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Keywords:

  • laboratory biomarker;
  • mortality, prediction;
  • soluble urokinase plasminogen activator receptor;
  • systemic inflammatory response syndrome

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

Objective

The soluble urokinase plasminogen activator receptor (suPAR) reflects inflammation. However, the prognostic value of suPAR measurements, particularly at the very early onset of systemic inflammatory response syndrome (SIRS), is less well defined.

Methods

The prognostic potential of suPAR levels in patients with SIRS was evaluated. From November 2010 until April 2013, 902 adult patients presenting with SIRS were investigated. Blood samples for laboratory testing of inflammation markers were collected simultaneously with initial blood cultures. suPAR testing was performed using suPARnostic© assay.

Results

Analyses of receiver operating characteristics curves revealed areas under the curve (AUCs) of 0.818 for predicting overall mortality within 48 h (36/902 patients died), 0.739 for 30-day mortality (117/902 died) and 0.706 for predicting 90-day mortality (151/902 died). AUCs for procalcitonin (0.777, 0.671 and 0.638), interleukin-6 (0.709, 0.593 and 0.569) and C-reactive protein (0.66, 0.594 and 0.586) as well as renal function and age were markedly lower. Using multivariable regression analyses, suPAR levels (P < 0.001) remained significant predictors of 48-h mortality, whereas suPAR levels (P < 0.001) and bacteraemia (P = 0.002 and P = 0.001, respectively) remained significant predictors of 30- and 90-day mortality. Using Kaplan–Meier survival plots, patients with suPAR <9.15 ng mL−1 at SIRS onset had a clear benefit.

Conclusion

suPAR plasma level determined at early SIRS is predictive for mortality.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

Systemic inflammatory response syndrome (SIRS) is observed frequently in hospitals and can progress rapidly to life-threatening conditions [1]. Early triage of patients with suspected sepsis presents a major challenge. Initiation of intensive therapeutic measures at a very early stage of SIRS or sepsis can improve the outcome dramatically in those at the highest risk of mortality. In addition to identifying the causative pathogen and target therapy, highly sensitive and specific prognostic biomarkers can help the attending physician in making triage decisions but may also improve outcome by providing a ‘trigger’ for early initiation of intensified empirical therapy [2-4].

C-reactive protein (CRP), procalcitonin (PCT) and interleukin-6 (IL-6) are widely used as biomarkers in infectious and inflammatory conditions [5, 6]. The diagnostic and prognostic potential of these biomarkers varies, but a biomarker that convincingly predicts mortality in SIRS is lacking. The soluble urokinase plasminogen activator system consists of a proteinase (uPA), a receptor (uPAR) and inhibitors. The soluble urokinase plasminogen activator receptor (suPAR) is the soluble form of uPAR and proven to be positively correlated with the activation level of the immune system. Increased plasma concentrations of suPAR can be found in inflammatory and infectious processes, including bacteraemia with endotoxaemia, human immunodeficiency virus (HIV) infection, viral infections, malaria, rheumatoid arthritis and liver cirrhosis [7-12].

Soluble urokinase plasminogen activator receptor has been investigated with regard to prognostic potential and outcome in mostly critically ill patients. Those studies revealed that systemic levels of suPAR were significantly higher in patients with fatal outcomes compared with those who survived [4, 13-18]. Low suPAR levels have been found to be a positive predictor of survival in the intensive care unit (ICU) and overall survival in critically ill patients, including septic and nonseptic patients [14].

We investigated the prognostic potential of suPAR for 48-h, 30- and 90-day mortality in 902 patients presenting with SIRS. The prognostic potential of suPAR was compared with that of the routinely tested biomarkers CRP, PCT and IL-6. In addition, survival benefit of the cut-off-related plasma level of suPAR was determined.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

The study protocol was approved by the Ethics Committee of the Medical University of Graz (Graz, Austria; EC-number 21–469 ex 09/10) and is registered with a ClinicalTrials.Gov Identifier of NCT01359891. All patients provided written informed consent to be included in the study.

Study population

This prospective explorative study was conducted from November 2010 to April 2013 at University Hospital Graz (Graz, Austria). Within this period, adult patients presenting with SIRS at this hospital were screened for study inclusion. A total of 902 patients formed the study cohort by fulfilling SIRS criteria, as described previously [19, 20]. Inclusion criteria were (i) age >18 years, (ii) presentation at, or admitted to, the University Hospital of Graz, (iii) clinical suspicion of bacteraemia/septicaemia by the attending physician and (iv) a consecutive order of blood cultures. A total of 520 patients were included when presenting to the emergency department (ED) and 382 patients were already hospitalized (286 normal wards, 96 ICUs) at the time of study inclusion. Together with initial blood cultures, EDTA plasma samples were obtained for determination of suPAR and lithium heparin plasma samples for laboratory testing of the routine markers of infection CRP, PCT and IL-6. Medical records were reviewed individually using a standardized data collection template to collect demographic information and clinical data. Mortality and duration of hospitalization as well as microbiological test results were extracted from computerized databases.

Laboratory testing

Determination of suPAR was carried out on plasma samples which were immediately aliquoted, frozen and stored at −80 °C after blood collection using suPARnostic ELISA kit (ViroGates, Copenhagen, Denmark) according to manufacturer instructions. Measurements were made at the Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, on an ELISA platform reader (Flex Station 3; Molecular Devices, Munich, Germany). Lithium heparin plasma samples were obtained for testing CRP, PCT and IL-6 immediately after blood collection on a fully automated laboratory analyser (Cobas 8000; Roche Diagnostics, Rotkreuz, Switzerland).

Statistical analyses

Statistical analysis was undertaken using spss v20 (SPSS, Chicago, IL, USA). Continuous data (e.g., suPAR values) are presented as medians [interquartile ranges (IQR)] or means (±standard deviation) and categorical data as proportions. Patient groups were compared using Fisher's exact/chi-squared test for proportions (only two-tailed values are displayed) and the Mann–Whitney U-test for categorical data. The P-values of the Mann–Whitney U-tests were not corrected for multiple comparisons and are therefore only descriptive. Analyses of receiver operating characteristics (ROC) curves were carried out for biomarkers and combinations. Values of area under the curve (AUC) are displayed including 95% confidence interval (CI). Univariate and multivariate logistic regression analyses were conducted for biomarkers and odds ratios (OR) displayed. In the first step, univariate logistic regression analyses were carried out. Explanatory variables with P < 0.20 in univariate logistic regression analysis were included in the multivariable logistic models. Variables in the final model were selected with a forward stepwise procedure. Correlation was calculated using Spearman-ρ correlation analyses. P < 0.05 was considered significant. In addition, a Kaplan–Meier curve was constructed for 30-day mortality. Cut-off values were determined using Youden's index.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

A total of 902 patients presenting with SIRS were included prospectively. Baseline characteristics of the entire study population, those of the subgroup of patients that died within 48 h of study inclusion, and those that survived at day-90, are displayed in Table 1. suPAR levels were slightly higher (but not significantly so) in patients hospitalized at the time of study inclusion (median 7.8 ng mL−1, IQR 4.98–12.7 vs. median 7.1 ng mL−1, IQR 4.93–10.68, P = 0.062).

Table 1. Baseline characteristics as well as levels of soluble urokinase plasminogen activator receptor (suPAR), C-reactive protein (CRP), procalcitonin (PCT) and IL-6 [median and interquartile ranges (IQR) or mean ± standard deviation] for the whole study population, patients who died within 48 h and those who survived at 90 days after study inclusion
 Study population (n = 902)Patients with systemic inflammatory response syndrome (SIRS) who died at 48 h (n = 36)Patients with SIRS surviving at day 90 (n = 751)P-value if significanta
  1. P-values displayed in case of significant differences between the two subgroups.

  2. a

    P-values calculated with the chi-squared/Fisher's exact or Mann–Whitney U-test.

Demographic data
Age (years)63 ± 2670 (60–78)67 (53–77)0.014
Sex (male/female) (%)543 (60)/359 (40)22 (61)/14 (39)428 (57)/323 (43) 
BMI26 ± 826 ± 526 ± 6 
Number of days hospitalized11 (7–19)1 (1–2)11 (7–19)<0.001
Admission to the intensive care unit (n) (%)175 (19)16 (44)114 (15)<0.001
Underlying conditions (%)
Impaired renal function (glomerular filtration rate <60 mL min−1)426 (47)27 (75)335 (44)<0.001
Neutropaenia (<0.05 × 109)95 (11)4 (11)74 (10)0.81
Malignancies212 (24)10 (28)173 (23)0.51
Cardiovascular disease456 (51)23 (58)395 (53)0.18
Haematological disease159 (18)7 (19)125 (17)0.65
Positive blood culture678 (75)35 (97)555 (74)<0.001
Biomarkers
suPAR (ng mL−1)7.3 (IQR 5–11.3)14.7 (IQR 9.8–20)6.8 (IQR 4.7–10.2)<0.001
CRP (mg L−1)105 (IQR 43–200)198 (IQR 77–264)102 (IQR 42–193)<0.001
PCT (ng mL−1)0.7 (IQR 0.2–4.5)14.49 (IQR 1.37–59)0.63 (IQR 0.18–3.99)<0.001
IL-6 (pg mL−1)218 (IQR 86–854)1135 (IQR 223–5000)195 (IQR 79–831)<0.001
Creatinine (mg dL−1)1.22 (IQR 0.91–1.99)2.03 (IQR 1.37–3.42)1.17 (IQR 0.88–1.87)<0.001

Correlation analyses revealed a positive correlation of suPAR with age (P = 0.002), glomerular filtration rate (GFR, P < 0.001) and creatinine level (P < 0.001), but not with the duration of hospitalization (P = 0.18). suPAR levels were significantly higher in patients admitted to the ICU than in those who did not require ICU admission (median 9 ng mL−1, 95% CI 6.3–14.3 vs. median 7 ng mL−1, 95% CI 4.7–10.75; P < 0.001).

Death was recorded in 36/902 (4%) patients within 48 h, in 117/902 (13%) within the first 30 days and in 152/902 (17%) within 90 days of study inclusion. Patients who died within the first 48 h had higher median suPAR values (median 13.4 ng mL−1, IQR 9.5–20) than those who died between day 3 and day 90 after study inclusion (median 10 ng mL−1, IQR 6.25–15.86; P = 0.062) and those who survived at day 90 (median 6.9 ng mL−1, IQR 4.7–10.2; P < 0.001).

Analyses of ROC curves were performed for levels of suPAR, IL-6, PCT and CRP as well as for patient age for prediction of mortality, ICU admission and positive blood cultures. AUC values are depicted in Table 2, and ROC curves for 30-day mortality in Fig. 1. We further analysed differences between patients included when presenting to the ED (n = 520) and those that were hospitalized at the time of study inclusion (n = 382). Significant differences were not observed for 48-h mortality, but AUCs for suPAR were slightly lower in hospitalized patients than in ED patients for 30-day mortality (AUC 0.718 vs. 0.756) and markedly lower for 90-day mortality (0.673 vs. 0.750). No significant differences were observed for levels of PCT and IL-6.

Table 2. Receiver operating characteristics curve analysis for soluble urokinase plasminogen activator receptor (suPAR), IL-6, procalcitonin (PCT), C-reactive protein (CRP), creatinine and patients age for 48 h-, 30-, and 90-day overall mortality as well as intensive care unit (ICU) admission and positive blood culture result. Area under the curve values and 95% confidence intervals displayed
 48-h mortality (n = 36)30-day mortality (n = 117)90-day mortality (n = 151)ICU admission (n = 175)Positive blood culture (n = 296)a
  1. a

    Diagnostic potential to differentiate between positive and negative blood cultures was calculated for emergency department patients (n = 520) only. All other areas under the curve (AUCs) calculated for the entire study population (n = 902).

  2. b

    AUC 0.642 (0.581–0.704) for gram-positive and 0.670 (0.616–0.724) for gram-negative pathogens.

suPAR0.818 (0.763–0.873)0.739 (0.693–0.785)0.706 (0.660–0.752)0.619 (0.572–0.665)0.665b (0.619–0.712)
IL-60.709 (0.627–0.792)0.593 (0.536–0.651)0.569 (0.519–0.618)0.573 (0.525–0.621)0.696 (0.65–0.741)
PCT0.777 (0.715–0.839)0.671 (0.624–0.718)0.638 (0.593–0.682)0.599 (0.551–0.646)0.699 (0.654–0.744)
CRP0.660 (0.587–0.733)0.594 (0.544–0.644)0.586 (0.541–0.630)0.585 (0.538–0.632)0.575 (0.526–0.624)
Creatinine0.667 (0.585–0.750)0.625 (0.572–0.677)0.567 (0.516–0.618)0.565 (0.518–0.612)0.599 (0.55–0.647)
Age0.613 (0.538–0.689)0.544 (0.497–0.591)0.520 (0.476–0.564)0.45 (0.408–0.492)0.564 (0.514–0.614)
image

Figure 1. Analyses of receiver operating characteristics curved: levels of suPAR, procalcitonin (PCT), IL-6 and C-reactive protein (CRP) for prediction of 30-day mortality in patients with systemic inflammatory response syndrome.

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Using multivariable regression analyses, suPAR (P < 0.001; OR 1.147, 95% CI 1.096–1.201) remained a significant predictor of 48-h mortality. suPAR (P < 0.001; OR 1.16, 95% CI 1.084–1.150) and bacteraemia (P = 0.002; OR 2.900, 95% CI 1.4609–5.764) remained significant predictors of 30-day mortality. suPAR (P < 0.001; OR 1.125, 95% CI 1.089–1.162) and bacteraemia (P = 0.001; OR 2.600, 95% CI 1.459–4.632) remained significant predictors of 90-day mortality. Detailed results of univariate and multivariable logistic regression analyses for 48-h, 30- and 90-day mortality are depicted in Table 3.

Table 3. Results of univariate and multivariable analyses for 48-h, 30- and 90-day mortality (NS, not significant)
ParameterUnivariate analysis 48 hMultivariate analysis 48 hUnivariate analysis 30 dayMultivariate analysis 30 dayUnivariate analysis 90 dayMultivariate analysis 90 day
OR 95% CI P OR 95% CI P OR 95% CI P OR 95% CI P OR 95% CI P OR 95% CI P
Age (years)

1.022

0.988–1.057

0.204  

1.011

0.996–1.026

0.154 NS

1.005

0.993–1.017

0.409  
Soluble urokinase plasminogen activator receptor

1.138

1.067–1.213

<0.001

1.147

1.096–1.201

<0.001

1.127

1.089–1.167

<0.001

1.116

1.084–1.150

<0.001

1.131

1.094–1.170

<0.001

1.118

1.087–1.149

<0.001
C-reactive protein

1.004

1.000–1.008

0.071 NS

1.001

0.998–1.003

0.604  

1.000

0.998–1.002

0.717  
Procalcitonin

1.003

0.993–1.013

0.534  

1.002

0.997–1.006

0.522  

1.005

1.000–1.009

0.061 NS
IL-6

1.000

1.000–1.000

0.043 NS

1.000

1.000–1.000

0.600  

1.000

1.000–1.000

0.371  
Creatinine

0.678

0.421–1.091

0.110 NS

0.889

0.762–1.036

0.131 NS

0.817

0.700–0.953

0.01 NS
Blood culture

1.527

0.416–5.603

0.523  

2.634

1.311–5.292

0.007

2.900

1.460–5.764

0.002

2.457

1.367–4.417

0.003

2.600

1.459–4.632

0.001

To further evaluate the potential of suPAR to predict 48-h mortality, a 10.15-ng mL−1 suPAR cut-off value was determined using Youden's index by comparing the median number of patients who died within 48 h with those who survived at day 90. Patients who died between day 3 and day 90 were excluded from this analysis (55 of those patients had suPAR levels above, and 57 below, the cut-off value). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) as well as diagnostic odds ratio (DOR) for suPAR levels >10.15 ng mL−1 for death within 48 h (compared with those who survived at day 90) were 67%, 66%, 12% and 98%, DOR 5.82 (95% CI 2.93–11.56), respectively. Patients above this cut-off value had a 43% probability of requiring intensified medical care (i.e. ICU), whereas the probability was 16% in patients below the cut-off value.

A Kaplan–Meier survival plot using a suPAR cut-off value of 9.15 ng mL−1 (calculated using Youden's index) was created: it showed a survival benefit for SIRS patients with initial suPAR levels below this cut-off value (Fig. 2). Sensitivity, specificity, PPV and NPV as well as DOR for suPAR levels >9.15 ng mL−1 for death within 30 days (compared with those who survived on day-90) were 69%, 67%, 25% and 93%, DOR 4.62 (95% CI 3.04–7.02), respectively. For 90-day mortality, a suPAR cut-off of 8.73 ng mL−1 was calculated. Sensitivity, specificity, PPV and NPV as well as DOR for suPAR levels >8.73 ng mL−1 for death within 90 days were 64%, 67%, 28% and 82%, DOR 3.61 (95% CI 2.51–5.2), respectively.

image

Figure 2. Kaplan–Meier survival plots for patients with systemic inflammatory response syndrome using a soluble urokinase plasminogen activator receptor (suPAR) cut-off of 9.15 ng mL−1 (dotted line <9.15 ng mL−1; solid line <9.15 ng mL−1).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

We undertook a prospective study involving 902 patients with SIRS. suPAR plasma levels determined at early SIRS were predictive for 48-h (AUC 0.818), 30-day (AUC 0.739) and 90-day mortality (AUC 0.706). suPAR levels were superior to other biomarkers with respect to reflecting inflammation (IL-6, PCT, CRP), as well as renal function and age.

Our findings are – in part – in accordance with results obtained in notably smaller studies. Kofoed et al. [4] evaluated 151 patients with SIRS and found that suPAR levels upon hospital admission were significantly higher in both day 30 (n = 9, AUC 0.8) and day 180 nonsurvivors (n = 19, AUC 0.69). The cut-off value used in that small patient cohort (i.e. >6.61 ng mL−1) was surprisingly low and would have yielded in very low specificity in our study cohort. We found that a suPAR cut-off between 9.15 and 10.15 ng mL−1 may be optimal for prediction of mortality in patients with SIRS. Mölkänen et al. found that suPAR predicted fatality (n = 19) amongst patients with Staphylococcus aureus bacteraemia (n = 59). AUC was 0.754, and the optimal cut-off value in predicting 30-day mortality was 9.25 ng mL−1, which was comparable with our findings [13]. Uusitalo-Seppälä et al. [18] showed that a high suPAR plasma level remained an independent predictor of fatality and severe sepsis in 539 patients with suspected infection in the ED. The levels were significantly higher in nonsurvivors compared with survivors (8.3 vs. 4.9 ng mL−1), and the AUC for prediction of fatality was 0.79. The optimal suPAR cut-off in that patient cohort with suspected infection was 6.4 ng mL−1 (sensitivity 76%, specificity 69%) and therefore substantially lower than that found in our study [18]. Two reasons for the lower cut-off value found by Uusitalo-Seppälä et al. may have been the mixed patient population in that study (SIRS criteria were not fulfilled amongst the entire cohort, whereas all patients fulfilled SIRS criteria in our study) and because they evaluated ED patients only.

Soluble urokinase plasminogen activator receptor levels were robust markers for predicting mortality, but less reliable for predicting ICU admission (AUC 0.619). Several studies evaluated the prognostic potential of suPAR levels at ICU admission. Koch et al. evaluated 273 patients admitted to the ICU (median suPAR level 9.8 ng mL−1) and found that suPAR levels at ICU admission were significant predictors of ICU and long-term mortality (median ≈1 year with a range of observation 29–884 days). AUCs (0.67 for both) were lower, however, than those found in our cohort [14, 17]. Another study that evaluated the prognostic value of suPAR levels obtained upon ICU admission found an AUC of 0.726 for ICU mortality (n = 35). Surprisingly, the optimal suPAR cut-off in that study was 6.15 ng mL−1 and therefore markedly lower than the cut-offs proposed in the study by Koch et al. and our study [21]. Comparable AUC results were also reported by another small study evaluating the prognostic value of suPAR levels in the ICU for in-hospital mortality (AUC 0.67, n = 41) with an optimal suPAR cut-off of 9.6 ng mL−1 [22]. Jalkanen et al. [23] evaluated the predictive potential of suPAR levels in 454 critically ill and mechanically ventilated patients (median ICU baseline suPAR 11.6 ng mL−1) and found a markedly lower AUC of 0.61 for 90-day mortality.

Summarizing previous studies, the predictive potential of suPAR levels was lower in ICU patients than in those presenting to the ED. In our study, the predictive potential for 30- and in particular 90-day mortality was lower in hospitalized patients than in those in the ED, but no difference was found for 48-h mortality. Our findings confirm that suPAR values upon admission to the ED may be more valuable for prediction of long-term mortality than those obtained if patients are already hospitalized. In the ED, suPAR levels may be used for triage to determine which patients with SIRS require more comprehensive monitoring because high suPAR plasma levels may predict the need for more intensive therapeutic interventions.

In conclusion, we showed that suPAR plasma levels serve as prognostic markers in patients with SIRS. suPAR levels were an independent predictor of 48-h, 30- and 90-day mortality.

Conflicts of interest

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

Soluble urokinase plasminogen activator receptor kits used in this study were provided by the companies suPARnostic (Kopenhagen, Denmark) and Biomedica Medical Products (Vienna, Austria). No other funding was obtained. We declare no conflict of interest.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References

We thank Christina Strempfl, Bernadette Neuhold and Verena Posch for their support in the microbiology laboratory and Elisabeth Winter for conducting suPAR assays.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. Acknowledgements
  9. References
  • 1
    American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference: definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. 1992; 86474.
  • 2
    Rivers E, Nguyen B, Havstad S et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med 2001; 345: 136877.
  • 3
    Nguyen HB, Rivers EP, Havstad S et al. Critical care in the emergency department: a physiologic assessment and outcome evaluation. Acad Emerg Med 2000; 7: 135461.
  • 4
    Kofoed K, Eugen-Olsen J, Petersen J, Larsen K, Andersen O. Predicting mortality in patients with systemic inflammatory response syndrome: an evaluation of two prognostic models, two soluble receptors, and a macrophage migration inhibitory factor. Eur J Clin Microbiol Infect Dis 2008; 27: 37583.
  • 5
    Kofoed K, Andersen O, Kronborg G et al. Use of plasma C-reactive protein, procalcitonin, neutrophils, macrophage migration 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.
  • 6
    Hoenigl M, Raggam RB, Wagner J et al. Diagnostic accuracy of soluble urokinase plasminogen activator receptor (suPAR) for prediction of bacteremia in patients with systemic inflammatory response syndrome. Clin Biochem 2013; 46: 2259.
  • 7
    Yilmaz G, Köksal I, Karahan SC, Mentese A. The diagnostic and prognostic significance of soluble urokinase plasminogen activator receptor in systemic inflammatory response syndrome. Clin Biochem 2011; 44: 122730.
  • 8
    Andersen O, Eugen-Olsen J, Kofoed K, Iversen J, Haugaard SB. suPAR associates to glucose metabolic aberration during glucose stimulation in HIV-infected patients on HAART. J Infect 2008; 57: 5563.
  • 9
    Rabna P, Andersen A, Wejse C et al. Urine suPAR levels compared with plasma suPAR levels as predictors of post-consultation mortality risk among individuals assumed to be TB-negative: a prospective cohort study. Inflammation 2010; 33: 37480.
  • 10
    Perch M, Kofoed P, Fischer TK et al. Serum levels of soluble urokinase plasminogen activator receptor is associated with parasitemia in children with acute Plasmodium falciparum malaria infection. Parasite Immunol 2004; 26: 20711.
  • 11
    Toldi G, Bekő G, Kádár G et al. Soluble urokinase plasminogen activator receptor (suPAR) in the assessment of inflammatory activity of rheumatoid arthritis patients in remission. Clin Chem Lab Med 2013; 51: 32732.
  • 12
    Zimmermann HW, Koch A, Seidler S, Trautwein C, Tacke F. Circulating soluble urokinase plasminogen activator is elevated in patients with chronic liver disease, discriminates stage and aetiology of cirrhosis and predicts prognosis. Liver Int 2012; 32: 5009.
  • 13
    Mölkänen T, Ruotsalainen E, Thorball CW, Järvinen A. Elevated soluble urokinase plasminogen activator receptor (suPAR) predicts mortality in Staphylococcus aureus bacteremia. Eur J Clin Microbiol Infect Dis 2011; 30: 141724.
  • 14
    Koch A, Voigt S, Kruschinski C et al. Circulating soluble urokinase plasminogen activator receptor is stably elevated during the first week of treatment in the intensive care unit and predicts mortality in critically ill patients. Crit Care 2011; 15: R63.
  • 15
    Wittenhagen P, Kronborg G, Weis N et al. The plasma level of soluble urokinase receptor is elevated in patients with Streptococcus pneumoniae bacteraemia and predicts mortality. Clin Microbiol Infect 2004; 10: 40915.
  • 16
    Huttunen R, Syrjänen J, Vuento R et al. Plasma level of soluble urokinase-type plasminogen activator receptor as a predictor of disease severity and case fatality in patients with bacteraemia: a prospective cohort study. J Intern Med 2011; 270: 3240.
  • 17
    Backes Y, van der Sluijs KF, Mackie DP et al. Usefulness of suPAR as a biological marker in patients with systemic inflammation or infection: a systematic review. Intensive Care Med 2012; 38: 141828.
  • 18
    Uusitalo-Seppälä R, Huttunen R, Tarkka M et al. Soluble urokinase-type plasminogen activator receptor in patients with suspected infection in the emergency room: a prospective cohort study. J Intern Med 2012; 272: 24756.
  • 19
    Alberti C, Brun-Buisson C, Burchardi H et al. Epidemiology of sepsis and infection in ICU patients from an international multicentre cohort study. Intensive Care Med 2002; 28: 10821.
  • 20
    Bone RC, Balk RA, Cerra FB et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. 1992; 164455.
  • 21
    Donadello K, Scolletta S, Taccone FS et al. Soluble urokinase-type plasminogen activator receptor as a prognostic biomarker in critically ill patients. J Crit Care 2014; 29: 1449.
  • 22
    Suberviola B, Castellanos-Ortega A, Ruiz Ruiz A, Lopez-Hoyos M, Santibañez M. Hospital mortality prognostication in sepsis using the new biomarkers suPAR and proADM in a single determination on ICU admission. Intensive Care Med 2013; 39: 194552.
  • 23
    Jalkanen V, Yang R, Linko R et al. SuPAR and PAI-1 in critically ill, mechanically ventilated patients. Intensive Care Med 2013; 39: 48996.