• Users Online: 315
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 6  |  Issue : 3  |  Page : 313-320

Presepsin as a predictor of sepsis outcome in comparison with procalcitonin and C-reactive protein


1 Critical Care Medicine Department, Beni Suef University, Beni Suef, Egypt
2 Critical Care Medicine Department, Cairo University, Giza, Egypt

Date of Submission02-Jul-2018
Date of Acceptance12-Apr-2019
Date of Web Publication29-Aug-2019

Correspondence Address:
MD Khaled M Taema
7985 Almadeena Almonawara Street, Mokattam, Cairo 11571
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/roaic.roaic_52_18

Rights and Permissions
  Abstract 

Introduction Identification of predicted sepsis-related mortality is important for patient stratification. We evaluated the significance of presepsin in predicting sepsis-related mortality.
Patients and Methods We enrolled 83 patients with sepsis according to the SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference in a prospective observational study.
Results After excluding 28 patients owing to different exclusion criteria, 55 continued the study. Their age was 58 (47–65) years old and comprised 33 (60%) males. We measured serum presepsin, procalcitonin (PCT), and C-reactive protein (CRP) on admission and 24 and 72 h later. Acute Physiology and Chronic Health Evaluation II score and capillary leak index were estimated. The primary outcome was in-hospital mortality. The median (Q1–Q3) presepsin24 and presepsin72 levels were 127.5 (835.75–2137.5) and 883 (429–1214.5) pg/ml, respectively, in survivors compared with 2321 (1264–3456) and 3421 (1900–5432) pg/ml, respectively, in nonsurvivors (P=0.01 and 0.000, respectively). The serum CRP24 and CRP72 were 123 (76–154) and 94 (42.5–127) mg/l, respectively, in survivors compared with 156 (101–201) and 187 (139–233) mg/l, respectively, in nonsurvivors (P=0.02 and 0.000, respectively). PCT72 was 111.5 (66–186.25) pg/ml in survivors compared with 231 (187–324) pg/ml in nonsurvivors (P=0.000). Presepsin0, CRP0, PCT0, and PCT24 were not significantly different between survivors and nonsurvivors (P=0.4, 0.7, 0.5, and 0.2, respectively). The Acute Physiology and Chronic Health Evaluation II score was 18 (15–20.8) in survivors compared with 21 (19–24) in nonsurvivors, (P=0.02), whereas the capillary leak index was 42 (27.6–57.7) and 42.4 (33.3–62.3) in survivors and nonsurvivors, respectively (P=0.8). The area under the curve was the highest for presepsin72 (0.918). Presepsin72 of 1262 pg/ml was seen to be 92.3% sensitive and 81.3% specific for mortality prediction.
Conclusion This study showed that the serum presepsin could be a valuable biomarker for predicting in-hospital mortality in sepsis.

Keywords: C-reactive protein, presepsin, procalcitonin, sepsis prognosis


How to cite this article:
Mahmoud AM, Sherif HM, Saber HM, Taema KM. Presepsin as a predictor of sepsis outcome in comparison with procalcitonin and C-reactive protein. Res Opin Anesth Intensive Care 2019;6:313-20

How to cite this URL:
Mahmoud AM, Sherif HM, Saber HM, Taema KM. Presepsin as a predictor of sepsis outcome in comparison with procalcitonin and C-reactive protein. Res Opin Anesth Intensive Care [serial online] 2019 [cited 2019 Nov 18];6:313-20. Available from: http://www.roaic.eg.net/text.asp?2019/6/3/313/265722


  Introduction Top


Sepsis is a well-known cause of death in critically ill. It was involved accordingly in many publications of the critical care medicine [1]. The patients’ response to sepsis syndrome is extremely complex. It involves many inflammatory and anti-inflammatory reactions, endothelial and cellular dysfunction, and the release of innumerable humoral responses that could be used as biomarkers [2]. The evaluation of sepsis severity and outcome is complicated by the lack of gold standard for the diagnosis of sepsis and the variability in its presentation [3]. Many scores and biomarkers had been studied in this perspective, with Acute Physiology and Chronic Health Evaluation II (APACHE II) score being traditionally used for this context [4],[5],[6],[7].

sCD14 subtypes (presepsin) is a biomarker that was evaluated for the diagnosis and prognosis of sepsis [8]. Compared with other biomarkers, presepsin seems to have a better sensitivity and specificity in the prognostic evaluation of sepsis. It was found that the plasma concentration of presepsin is significantly higher in nonsurvivors of sepsis [9].

This study was intended to assess the prognostic significance of presepsin in sepsis evaluation in comparison with procalcitonin (PCT) and C-reactive protein (CRP).


  Patients and methods Top


Our study was done as a prospective observational cohort study including patients admitted to a single critical care center with sepsis during the period from January 2014 to December 2014. Sepsis was identified as the presence of SIRS according to the SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference [10] exhibiting two or more of the following signs: (a) temperature of more than 38°C or less than 36°C, (b) pulse rate of more than 90 beats/min, (c) respiratory rate of more than 20 breaths/min or hyperventilation with a partial pressure of arterial carbon dioxide of less than 32 mmHg, or (d) white blood cell count of more than 12 000/mm3 or less than 4000/mm3, or more than 10% immature cells in addition to the presence of infection identified by two independent experts according to the clinical and microbiological criteria of the CDC definitions [11].

Excluded from that study were patients less than 17 years old, patients who had received anti-inflammatory drugs or corticosteroids before admission, patients who received blood transfusion before enrollment, patients with terminal disease (e.g. metastatic malignancy), or those who died within 24 h of enrollment.

Full history taking and physical examination was done for all included patients, with Acute Physiology and Chronic Health Evaluation II score (APACHE II score) assessed on admission [6].

Routine laboratory investigations were done including complete blood count, alanine transaminase, aspartate transaminase, total and direct bilirubin, total protein, serum albumin, Prothrombin concentration (PC), Prothrombin time (PT), international normalization ratio, serum electrolytes, for example, Na+ and K+, and arterial blood gases.

At least two blood cultures from different sites were collected from each patient on admission. Cultures from any suspected site of infection such as sputum, wound, or urine were collected on admission.

Serum levels of presepsin were assessed on admission (presepsin0), 24 h (presepsin24), and 72 h (presepsin72) after admission. Presepsin was estimated using immunoassay analyzer (PATHFAST; Mitsubishi Chemical Medience Corporation, Tokyo, Japan) [12]. Presepsin level was expressed as pg/ml; normal value is 60–360 pg/ml.

Serum levels of PCT were done using ELISA technique on admission (PCT0), 24 h (PCT24), and 72 h (PCT72) after admission. PCT level was expressed as pg/ml; normal value is less than 150 pg/ml.

Serum levels of CRP using ELISA technique were done on admission (CRP0), 24 h (CRP24), and 72 h (CRP72) after admission [13]. CRP level was expressed as mg/l; normal value is 1–3 mg/l.

We estimated the change of different biomarkers over time by the formulas Δpresepsin=presepsin72−presepsin0, ΔPCT=PCT72−PCT0, and ΔCRP=CRP72−CRP0. Presepsin, PCT, and CRP were considered either increasing if 72-h measurements were more than day 0 measurements or decreasing if 72-h measurements were less than day 0 measurements.

The capillary leak index (CLI) was calculated as the admission CRP (mg/l) divided by the serum albumin (g/l) [7].

The primary outcome of the study was the in-hospital mortality, whereas the secondary outcome was the average ICU length of stay (ICU-LOS).

The study protocol was approved by the institutional review board at Cairo University.

Statistical analysis

Data were prospectively collected and coded before analysis using the statistical package of the social sciences (SPSS version 22, IBM, USA). Normal distribution of different dependent variables in relation to their independent variables was studied. A variable was considered normally distributed if the Shapiro–Wilk’s test had a P value more than 0.05 [14],[15] and with z-value of skewness and kurtosis between −1.96 and +1.96 [16]. Most of the variables were non-normally distributed. Accordingly, continuous variables were expressed as median, 25th, and 75th quartiles [median (Q1–Q3)]. Categorical variables were expressed as frequency and proportion. When two groups were studied, all variables were non-normally distributed. Accordingly, nonparametric test (Mann–Whitney U-test) was used for comparison between two groups regarding quantitative variables. χ2 was used for comparison between two groups regarding qualitative data. Exact test was used instead when the expected frequency is less than 5. Spearman correlation coefficient test (r) was used to test a positive or negative correlation between two variables (nonparametric). Receiver operator characteristic analysis was performed to define a cutoff value of a variable. The best cutoff values were calculated by using the Youden’s index. Youden’s index was estimated as (sensitivity+specificity) −1. The best cutoff values are those associated with highest index. Results were considered statistically significant if P value up to 0.05.


  Results Top


A total of 83 patients were initially recruited for the study with the initial diagnosis of sepsis. After initial enrollment, 10 patients were excluded as they were maintained on corticosteroids and/or immunosuppressant therapy before admission, five were excluded owing to terminal disease, four received blood transfusion before enrollment, and nine died within 24 h of admission.

The remaining 55 patients represented the study population. They had a mean age of 58 (47–65) years old. There were 33 (60%) males and 22 (40%) females.

The baseline hemodynamics and the source of infection of the included population are seen in [Table 1], and the baseline laboratory findings are seen in [Table 2].
Table 1 Baseline hemodynamics and source of infection in our population

Click here to view
Table 2 The baseline laboratory findings

Click here to view


APACHE II score of our population was 20 (18–23). CLI was 42.4 (31.6–58.9) mg/g. Of our 55 patients, 47 (85.5%) needed mechanical ventilation, 44 (80%) needed vasoactive and/or inotropic support, and 12 (21.8%) needed renal replacement therapy. The ICU-LOS was 11 (9–13) days. Thirty-nine of our patients died, with an in-hospital mortality rate of 70.9%.

We measured presepsin, PCT, and CRP on admission and 24 and 72 h later. Presepsin0 had a median (Q1–Q3) of 1322 (890–2437) pg/ml. Presepsin24 was 1879 (997–3421) pg/ml and presepsin72 was 2313 (1156–4331) pg/ml. PCT0 was 165 (79–231) pg/ml, PCT24 was 189 (111–254) pg/ml, and PCT72 was 198 (121–319) pg/ml. CRP0 was 123 (89–177) mg/l, CRP24 was 154 (98–189) mg/l, and CRP72 was 150 (111–211) mg/l.

The presepsin and PCT were decreased in 14 (25.5%) patients by 1242 (308–2537) and 55 (29.5–103.5) pg/ml, respectively and, were increased in 41 (74.5%) patients by 1412 (792.5–2758) and 78 (33.5–130) pg/ml, respectively. The CRP was decreased in 13 (23.6%) patients by 67 (50–87.5) mg/l, and it was increased in 42 (76.4%) patients by 60.5 (32–90.75) mg/l.

None of the studied biomarkers nor APACHE II score or CLI was significantly correlated with the ICU-LOS ([Table 3]).
Table 3 The correlation between different biomarkers and ICU length of stay

Click here to view


The presepsin24, presepsin72, CRP24, and CRP72 whereas not on admission were predictors for mortality. The presepsin24 and presepsin72 were 1127.5 (835.75–2137.5) and 883 (429–1214.5) pg/ml, respectively, in survivors compared with 2321 (1264–3456) and 3421 (1900–5432) pg/ml, respectively, in nonsurvivors (P=0.01 for presepsin24 and 0.000 for presepsin72). The serum CRP24 and CRP72 were 123 (76–154) and 94 (42.5–127) mg/l, respectively, in survivors compared with 156 (101–201) and 187 (139–233) mg/l, respectively, in nonsurvivors (P=0.02 for CRP24 and 0.000 for CRP72). The presepsin0 and CRP0 were, however, 1573 (945.5–3547.75) pg/ml and 133 (89.25–184.75) mg/l, respectively, in survivors compared with 1276 (890–2321) pg/ml and 123 (89–165) mg/l, respectively, in nonsurvivors (P=0.4 and 0.7 for presepsin0 and CRP0, respectively).

Only PCT72 was significantly lower in survivors and not PCT0 or PCT24. The PCT0 and PCT24 were 192 (115.5–233.25) and 162 (98–207.5) pg/ml, respectively, in survivors compared with 156 (78–231) and 198 (123–289) pg/ml, respectively, in nonsurvivors (P=0.5 and 0.2 for PCT0 and PCT24, respectively). PCT72 was 111.5 (66–186.25) pg/ml in survivors compared with 231 (187–324) pg/ml in nonsurvivors (P=0.000; [Figure 1]).
Figure 1 The three measured biomarkers in survivors and nonsurvivors. (a) The three measured presepsin levels in survivors and nonsurvivors. (b) The three measured CRP levels in survivors and nonsurvivors. (c) The three measured procalcitonin levels in survivors and nonsurvivors.

Click here to view


The APACHE II score but not the CLI was shown to be a significant mortality predictor. APACHE II score was 18 (15–20.8) in survivors compared with 21 (19–24) in nonsurvivors (P=0.02), whereas the CLI was 42 (27.6–57.7) and 42.4 (33.3–62.3) for survivors and nonsurvivors, respectively (P=0.8).

The cutoff values for mortality prediction were evaluated for the significant predictors using receiver operator characteristic analysis ([Figure 2]). The area under the curve was the highest for presepsin72 (0.918). It was seen that presepsin level of 1262 pg/ml at 72 h following admission is 92.3% sensitive and 81.3% specific for mortality prediction in patients with sepsis ([Table 4]).
Figure 2 Receiver operator characteristic curve for different variables.

Click here to view
Table 4 The area under the curve, the sensitivity, and the specificity of different variables for mortality prediction

Click here to view


The trend of the biomarkers was evaluated for mortality prediction. The increase of the three biomarkers was seen to be significantly associated with mortality ([Table 5]). The increase of presepsin over time was seen to be 100% sensitive and 87.5% specific for predicting mortality, with Positive predictive value (PPV) and Negative predictive value (NPV) of 95.1 and 100%, respectively ([Table 6]).
Table 5 The relation between the trend of the biomarkers and mortality

Click here to view
Table 6 The sensitivity, specificity, PPV, and NPV for the trend of different biomarkers

Click here to view



  Discussion Top


Identification of sepsis prognosis and predicted mortality is an important factor in patient stratification and management. High-risk patients may benefit from earlier interventions. The early prediction of mortality and ICU-LOS in critically ill patients is a cornerstone in patient/family counseling, an important socioeconomic factor, and improves satisfaction [17]. Traditionally, the APACHE II score was used in this context [6].

We intended in this study to evaluate the prognostic value of monitoring presepsin level in patients with sepsis and to compare it with PCT and CRP. We compared it also with the commonly used APACHE II score and with the CRP, PCT and CLI. We included a cohort of 55 patients with sepsis.

Till starting patient recruitment for this study, the gold standard for the diagnosis of sepsis was the 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference [10]. More recently following this study, a newer definition for sepsis was published considering ‘confirmed’ or ‘suspected’ infection as a prerequisite [18].

Our results demonstrated that none of the biomarkers studied nor APACHE II score and CLI were correlated with the ICU-LOS. These results are against the results of many others who revealed a positive correlation between average LOS and the APACHE II score, presepsin levels, and CRP levels [4],[5],[19],[20]. They explained this association with the more lengthy ICU care by more disease severity. We included a cohort of patients with severe disease parameters indicated by the high median APACHE II score and a high in-hospital mortality of 70.9%. Early death of patients made it difficult to study the association with ICU-LOS in our study.

This study revealed that the presepsin and CRP levels after 24 and 72 h and not on admission can predict mortality. PCT after 72 h and admission APACHE II score were also significantly higher in nonsurvivors. The area under the curve (AUC) for the presepsin72 for survival prediction was the highest (0.918) compared with PCT (0.84), CRP (0.888), and APACHE II score (0.695), with cutoff value of 1262 pg/ml to be 92.3% sensitive and 81.3% specific for predicting mortality in patients with sepsis.

El-Shafie et al. [9] showed that presepsin measures on admission and 2 and 4 days after admission are mortality predictors but none of the CRP measures. They revealed an AUC of 0.834 for presepsin at 4 days after admission compared with 0.918 in our study. A lower cut of value of only 900 pg/ml was found to be 73% sensitive and 100% specific for predicting mortality. They, however, included all patients admitted by SIRS rather than sepsis only, as we did. Behnes et al. [19] found that the presepsin levels on days 1, 3, and 8 of admission as well as the APACHE II score but not the PCT nor the CRP levels had a significant 30-day and 6-month mortality prediction. The AUC for day 3 presepsin and APACHE II score were 0.70 for 30-day mortality. On admission to the emergency department, Liu et al. [21] showed that the APACHE II score and PCT had higher AUC for 28-day mortality prediction (0.722 and 0.679, respectively) compared with presepsin (0.679). Compared with our study, they considered the T0 measures of ED admission, which was not significant mortality predictor in our study, but they used longer term mortality than we did (28-day mortality rather than in-hospital mortality). Liu et al. [21] had much lower cutoff value of presepsin than ours (556 pg/ml) to be 62% sensitive and 66% specific for mortality prediction. Ulla et al. [22] found that despite the ED admission presepsin level is significantly higher in nonsurvivors, the PCT was not. Silvesta et al. [23] showed similar results to ours regarding the lack of association between CRP and mortality which contradicts other results [24]. Presepsin, PCT, and CRP were also found to be elevated in nonsurvivors of patients with septic burn [25]. In a Korean population, Kweon et al. [26] found, however, that the presepsin does not correlate with 30-day mortality. In a systematic review and meta-analysis published in January 2018, Yang et al. [27] showed, however, that the first-day presepsin level had prognostic value to predict in-hospital or 30-day mortality in adult patients with sepsis.

In a prospective cohort study, Pettila et al. [28] showed, like us, that the PCT on day 3 is higher in nonsurvivors, whereas unlike our results, the CRP levels on days 1 and 3 were similar in survivors and nonsurvivors. They found an AUC for hospital mortality of 0.75 compared with 0.841 in our study.

Zhang et al. [29] studied the biomarkers for longer duration when the CRP and PCT were found to be significantly higher in nonsurvivors at days 10 and 14 after admission, with no significant difference between them in both groups up to 7 days of admission. They considered that PCT was more of a diagnostic tool rather than a prognostic tool. Others found that the baseline CRP did not differ between survivors and nonsurvivors whereas the PCT levels in nonsurvivors were almost four times higher than levels in survivors [30]. In a smaller study of 20 patients with sepsis and severe sepsis, both CRP and PCT were higher in nonsurvivors than survivors [31]. These findings might support the use of presepsin for predicting patients with more severe sepsis with worse outcome.

CLI was proposed by Malbrain et al. [7] to predict disease severity in patients with sepsis. They found that the CLI is correlated with LS, use of ICU resources, and organ failure. They also found that the CLI is an independent predictor for mortality. It was assumed that an increased CRP [32] and decrease albumin [33] with the systemic inflammation of sepsis are the basis of this index. The lack of efficacy of the CLI was explained by the fact that it reaches its maximum on the third day of sepsis [34] and we estimated it using the admission measures only.

Rather than the absolute value of the biomarker, we studied its trend over time. We found that the decrease of the serum level of the three studied biomarkers was significantly associated with survival, with best sensitivity and specificity for presepsin (90 and 100%, respectively). In another Egyptian population but with patients with SIRS rather than those with only sepsis, El-Shafie et al. [9] found that decreasing trend of presepsin was 70% sensitive and 91% specific for predicting survival; however, they found no association between CRP trend and survival. Endo et al. [35] divided patients with sepsis to favorable and unfavorable groups and found that the patients with favorable group exhibited significant decrease of presepsin, PCT, and CRP on day 3, whereas in the unfavorable group, only presepsin did not decrease significantly.

Our study was limited by the small number of the study sample, which included only 55 patients. Owing to the small sample size, we could not analyze the relationship between the studied biomarkers and the infection site or the organism type. We considered only the in-hospital mortality rather than the long-term follow-up.


  Conclusion Top


This study showed that the serum presepsin is a valuable biomarker in term of risk stratification and in in-hospital mortality prediction of patients with sepsis and might be more accurate than PCT and CRP in this context.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 2001; 29:1303–1310.  Back to cited text no. 1
    
2.
Hotchkiss RS, Karl IE. The pathophysiology and treatment of sepsis. N Engl J Med 2003; 348:138–150.  Back to cited text no. 2
    
3.
Lever A, Mackenzie I. Sepsis: definition, epidemiology, and diagnosis. Br Med J 2007; 335:879–883.  Back to cited text no. 3
    
4.
Cesur S, Şengül A, Kurtoğlu Y, Kalpakçı Y, Özel SA, Bilgetürk A et al. Prognostic value of cytokines (TNF-α,IL-10, leptin) and C-reactive protein serum levels in adult patients with nosocomial sepsis. J Microbiol Infect Dis 2011; 1:101–109.  Back to cited text no. 4
    
5.
Barie P, Hydo L, Fischer E. Utility of illness severity scoring for prediction of prolonged surgical critical care. J Trauma 1996; 40:513–519.  Back to cited text no. 5
    
6.
Knaus WA, Draper EA, Wagner DP, Zimmerman J. APACHE II: a severity of disease classification system. Crit Care Med 1985;13:818–829.  Back to cited text no. 6
    
7.
Malbrain ML, Debaveye Y, De Coninck J, Delmarcelle D. Capillary leakage index as outcome predictor? Intensive Care Med 2001; 27:S229.  Back to cited text no. 7
    
8.
Yaegashi Y, Shirakawa K, Sato N, Suzuki Y, Kojika M, Imai S et al. Evaluation of a newly identified soluble CD14 subtype as a marker for sepsis. J Infect Chemother 2005; 11:234–238.  Back to cited text no. 8
    
9.
El-Shafie MES, Taema KM, El-Hallag MM, Kandeel AMA. Role of presepsin compared to C-reactive protein in sepsis diagnosis and prognostication. Egypt J Crit Care Med 2017; 5:1–12.  Back to cited text no. 9
    
10.
Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Intensive Care Med 2003; 29:530–538.  Back to cited text no. 10
    
11.
Garner JS, Jarvis WR, Emori TG, Horan TC, Hughes JM. CDC definitions for nosocomial infections, 1988. AJIC Am J Infect Control 1988; 16:128–140.  Back to cited text no. 11
    
12.
Okamura Y, Yokoi H. Development of a point-of-care assay system for measurement of presepsin (sCD14-ST). Clin Chim Acta 2011; 412: 2157–2161.  Back to cited text no. 12
    
13.
Póvoa P, Coelho L, Almeida E, Fernandes A, Mealha R, Moreira P et al. C-reactive protein as a marker of infection in critically ill patients. Clin Microbiol Infect 2005; 11:101–108.  Back to cited text no. 13
    
14.
Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika 1965; 52:591–611.  Back to cited text no. 14
    
15.
Razali NM, Wah YB. Power comparisons of Shapiro-Wilk,Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. J Stat Model Anal 2011; 2:21–33.  Back to cited text no. 15
    
16.
Doane DP, Seward LE. Measuring skewness: a forgotten statistic? J Stat Educ 2011; 19: 1–18.  Back to cited text no. 16
    
17.
Rapoport J, Teres D, Zhao Y, Lemeshow S. Length of stay data as a guide to hospital economic performance for ICU patients. Med Care 2003; 41:386–397.  Back to cited text no. 17
    
18.
Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315:801–810.  Back to cited text no. 18
    
19.
Behnes M, Bertsch T, Lepiorz D, Lang S, Trinkmann F, Brueckmann M et al. Diagnostic and prognostic utility of soluble CD 14 subtype (presepsin) for severe sepsis and septic shock during the first week of intensive care treatment. Crit Care 2014; 18:507.  Back to cited text no. 19
    
20.
Schmit X, Vincent JL. The time course of blood c-reactive protein concentrations in relation to the response to initial antimicrobial therapy in patients with sepsis. Infection 2008; 36:213–219.  Back to cited text no. 20
    
21.
Liu B, Chen YX, Yin Q, Zhao YZ, Li CS. Diagnostic value and prognostic evaluation of Presepsin for sepsis in an emergency department. Crit Care 2013; 17:R244.  Back to cited text no. 21
    
22.
Ulla M, Pizzolato E, Lucchiari M, Loiacono M, Soardo F, Forno D et al. Diagnostic and prognostic value of presepsin in the management of sepsis in the emergency department: a multicenter prospective study. Crit Care 2013; 17:R168.  Back to cited text no. 22
    
23.
Silvestre J, Póvoa P, Coelho L, Almeida E, Moreira P, Fernandes A et al. Is C-reactive protein a good prognostic marker in septic patients? Intensive Care Med 2009; 35:909–913.  Back to cited text no. 23
    
24.
Ho KM, Lee KY, Dobb GJ, Webb SAR. C-reactive protein concentration as a predictor of in-hospital mortality after ICU discharge: a prospective cohort study. Intensive Care Med 2008; 34:481–487.  Back to cited text no. 24
    
25.
Cakir Madenci O, Yakupoglu S, Benzonana N, Yucel N, Akbaba D, Orcun Kaptanagasi A. Evaluation of soluble CD14 subtype (presepsin) in burn sepsis. Burns 2014; 40:664–669.  Back to cited text no. 25
    
26.
Kweon OJ, Choi JH, Park SK, Park AJ. Usefulness of presepsin (sCD14 subtype) measurements as a new marker for the diagnosis and prediction of disease severity of sepsis in the Korean population. J Crit Care 2014; 29:965–970.  Back to cited text no. 26
    
27.
Yang HS, Hur M, Yi A, Kim H, Lee S, Kim SN. Prognostic value of presepsin in adult patients with sepsis: systematic review and meta-analysis. PLoS One 2018; 13:e0191486.  Back to cited text no. 27
    
28.
Pettila V, Hynninen M, Takkunen O, Kuusela P, Valtonen M. Predictive value of procalcitonin and interleukin 6 in critically ill patients with suspected sepsis. Intensive Care Med 2002; 28:1220–1225.  Back to cited text no. 28
    
29.
Zhang J, She D, Feng D, Jia Y, Xie L. Dynamic changes of serum soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) reflect sepsis severity and can predict prognosis: a prospective study. BMC Infect Dis 2011; 11:53.  Back to cited text no. 29
    
30.
Gibot S, Cravoisy A, Kolopp-Sarda MN, Bene MC, Faure G, Bollaert PE et al. Time-course of sTREM (soluble triggering receptor expressed on myeloid cells)-1, procalcitonin, and C-reactive protein plasma concentrations during sepsis. Crit Care Med 2005; 33: 792–796.  Back to cited text no. 30
    
31.
Piechota M, Banach M, Irzmanski R, Misztal M, Rysz J, Barylski M et al. N-terminal brain natriuretic propeptide levels correlate with procalcitonin and C-reactive protein levels in septic patients. Cell Mol Biol Lett 2007; 12: 162–175.  Back to cited text no. 31
    
32.
Pepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest 2003; 111:1805–1812.  Back to cited text no. 32
    
33.
Fleck A, Hawker F, Wallace PI, Raines G, Trotter J, Ledingham IM et al. Increased vascular permeability A major cause of hypoalbuminaemia in disease and injury. Lancet 2018; 325:781–784.  Back to cited text no. 33
    
34.
Cordemans C, De Laet I, van Regenmortel N, Schoonheydt K, Dits H, Malbrain ML et al. Fluid management in critically ill patients: the role of extravascular lung water, abdominal hypertension, capillary leak, and fluid balance. Ann Intensive Care 2012; 2012:S1.  Back to cited text no. 34
    
35.
Endo S, Suzuki Y, Takahashi G, Shozushima T, Ishikura H, Murai A et al. Presepsin as a powerful monitoring tool for the prognosis and treatment of sepsis: a multicenter prospective study. J Infect Chemother 2014; 20:30–34.  Back to cited text no. 35
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed199    
    Printed18    
    Emailed0    
    PDF Downloaded47    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]