Article

Clinical value of soluble urokinase-type plasminogen activator receptor in the diagnosis, prognosis, and therapeutic guidance of sepsis

a b s t r a c t

Objectives: The level of soluble urokinase-type plasminogen activator receptor (suPAR) is significantly increased in sepsis. We investigated whether suPAR could be a valuable biomarker in sepsis.

Methods: We measured suPAR and procalcitonin levels, recorded the Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment scores of engaged subjects, and drew receiver operating characteristics curves.

Results: The plasma suPAR and serum PCT levels of the sepsis group were higher than those of the systemic in- flammatory response syndrome and control groups. Using suPAR to distinguish systemic inflammatory response syndrome from sepsis on day 1, the area under the curve (AUC) curve was 0.817, and when suPAR and PCT were used in combination to diagnose sepsis, the AUC was 0.927. At a cutoff point of 9.52 ng/mL, the sen- sitivity and specificity for diagnosis of sepsis using suPAR were 71.93% and 95.46%, respectively. At a cutoff point of 12.01 ng/mL, the sensitivity and specificity for distinguishing survival and mortality by suPAR were 87.1% and 72.5%, respectively. When suPAR and the APACHE II score were combined to distinguish survival from mortality, the AUC was 0.857. The plasma suPAR level was positively correlated with the serum PCT level (r = 0.326, P b

.001), APACHE II score (r = 0.492, P b .001), and Sequential Organ Failure Assessment score (r = 0.386, P b .001). Conclusions: Use of both plasma suPAR and PCT levels enhanced the efficiency of sepsis diagnosis, and the combination of plasma suPAR and APACHE II score improved Mortality prediction.

(C) 2015

Introduction

Sepsis is the most common reason for intensive care unit admission, and mortality remains higher than 30% [1]. Only early recognition of sepsis can provide the possibility of timely and targeted treatment [2]. Clinically, culture of pathogenic microorganisms is the gold standard for diagnosis of bacterial infections. However, in cases of severe sepsis or septic shock, the positive rate for blood cultures is only approximately 30% [3]. Therefore, inflammatory markers that could aid in the early diagnosis, Severity assessment, and prognosis prediction for sepsis are in urgent need.

Soluble urokinase-type plasminogen activator receptor (suPAR) is the soluble form of uPAR, which is a glycoprotein with a molecular weight of 55 to 60 kDa. It adheres to the lipid bilayer cytomembrane of activated immune cells and other cells with a glycosylphosphatidylinositol anchor [4]. Under inflammatory stimulation, effects of proteases, or immune system activation [5], uPAR detaches from the surface of cells and

? Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article.

* Corresponding author. Department of Medical Intensive Care Unit, The First Affiliated Hospital, Sun Yat-Sen University, 58# Zhongshan 2nd Road, Guangzhou, 510080, China.

E-mail address: [email protected] (M. Zeng).

assumes a soluble form, suPAR, increasing suPAR levels in the blood and other bodily fluids in humans and animals. suPAR increases remark- ably in sepsis, and shows potential for use in determining the severity of sepsis [6]. However, whether it can be used as a biomarker for the early recognition of sepsis remains to be confirmed. In addition, whether suPAR levels decline with effective therapy, and whether suPAR could serve as a valuable prognostic indicator remain unclear. We measured the serum suPAR levels of patients with sepsis and investigated its value in diagnosis, severity assessment, and prognosis prediction for sepsis.

Methods

Study design and patient enrolment

Patients with sepsis (n = 82) who were hospitalized in the intensive care unit of The First Affiliated Hospital, Sun Yat-Sen University, from June 2013 to March 2014 were recruited. Systemic inflammatory re- sponse syndrome (SIRS) patients (n = 29) and healthy volunteers (n = 15) were selected as Control subjects.

Inclusion criteria: age >=18 y, SIRS diagnosis conforms to the standards of American College of Chest Physicians/Society of Critical Care Medicine,

http://dx.doi.org/10.1016/j.ajem.2015.11.004

0735-6757/(C) 2015

1991 [7], sepsis diagnosis conforms to the guidelines of Surviving Sepsis Campaign, 2012 [1]. Exclusion criteria were the following: HIV-positive, confirmed malignant tumor, rheumatoid arthritis, pulmonary tuberculo- sis, white blood cells b 1x 109/L or neutrophils b 0.5 x 109/L, use of glu- cocorticoids equal to a dosage of 1 mg/kg of prednisone for N 1 month, use of immunosuppressive drugs, or death within 24 hours of enrollment in the intensive care unit.

During the 28-day observation period, subjects were classified in either the sepsis surviving group or the mortality group, depending on survival. The study was approved by the Ethical Committee of the Sun Yat-Sen University, and the subjects provided consent for participation in the study.

Collection of blood samples and measurement of suPAR and procalcitonin

Venous blood (2 mL) was collected into EDTA-containing tubes. Within 30 minutes the blood was centrifuged at 4?C, 600g for 10 minutes to collect the plasma, which was aliquoted and stored at -80?C until suPAR testing using kits purchased from Uscn Life Science (Wuhan, China). An additional 2 mL of venous blood was collected into coagulant-containing tubes and stored for 30 min, until the blood had coagulated. Then the serum was sep- arated by centrifuging at 4?C, 600g for 10 minutes and tested using procalcitonin test kits purchased from Diasorin (Vercelli, Italy) and VIDAS test kits purchased from Liaison (Dietzenbach, Germany). Blood samples were collected on days 1, 3, 5, 7, and the day of discharge/mortal- ity. In addition, Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment scores were calculated for all subjects in the sepsis group.

Statistical analysis

The Mann-Whitney U test was used to compare continuous para- metric variables. One-way analysis of variance or the Kruskal-Wallis test was used to compare more than two groups of quantitative data. A 2-sided P b .05 was considered significant. Spearman’s rank correla- tion analysis was used to determine bi-variant relationships. Receiver operating characteristics (ROC) curves were constructed and the area under the curve (AUC) was calculated. Significant indexes were combined as joint diagnostic indexes. Logistic regression analysis was used to construct combined predictors.

Results

Patient characteristics

The sepsis group contained 51 male and 31 female patients, and the average age was 58.74 +- 1.91 years. The observation period was 28 days long. The sepsis group was divided into 2 sub-groups, the surviving group (51 patients, 31 males and 20 females) and the mortality group (31 patients, 20 males and 11 females). The SIRS group contained 29 subjects, including 20 male and 9 female patients, and the average age was 59.76 +- 3.37 years. The healthy control group

included 15 individuals (8 males and 7 females) and the average age was 50.0 +- 4.38 years.

The sepsis group included patients with the following conditions: 52 patients with pulmonary infection, 13 patients with abdominal infec- tion, 11 patients with postoperative Wound infection or deep tissue infection, 3 patients with catheter-related infection, 1 patient with Infective endocarditis, 1 patient with a urinary system infection, and 1 patient with a Pelvic cavity infection. Of these, 31 patients died within 28 days, and the 28-day mortality rate was 37.8%. In the SIRS group, the primary diseases included coronary heart disease, diabetes mellitus, chronic obstructive pulmonary disease, rheumatoid heart disease, bone fracture, and postoperative complications.

Plasma suPAR, serum PCT, and serum C-reactive protein of each group on day 1

The serum suPAR levels on day 1 were as follows: sepsis group (13.89 +- 0.65 ng/mL) N SIRS group (8.22 +- 0.61 ng/mL) N control group (4.65 +- 0.30 ng/mL) (P b .001). The serum PCT levels were as follows: sepsis group (19.18 +- 4.83 ng/mL) N SIRS group (1.10 +- 0.77 ng/mL) (P b .001). The serum C-reactive protein levels were as follows: sepsis group (94.29 +- 10.12) mg/L N SIRS group (6.86 +- 13.81) mg/L, p = 0.013. (Table 1).

Values of suPAR, PCT, and CRP for distinguishing SIRS from sepsis

When suPAR was used to distinguish SIRS from sepsis, the AUC was 0.817 (P b .001, 95% CI: 0.714-0.921). When the suPAR level was

9.52 ng/mL, the Youden index reached a peak of 0.674 (YI = 0.674). At this point, the sensitivity and specificity for distinguishing SIRS from sepsis by suPAR were 71.93% and 95.46%, respectively. In contrast, when PCT was used to distinguish SIRS from sepsis the AUC was 0.892 (P b .001, CI: 0.822-0.961). When the PCT was 0.675 ng/mL, the Youden index reached a peak of 0.663 (YI = 0.663). At this point, the sensitivity and specificity for distinguishing SIRS from sepsis using PCT were 75.4% and 90.9%, respectively. Furthermore, when CRP was used to distinguish SIRS from sepsis, the AUC was 0.681 (P = .013, 95% CI: 0.541-0.822). When the CRP was 38.85 mg/L, the Youden index reached a peak of 0.038 (YI = 0.0.38). At this point, using CRP to distinguish SIRS from sepsis, the sensitivity and specificity were 78.9% and 59.1%, respectively (Figure A).

The value of combining suPAR and PCT for distinguishing SIRS from sepsis

In the logistic regression analysis, we defined suPAR as X1 and PCT as X2, to obtain the following regression equation: P = 1/[1 + e]-(-3.219 + 0.248×1 + 1.208×2) (Table 2). When suPAR and PCT

combined were used to distinguish SIRS from sepsis, the AUC was 0.927 (P b .001, CI: 0.870-0.985), higher than for suPAR (AUC = 0.817) or PCT (AUC = 0.892) alone (Figure B ). Thus, this combina- tion enhanced the accuracy and prediction efficiency, compared to a single index.

Table 1

suPAR, PCT, and other indexes of patients and healthy controls on the day of admission

Controls (n = 15)

SIRS (n = 29)

Sepsis (n = 82)

F/?2/Z

p

Age (years) (a)

50.0 +- 4.38

59.76 +- 3.37

58.74 +- 1.91

1.773

0.174

Male/Female (b)

8/7

20/9

51/31

1.058

0.589

Plasma suPAR (ng/ml) (c)

4.65 +- 0.30

8.22 +- 0.61

13.89 +- 0.65

53.734

b0.001

Serum PCT(ng/mL) (d)

1.10 +- 0.77

19.18 +- 4.83

-5.88

b0.001

Serum CRP (mg/L) (d)

56.86 +- 13.81

94.29 +- 10.12

-2.36

0.018

APACHE II score (d)

8.97 +- 0.84

18.32 +- 0.92

-5.39

b0.001

SOFA score (d)

6.48 +- 0.33

10.09 +- 0.43

-4.85

b0.001

WBC (x109/L) (c)

7.61 +- 0.39

9.95 +- 0.90

12.96 +- 1.02

6.82

0.033

PLT (x109/L) (c)

228.73 +- 10.96

198.03 +- 11.99

145.84 +- 12.35

23.436

b0.001

(a) One-way ANOVA; (b) ?2 test; (c) Kruskal-Wallis test; (d) Mann-Whitney U test.

The level of serum suPAR in patients with sepsis

The serum suPAR level of the sepsis group on day 1 was higher than that in the SIRS and control groups. The serum suPAR level in the surviving group decreased over time, and on the day of

discharge the serum suPAR level was lower than on days 1, 3, 5, or 7 (P b .05). The serum suPAR levels at other time points did not differ significantly (P N .05). The serum suPAR level of the mortality group fluctuated but remained high on days 1, 3, 5, and 7 and the day of mortality. No significant differences were observed between serum

Figure. A, Receiver operating characteristics of suPAR, PCT and CRP in distinguishing sepsis from SIRS. B, Receiver operating characteristics of suPAR, PCT and suPAR combined with PCT in distinguishing sepsis from SIRS. C, Daily variations of plasma suPAR levels between survivors and non-survivors in sepsis. D, Daily variations of serum PCT levels between survivors and non-survivors in sepsis. E, ROC curve of suPAR, PCT, Lac, APACHE II score and SOFA score in predicting mortality in sepsis. F, ROC curve of suPAR, APACHE II score and suPAR, combined with APACHE II score in predicting mortality in sepsis.

Table 2

Logistic regression analysis of suPAR and PCT

Index variable

Bate

SE

Wald

df

P

OR

OR, 95%

CI

Lower

Upper

suPAR

0.284

0.124

5.241

1

.022

1.328

1.042

1.694

PCT

1.208

0.612

3.898

1

.048

3.347

1.009

11.104

Constant

-3.219

1.227

6.880

1

.009

0.040

suPAR levels at any time point in this group (P = .384). At each time point, the serum suPAR level of the mortality group was higher than that of the surviving group (P b .001) (Table 3, Figure C).

The PCT level in patients with sepsis

The serum PCT level of the sepsis group on day 1 was higher than that in the SIRS group (Table 1). The serum PCT levels of the surviving group on days 1, 3, 5, 7, and the day of discharge were 17.33 +- 5.51 ng/mL,

11.62 +- 4.68 ng/mL, 10.08 +- 4.61 ng/mL, 9.63 +- 4.61 ng/mL, and

9.13 +- 4.61 ng/mL, respectively (Table 4). The serum PCT level of the surviving group was higher on day 1 than on days 3, 5, 7, or the day of discharge (P b .05). Thus, the serum PCT level decreased with time in the surviving group (Figure D).

The serum PCT levels of the mortality group on days 1, 3, 5, 7, and the day of discharge were 22.31 +- 9.11 ng/mL, 13.83 +- 3.52 ng/mL,

13.38. +- 3.31 ng/mL, 21.04 +- 8.28 ng/mL, and 25.92 +- 9.95 ng/mL,

respectively. No significant differences were observed between serum PCT levels at any time point in this group (P = .384) (Table 4). In the mortality group, the serum PCT level first decreased and then increased (Figure D). On days 1, 3, and 5, serum PCT levels did not differ signifi- cantly between the mortality group and the surviving group (P N .05). On day 7 and the day of discharge/mortality, the serum PCT levels of the mortality group were higher than those of the surviving group (P b .05) (Table 4).

Comparison of single indexes for predicting mortality from sepsis

When serum suPAR was used to predict mortality, the AUC under the ROC curve was 0.765 (P b .001, 95% CI: 0.658-0.872). The Youden Index reached a peak (YI = 0.60) when the serum suPAR was 12.01 ng/mL. At this point, when serum suPAR was used to distinguish survival from mor- tality, the sensitivity and specificity were 87.1% and 72.5%, respectively.

When the APACHE II score was used to predict mortality, the AUC

was 0.83 (P b .001, 95% CI: 0.744-0.917), and the Youden Index reached a peak (YI = 0.69) when the APACHE II score was 17.5. At this point, the sensitivity and specificity were 87.1% and 70.6%, respectively.

When the SOFA score was used to predict mortality, the AUC was 0.782 (P b .001, 95% CI: 0.673-0.890), and the Youden Index reached a peak (YI = 0.51) when the SOFA score was 9.5. At this point, the sensi- tivity and specificity were 83.9% and 66.7%, respectively.

When plasma PCT and blood lactic acid were used to predict mortality, the AUC was 0.571 (p = 0.286, 95% CI: 0.443-0.698) and 0.638 (P = .038,

95% CI: 0.513-0.763), respectively. Since the AUC was less than 0.7, these indexes were considered to be inadequate (Figure E).

The value of combining suPAR and APACHE II scores for distinguishing survival and mortality

In the logistic regression analysis, we defined the suPAR level as X1 and the APACHE II score as x2, yielding a regression equation of P = 1/[1 + e]-(-6.362 + 0.131×1 + 0.206×2) (Table 5). When suPAR level and APACHE II score were used in combination to distinguish the surviving and mortality groups, the AUC was 0.857 (P b .001, 95% CI: 0.778- 0.936), higher than with either index alone (suPAR AUC = 0.765 and APACHE II score AUC = 0.83). Thus, using the 2 indexes in combination enhanced the efficiency of prediction (Figure F).

Correlation of suPAR levels with other clinical indexes

To determine the correlation between suPAR levels and other clini- cal indexes, the indexes of the SIRS and sepsis groups were subjected to correlation analysis. Plasma suPAR was positively correlated with serum PCT (r = 0.326, P b .001), APACHE II score (r = 0.492, P b

.001), and SOFA score (r = 0.386, P b .001).

Discussion

It has been shown that under many disease circumstances, including sepsis, activation and amplification of the immune system can enhance plasma suPAR levels, because suPAR becomes detached from the surface of the cell membrane. Combined with its ligand uPA, suPAR can exert many biological functions. The combination of uPAR and uPA can con- vert plasminogen into plasmin, therefore accelerating the degradation of the Extracellular matrix, which plays a key role in tissue infiltration of tumors [8]. Combined with ?-integrin, uPAR can also regulate bio- logical functions of white blood cells, such as adherence, migration, and differentiation, which play a pivotal role in immune defense [9]. The plasma suPAR level and the presentation of uPAR on the surface of monocytes rise in endotoxemia [10]. Moreover, most studies of uPAR/suPAR in an infectious background have been conducted using patients with pulmonary infection. In this study, 52 of the patients in the sepsis group had been diagnosed with pulmonary infections. When the lungs are infected by bacteria, neutrophils are triggered to gather in the lung tissue and the alveolar septum immediately after the activation of innate immunity [11]. In the animal model of Pseudomonas aeruginosa pneumonia, mice lacking uPAR show fewer accumulating neutrophils than wild-type mice. The necessity of uPAR for accumulation of neutrophils does not depend on uPA [12]. In a mouse model of Bacillus whitmori pneumonia, the expression of uPAR mRNA (from peripheral blood monocytes, neutrophils, and the alveolar septum) and uPAR (on the cell surface) increases. Owing to chemotaxis of uPAR, neutrophils migrate to a key position of the infection and show increased phagocytic activity [13], enhancing the immune reaction. Based on the above data, activation of the uPA/uPAR system plays a key role at the beginning of the inflammatory reaction (chemotaxis

Table 3

Dynamic changes of plasma suPAR levels(ng/mL) in septic patients

Group

Day 1

Day 3

Day 5

Day 7

Day of discharge/mortality

F

P?

Surviving group (n = 51)

12.0 +- 5.56

11.21 +- 4.78

10.91 +- 4.02

10.64 +- 3.79

9.74 +- 3.55

3.73

.016a

Mortality group (n = 31)

17.0 +- 5.17

16.02 +- 5.62

17.40 +- 6.12

16.22 +- 5.26

16.80 +- 6.07

1.006

.384b

Z

-4.00

-3.82

-4.40

-4.22

-4.77

P#

b.001c

b.001d

b.001e

b.001f

b.001g

c, d, e, f: Plasma suPAR level comparison between survivors and non-survivors on each time point.

a Plasma suPAR level comparison on day 1, day 3, day 5, day 7 and the day of discharge in survivors.

b Plasma suPAR level comparison on day 1, day 3, day 5, day 7 and the day of mortality in non-survivors.

* Within group: repeated measures data of ANOVA;

# Between group: Mann-Whitney U test.

Table 4

Dynamic changes of serum PCT levels(ng/mL) in septic patients

Group

Day 1

Day 3

Day 5

Day 7

Day of discharge/mortality

F

P?

Surviving group(n = 51)

17.33 +- 5.51

11.62 +- 4.68

10.08 +- 4.61

9.63 +- 4.61

9.13 +- 4.61

5.58

.02a

Death group(n = 31)

22.31 +- 9.11

13.83 +- 3.52

13.38. +- 3.31

21.04 +- 8.28

25.92 +- 9.95

0.965

.384b

Z

-0.96

-1.54

-1.94

-2.36

-3.12

P#

.339c

.122d

.052e

.018f

.002g

c, d, e, f: Serum PCT level l comparison between survivors and non-survivors on each time point.

a Serum PCT level comparison on day 1, day 3, day 5, day 7 and the day of discharge in survivors.

b Serum PCT level comparison on day 1, day 3, day 5, day 7 and the day of mortality in non-survivors.

* Within group: repeated measures data of ANOVA;

# Between group: Mann-Whitney U test.

and infiltration of inflammatory cells), which aids in eliminating infec- tion. The increase in uPAR levels is related to the increase in suPAR levels [14]. At the onset of infection, uPAR is expressed on the surface of white blood cells at very high levels. When the glycosylphosphatidylinositol anchors break, soluble suPAR is released into the blood stream. It is easier to detect suPAR than uPAR, which is located on the surface of cells. Thus, detecting suPAR can reveal infection at its early stage.

In this study, the 28-day mortality rate of sepsis was 37.8%, which is concordant with the 20% to 50% mortality rate reported in the domestic and foreign literature [15-17]. Males were more susceptible to sepsis. It is possible that male patients’ susceptibility to sepsis was related to their susceptibility to tumors or lung diseases such as chronic obstructive pul- monary disease; these results are also concordant with those reported in domestic and foreign studies [15,18]. Following the implementation of the SSC guidelines 2 years ago, the mortality rate of hospitalized patients with sepsis dropped from 37% to 30.8% [19]. Successful treatment of sepsis depends on early diagnosis. A previous study showed that PCT can aid in recognition of bacteremia [20], and some guidelines have therefore proposed PCT as a diagnostic index in sepsis [3]. Our study indicated that use of either suPAR or PCT levels to distinguish SIRS from sepsis generated a ROC curve with an AUC N 0.8. Therefore, these two indexes could be used in tandem to detect the early stage of Systemic Infection. The PCT cutoff point for distinguishing sepsis from SIRS was 0.675 ng/mL, similar to the results of previous studies [21,22]. Our findings indicated that an increase in PCT was valuable for identification of bacterial and non-bacterial infections [23]. In this study, most patients with sepsis had bacterial infections. Bacterial infections brought about a significant increase in suPAR levels, related to the order of Severity of disease. Whether infections with other pathogens cause an increase in suPAR levels has not yet been reported.

In this study (Table 3, Figure C), suPAR levels were observed to be decreasing in patients that survived sepsis. Meanwhile, the suPAR level in the mortality group fluctuated but remained high, indicating that high levels of suPAR are present in patients with severe sepsis. During the therapeutic process, the suspension of suPAR levels indicated a poor prognosis. Therefore, monitoring of suPAR levels aids in estimating patients’ condition and making prognoses. The prognostic value of suPAR was confirmed by a previous study [24]. In this study, analysis of ROC curves showed that suPAR was inferior to the APACHE II score but supe- rior to blood lactic acid and blood PCT and similar to the SOFA score for distinguishing the surviving and mortality groups. To predict mortality, the APACHE II score was better than the SOFA score, similar to the results of the study published by Duseja [25]. Our findings showed that when distinguishing survival from mortality using suPAR, the optimal cutoff

Table 5

The logistic regression model fitting results of suPAR, APACHE II score

Index variable Bate (B) SE Wald df P OR 95% CI for OR

Lower

Upper

suPAR

0.131

0.051

6.513

1

.011

1.140

1.031

1.260

APACHE II

0.206

0.055

13.994

1

b.001

1.228

1.103

1.368

Constant

-6.362

1.446

19.356

1

b.001

0.002

point was 12.01 ng/mL. At this point, the sensitivity was 87.1% and the specificity was 72.5%, indicating that suPAR had a better sensitivity in recognizing patients with a higher risk of mortality. This cutoff point was similar to those reported in a previous study [6]. As classic clinical severity scales, the APACHE II and SOFA scores are widely applied in clinical settings, and they help clinicians to judge the order of severity of disease and recognize critical patients in a timely fashion. The correla- tion analysis performed in our study revealed that suPAR and APACHE II score were positively correlated to the SOFA scoring system, which indicated that suPAR was positively correlated with the severity of sepsis. Therefore, suPAR can aid clinicians in recognizing high-risk patients, facilitating early treatment.

Our data indicated that in the early stage (days 1, 3, and 5) of sepsis, PCT levels did not differ between the surviving and mortality groups. However, at the later stage (day 7 and the day of discharge/mortality) the PCT level of the mortality group was significantly higher than that of the surviving group. This indicates that the PCT level cannot be used as an early index to distinguish patients likely to survive from those at high risk of mortality. However, a study published by Harbarth et al indicated that if the PCT level drops slowly or does not drop within 48 hours, it indicates a poor prognosis [23]. Therefore, the PCT level does not reflect the order of severity of sepsis, and dynamic changes in PCT are more valuable in evaluating severity.

A previous study indicated that the diel variation in suPAR (determined every 20 min in 24 h) is steady [26]. The suPAR level is also unaffected by diet [27]. Therefore, suPAR shows great promise for use as a biomarker.

In conclusion, blood suPAR rises significantly in patients with sepsis and it is also valuable for distinguishing SIRS from sepsis. Use of a com- bination of suPAR and PCT enhances the diagnostic efficiency for sepsis. As a marker that reflects the order of severity and the risk of mortality of sepsis at its early stage, suPAR is likely to be sustained at high levels in critical patients. A decrease in suPAR levels indicates that the infection is under control and the patient’s condition is improving. The combina- tion of plasma suPAR and APACHE II score enhances the efficiency of predicting mortality from sepsis.

Acknowledgments

This study was supported by a grant from the Science and Technol- ogy Program of Guangzhou City of China (2014Y2-00136) and a grant from the Science and Technology Program of Guangdong Province of China (2014A020212151).

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