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Prognostic significance of APACHE II score and plasma suPAR in Chinese patients with sepsis: a prospective observational study
© Liu et al. 2016
Received: 12 January 2016
Accepted: 15 July 2016
Published: 29 July 2016
Timely risk stratification is the key strategy to improve prognosis of patients with sepsis. Previous study has proposed to develop a powerful risk assessment rule by the combination of Acute Physiology and Chronic Health Evaluation II (APACHE II) score and plasma soluble urokinase plasminogen activator receptor (suPAR). That reaffirmation of suPAR as a prognostic marker in Chinese patients with severe sepsis is the aim of the study.
A total of 137 consecutive Chinese patients with sepsis were enrolled in a prospective study cohort. Demographic and clinical characteristics, conventional risk factors and important laboratory data were prospectively recorded. Sequential plasma suPAR concentrations were measured by an enzymeimmunoabsorbent assay on days 1, 3, and 7 after admission to the intensive care unit (ICU). Receiver operating characteristic (ROC) curves and Cox regression analysis were used to examine the performance of suPAR in developing a rule for risk stratification.
The results showed that plasma suPAR concentrations remained relatively stable within survivors and non-survivors during the first week of disease course. Regression analysis indicated that APACHE II ≥15 and suPAR ≥10.82 ng/mL were independently associated with unfavorable outcome. With the above cutoffs of APACHE II and suPAR, strata of disease severity were determined. The mortality of each stratum differed significantly from the others.
Combination of APACHE II score and suPAR may supply the powerful prognostic utility for the mortality of sepsis.
KeywordsSepsis Risk stratification Soluble urokinase plasminogen activator receptor (suPAR) Acute Physiology and Chronic Health Evaluation II (APACHE II)
The incidence of sepsis in adults has been increasing, with severe sepsis and septic shock remaining among the major causes of death worldwide . Despite the mortality is on a declining trend in recent years , low awareness, late recognition, and improper treatment are still common .
One of the fundamental principles for the appropriate management of sepsis is timely discrimination of the patients at high risk for death . This is generally dependent on the application of score systems and plasma biomarkers. Although the well-recognized score is the Acute Physiology and Chronic Health Evaluation II (APACHE II), APACHE II score has some potential pitfalls that may lead to inaccurate evaluation. Take young patients with severe sepsis but without chronic organ dysfunction for instance, the APACHE II score may be relatively low despite the risk for an unfavorable outcome is high .
Although various biological markers are widely explored [6–9], only a few have been applied in the clinical practice. The soluble urokinase plasminogen activator receptor (suPAR), which exists in three forms (I-III, II-III and I), is regarded as a novel biomarker of immune system activation . Urokinase plasminogen activator receptor (uPAR) is embedded in the cell membranes of various immunologically active cells and, with its ligand, urokinase plasminogen activator (uPA), takes part in a range of immunologic activities . Upon inflammatory stimulation, uPAR is cleaved from the cell surface by proteases into the soluble form of the receptor-suPAR-which can be assessed in blood, urine, bronchoalveolar lavage, and cerebrospinal fluid [12, 13]. Recent studies have revealed that suPAR may have the ability to predict the mortality of sepsis [14–17]. It is noteworthy that Giamarellos-Bourboulis et al. have proposed a new prognostication rule for predicting the outcome of sepsis by APACHE II score and suPAR .
The primary purpose of the present study was to further reaffirm the prediction rule for the mortality in Chinese patients with sepsis by combining APACHE II score and plasma suPAR concentrations.
This prospective trial involved consecutive Chinese patients with sepsis presenting to the intensive care unit (ICU) of the Department of Emergency, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, from March 2013 to February 2015.
For each patient with suspected infection, a complete diagnostic work-up was performed. The work-up comprised demographic and clinical characteristics, conventional risk factors, and important laboratory data including blood routine examination, microbiological culturing, chest x-ray, and chest or abdominal computed tomography if necessary. Broad spectrum antimicrobial treatment was used within 1 h from the recognition of the septic status.
Patients were eligible if they met the inclusion criteria: (1) age of at least 18 years; (2) sepsis due to one of the following infections: community acquired pneumonia, hospital acquired pneumonia, ventilator-associated pneumonia, acute pyelonephritis, intra-abdominal infection, or primary bacteremia; and (3) blood sampling within 24 h from the presentation of signs of sepsis. Patients affected by advanced cancer or terminal patients with other pathologies were excluded.
All eligible patients were further classified according to standard definitions of sepsis, severe sepsis, and septic shock . More specifically, sepsis was defined as the presence of suspected or confirmed infection together with two or more criteria for a systemic inflammatory response; severe sepsis was defined as sepsis with sepsis-induced organ dysfunction, hypotension or hypoperfusion; septic shock was defined as refractory hypotension or hypoperfusion despite sufficient fluid resuscitation.
Venous blood (3 mL) was collected from patients presenting to the ICU (day 1) and repeated on the following day 3 and day 7 after admission. Whole blood was drawn into a centrifuge tube containing EDTA anti-coagulant. After centrifugation at 3,000 g for 10 min at 4 °C, plasma samples were kept frozen at −80 °C until assayed. suPAR was determined in duplicate by a commercial double monoclonal antibody sandwich enzyme immunoassay (suPARnostic® Standard kit; ViroGates A/S, Birkerød, Denmark) in accordance with the instructions of the manufacturer. Every 45 blood samples can be measured within about 4 h. The linearity of this assay is comprised between 2.0 and 15.6 ng/mL, and the total imprecision, expressed as coefficient of variation (CV %), ranges from 2.3 to 6.0 %.
Patients who survived were further followed up by telephone calls. The unfavorable outcome of the study was defined as death from any cause within 28 days after admission to the ICU.
Continuous variables were presented as mean values ± standard deviation (SD) or median with interquartile ranges (IQR), while categorical variables were expressed as percentages. The statistical significance of intergroup differences was compared through unpaired Student’s t-test or Mann–Whitney U test for continuous variables and through Pearson’s χ 2 test for categorical variables.
The following steps were performed to establish a risk stratification rule: First, receiver operating characteristic (ROC) analysis was conducted with baseline levels of APACHE II score and suPAR to determine the prediction sensitivity and specificity of the variables. Second, we used univariate and multivariate Cox regression analyses to calculate hazard ratios (HR) with 95 % confidence intervals (CIs). Third, strata of disease severity were established using the cutoffs of APACHE II score and suPAR. Odds ratios (OR) and 95 % CIs for risk prediction within each stratum were assessed using Mantel and Haenszel statistics. Fourth, mortalities between strata were estimated using the log-rank test.
A two-sided P value < 0.05 was considered statistically significant. All analyses were performed by the IBM SPSS Statistics software version 19.0 (SPSS, Chicago, IL, USA).
Baseline characteristics of the study population
Baseline clinical and laboratory characteristics of the study subjects
Demographics and underlying conditions
Number of patients
Males, no. (%)
Age (years), mean ± SD
COPD, no (%)
Hypertension, no (%)
Diabetes mellitus, no (%)
68.04 ± 9.36
71.39 ± 8.85
69.16 ± 9.73
Baseline parameters, mean ± SD
APACHE II score
9.87 ± 3.12
5.26 ± 2.09
12.50 ± 4.75
7.83 ± 2.53
18.34 ± 6.09
11.42 ± 3.74
White blood cell count (109/L)
6.58 ± 3.17
6.14 ± 3.54
11.96 ± 2.866
8.62 ± 4.80
11.05 ± 4.60
18.26 ± 3.98
15.97 ± 5.44
27.69 ± 7.28
26.67 ± 7.04
Lactic acid (mmol/L)
1.75 ± 1.16
3.27 ± 1.48
6.03 ± 3.82
Plasma glucose (mmol/L)
6.42 ± 3.85
70.32 ± 19.56
31.23 ± 10.27
32.95 ± 11.02
14.60 ± 8.03
154.19 ± 71.52
7.25 ± 4.89
109.84 ± 33.14
9.05 ± 4.13
103.59 ± 31.07
45.62 ± 16.44
60.38 ± 21.37
16.23 ± 9.15
134.08 ± 75.17
8.35 ± 5.18
117.08 ± 20.49
11.91 ± 9.39
154.08 ± 40.87
153.89 ± 48.01
196.35 ± 65.29
20.01 ± 9.66
127.60 ± 65.95
10.02 ± 7.11
118.05 ± 20.65
Pathogen strains, no (%)
Other Gram-negative bacteria
5 (15.63 %)
Site of infection, no (%)
Intervention, no (%)
Study outcome, no (%)
There were no significantly statistical differences in patients with sepsis compared to those in severe sepsis or septic shock for gender or age. Patients with severe sepsis or septic shock tended to have higher baseline levels of APACHE II score, Sequential Organ Failure Assessment (SOFA) score, suPAR, procalcitonin (PCT) and lactic acid compared with patients with sepsis. In addition, there were 19 patients (13.87 %) receiving mechanical ventilation treatment, 23 patients (16.79 %) receiving continuous renal replacement therapy, and 17 patients (12.41 %) receiving vasopressor support. There were significant differences in the proportion of patients receiving mechanical ventilation, continuous renal replacement therapy or vasopressor support among the three groups (Table 1).
Kinetics of suPAR
Value of indicators in predicting poor outcome
Performance of variables in predicting unfavorable outcome
APACHE II score SOFA score
0.813 ± 0.055
0.779 ± 0.075
0.788 ± 0.058
0.651 ± 0.081
Univariate Cox regression analysis
Predictors of unfavorable outcome by univariate Cox regression analysis
95 % CI
APACHE II score
Multivariate Cox regression analysis
Independent predictors of unfavorable outcome by multivariate Cox regression analysis
95 % CI
APACHE II score
Validation of the novel stratification rule
Survivors, Number (%)
Non-survivors, Number (%)
OR (95 % CI)
Risk stratification rule of APACHE II score and suPAR
Undoubtedly, APACHE II score has been advocated as the gold standard for risk evaluation in critically ill patients . Nevertheless, a growing body of evidence has suggested that the score may supply inaccurate information in the certain patients, such as disproportionately high scores in patients who are loss of consciousness . This translates into a real-world context in which the efficacy of APACHE II score to predict death is not as powerful as clinicians would consider.
To our knowledge, previous study conducted by Giamarellos-Bourboulis et al. has proposed a new prognostication rule for predicting the outcome of sepsis by APACHE II score and suPAR . Our study was to further reaffirm the risk stratification system for Chinese patients with sepsis by combining APACHE II score and plasma suPAR concentrations. There were some differences between our study and Giamarellos-Bourboulis’s study. First, the enrolled patients of the two studies were from different ethnic groups. We enrolled Asian populations (Chinese origin), while Giamarellos-Bourboulis et al. mainly enrolled the European populations. Second, the cutoffs of APACHE II and suPAR which were used to determine the strata of disease severity were not uniformly the same. Specifically, our study indicated that APACHE II ≥15 and suPAR ≥10.82 ng/mL were independently associated with unfavorable outcome while Giamarellos-Bourboulis’s study showed that APACHE II ≥17 and suPAR ≥12 ng/ml were the optimal cutoffs. Third, we constructed ROC analysis and calculated the AUC to compare the performance of suPAR, PCT, APACHE II score, and SOFA score as predictors of poor outcome. We found that suPAR had a strong power for predicting unfavorable outcome as suggested by AUC of 0.788 ± 0.058, which was less than that of APACHE II score (0.813 ± 0.055) but greater than that of SOFA score (0.779 ± 0.075) and PCT (0.651 ± 0.081). However, Giamarellos-Bourboulis et al. just conducted ROC analysis with suPAR and APACHE II score as independent variables to predict unfavorable outcome. Taken together, given enrolled patients were from different ethnic groups, our study may further confirm the preliminary conclusion that a prediction rule with four levels of risk in sepsis based on APACHE II score and suPAR was proposed.
Similar to the findings of a previous clinical trial concerning plasma suPAR measurement , our study clearly showed that suPAR concentrations were relatively stable in the systemic circulation in both survivors and non-survivors during the first week of the disease course. Therefore, we infer that the validity of the developed prognostication score remains constant even if suPAR is not measured during the very first days after ICU admission due to the stability of suPAR concentrations over the disease course. These findings were comparable to other diseases including chronic obstructive pulmonary disease (COPD)  or acute respiratory distress syndrome (ARDS) , in which suPAR was regarded as an independent predictor for unfavorable outcomes.
Severe sepsis has a reported annual incidence in adults of up to 300 cases per 100,000 population [23, 24]. Affected patients have high mortalities, complications, and resource utilization. Although figures have improved in the recent years [2, 3], the risk for death remains high . Consequently, improving outcome may be a daunting work. One of pivotal measures is to identify the septic patients with poor prognosis rapidly . Our study suggested one composite rule for determining patients with sepsis at high risk on the basis of APACHE II score and plasma suPAR concentrations. Actually, the measurement procedure is so simple that we can complete the measurement for every 45 patient samples within about 4 h. The price for the measurement is also relatively reasonable and we only spend 6,000 CNY (about 924 USD) on evaluating 45 patient samples, that means we need spend about 133 CNY (20 USD) on measuring one patient sample. Undoubtedly, the suPAR measurement is relatively cost-effective. Therefore, given the simple and inexpensive measurement, the combination of APACHE II score and plasma suPAR concentrations may contribute to intensive care management in the septic patients properly.
Currently, evidence has suggested that the value of single scoring system as a standard of clinical decision-making in septic patients is questionable. APACHE II score is likely to recognize either low-risk patients or very-high-risk patients, but not these patients between the two extremes . The proposed risk stratification rule fulfills this need because it discriminates not only patients lying at one of the two extremes - strata (A) and (D) - but also patients with moderate disease severity, namely patients with an APACHE II score of less than 15 and suPAR of at least 10.82 ng/mL or patients with an APACHE II score of at least 15 and suPAR of less than 10.82 ng/mL, who belong to strata (B) and (C), respectively.
In summary, combination of APACHE II score and suPAR may supply the powerful prognostic utility for the mortality of sepsis. Our findings suggest that incorporating suPAR into APACHE II score as a composite risk stratification rule for sepsis is worth considering.
APACHE II, Acute Physiology and Chronic Health Evaluation II; ARDS, acute respiratory distress syndrome; AUC, area under the curve; CI, confidence interval; COPD, chronic obstructive pulmonary disease; ICU, intensive care unit; IQR, interquartile ranges; OR, odds ratio; PCT, procalcitonin; ROC, receiver operating characteristic; SD, standard deviation; SOFA, sequential organ failure assessment; suPAR, soluble urokinase plasminogen activator receptor; uPA, urokinase plasminogen activator; uPAR, urokinase plasminogen activator receptor
This work was financially supported by the grant from the 2013-2014 National Clinical Key Specialty Construction Project.
Availability of data and materials
All datasets are presented in the main paper or additional supporting files.
XL and SP have made substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; XL, YS, and ZL have been involved in drafting the manuscript or revising it critically for important intellectual content; AF and HW have given final approval of the version to be published; QG and SP have agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
The study was approved by Shanghai Jiaotong University Xinhua Hospital Ethics Committee and was carried out in accordance with the Declaration of Helsinki. Informed consents were obtained from all patients.
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