of infection in critically ill patients. Crit Care Med 2003;31:2579–84. Calandra T, Cohen J. The international sepsis forum consensus conference on definitions of infection in the intensive care unit. Crit Care Med 2005;33:1538–48. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, et al . The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
of the European Society of Intensive Care Medicine. Intensive. Care Med 1996;22: 707–10. Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, et al . SAPS 3— From evaluation of the patient to evaluation of the intensive care unit: Part 2. Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med 2005;31:1345–55. Alberti C, Brun-Buisson C, Burchardi H, Martin C, Goodman S, Artigas A, et al . Epidemiology of sepsis and infection in ICU patients from an international multicentre cohort study. Intensive Care Med 2002;28:108–21. Esteban A, Frutos-Vivar F, Ferguson ND, Penuelas O, Lorente JA, Gordo F, et al . Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med 2007;35:1284–9. Vincent JL, Rello J, Marshall J, Silva E, Anzueto A, Martin CD, et al . International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009;302:2323–9. Vincent JL, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, et al . Sepsis in European intensive care units: results of the SOAP study. Crit Care Med 2006;34: 344–53. Lijmer JG, Mol BW, Heisterkamp S, Bonsel GJ, Prins MH, van der Meulen JH, et al . Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 1999;282:1061–6. Dimopoulou I, Orfanos SE, Pelekanou A, Kotanidou A, Livaditi O, Augustatou C, et al. Serum of patients with septic shock stimulates the expression of Trem-1 on U937 monocytes. Inflamm Res 2009;58:127–32. Latour-Perez J, Alcala-Lopez A, Garcia-Garcia MA, Sanchez-Hernandez JF, AbadTerrado C, Viedma-Contreras JA, et al . Prognostic value of the sTREM-1 plasma values in patients with sepsis: a cohort study. Med Intensiva 2010.
Contents lists available at ScienceDirect
Clinical Biochemistry j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / c l i n b i o c h e m
Diagnostic accuracy of sTREM-1 to identify infection in critically ill patients with systemic inflammatory response syndrome Jaime Latour-Pérez a,⁎, Adoración Alcalá-López a, Miguel-Ángel García-García b, José F. Sánchez-Hernández c, Carmen Abad-Terrado a, José A. Viedma-Contreras c, Mar Masiá d, Matilde González-Tejera e, David Arizo-León b, María-Jesús Broch Porcar b, Fernando Bonilla-Rovira e, Félix Gutiérrez d a
Hospital General Universitario de Elche, Servicio de Medicina Intensiva, Camí Vell de l´almàssera 11, 03203 Elche, Spain Hospital de Sagunto, Servicio de Medicina Intensiva, Ramón y Cajal, 46, 46520 Sagunto, Spain c Hospital General Universitario de Elche, Servicio de Bioquímica, Camí Vell de l´almàssera 11, 03203 Elche, Spain d Hospital General Universitario de Elche, Unidad de Enfermedades Infecciosas, Camí Vell de l´almàssera 11, 03203 Elche, Spain e Hospital General Universitario de Elche, Departamento de Urgencias, Camí Vell de l´almàssera 11, 03203 Elche, Spain b
a r t i c l e
i n f o
Article history: Received 23 December 2009 Received in revised form 2 March 2010 Accepted 4 March 2010 Available online 17 March 2010 Keywords: Sepsis Systemic inflammatory response syndrome sTREM-1 Soluble triggering receptor expressed on myeloid cells-1 Sensitivity and specificity ROC curve
a b s t r a c t Objectives: To assess the accuracy of plasma levels of soluble Triggering Receptor Expressed on Myeloid cells (sTREM)-1 to diagnose infection in critical patients with systemic inflammatory response syndrome (SIRS). Design and methods: We prospectively studied 114 patients with SIRS criteria. The patients’ plasma levels of sTREM-1 were measured within 24 h of admission to the intensive care unit. The final diagnosis of infection was made independently by two investigators, who were blinded to the levels of sTREM-1. Results: The area under the ROC curve of sTREM-1 for the diagnosis of sepsis was 0.62 (95% confidence interval [95% CI] 0.51–0.72). The diagnostic odds ratio of sTREM-1 after adjusting for the Infection Probability Score and procalcitonin plasma levels was 1.81 (95% CI 0.66–4.98; p = 0.2508). Conclusions: In critical patients admitted with SIRS, sTREM-1 has poor discriminative power to identify patients with infection, and sTREM-1 levels do not add diagnostic information to that provided by other routinely available clinical tests. © 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction The diagnosis of sepsis is based on the presence of systemic inflammatory response syndrome (SIRS) and the clinical suspicion of infection [1]. Unfortunately, microbiological data are late and insensitive, while classic signs of infection (such as fever and leukocytosis) are often present in patients with non-infectious causes of SIRS such as trauma, pancreatitis or stroke. During the last few years, different biological markers (such as Creactive protein [CRP], procalcitonin [PCT], interleukin-6, interleukin8 and C3a) have been proposed for the diagnosis of infection; however, none of them has proved to be sufficiently sensitive and specific [2–4].
Triggering receptor expressed on myeloid cells (TREM)-1 is a recently discovered cell-surface molecule that is present on neutrophils and mature monocytes and is actively expressed in response to infection by bacteria or fungi [5]. This upregulation is accompanied by an increased release of its soluble form (sTREM-1) [6]. The value of plasma levels of sTREM-1 for diagnosing infection has been addressed in several studies, with inconsistent results [6–14]. Moreover, there is much uncertainty about the incremental sensitivity and specificity of sTREM-1 compared with other tests that are more easily performed. It seems appropriate, therefore, to assess the diagnostic accuracy of this biomarker in a representative group of critical patients admitted to the intensive care unit. Methods
⁎ Corresponding author. Fax: +34 966 679 108. E-mail addresses: [email protected] (J. Latour-Pérez), [email protected] (A. Alcalá-López), [email protected] (M.-Á. García-García), [email protected] (J.F. Sánchez-Hernández), [email protected] (C. Abad-Terrado), [email protected] (J.A. Viedma-Contreras), [email protected] (M. Masiá), [email protected] (M. González-Tejera), [email protected] (D. Arizo-León), [email protected] (M.-J.B. Porcar), [email protected] (F. Bonilla-Rovira), [email protected] (F. Gutiérrez).
Objectives The main goal of the study was to estimate the accuracy of sTREM-1 plasma levels in the diagnosis of infection in critical patients with SIRS. The secondary goal was to assess the added value of sTREM-1 to clinical and laboratory data usually available in hospital settings, such as the Infection Probability Score (IPS) [15] or PCT serum levels.
0009-9120/$ – see front matter © 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.clinbiochem.2010.03.001
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
Participants All patients older than 18 years admitted into two general intensive care units through the study period with a diagnosis of SIRS, according to the criteria of the ACCP/SCCM Consensus Conference [1], were suitable for inclusion in the study. However, the ultimate inclusion of patients in the study required the availability of one of the researchers; therefore, the patients included in the study were not strictly consecutive. Daily, one of the clinical investigators reviewed all patients admitted to the Intensive Care Unit using a screening form to identify those patients who met the inclusion criteria. After obtaining informed consent from the patient or his/her relatives, one serum sample was obtained as soon as possible after detection of SIRS, and the sample was frozen at −80 °C until determination of sTREM-1 levels. Patients who did not sign the informed consent form and those from whom a serum sample could not be obtained within the first 24 h after the onset of SIRS were excluded from the study.
721
parametric ROC curve (AUC) along with its 95% confidence intervals. In the case of continuous variables, the sensitivity, specificity and likelihood ratios were calculated at the optimal cutoff point of the ROC curve. Finally, in order to assess the independent diagnostic value of sTREM-1 (i.e., its added value), we built a multiple logistic regression model that included the presence of infection as the outcome variable and sTREM-1 as the main predictor. Thereafter, the routinely available diagnostic tests (e.g., IPS and PCT) were added to the model (one each time) as potential confounding variables, and the crude and adjusted sTREM-1 diagnostic odds ratios were compared. Ethical considerations The study was approved by the corresponding ethics committees. Results Study population
Gold standard The final diagnosis of infection was made by two investigators who had access to all patient clinical data, including microbiological results and diagnostic imaging, but without knowledge of the levels of sTREM-1. The origin of the final infection was established following the criteria of the International Sepsis Forum Consensus Conference on Definitions of Infection in the Intensive Care Unit [16]. Any disagreements between the two investigators were resolved by consensus. Variables In addition to the final diagnosis and sTREM-1 plasma levels, other variables were collected prospectively, including biological data (blood count, CRP, PCT, lactate), the Sepsis-related Organ Failure Assessment (SOFA) score on admission [17], IPS [15], the Simplified Acute Physiological Score-III (SAPS-3) on admission[18], and variables related to the spectrum of patients (age, sex, history of immunodeficiency, and so on).
Due to logistic restrictions (non-availability of reagents), the patients were recruited during two periods, the first from October 2007 to April 2008 and the second from November 2008 to March 2009. During the enrollment period, 144 patients presented SIRS criteria on admission to the ICU. This figure represents 28% of all noncoronary admissions during the study period. Thirty patients were further excluded due to age less than 18 years (5 patients), missing sTREM-1 values during the first 24 h of admission (24 patients) and withdrawal of informed consent (1 patient). Therefore, 114 patients were finally analyzed. Forty-two patients (37% of the study population) were identified as having non-infectious SIRS, 5 (4%) as having sepsis, 24 (21%) as having severe sepsis, and 43 (38%) as having septic shock (Table 1, Fig. 1). Eighty-three percent of sepsis were community acquired, whereas the remaining 17% were classified as nosocomial. The most prevalent source of infection was respiratory (40%), followed by abdominal-pelvic (21%) and urinary (12.5%). The most frequent causes of non-infectious SIRS were acute respiratory failure without signs of infection (29%), post-cardiac arrest status (14%), acute heart failure (12%) and non-septic shock (10%).
Test methods Diagnostic value of sTREM-1 serum levels Plasma levels of sTREM-1 were determined by sandwich type ELISA using a commercial kit (R & D Systems, Inc., Minneapolis, MN). The concentration of sTREM-1 was calculated from the calibration curve of reference standards included in the kit. The range of the assay was 0–4000 pg/mL. Determinations were performed in duplicate, and the results were averaged. The intra- and inter-assay coefficients of variation were 5% and 10%, respectively. An immunochromatographic test was used for the semiquantitative determination of the plasma procalcitonin (BRAHMS PCT-Q, Berlin, Germany); the sensitivity of the method was 0.5 ng/mL. C-Reactive protein levels were measured by an automated particle-enhanced turbidimetric immunoassay using the Olympus CRP latex kit (OSR 6299).
The sTREM-1 levels were higher in patients with infection than in patients with non-infectious SIRS (median 420.5 versus 326.5 pg/mL; p = 0.0406). However, there was a huge overlap between the sTREM1 distributions in patients with infectious and non-infectious SIRS (Fig. 1). This overlap is reflected in the ROC curve, with an AUC of 0.62 (95% CI 0.51 to 0.72). This figure compares disadvantageously with the AUCs of other classical tests, such as CRP, PCT and IPS (Fig. 2, Table 2). The AUC was similar (close to 0.50) in each of the subgroups analyzed (age, sex, clinical suspicion of infection, immunity status or severity of disease). Added diagnostic value of sTREM-1
Statistical analysis Since most of the continuous variables did not follow a normal distribution, the statistical analyses were performed using nonparametric methods (Mann–Whitney, Kruskal–Wallis and nonparametric linear regression). The categorical variables were analyzed using the chi-squared test for 2 × 2 tables. For the ordinal variables with more than two categories, a chi-squared test for trend was performed. All hypothesis tests were two-tailed. The diagnostic accuracy of different variables was assessed by estimating their sensitivity, specificity, and area under the non-
After adjusting by logistic regression analysis to IPS (two categories) and PCT (two categories), the diagnostic odds ratio of sTREM-1 was 1.81 (95% CI 0.66–4.98; p = 0.2508). This result indicates that sTREM-1 levels did not add significant diagnostic information to that offered by these typically available tests (Table 3). Variables associated with sTREM-1 Plasma levels of sTREM-1 were positively correlated with hospital mortality (p = 0.0013) and other severity of illness indexes such as
722
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
Table 1 Study population. Variable
Sepsis (n = 72)
No sepsis (n = 42)
p
Gender: women, n (percent) Age: median (percentile 25–75) Clinical suspicion of infection: n (percent) Fever/hypothermia: n (percent) Tachycardia: n (percent) Tachypnea: n (percent) Leukocytosis/leukopenia: n (percent) Hypo-perfusion: n (percent) Organ failure: n (percent) MODS: n (percent) Shock: n (percent) Hospital mortality: n (percent) SAPS 3: median (percentile 25–75) SOFA: median (percentile 25–75) IPS: median (percentile 25–75) sTREM-1: median (percentile 25–75) PCT: ≤0.5 ng/mL N0.5 b 2 ng/mL N2 b 10 ng/mL N= 10 ng/mL CRP: median (percentile 25–75) mg/mL Lactate: median (percentile 25–75) mmol/L
30 (41.7%) 68 (58–75) 69 (95.8%) 39 (54.2%) 60 (62.5%) 60 (64.5%) 61 (67.8%) 44 (62.0%) 65 (90.3%) 46 (65.7%) 43 (63.2%) 27 (37.5%) 71 (58–84) 8 (5–11) 18 (16–20) 420.5 (265–694.5) 17 (27.4%) 14 (22.6%) 7 (11.3%) 24 (38.7%) 158 (79–313) 2.3 (1.5–4.3)
15 (35.7%) 69.5 (58–76) 16 (38.1%) 11 (26.2%) 12 (66.7%) 12 (57.1%) 10 (43.5%) 17 (44.7%) 27 (65.9%) 14 (34.2%) 4 (10.0%) 15 (35.7%) 63.5 (52–73) 6 (3–8) 14 (10–17) 326.5 (231–453) 30 (88.2%) 3 (8.8%) 1 (2.9%) 0 (0%) 41 (14.5–113) 1.6 (1.1–2.4)
0.5305 0.7576 b 0.0001 0.0037 0.7366 0.5270 0.0314 0.0841 0.0013 0.0013 b 0.0001 0.8488 0.0139 0.0097 0.0003 0.0406 b 0.0001
b 0.0001 0.0031
Abbreviations: CRP, C-reactive protein; IPS, infection probability score; MODS, multi-organ dysfunction syndrome; PCT, procalcitonin; SAPS, simplified acute physiology score; SOFA, sepsis-related organ failure assessment score; sTREM-1, soluble triggering receptor on myeloid cells-1.
PCT, CRP, IPS, lactate, SAPS-3 or SOFA (Table 4). Indeed, sTREM-1 levels showed a moderate discriminative power to identify patients with Multiple Organ Dysfunction Syndrome (AUC 0.77, 95% CI 0.68– 0.86) and patients who did not survive to hospitalization (AUC 0.68, 95% CI 0.58–0.78). The hospital mortality of patients with positive or negative results of sTREM-1 was 50% and 29%, respectively.
probability after a positive test (sTREM-1 greater than 463.2 pg/mL) increases up to 80%, whereas after a negative test this probability is reduced to 53%. Moreover, sTREM-1 levels did not add diagnostic information to that provided by other usually available tests, such as the IPS, CRP or the PCT levels. Consequently, it would probably be of limited usefulness to include sTREM-1 levels in a panel of biomarkers for the diagnosis of sepsis that already included PCT and CRP.
Discussion Validity of the study Summary of results The study results show that in critically ill patients with SIRS, sTREM-1 plasma levels have a low power to discriminate between patients with or without infection. Given the heterogeneity of the sepsis processes and the different evolution times of the included patients, it would not necessarily be expected for a particular biomarker to have perfect sensitivity and specificity. However, our study showed that the sTREM-1 levels had little effect on the probability of sepsis. For example, for a pre-test probability of infection of 63% (similar to our prevalence of infection), the revised
Fig. 1. Study population (Box and whisker plot). The central “box” represents the first and third quartiles with the median between them marked with a diamond, with the minimum as the origin of the leading “whisker” and with the maximum as the limit of the trailing “whisker”.
Our study had some limitations. First of all, an imperfect gold standard (expert criteria) was used for the diagnosis of infection. Consequently, despite efforts to apply explicit criteria for diagnosis [16], some degree of misclassification, and hence a sub-estimation of
Fig. 2. ROC curves for the diagnosis of infection.
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724
723
Table 2 Comparative accuracy of diagnostic tests. Variable
AUC (95% CI)
Cutpoint
Sensitivity (95% CI)
Specificity (95% CI)
Positive predictive value (95% CI)
Negative predictive value (95% CI)
sTREM-1 PCT CRP Lactate IPS
0.62 0.83 0.75 0.67 0.70
463.2 pg/mL ≥0.5 ng/mL ≥94.5 mg/L ≥2.21 mmol/L ≥15
0.49 0.73 0.72 0.55 0.82
0.79 0.88 0.73 0.74 0.54
0.80 0.92 0.82 0.80 0.75
0.47 0.64 0.60 0.47 0.63
(0.51–0.72) (0.76–0.91) (0.66–0.85) (0.57–0.78) (0.60–0.81)
(0.37–0.61) (0.60–0.83) (0.60–0.82) (0.43–0.67) (0.71–0.90)
(0.63–0.90) (0.73–0.97) (0.57–0.86) (0.57–0.87) (0.37–0.69)
(0.65–0.90) (0.80–0.98) (0.70–0.91) (0.66–0.90) (0.64–0.84)
(0.35–0.59) (0.49–0.77) (0.45–0.74) (0.34–0.60) (0.45–0.79)
Abbreviations: CRP, C-reactive protein; IPS, infection probability score; PCT, procalcitonin; SAPS, simplified acute physiology score; sTREM-1, soluble triggering receptor on myeloid cells-1.
Table 3 Incremental diagnostic value of sTREM-1.
Consistency with other studies
Variables controlled
Adjusted DOR (95% CI)
p
None (crude odds ratio) CRP (2 categories) IPS (2 categories) PCT (2 categories) IPS + PCT (2 categories) PCT (2 categories) + PCR (2 categories)
3.47 2.11 2.40 2.46 1.81 1.70
0.0051 0.1242 0.0638 0.0655 0.2508 0.3111
(1.45–8.28) (0.81–5.47) (0.95–6.05) (0.94–6.39) (0.66–4.98) (0,61–4.75)
Abbreviations: CRP, C-reactive protein; DOR, diagnostic odds ratio; IPS, infection probability score; PCT, procalcitonin.
the diagnostic accuracy of sTREM-1, could have occurred. Nevertheless, the AUC of other established biomarkers, like PCT or CRP, was similar to that reported in other studies, suggesting that the magnitude of this potential bias was not substantial. Given the non-consecutive recruitment and the low prevalence of sepsis in the study, the issue of selection bias must be considered. However some study findings argue against this possibility. First, the relative prevalence of the infection sources and severity of illness was similar to other epidemiologic studies in sepsis [19–22]. Second, the diagnostic accuracy of other tests such as PCT and PCR was consistent with the published literature [3,4]. Third, recruitment was performed using a prospectively designed screening instrument that required the review of inclusion and exclusion criteria for each patient remaining in ICU, so that the final inclusion in the study was independent of the a priori likelihood of infection. The possibility of ascertainment bias, another important source of error in diagnostic evaluations, can also be disregarded, since the determination of sTREM-1 was deferred so that neither the clinical investigators that established the final diagnostic knew the test results, nor did the researchers that performed the biochemical analyses know the final diagnosis of the patient. Certainly, the researchers responsible for the final diagnosis were not blinded to the levels of other biomarkers such as PCT and PCR. Therefore, it could be argued that the diagnostic accuracy of these biomarkers could have been favored as compared with sTREM-1. This possibility seems, however, unlikely, since—as noted previously—the AUCs of PCT and PCR were similar to those published in other studies.
Table 4 Variables related to sTREM-1. Variables
Kendall's Tau
p
PCT CRP IPS lactate SAPS-3 SOFA
0.2916 0.1985 0.1693 0.2898 0.3554 0.3541
0.0001 0.0019 0.0108 b0.0001 b0.0001 b0.0001
Abbreviations: PCT, procalcitonin; CRP, C-reactive protein; IPS, infection probability score; SAPS-3, simplified acute physiology score-3; SOFA, sepsis-related organ failure assessment score; sTREM-1, soluble triggering receptor on myeloid cells-1.
The accuracy of sTREM-1 plasma levels for the diagnosis of infection has been addressed in several studies [6–14] with conflicting results. The causes of this heterogeneity are not straightforward. Some plausible sources are the use of different laboratory techniques for the measurement of sTREM-1[7], differences in the spectrum of patients and different study designs (case-control versus cohort-transversal design [23]). Furthermore, several previous studies have suggested that sTREM-1 is a marker of the intensity of the SIRS [10,14,24,25]. Indeed, if patients with sepsis included in the study had a higher level of severity, higher sTREM-1 levels would be expected in patients with sepsis, which could be wrongly attributed to infection when in fact it is due to the different severity of SIRS (confounding by severity). Our results support this hypothesis. Conclusions We conclude that in critical patients admitted with SIRS, sTREM-1 levels are positively correlated with disease severity and organ dysfunction. The discriminative power of serum sTREM-1 levels is poor, and sTREM-1 levels do not add diagnostic information to that provided by routine clinical tests. Acknowledgments We are grateful to the medical and nursing staff of the Biochemistry Departments of the participating hospitals for their support in the processing of blood samples. This study was supported by a grant from the Fondo de Investigación Sanitaria (FIS) PI-060457 and by an award from Brahms Inc. and the Spanish Society of Intensive Care Medicine (SEMICYUC). References [1] Bone RC, Sibbald WJ, Sprung CL. The ACCP-SCCM consensus conference on sepsis and organ failure. Chest 1992;101:1481–3. [2] Selberg O, Hecker H, Martin M, Klos A, Bautsch W, Kohl J. Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin6. Crit Care Med 2000;28:2793–8. [3] Tang BM, Eslick GD, Craig JC, McLean AS. Accuracy of procalcitonin for sepsis diagnosis in critically ill patients: systematic review and meta-analysis. Lancet Infect Dis 2007;7:210–7. [4] Uzzan B, Cohen R, Nicolas P, Cucherat M, Perret GY. Procalcitonin as a diagnostic test for sepsis in critically ill adults and after surgery or trauma: a systematic review and meta-analysis. Crit Care Med 2006;34:1996–2003. [5] Bouchon A, Facchetti F, Weigand MA, Colonna M. TREM-1 amplifies inflammation and is a crucial mediator of septic shock. Nature 2001;410:1103–7. [6] Gibot S, Massin F. Soluble form of the triggering receptor expressed on myeloid cells 1: an anti-inflammatory mediator? Intensive Care Med 2006;32:185–7. [7] Gibot S, Kolopp-Sarda MN, Bene MC, Cravoisy A, Levy B, Faure GC, et al . Plasma level of a triggering receptor expressed on myeloid cells-1: its diagnostic accuracy in patients with suspected sepsis. Ann Intern Med 2004;141:9–15. [8] Phua J, Koay ES, Zhang D, Tai LK, Boo XL, Lim KC, et al . Soluble triggering receptor expressed on myeloid cells-1 in acute respiratory infections. Eur Respir J 2006;28: 695–702. [9] Kofoed K, Andersen O, Kronborg G, Tvede M, Petersen J, Eugen-Olsen J, et al . Use of plasma C-reactive protein, procalcitonin, neutrophils, macrophage migration
724
[10]
[11]
[12]
[13]
[14]
[15]
[16] [17]
J. Latour-Pérez et al. / Clinical Biochemistry 43 (2010) 720–724 inhibitory factor, soluble urokinase-type plasminogen activator receptor, and soluble triggering receptor expressed on myeloid cells-1 in combination to diagnose infections: a prospective study. Crit Care 2007;11:R38. Yasuda T, Takeyama Y, Ueda T, Shinzeki M, Sawa H, Takahiro N, et al . Increased levels of soluble triggering receptor expressed on myeloid cells-1 in patients with acute pancreatitis. Crit Care Med 2008;36:2048–53. Bopp C, Hofer S, Bouchon A, Zimmermann JB, Martin E, Weigand MA. Soluble TREM-1 is not suitable for distinguishing between systemic inflammatory response syndrome and sepsis survivors and nonsurvivors in the early stage of acute inflammation. Eur J Anaesthesiol 2009;26:504–7. Carrol ED, Mankhambo LA, Jeffers G, Parker D, Guiver M, Newland P, et al . The diagnostic and prognostic accuracy of five markers of serious bacterial infection in Malawian children with signs of severe infection. PLoS One 2009;4:e6621. Jiyong J, Tiancha H, Wei C, Huahao S. Diagnostic value of the soluble triggering receptor expressed on myeloid cells-1 in bacterial infection: a meta-analysis. Intensive Care Med 2009;35:587–95. Park JJ, Cheon JH, Kim BY, Kim DH, Kim ES, Kim TI, et al . Correlation of serumsoluble triggering receptor expressed on myeloid cells-1 with clinical disease activity in inflammatory bowel disease. Dig Dis Sci 2009;54:1525–31. Peres Bota D, Melot C, Lopes Ferreira F, Vincent JL. Infection probability score (IPS): a method to help assess the probability of infection in critically ill patients. Crit Care Med 2003;31:2579–84. Calandra T, Cohen J. The international sepsis forum consensus conference on definitions of infection in the intensive care unit. Crit Care Med 2005;33:1538–48. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, et al . The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
of the European Society of Intensive Care Medicine. Intensive. Care Med 1996;22: 707–10. Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, et al . SAPS 3— From evaluation of the patient to evaluation of the intensive care unit: Part 2. Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med 2005;31:1345–55. Alberti C, Brun-Buisson C, Burchardi H, Martin C, Goodman S, Artigas A, et al . Epidemiology of sepsis and infection in ICU patients from an international multicentre cohort study. Intensive Care Med 2002;28:108–21. Esteban A, Frutos-Vivar F, Ferguson ND, Penuelas O, Lorente JA, Gordo F, et al . Sepsis incidence and outcome: contrasting the intensive care unit with the hospital ward. Crit Care Med 2007;35:1284–9. Vincent JL, Rello J, Marshall J, Silva E, Anzueto A, Martin CD, et al . International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009;302:2323–9. Vincent JL, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, et al . Sepsis in European intensive care units: results of the SOAP study. Crit Care Med 2006;34: 344–53. Lijmer JG, Mol BW, Heisterkamp S, Bonsel GJ, Prins MH, van der Meulen JH, et al . Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 1999;282:1061–6. Dimopoulou I, Orfanos SE, Pelekanou A, Kotanidou A, Livaditi O, Augustatou C, et al. Serum of patients with septic shock stimulates the expression of Trem-1 on U937 monocytes. Inflamm Res 2009;58:127–32. Latour-Perez J, Alcala-Lopez A, Garcia-Garcia MA, Sanchez-Hernandez JF, AbadTerrado C, Viedma-Contreras JA, et al . Prognostic value of the sTREM-1 plasma values in patients with sepsis: a cohort study. Med Intensiva 2010.