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Presepsin (sCD14-ST), an innate immune response marker in sepsis
Presepsin (sCD14-ST), an innate immune response marker in sepsis Camille Chenevier-Gobeaux, Didier Borderie, Nicolas Weiss, Thomas Mallet-Coste, Yann-Erick Claessens PII: DOI: Reference:
S0009-8981(15)00335-6 doi: 10.1016/j.cca.2015.06.026 CCA 14036
To appear in:
Clinica Chimica Acta
Received date: Revised date: Accepted date:
18 December 2014 24 June 2015 26 June 2015
Please cite this article as: Chenevier-Gobeaux Camille, Borderie Didier, Weiss Nicolas, Mallet-Coste Thomas, Claessens Yann-Erick, Presepsin (sCD14-ST), an innate immune response marker in sepsis, Clinica Chimica Acta (2015), doi: 10.1016/j.cca.2015.06.026
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ACCEPTED MANUSCRIPT Ms. Ref. No.: CCA-D-14-01321 Presepsin (sCD14-ST), an innate immune response marker in sepsis
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Camille Chenevier-Gobeaux (1), Didier Borderie (1, 2), Nicolas Weiss (3), Thomas Mallet-Coste (3), Yann-Erick Claessens (3).
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1. Service de Diagnostic Biologique Automatisé, Hôpital Cochin (Hôpitaux Universitaires Paris Centre, HUPC), Assistance Publique des Hôpitaux de Paris (APHP), 27 rue du Faubourg Saint-Jacques, 75679 Paris Cedex 14, France. [email protected]
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2. UMR 1124 Pharmacologie, Toxicologie et signalisation cellulaire, Université Paris Descartes, Sorbonne Paris Cité, Paris, France. [email protected]
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3. Département de Médicine d’Urgence, Centre Hospitalier Princesse Grace, 1 avenue Pasteur BP489 MC-98012 Principauté de Monaco. [email protected]
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Corresponding Author: Service de Diagnostic Biologique Automatisé, Hôpital Cochin (Hôpitaux Universitaires Paris Centre, HUPC), Assistance Publique des Hôpitaux de Paris (AP-HP), 27 rue du Faubourg Saint-Jacques, 75679 Paris Cedex 14, France. [email protected]
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Keywords
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1. Introduction
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Abstract
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2. The host-pathogen response: engagement of the coreceptor CD14, and production of presepsin
Presepsin as an early marker in infectious diseases
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3.
3.2. Measurement of presepsin
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4. Clinical data on Presepsin
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3.1. Kinetics of presepsin release
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4.2. Accuracy for the diagnosis of infection
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4.3. Accuracy for prognosis
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4.1. Presepsin values in the Reference population
5. Conclusion and perspectives
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6. Acknowledgement
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7. References
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ACCEPTED MANUSCRIPT Abstract. Innate immunity is the first barrier to fight off bacteria, and partly relies on the
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engagement of the membrane coreceptor CD14. A product of cleavage of CD14, the
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soluble subtype of CD14 (sCD14-ST) or presepsin, is released in circulation after
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activation of defense mechanisms. Presepsin can be detected by biochemical methods and therefore appears as an emergent biomarker of infection. Here we
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present the rationale for presepsin development and recent data supporting its use at bedside. Presepsin may be worthwhile for early diagnosis and prognostic
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assessment of patients with systemic infections. This biomarker shows high specificity, and results from experimental and clinical studies are reinforcing the proof
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of concept. Performances place presepsin at the level of PCT who is used as a
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comparator. Biomarkers of infection are futile to diagnose infection with direct access to bacteria (as urinary tract infection, meningitis), but their use can be advocated to
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ascertain unclear diagnosis. Future developments of presepsin will probably use clinical models with a Bayesian approach to ascertain the additional value of the
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biomarker at bedside.
Keywords Biomarker; infection; presepsin; sCD14-ST; sepsis; soluble subtype of CD14.
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ACCEPTED MANUSCRIPT 1. Introduction Acute infections are frequent, they impact daily living and are responsible for
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significant morbi-mortality [1]. The systemic inflammatory response to infection has
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been termed sepsis; severe sepsis is accompanied by single or multiple organ
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dysfunctions or failures, often leading to death [1]. The wide variety of microbes and the poor specificity of symptoms frequently lead to inappropriate and overuse of
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antimicrobial agents. Therefore, developing strategies to improve diagnosis of infection and assess severity is still mandatory to guide physicians’ decisions at
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bedside. There is no doubt that the best way to ascertain infection is to identify a pathogen in a normally sterile tissue; a typical illustration could be the presence of
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germs in the urinary tract. Indirect finding such as urinary antigens tests are
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surrogate attempts to prove pathogens invasion of the organism; this may help but it targets specific microorganisms. Whereas multiple germs and viruses testing assays
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are under development, no strategy based on these tests is currently developed for daily practice. Therefore, the use of biomarkers of the inflammatory response to
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infection has been largely investigated. Biomarkers can be useful for identifying or for ruling out sepsis, identifying patients who may benefit from specific therapies, and for assessing response to therapy and severity [2]. The implementation of biomarkers to algorithms developed upon a Bayesian approach, has significantly modified medical reasoning. C-reactive protein (CRP) and procalcitonin (PCT) have been extensively studied in the setting of acute community infection. Though their utility is still debatable, physicians have integrated these tools in their daily practices [2]. CRP and PCT are indirect witnesses of the host-pathogen response. In response to IL-6 (a major initiative pro-inflammatory cytokine), CRP is mainly produced by liver, while PCT is released by monocytes and the liver but the 4
ACCEPTED MANUSCRIPT significance of this protein in the host-pathogen network is still unclear [3; 4; 5]. As a matter of fact, CRP and PCT are acute phase biomarkers of a systemic reaction.
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Nevertheless, PCT is supposed to be more specific for bacterial systemic infection
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[2]. Actually, the main challenge is to develop infection-specific biomarkers. Organ
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specificity of biomarkers is a concept that merely applies to infectious disorders, since infection implies multiple organ involvement and complex intricate responses. Approaching this specificity requires more precise targeting of host-pathogens
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response. Biomarkers with better specificity for the systemic response against
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microorganism could certainly be found among molecules involved in the innate immune response.
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Innate immunity is the first barrier to fight off bacteria, virus and fungi. Innate immune
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response relies on the monocyte-macrophage lineage [6]. Activation of monocytemacrophage is obtained by contact with various elements from the pathogen.
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Examples of elements are: membrane and structural proteins, sugars and lipids, nucleic acids, which are called ‘pathogen associated molecular patterns’ (PAMPs).
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When PAMPs are recognized at the cell membrane by receptors and their coreceptors (dedicated to one or multiple panels of PAMPs), the molecular cluster transduces anti-infectious signals. CD14 is a ubiquitous coreceptor of this system. Presepsin, a soluble subtype of CD14 or sCD14-ST, is a complex product of CD14 cleavage that is released in the general circulation after bacterial antigen binding. Presepsin is stable in the general circulation and an automatized rapid quantification is currently available [7]. Thus, presepsin represents a candidate biomarker of the initial phase of systemic infection. Data from the literature indicate that mechanisms to produce presepsin seem specific to infection. Here we report current knowledge and recent advances on presepsin. 5
ACCEPTED MANUSCRIPT 2. The host-pathogen response: engagement of the coreceptor CD14, and production of presepsin
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Survival of species depends on the ability of its immune system to recognize
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pathogens and to provide an immediate and efficient response to the invasion. This
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response is schematically divided in an innate and an adaptative system. Though the two systems differ for receptors that recognize the germs and for the downstream
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effector signals, both mechanisms are tightly linked. However, innate and adaptative immunities correspond to different steps of the physiological response. In comparison
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to adaptative immunity, innate immunity relies on immediately efficient defense effectors such as antimicrobial peptides, alternative complement pathway, and
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phagocytes. These effectors have the advantage of allowing rapid control of
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pathogens spreading and replicating. Activation of innate immunity is obtained after recognition of the microorganism pattern by receptors and coreceptors at the
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membrane of monocyte-macrophage [6]. Innate immunity receptors are genetically pre-determined, and they recognize a wide variety of patterns that cover most
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pathogens. This recognition is based on commune motifs presented by pathogens, namely PAMPs, which are highly conserved along evolution [8]. Receptors and coreceptors of innate immunity are present at the membrane of several effector cells; a major effector system corresponds to monocytesmacrophages [6]. After PAMPs bind to receptors and coreceptors, effector cells are activated in a direct pathway without any previous proliferation; therefore innate immunity provides an immediate and efficient response to microbial invasion [8, 9]. Activation of innate immunity receptors and co-receptors leads to intracellular signals that promote expression of genes responsible for the host defense, including genes
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ACCEPTED MANUSCRIPT encoding for proinflammatory cytokines. These receptors are members of the Tolllike receptor (TLR) family.
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CD14 (356 aminoacids, 55kDa) has the ability to recognize different families of
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ligands, including lipids, peptidoglycan and other surface structures in both Gram-
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positive and Gram-negative bacteria [10]. The best studied PAMP is bacterial lipopolysaccharid (LPS) [11]. To be efficiently recognized, LPS requires association
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to serum protein LBP (Lipoprotein Binding Protein); LBP presents LPS to CD14, a coreceptor expressed at the external membrane of monocyte-macrophage. CD14 is
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recruited to the receptor after ligand binding. CD14 is involved in the presentation of LPS to TLR and actively participates to signal transduction and downstream
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response, i.e. cytokines production by effector cells. CD14 lacks a transmembrane
multimolecular
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domain and is unable to transmit signal by itself [8, 9]. Combination of TLR to the complex
CD14-LPS-LBP
activates
intracelullar
signals
and
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responses. Recruitment of CD14 to TLR in multimolecular clusters includes adaptors and cell transduction proteins. These clusters are responsible for production of
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proteins that participate in the host defense against pathogens. After TLR4 activation, monocyte-macrophage proceeds to phagocytosis of microbial particles linked to the receptor. CD14 modulates the cell machinery to control TLR endocytosis after LPS stimulation [12]. After LPS binding, membrane expression of CD14 decreases at the monocytes membrane. This decrease has been linked to cleavage [13]. CD14 is subject to proteolysis after LPS exposure and leads to release of various fragments of 47kD and 30kD related to digestion by human leucocyte elastase [14]. Soluble subtypes of CD14 are released and can be detected in the systemic blood flow [15, 16]. Internalization of CD14 also participates to a decreased expression at the cell membrane; CD14 is distributed in caveolae [17] and other cell 7
ACCEPTED MANUSCRIPT compartments [18]. The molecular complex CD14-LPS-LBP is also internalized into a phagolysosome. In this organelle, the complex CD14-LPS-LBP is submitted to an
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enzymatic processing that requires cathepsin D. In addition, soluble CD14 is directly
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secreted by hepatocytes [19]. Finally, CD14 proteolysis and internalization processes
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generate a small soluble peptid structure (64 aminoacids, 13kDa) derived from the seminal CD14. The product of CD14 cleavage has been named soluble CD14
proteolysis and exocytosis (Figure 1).
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subtype (sCD14-ST) or presepsin. Presepsin is released in the general circulation by
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Whereas biological activity of presepsin is not exhaustively elucidated, it is established that this CD14 fragment has lost its ability to link LPS [3]. However,
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sCD14-ST has been described as a regulatory factor. It can modulate cellular and
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humoral immune responses by interacting directly with T and B cells, and also reduce
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mortality rate caused by endotoxin shock and severity of infections [19; 20]. Circulating presepsin levels can be perceived has a witness of activated monocytemacrophage in response to pathogens. Monocytes-macrophages are present in the
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circulating compartment and baseline activation of these cells physiologically exists. Consequently, detection of presepsin is forecast even in healthy non-septic patients. The concept for this biomarker suggests that concentrations of presepsin (1) should be detectable in healthy individuals, (2) should increase early in case of a bacterial infection, and (3) its increase should be dependent on intensity of the innate immune response.
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ACCEPTED MANUSCRIPT 3. Presepsin as an early marker in infectious diseases Measurements of circulating sCD14 have been tested to detect systemic infection
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related to enterobacteriacae [21]. Blood concentrations of soluble CD14 have also
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been associated with severity of sepsis in neonates [16] and adult patients [21]. In
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2005, presepsin was described as highly specific in discriminating septic patients; this new biomarker detected by conventional immunoassay increases significantly in
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blood plasma in the early stages of sepsis [22]. A few years later, a one-step assay was validated for routine measurement of presepsin [23], leading presepsin to be a
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good candidate for sepsis biomarker [19].
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3.1. Kinetic of presepsin release
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Today, there is very few data on presepsin kinetics, on how long presepsin levels are sustained, and whether presepsin levels fluctuate during time course of sepsis. In a rabbit model of experimental sepsis (peritonitis using caecum ligation and
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puncture), presepsin is detected in the blood of animals two hours after the procedure begun [3]. Presepsin levels were found to be elevated earlier than IL-6 and PCT, with a peak at 3 hours and sustained elevation for at least 5 hours. In a very recent work that we performed, presepsin concentrations were studied after challenge with LPS in a human cell line of monocytic cells (THP1), and in peripheral mononuclear cells (PMNC) collected from 5 healthy volunteers [24]. In THP1 cells, presepsin was detected at 1 hour after LPS exposure, and peaked at 3 hours. In human peripheral mononuclear cells collected from healthy volunteers and stimulated in vitro with LPS, we observed a secretion of presepsin levels within the first hour,
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ACCEPTED MANUSCRIPT concomitantly to IL-6 release (personal data, submitted). Our findings might confirm the potential usefulness of presepsin at bedside as an early marker of infectious
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diseases.
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Finally, it has been described that presepsin levels begin to increase earlier than PCT
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and CRP, and remain elevated during 7 days before decreasing, in burns [25].
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3.2. Measurement of presepsin
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ELISA methods have been developed to detect presepsin in blood. First in 2005, presepsin was described as highly specific in discriminating septic patients, using a
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conventional enzyme-linked immunosorbent assay (ELISA) [22]. A few years later, a
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one-step chemiluminescent ELISA assay was validated for routine measurement of
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presepsin [23]; this relatively simple and rapid method showed satisfactory results. Moreover, the method is adapted to measurement in whole blood samples, further reducing the analytical time. With this assay, a preliminary threshold value (415 μg/L)
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was associated with a performing sensitivity (80%) and specificity (81%) for the diagnosis of sepsis [25]. Characteristics of presepsin have prompted physicians to test its ability to detect bacteria-related infection at bedside. Therefore, more recently, a fully automated rapid point-of-care immunoassay was evaluated, and this assay demonstrated good analytical performances for detecting presepsin in human whole blood [7].
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ACCEPTED MANUSCRIPT 4. Clinical data on presepsin Characterization of presepsin is relatively recent. Using Pubmed, we recorded 1
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original study in 2005, 4 in 2011, 2 in 2012, 5 in 2013, 15 in 2014; 10 publications
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were conducted in Asia, and the remaining in Europe. Data from clinical trials are
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currently available to help us understanding how presepsin could help at bedside. Published results demonstrate that bacteria-related infections are responsible for
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elevation of presepsin levels [22, 25]. This demonstrates that a cell marker of the innate immunity engagement can be used to assist diagnosis of infection. In addition,
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presepsin can be measured on delocalized automatic devices in plasma as well as in total blood. Therefore reliable results of presepsin can be obtained within a few
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minutes at bedside [7]. However, as presepsin is a recent biomarker, literature
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remains sparse regarding normal ranges and cutoff values to guide physicians’
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decisions.
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4.1. Presepsin values in the reference population The first step in the development of a biomarker is to determine normal range. As suggested by the rationale to use presepsin, this biomarker can be detected in the absence of any disorder (Table 1) [7, 22, 25-36]. In 20 healthy participants, median concentration was 123 pg/mL [7]. According to the manufacturer, these normal values are highly reproducible; in a series of 119 healthy volunteers, presepsin concentrations ranged 60 to 365 pg/mL, the median value was 160 pg/mL, and 320 pg/mL corresponded to the 95th percentile (Table 1). In another series [37], presepsin levels of a control population were 89-382 pg/mL (median 200 pg/mL). However current literature suggests an operational cutoff for decision making process at the 11
ACCEPTED MANUSCRIPT 95th percentile value like for most of the traditional biomarkers (except for high sensitive troponins). However, this value can be measured with enough statistical
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confidence (>95% CI) only if the studied population is >300 volunteers [38]. Thus,
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this detection remains to be established for presepsin use today.
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Even in the absence of sepsis, several physiological conditions modify presepsin values in the adult reference population. Extreme ages influence the thresholds: in 36
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preterm newborns, mean+/- SD presepsin value was 643.1 +/- 304.8 ng/L [31], which is clearly not the same value as in young adults. Presepsin levels are also higher in
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patients without systemic inflammation or infection who visit the emergency department as compared in healthy volunteers [28]. In these patients, levels are
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significantly more elevated in patients aged 70 and above, or eGFR below
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60mL/min/1.73m2.
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The levels of presepsin in patients with non infectious SIRS constitute an interesting comparator. Depending on the studies, these levels are sometimes comparable to those of healthy volunteers [22; 25]. However most studies show that patients with
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non infectious SIRS present an increase in presepsin levels [22, 25, 27, 29, 30, 33-
These results question the appropriate threshold in acutely ill patients, and the possibility of either a double cutoff for rule in / rule out (with a possible grey zone, as proposed for other biomarkers [39]), either a dynamic cutoff strategy based on the observation of the variation between two measurements (as proposed for highsensitivity troponins, [40]).
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ACCEPTED MANUSCRIPT 4.2. Accuracy for the diagnosis of infection According to results of a seminal study, a cutoff value of 399 pg/mL was associated
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with good sensitivity (80.3%) and specificity (78.5%) to detect patients with an
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infection [25]. Comparison of areas under the ROC curve revealed that global
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diagnosis performance was better for presepsin than for other biomarkers including CRP and PCT. Other studies also found better sensitivity, specificity, and global
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diagnostic performances for presepsin than PCT (AUC=0.82 and 0.724, respectively, P<0.01) [34]. However superiority of presepsin for diagnosis has not been
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reproduced in all studies (Table 2) [7, 22, 25, 27, 29, 30, 33-36, 41-48], and the interstudy variability in presepsin levels could be related to the nature and severity of
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infection [22, 25, 27, 29, 30, 34]. Presepsin showed better performance than PCT for
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60-days mortality in 105 septic patients but PCT significantly outlined presepsin for diagnostic accuracy (AUC 0.875 vs. 0.701, p<0.001) [33]. Presepsin seems to
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specifically increase in the case of infection-associated response. Presepsin concentrations were significantly lower in 41 patients with non septic SIRS (333.5
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pg/mL, p<0.05) [22]. Interestingly, presepsin concentrations from these patients did not differ from 22 normal participants (294.2 pg/mL) and 128 controls (190 pg/mL) [22]. In 83 SIRS compared to 106 septic patients, presepsin had a good sensitivity but a mediocre (61.9%) specificity to detect infection at a cutoff 600 pg/mL [33]. As CD14 is present at the circulating monocytes membrane, it could be suggested that white blood cell count could influence presepsin levels. However, it has been established that presepsin levels were not correlated to the leucocytes count [37]. Interestingly, several studies compared levels of presepsin in septic patients with positive and negative blood culture. Patients with bacteremia had higher concentrations of presepsin [7, 43]. In one study, only PCT showed a significant 13
ACCEPTED MANUSCRIPT difference between Gram-positive and Gram-negative blood culture results, with higher levels in the latter (p=0,008) [43]. Neither presepsin nor PCT could
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differenciate infection due to S. aureus from infection due to E. coli. However,
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presepsin was found to be significantly higher in patients with candidemia compared
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to patients with negative blood culture [43]. This observation supports a potential influence of the nature of the etiological agent on presepsin response, and an association of presepsin release and the burden of the host invasion by
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microorganisms. As suggested by studies in non-septic patients, performance of
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presepsin may decrease in patients with kidney injury, especially in those with lower glomerular function [3].
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In a recent prospective multicentre observational study (191 patients), presepsin in
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association to procalcitonin had a higher diagnostic accuracy for discriminating SIRS
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from sepsis, in comparison to presepsin or procalcitonin alone [47].
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4.3. Accuracy for prognosis A gradual increase in presepsin levels has been associated with the burden and severity of infection. More precisely, in a study that included 170 patients, the mean presepsin concentrations were 721 pg/mL for local infections, 818 pg/mL for sepsis and 1993 pg/mL for severe sepsis [25]. Notably presepsin concentrations were higher in case of very severe infection [25]. These results have been reproduced in a series of studies, listed in Table 2. Presepsin showed substantial ability to detect severe sepsis and septic shock [27]. Combining presepsin to usual severity scoring systems improved their performance to detect more severely ill patients [27]. Presepsin has also the capacity to predict mortality. Performances of presepsin to 14
ACCEPTED MANUSCRIPT determine risk of death are close to PCT and vary between studies [27, 33]. Some reports show a modest sensitivity and specificity of the test [27]. Presepsin slightly
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improved MEDS and APACHE2 performance to predict d-28 mortality. Appraisal of
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mortality seems of interest for the first few days after the beginning of the infection
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and less relevant for mid-term evaluation [33, 42]. Very recently, presepsin levels were shown to be correlated with severity of sepsis during follow-up [44]. Correlation of presepsin level and SOFA score increased with the elapsed time, and was highest
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at day 7; the same observation was done for prognostic accuracy of presepsin for 28-
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day mortality [47]. Prognosis and severity of infection might be assessed more
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accurately by measuring prespesin level during the early days of sepsis.
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ACCEPTED MANUSCRIPT 5. Conclusion and perspectives Presepsin may have an interest for early diagnosis and prognostic assessment of
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patients with systemic infections. This biomarker shows high specificity, and results
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from experimental and clinical studies are reinforcing the proof of concept.
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Performances place presepsin at the level of PCT who is used as a comparator. Therefore comparing PCT and presepsin to determine which biomarker (or which
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combination) has the best characteristics at bedside is mandatory. In comparison to PCT, significance of presepsin elevation is easy to understand, as it results from a
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dose-response mechanism of the host-pathogen interaction. As suggested by scientific literature, presepsin increases with every type of bacteria and fungi. This is
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understandable, as molecular mechanisms that involve CD14 allow innate immune
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response against most microorganisms and therefore lead to presepsin release.
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Using a biomarker of infection is futile in case of direct access to bacteria (such as urinary tract infection, meningitis). Conversely, when diagnosis of infection is unclear, the use of biomarkers can be suggested. Future developments of presepsin will
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probably use clinical models with a Bayesian approach to ascertain the additional value of the biomarker at bedside.
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ACCEPTED MANUSCRIPT 6. Acknowledgements We thank Akli Bouaziz (Nephrotek Laboratories) and Dr Ralf Thomae (Mitsubishi
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Chemical Europe GmbH) for providing support in collecting scientific data on
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presespin.
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Shozushima T, Takahashi G, Matsumoto N, Kojika M, Okamura Y, Endo S.
Usefulness of presepsin (sCD14-ST) measurements as a marker for the diagnosis 20
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M, Schmidt J, de la Coussaye JE, Gayet A, Casalino E, Batard E, Lecomte F,
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Borderie D, Chenevier-Gobeaux C. Plasmatic presepsin (sCD14-ST) concentrations in acute pyelonephritis in adult patients. Crit Care 2013; in press Liu B, Chen YX, Yin Q, Zhao YZ, Li CS. Diagnostic value and prognostic
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Chenevier-Gobeaux C, Trabattoni E, Roelens M, Borderie D, Claessens YE.
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Presepsin (sCD14-ST) in emergency department: the need for adapted threshold
Behnes M, Bertsch T, Lepiorz D, Lang S, Trinkmann F, Brueckmann M,
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Borggrefe M, Hoffmann U. Diagnostic and prognostic utility of soluble CD 14 subtype (presepsin) for severe sepsis and septic shock during the first week of intensive care
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treatment. Crit Care 2014;18:507. Kweon OJ, Choi JH, Park SK, Park AJ. sefulness 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;29:965-70. [31]
Mussap M, Puxeddu E, Burrai P, Noto A, Cibecchini F, Testa M, Puddu M,
Ottonello G, Dessi A, Irmesi R, Dalla Gassa E, Fanni C, Fanos V. Soluble CD14 subtype (sCD14-ST) presepsin in critically ill preterm newborns: preliminary reference ranges. J Matern Neonat Med 2012;25:51-3. [32]
Malíčková K, Koucký M, Pařízek A, Pelinková K, Brodská H, Hájek Z,
Germanová A, Mestek O, Zima T. Diagnostic and prognostic value of presepsin in 21
ACCEPTED MANUSCRIPT preterm deliveries. Matern Fetal Neonatal Med. 2014 Jul 28:1-6. [33]
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Lupia E, Moiragho C, Mengozzi G, Battista S. Diagnostic and prognostic value of
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Ishikura H, Nishida T, Murai A, Nakamura Y, Irie Y, Tanaka J, Umemura T.
New diagnostic strategy for sepsis-induced disseminated intravascular coagulation: a
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AO, Acebes SR, Otón MD. Diagnostic accuracy of presepsin (soluble CD14 subtype) for prediction of bacteremia in patients with systemic inflammatory response
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Kaptanağası A. Evaluation of soluble CD14 subtype (presepsin) in burn sepsis. Burns 2014;40:664-9.
Mallet-Coste T, Chenevier-Gobeaux C, Fissore-Magdelein C, Magdelein X,
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Brod F, Claessens YE. Presepsin (sCD14-ST), an emergent and promising biomarker of infection. Ann Fr Med Urgence 2013 ;3 :305-9. [article in French] [38]
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new tool for pathophysiological investigation and clinical practice. Adv Clin Chem 2009;49:1-30. [39]
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J, Santalo-Bel M, Pinto YM, Richards M. NT-proBNP testing for diagnosis and shortterm prognosis in acute destabilized heart failure: an international pooled analysis of
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K, Plebani M, Biasucci LM, Tubaro M, Collinson P, Venge P, Hasin Y, Galvani M,
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Koenig W, Hamm C, Alpert JS, Katus H, Jaffe AS; Study Group on Biomarkers in Cardiology of ESC Working Group on Acute Cardiac Care. How to use high-
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sensitivity cardiac troponins in acute cardiac care. Eur Heart J 2012;33:2252-7. Palmiere C, Mussap M, Bardy D, Cibecchini F, Mangin P. Diagnostic value of
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soluble CD14 subtype (sCD14-ST) presepsin for the post-mortem diagnosis of sepsis-related fatalities. Int J Legal Med 2013; 127:799-808. Masson S, Caironi P, Spanuth E, Thomae R, Panigada M, Sangiorgi G,
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Fumagalli R, Mauri T, Isgrò S, Fanizza C, Romero M, Tognoni G, Latini R, Gattinoni
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L. Presepsin (soluble CD14 subtype) and procalcitonin levels for mortality prediction in sepsis ; data from the Albumin Italian Outcome Sepsis trial. Crit Care 2014;18:R6. [43]
Rabensteiner J, Skvarc M, Hoenigl M, Osredkar J, Prueller F, Reichsoellner
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M, Krause R, Raggam RB. Diagnostic and prognostic potential of presepsin in Emergency Department patients presenting with systemic inflammatory response syndrome. J Infect 2014;69:627-30. [44]
Endo S, Suzuki Y, Takahashi G, Shozushima T, Ishikura H, Murai A, Nishida
T, Irie Y, Miura M, Iguchi H, Fukui Y, Tanaka K, Nojima T, Okamura Y. Presepsin as a powerful monitoring tool for the prognosis and treatment of sepsis : a multicenter prospective study. J Infect Chemother 2014;20:30-34. [45]
Liu B, Yin Q, Chen YX, Zhao YZ, Li CS. Role of Presepsin (sCD14-ST) and
the CURB65 scoring system in predicting severity and outcome of communityacquired pneumonia in an emergency department. Respir Med 2014;108:1204-13. 23
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Nakamura A, Wada H, Ikejiri M, Hatada T, Sakurai H, Matsushima Y, Nishioka
J, Maruyama K, Isaji S, Takeda T, Nobori T. Efficacy of procalcitonin in the early
Takahashi G, Shibata S, Ishikura H, Miura M, Fukui Y, Inoue Y, Endo S.
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diagnosis of bacterial infections in a critical care unite. Shock 2009;31:591.
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Presepsin in the prognosis of infectious diseases and diagnosis of infectious disseminated intravascular coagulation: A prospective, multicentre, observational study. Eur J Anaesthesiol 2014; in press
Poggi C, Bianconi T, Gozzini E, Generoso M, Dani C. Presepsin for the
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Detection of Late-Onset Sepsis in Preterm Newborns. Pediatrics 2015;135 :68-75.
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ACCEPTED MANUSCRIPT Table 1. Control presepsin values in healthy volunteers, patients without SIRS and patients with SIRS without infection. Population
No
Presepsin (pg/mL)
Author [ref.]
119
range 60-365, med 160
Manufacturer data
20
mean 123 (SD 67,6)
Okamura et al. [7]
75
mean 21.8 (SD 8,45)
22
mean 294.2 (SD 121,4)
47
mean 200 [IQR149-275]
100
mean 130 (25 -75 perc. 104-179)
Liu et al. [27]
54
med 202 [IQR 167-266]
Chenevier-Gobeaux et al. [28]
60
med 216 (IQR 146-350)
Behnes et al. [29]
25
mean 92.74 (SD 21.43)
Kweon et al. [30]
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th
Yaegashi et al. [22] Shozushima et al. [25] Claessens et al. [26]
D
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th
IP
T
Healthy volunteers :
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Patients without SIRS : 144
med 442 [IQR 337-562]
<70yrs
22
med 300 [IQR 201-457]
122
med 470 [IQR 380-601]
26
mean 643, med 578
Mussap et al. [31]
60
med 454 (IQR 262-569.5)
Malickova et al. [32]
80
mean 81,3* (SD 49,5)
Yaegashi et al. [22]
41
mean 333.5 (SD 130,6)
Shozushima et al. [25]
179
mean 212 (IQR. 143-300)
Liu et al. [27]
9
med 393 (IQR 249-745)
Behnes et al. [29]
20
mean 421.83 (SD 338.21)
Kweon et al. [30]
83
mean 2516.4 (95%CI 1360.3-3672.4)
Ulla et al. [33]
39
mean 503 (SD 464)
Ishikura et al. [34]
189
mean 606 (SD 494)
Romualdo et al. [35]
11
med 332 (2.5-95.5 perc. 64-1523)
Cakır Madenci et al. [36]
>70yrs Preterm neonates
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Preterm females
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Total
Chenevier-Gobeaux et al. [28]
Patients with SIRS :
Burn
25
ACCEPTED MANUSCRIPT Footnote: SIRS : systemic inflammation response syndrome; med : median ;IQR :
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interquartile range ; SD : standard deviation ; perc. : percentile. * results in ng/mL.
26
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Table 2. Synoptic presentation of presepsin values and main results of studies on presepsin. Setting
Population (n)
Presepsin (pg/mL)
Okamura et al. [7]
NA
Reference population (n=20)
mean 123 (SD 67,6)
Patients with bacteremia (n=20)
mean 2363 (SD 2161)
Reference population (n=75)
mean 21,8ng/mL (SD 8,45)
SIRS (n=80)
mean 81,3ng/mL (SD 49,5)
Systemic infection (n=66)
mean 220,7ng/mL (SD 142,8)
Reference population (n=22)
mean 294,2 (SD 121,4)
(Infection + sepsis) vs. (SIRS + reference population) :
SIRS (n=41)
mean 333,5 (SD 130,6)
PSEP AUC 0,845 ; threshold = 399 pg/mL
ED/ICU
[25]
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mean 721 (SD 611,3)
Systemic infection (n=87)
Main results P<0.0001
Systemic infection vs. (SIRS + reference population) PSEP AUC 0,817
PCT AUC 0.666
mean 817,9 (SD 572,7) mean 1992,9 (SD 1505,2)
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Severe sepsis (n=14)
mean 130 (IQR 104-179)
mean 212 (IQR 143-300)
PSEP AUC 0.820; threshold = 317 pg/ml: Se=70.8%
mean 325 (IQR 210-480)
Sp=85.8%, PPV=93.2% NPV=51.6%
Severe sepsis (n=210)
mean 787 (IQR 464-1249)
Septic shock (n=98)
mean 1084 (IQR 695-2365)
PCT 0.741 (95%CI 0.703-0.779)
Healthy volunteers (n=100) SIRS (n=179) Sepsis (n=372)
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ED
CR
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Local infection (n=28)
Liu et al. [27]
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Shozushima et al.
ED/ICU
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Yaegashi et al. [22]
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Auteur [réf.]
Infection vs. (healthy volunteers + SIRS):
Sepsis vs. (severe sepsis + septic shock):
PSEP AUC 0.840 (95%CI 0.809-0.872); threshold = 349 pg/mL APACHE II 0.744 (95%CI 0.706-0.782) PSEP+APACHE II 0.858 (95%CI 0.829-0.887)
27
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d-28 mortality in septic patients:
APACHE II 0.722 (95%CI 0.681-0.763) PSEP+APACHE II 0.734 (95%CI 0.693-0.775)
SIRS (n=9)
med 393 (IQR 249-745)
PSEP AUC 0.80 (95%CI 0.73-0.86); threshold = 700
Sepsis (n=5)
med 362 (IQR 249-745)
pg/mL: Se=91% Sp=77% PPV=74% NPV=92%
Severe sepsis (n=28)
med 947 (IQR 523-2486)
PCT AUC 0.83 (95%CI 0.77-0.90)
Sepsis (n=25) Severe sepsis (n=22) Septic shock (n=26)
mean 92.74 (SD 21.43)
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Controls (n=25) SIRS (n=20)
Severe sepsis and septic shock vs. others:
med 2330 (IQR 1181-5219)
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ED
pg/mL
med 216 (IQR 146-350)
Septic shock (n=74) Kweon et al. [30]
PSEP AUC 0.658 (95%CI 0.614-0.703) ; threshold = 556
Control (n=60)
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ICU
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Behnes et al. [29]
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CR
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PCT 0.679 (95%CI 0.636-0.722)
Infection vs. no infection:
mean 421.83 (SD 338.21)
PSEP AUC 0.937; threshold = 430 pg/mL Se=87.7%
mean 875.8 (SD 591.63)
Sp=82.2%
mean 1452.23 (SD 729.82)
PCT AUC 0.915; threshold = 1 ng/mL Se=86.3%
mean 1869.58 (SD 1467.42)
Sp=86.7% PSEP to predict APACHEII increase : P>0.05 PSEP to predict d30 mortality : P>0.005
Ulla et al. [33]
ED
SIRS (n=83)
mean 2516.4 (95%CI 1360.3-3672.4)
Sepsis (n=55)
mean 2866.7 (95%CI 1579-4154)
PSEP threshold = 600pg/mL: Se=78.95% Sp=61.9%
Severe sepsis/septic shock (n=51)
mean 3167.1 (95%CI 1686.5-4647.7)
Sepsis:
d-60 in hospital mortality in septic patients:
28
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PSEP 4,232.4 vs.3,451.2pg/mL, P=0.04
No infection and SIRS (n=39)
mean 503 (SD 464)
Infection (n=43) :
mean 3290 (SD 4620)
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ED
CR
Ishikura et al. [34]
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PCT 17.12 vs. 9.59 ng/mL, P=0.87
US
. Sepsis (n=8) . Severe sepsis (n=14)
Romualdo et al. [35]
ED
SIRS without bacteremia (n=189)
Burn
AC
Cakır Madenci et al. [36]
Infection vs. no infection:
PSEP AUC 0.887; threshold = 647pg/mL Se=93% Sp=76.3% PCT AUC 0.904
DIC vs. no DIC :
PSEP AUC 0.808; threshold = 899pg/mL Se=83.3% Sp=78.3% PCT AUC 0.785
mean 606 (SD 494)
PSEP AUC 0.75; threshold = 729 pg/mL Se=81.1%
mean 1219 (SD 2188)
Sp=63% LR+=2.19 LR-=0.3
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SIRS with bacteremia (n=37)
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. Septic shock (n=21)
PCT AUC 0.783; threshold = 0.45 ng/mL Se=75.7% Sp=64% LR+=2.1 LR-=0.38
Burn without sepsis (n=11)
med 332 (2.5-95.5 perc. 64-1523)
PSEP to detect infection vs. no infection : P<0.0001
Burn and sepsis (n=26)
med 847 (2.5-95.5 perc. 207-12364)
PCT to detect infection vs. no infection : P=0.0012 PSEP to predict mortality : P<0.0001 PCT to predict mortality : P=0.0021
Palmiere et al. [41]
Masson et al. [42]
Post-
Non septic death (n=10)
med 670, range 180-4890
PSEP threshold = 600pg/mL: Se=0,94 Sp=0.83 AUC
mortem
Septic death (n=19)
med 4420, range 92-8960
0.81
ICU
Severe sepsis / septic shock
PSEP kinetics survivor/non survivor (d1, d2, d7)
29
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med 1184 (IQR 875-2113)
P=0.03
. non survivor (n=50)
med 2269 (IQR 1171-4300)
d28 mortality :
non adjusted OR 1.73 (95%CI 1.32-2.27) per unit adjusted OR 1.54 (95%CI 1.12-2.12) per unit
d90 mortality :
non adjusted OR 1.50 (95%CI 1.18-1.91) per unit adjusted OR 1.29 (95%CI 0.96-1.76) per unit
med 931 (IQR 500-1722)
Gram-positive bacteremia (n=102)
med 1078 (IQR 670-2422)
PSEP AUC 0.6 (95%CI 0.517-0.684)
Gram-negative bacteremia (n=124)
med 1295 (IQR 777-2654)
PCT AUC 0.693 (95%CI 0.617-0.768)
med 2293 (IQR 804-3027)
Gram-positive vs. Gram-negative PCT, p=0.008
Candidemia (n=15)
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Negative blood culture (n=59)
CE P
ED
AC
Rabensteiner et al. [43]
MA N
US
CR
IP
T
. Survivor (n=50)
Bacteraemia vs negative blood culture:
Candidemia vs. negative blod culture, PSEP p=0.038
Admission to ICU :
PSEP AUC 0.645 (95%CI 0.565-0.725) PCT AUC 0.612 (95%CI 0.529-0.694)
H48 mortality:
PSEP AUC 0.619 (95%CI 0.442-0.795) PCT AUC 0.709 (95%CI 0.557-0.861)
d30 mortality:
PSEP AUC 0.65 (95%CI 0.557-0.742) PCT AUC 0.583 (95%CI 0.497-0.668)
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d90 mortality:
ED /ICU
Patients with infection (n=53)
med 1523 (IQR 1014-2615)
CR
Endo et al. [44]
IP
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PSEP AUC 0.659 (95%CI 0.581-0.737)
US
. Sepsis (n=14) . Severe sepsis (n=19)
Liu et al. [45]
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. Septic shock (n=20)
CAP (n=359)
ICU
d0 levels of biomarkers:
PSEP, CRP, PCT, IL6 : not associated with SOFA / APACHEII
Kinetics (d0,d3,d7) of biomarkers:
PSEP : no decrease if unfavorable SOFA / APACHEII CRP,
PCT,
IL6:
decrease
regardless
of
SOFA/APACHEII
med 689 (IQR 395.5-1225.5)
ARDS : OR 1 (95%CI 1-1), P=0.708
AC
Nakamura et al. [46]
med 400 (IQR 231.5-691.5)
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Severe CAP (n=214)
PCT AUC 0.577 (95%CI 0.502-0.653)
PSEP to predict adverse outcome:
DIC : OR 1 (95%CI 1-1.001), P=0.001 Severe CAP : OR 1 (95%CI 1-1.001), P=0.614 d28 mortality : OR 1 (95%CI 1-1.001), P=0.006
Non acute kidney injury
sepsis in non acute kidney injury:
. SIRS without infection (n=75)
med 300 (range 86-4374)
AUC 0.784 (95%CI 0.683-0.86)
. Sepsis (n=37)
med 831 (range 187-9960)
Risk
sepsis in risk, injury and failure combined:
AUC 0.698 (95%CI 0.593-0.786)
. SIRS without infection (n=23)
med 467 (range 71–3361)
. Sepsis (n=27)
med 924 (range 290–16759)
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med 517 (range 144–1197)
. Sepsis (n=27)
med 1451 (range 237–4200)
IP
. SIRS without infection (n=9)
med 1535 (range 454–8516)
. Sepsis (n=27)
med 1523 (range 293–16764)
Infectious
disseminated
NA
Preterm newborns with late-onset
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sepsis (n=19)
Preterm newborns non infected controls (n=21)
med 1295 (p<0.0001 vs. controls)
med 562
Sepsis vs SIRS:
(PSEP+PCT) AUC = 0.91 PSEP AUC = 0.89 PCT AUC = 0.85
Late-onset sepsis:
PSEP AUC 0,972; threshold = 885 ng/L (Se94%, Sp100%)
AC
NA
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intravascular coagulation (n=191)
Poggi et al. [48]
US
. SIRS without infection (n=15)
MA N
NA
CR
Failure
Takahashi et al. [47]
T
Injury
32
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Footnote: NA: not available; ED: department of emergency medicine; ICU: intensive care unit; IQR: Interquartile range; SIRS:
IP
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systemic inflammation response syndrome; PSEP: presepsin; PSEP: presepsin; PCT: procalcitonin; DIC: disseminated
CR
intravascular coagulation; ARDS: acute respiratory distress syndrome; SOFA: sequential organ failure assessment score; APACHE
US
II: acute physiology and chronic health evaluation score; med: median; IQR: interquartile range; SD: standard deviation; perc.:
MA N
percentile; AUC: area under the ROC curve; 95%CI: 95% confidence interval; Se: sensitivity; Sp: specificity; PPV: positive
AC
CE P
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predictive value; NPV: negative predictive value; LR+: positive likelihood ratio; LR-: negative likelihood ratio. * results in ng/mL.
33
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CR
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Figure 1. Shematic production of presepsin. TLR: Toll-like-receptor; LPS: lipopolysaccharides ; LBP: LPS-binding protein; MD2: molecular dynamic-2; PSEP : presepsin. 34
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Presepsin (sCD14-ST) to detect sepsis: review and perspectives of a biomarker derived from innate immune response
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Camille Chenevier-Gobeaux (1), Didier Borderie (1, 2), Nicolas Weiss (3), Thomas Mallet-Coste (3), Yann-Erick Claessens (3).
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Highlights o Presepsin appears as an emergent biomarker of infection.
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o Recent data support presepsin use at bedside.
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o Presepsin may have an interest for early diagnosis of sepsis.
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o Presepsin may have an interest for prognostic assessment of sepsis.
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S0009-8981(15)00335-6 doi: 10.1016/j.cca.2015.06.026 CCA 14036
To appear in:
Clinica Chimica Acta
Received date: Revised date: Accepted date:
18 December 2014 24 June 2015 26 June 2015
Please cite this article as: Chenevier-Gobeaux Camille, Borderie Didier, Weiss Nicolas, Mallet-Coste Thomas, Claessens Yann-Erick, Presepsin (sCD14-ST), an innate immune response marker in sepsis, Clinica Chimica Acta (2015), doi: 10.1016/j.cca.2015.06.026
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Ms. Ref. No.: CCA-D-14-01321 Presepsin (sCD14-ST), an innate immune response marker in sepsis
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Camille Chenevier-Gobeaux (1), Didier Borderie (1, 2), Nicolas Weiss (3), Thomas Mallet-Coste (3), Yann-Erick Claessens (3).
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1. Service de Diagnostic Biologique Automatisé, Hôpital Cochin (Hôpitaux Universitaires Paris Centre, HUPC), Assistance Publique des Hôpitaux de Paris (APHP), 27 rue du Faubourg Saint-Jacques, 75679 Paris Cedex 14, France. [email protected]
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2. UMR 1124 Pharmacologie, Toxicologie et signalisation cellulaire, Université Paris Descartes, Sorbonne Paris Cité, Paris, France. [email protected]
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3. Département de Médicine d’Urgence, Centre Hospitalier Princesse Grace, 1 avenue Pasteur BP489 MC-98012 Principauté de Monaco. [email protected]
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Corresponding Author: Service de Diagnostic Biologique Automatisé, Hôpital Cochin (Hôpitaux Universitaires Paris Centre, HUPC), Assistance Publique des Hôpitaux de Paris (AP-HP), 27 rue du Faubourg Saint-Jacques, 75679 Paris Cedex 14, France. [email protected]
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Keywords
3
1. Introduction
4
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Abstract
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2. The host-pathogen response: engagement of the coreceptor CD14, and production of presepsin
Presepsin as an early marker in infectious diseases
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3.
3.2. Measurement of presepsin
10 10 11 11
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4. Clinical data on Presepsin
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3.1. Kinetics of presepsin release
7
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4.2. Accuracy for the diagnosis of infection
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4.3. Accuracy for prognosis
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4.1. Presepsin values in the Reference population
5. Conclusion and perspectives
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6. Acknowledgement
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7. References
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ACCEPTED MANUSCRIPT Abstract. Innate immunity is the first barrier to fight off bacteria, and partly relies on the
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engagement of the membrane coreceptor CD14. A product of cleavage of CD14, the
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soluble subtype of CD14 (sCD14-ST) or presepsin, is released in circulation after
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activation of defense mechanisms. Presepsin can be detected by biochemical methods and therefore appears as an emergent biomarker of infection. Here we
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present the rationale for presepsin development and recent data supporting its use at bedside. Presepsin may be worthwhile for early diagnosis and prognostic
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assessment of patients with systemic infections. This biomarker shows high specificity, and results from experimental and clinical studies are reinforcing the proof
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of concept. Performances place presepsin at the level of PCT who is used as a
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comparator. Biomarkers of infection are futile to diagnose infection with direct access to bacteria (as urinary tract infection, meningitis), but their use can be advocated to
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ascertain unclear diagnosis. Future developments of presepsin will probably use clinical models with a Bayesian approach to ascertain the additional value of the
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biomarker at bedside.
Keywords Biomarker; infection; presepsin; sCD14-ST; sepsis; soluble subtype of CD14.
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ACCEPTED MANUSCRIPT 1. Introduction Acute infections are frequent, they impact daily living and are responsible for
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significant morbi-mortality [1]. The systemic inflammatory response to infection has
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been termed sepsis; severe sepsis is accompanied by single or multiple organ
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dysfunctions or failures, often leading to death [1]. The wide variety of microbes and the poor specificity of symptoms frequently lead to inappropriate and overuse of
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antimicrobial agents. Therefore, developing strategies to improve diagnosis of infection and assess severity is still mandatory to guide physicians’ decisions at
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bedside. There is no doubt that the best way to ascertain infection is to identify a pathogen in a normally sterile tissue; a typical illustration could be the presence of
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germs in the urinary tract. Indirect finding such as urinary antigens tests are
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surrogate attempts to prove pathogens invasion of the organism; this may help but it targets specific microorganisms. Whereas multiple germs and viruses testing assays
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are under development, no strategy based on these tests is currently developed for daily practice. Therefore, the use of biomarkers of the inflammatory response to
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infection has been largely investigated. Biomarkers can be useful for identifying or for ruling out sepsis, identifying patients who may benefit from specific therapies, and for assessing response to therapy and severity [2]. The implementation of biomarkers to algorithms developed upon a Bayesian approach, has significantly modified medical reasoning. C-reactive protein (CRP) and procalcitonin (PCT) have been extensively studied in the setting of acute community infection. Though their utility is still debatable, physicians have integrated these tools in their daily practices [2]. CRP and PCT are indirect witnesses of the host-pathogen response. In response to IL-6 (a major initiative pro-inflammatory cytokine), CRP is mainly produced by liver, while PCT is released by monocytes and the liver but the 4
ACCEPTED MANUSCRIPT significance of this protein in the host-pathogen network is still unclear [3; 4; 5]. As a matter of fact, CRP and PCT are acute phase biomarkers of a systemic reaction.
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Nevertheless, PCT is supposed to be more specific for bacterial systemic infection
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[2]. Actually, the main challenge is to develop infection-specific biomarkers. Organ
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specificity of biomarkers is a concept that merely applies to infectious disorders, since infection implies multiple organ involvement and complex intricate responses. Approaching this specificity requires more precise targeting of host-pathogens
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response. Biomarkers with better specificity for the systemic response against
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microorganism could certainly be found among molecules involved in the innate immune response.
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Innate immunity is the first barrier to fight off bacteria, virus and fungi. Innate immune
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response relies on the monocyte-macrophage lineage [6]. Activation of monocytemacrophage is obtained by contact with various elements from the pathogen.
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Examples of elements are: membrane and structural proteins, sugars and lipids, nucleic acids, which are called ‘pathogen associated molecular patterns’ (PAMPs).
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When PAMPs are recognized at the cell membrane by receptors and their coreceptors (dedicated to one or multiple panels of PAMPs), the molecular cluster transduces anti-infectious signals. CD14 is a ubiquitous coreceptor of this system. Presepsin, a soluble subtype of CD14 or sCD14-ST, is a complex product of CD14 cleavage that is released in the general circulation after bacterial antigen binding. Presepsin is stable in the general circulation and an automatized rapid quantification is currently available [7]. Thus, presepsin represents a candidate biomarker of the initial phase of systemic infection. Data from the literature indicate that mechanisms to produce presepsin seem specific to infection. Here we report current knowledge and recent advances on presepsin. 5
ACCEPTED MANUSCRIPT 2. The host-pathogen response: engagement of the coreceptor CD14, and production of presepsin
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Survival of species depends on the ability of its immune system to recognize
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pathogens and to provide an immediate and efficient response to the invasion. This
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response is schematically divided in an innate and an adaptative system. Though the two systems differ for receptors that recognize the germs and for the downstream
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effector signals, both mechanisms are tightly linked. However, innate and adaptative immunities correspond to different steps of the physiological response. In comparison
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to adaptative immunity, innate immunity relies on immediately efficient defense effectors such as antimicrobial peptides, alternative complement pathway, and
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phagocytes. These effectors have the advantage of allowing rapid control of
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pathogens spreading and replicating. Activation of innate immunity is obtained after recognition of the microorganism pattern by receptors and coreceptors at the
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membrane of monocyte-macrophage [6]. Innate immunity receptors are genetically pre-determined, and they recognize a wide variety of patterns that cover most
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pathogens. This recognition is based on commune motifs presented by pathogens, namely PAMPs, which are highly conserved along evolution [8]. Receptors and coreceptors of innate immunity are present at the membrane of several effector cells; a major effector system corresponds to monocytesmacrophages [6]. After PAMPs bind to receptors and coreceptors, effector cells are activated in a direct pathway without any previous proliferation; therefore innate immunity provides an immediate and efficient response to microbial invasion [8, 9]. Activation of innate immunity receptors and co-receptors leads to intracellular signals that promote expression of genes responsible for the host defense, including genes
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ACCEPTED MANUSCRIPT encoding for proinflammatory cytokines. These receptors are members of the Tolllike receptor (TLR) family.
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CD14 (356 aminoacids, 55kDa) has the ability to recognize different families of
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ligands, including lipids, peptidoglycan and other surface structures in both Gram-
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positive and Gram-negative bacteria [10]. The best studied PAMP is bacterial lipopolysaccharid (LPS) [11]. To be efficiently recognized, LPS requires association
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to serum protein LBP (Lipoprotein Binding Protein); LBP presents LPS to CD14, a coreceptor expressed at the external membrane of monocyte-macrophage. CD14 is
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recruited to the receptor after ligand binding. CD14 is involved in the presentation of LPS to TLR and actively participates to signal transduction and downstream
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response, i.e. cytokines production by effector cells. CD14 lacks a transmembrane
multimolecular
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domain and is unable to transmit signal by itself [8, 9]. Combination of TLR to the complex
CD14-LPS-LBP
activates
intracelullar
signals
and
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responses. Recruitment of CD14 to TLR in multimolecular clusters includes adaptors and cell transduction proteins. These clusters are responsible for production of
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proteins that participate in the host defense against pathogens. After TLR4 activation, monocyte-macrophage proceeds to phagocytosis of microbial particles linked to the receptor. CD14 modulates the cell machinery to control TLR endocytosis after LPS stimulation [12]. After LPS binding, membrane expression of CD14 decreases at the monocytes membrane. This decrease has been linked to cleavage [13]. CD14 is subject to proteolysis after LPS exposure and leads to release of various fragments of 47kD and 30kD related to digestion by human leucocyte elastase [14]. Soluble subtypes of CD14 are released and can be detected in the systemic blood flow [15, 16]. Internalization of CD14 also participates to a decreased expression at the cell membrane; CD14 is distributed in caveolae [17] and other cell 7
ACCEPTED MANUSCRIPT compartments [18]. The molecular complex CD14-LPS-LBP is also internalized into a phagolysosome. In this organelle, the complex CD14-LPS-LBP is submitted to an
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enzymatic processing that requires cathepsin D. In addition, soluble CD14 is directly
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secreted by hepatocytes [19]. Finally, CD14 proteolysis and internalization processes
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generate a small soluble peptid structure (64 aminoacids, 13kDa) derived from the seminal CD14. The product of CD14 cleavage has been named soluble CD14
proteolysis and exocytosis (Figure 1).
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subtype (sCD14-ST) or presepsin. Presepsin is released in the general circulation by
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Whereas biological activity of presepsin is not exhaustively elucidated, it is established that this CD14 fragment has lost its ability to link LPS [3]. However,
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sCD14-ST has been described as a regulatory factor. It can modulate cellular and
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humoral immune responses by interacting directly with T and B cells, and also reduce
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mortality rate caused by endotoxin shock and severity of infections [19; 20]. Circulating presepsin levels can be perceived has a witness of activated monocytemacrophage in response to pathogens. Monocytes-macrophages are present in the
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circulating compartment and baseline activation of these cells physiologically exists. Consequently, detection of presepsin is forecast even in healthy non-septic patients. The concept for this biomarker suggests that concentrations of presepsin (1) should be detectable in healthy individuals, (2) should increase early in case of a bacterial infection, and (3) its increase should be dependent on intensity of the innate immune response.
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ACCEPTED MANUSCRIPT 3. Presepsin as an early marker in infectious diseases Measurements of circulating sCD14 have been tested to detect systemic infection
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related to enterobacteriacae [21]. Blood concentrations of soluble CD14 have also
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been associated with severity of sepsis in neonates [16] and adult patients [21]. In
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2005, presepsin was described as highly specific in discriminating septic patients; this new biomarker detected by conventional immunoassay increases significantly in
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blood plasma in the early stages of sepsis [22]. A few years later, a one-step assay was validated for routine measurement of presepsin [23], leading presepsin to be a
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good candidate for sepsis biomarker [19].
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3.1. Kinetic of presepsin release
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Today, there is very few data on presepsin kinetics, on how long presepsin levels are sustained, and whether presepsin levels fluctuate during time course of sepsis. In a rabbit model of experimental sepsis (peritonitis using caecum ligation and
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puncture), presepsin is detected in the blood of animals two hours after the procedure begun [3]. Presepsin levels were found to be elevated earlier than IL-6 and PCT, with a peak at 3 hours and sustained elevation for at least 5 hours. In a very recent work that we performed, presepsin concentrations were studied after challenge with LPS in a human cell line of monocytic cells (THP1), and in peripheral mononuclear cells (PMNC) collected from 5 healthy volunteers [24]. In THP1 cells, presepsin was detected at 1 hour after LPS exposure, and peaked at 3 hours. In human peripheral mononuclear cells collected from healthy volunteers and stimulated in vitro with LPS, we observed a secretion of presepsin levels within the first hour,
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ACCEPTED MANUSCRIPT concomitantly to IL-6 release (personal data, submitted). Our findings might confirm the potential usefulness of presepsin at bedside as an early marker of infectious
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diseases.
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Finally, it has been described that presepsin levels begin to increase earlier than PCT
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and CRP, and remain elevated during 7 days before decreasing, in burns [25].
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3.2. Measurement of presepsin
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ELISA methods have been developed to detect presepsin in blood. First in 2005, presepsin was described as highly specific in discriminating septic patients, using a
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conventional enzyme-linked immunosorbent assay (ELISA) [22]. A few years later, a
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one-step chemiluminescent ELISA assay was validated for routine measurement of
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presepsin [23]; this relatively simple and rapid method showed satisfactory results. Moreover, the method is adapted to measurement in whole blood samples, further reducing the analytical time. With this assay, a preliminary threshold value (415 μg/L)
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was associated with a performing sensitivity (80%) and specificity (81%) for the diagnosis of sepsis [25]. Characteristics of presepsin have prompted physicians to test its ability to detect bacteria-related infection at bedside. Therefore, more recently, a fully automated rapid point-of-care immunoassay was evaluated, and this assay demonstrated good analytical performances for detecting presepsin in human whole blood [7].
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ACCEPTED MANUSCRIPT 4. Clinical data on presepsin Characterization of presepsin is relatively recent. Using Pubmed, we recorded 1
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original study in 2005, 4 in 2011, 2 in 2012, 5 in 2013, 15 in 2014; 10 publications
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were conducted in Asia, and the remaining in Europe. Data from clinical trials are
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currently available to help us understanding how presepsin could help at bedside. Published results demonstrate that bacteria-related infections are responsible for
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elevation of presepsin levels [22, 25]. This demonstrates that a cell marker of the innate immunity engagement can be used to assist diagnosis of infection. In addition,
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presepsin can be measured on delocalized automatic devices in plasma as well as in total blood. Therefore reliable results of presepsin can be obtained within a few
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minutes at bedside [7]. However, as presepsin is a recent biomarker, literature
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remains sparse regarding normal ranges and cutoff values to guide physicians’
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decisions.
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4.1. Presepsin values in the reference population The first step in the development of a biomarker is to determine normal range. As suggested by the rationale to use presepsin, this biomarker can be detected in the absence of any disorder (Table 1) [7, 22, 25-36]. In 20 healthy participants, median concentration was 123 pg/mL [7]. According to the manufacturer, these normal values are highly reproducible; in a series of 119 healthy volunteers, presepsin concentrations ranged 60 to 365 pg/mL, the median value was 160 pg/mL, and 320 pg/mL corresponded to the 95th percentile (Table 1). In another series [37], presepsin levels of a control population were 89-382 pg/mL (median 200 pg/mL). However current literature suggests an operational cutoff for decision making process at the 11
ACCEPTED MANUSCRIPT 95th percentile value like for most of the traditional biomarkers (except for high sensitive troponins). However, this value can be measured with enough statistical
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confidence (>95% CI) only if the studied population is >300 volunteers [38]. Thus,
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this detection remains to be established for presepsin use today.
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Even in the absence of sepsis, several physiological conditions modify presepsin values in the adult reference population. Extreme ages influence the thresholds: in 36
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preterm newborns, mean+/- SD presepsin value was 643.1 +/- 304.8 ng/L [31], which is clearly not the same value as in young adults. Presepsin levels are also higher in
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patients without systemic inflammation or infection who visit the emergency department as compared in healthy volunteers [28]. In these patients, levels are
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significantly more elevated in patients aged 70 and above, or eGFR below
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60mL/min/1.73m2.
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The levels of presepsin in patients with non infectious SIRS constitute an interesting comparator. Depending on the studies, these levels are sometimes comparable to those of healthy volunteers [22; 25]. However most studies show that patients with
36].
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non infectious SIRS present an increase in presepsin levels [22, 25, 27, 29, 30, 33-
These results question the appropriate threshold in acutely ill patients, and the possibility of either a double cutoff for rule in / rule out (with a possible grey zone, as proposed for other biomarkers [39]), either a dynamic cutoff strategy based on the observation of the variation between two measurements (as proposed for highsensitivity troponins, [40]).
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ACCEPTED MANUSCRIPT 4.2. Accuracy for the diagnosis of infection According to results of a seminal study, a cutoff value of 399 pg/mL was associated
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with good sensitivity (80.3%) and specificity (78.5%) to detect patients with an
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infection [25]. Comparison of areas under the ROC curve revealed that global
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diagnosis performance was better for presepsin than for other biomarkers including CRP and PCT. Other studies also found better sensitivity, specificity, and global
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diagnostic performances for presepsin than PCT (AUC=0.82 and 0.724, respectively, P<0.01) [34]. However superiority of presepsin for diagnosis has not been
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reproduced in all studies (Table 2) [7, 22, 25, 27, 29, 30, 33-36, 41-48], and the interstudy variability in presepsin levels could be related to the nature and severity of
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infection [22, 25, 27, 29, 30, 34]. Presepsin showed better performance than PCT for
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60-days mortality in 105 septic patients but PCT significantly outlined presepsin for diagnostic accuracy (AUC 0.875 vs. 0.701, p<0.001) [33]. Presepsin seems to
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specifically increase in the case of infection-associated response. Presepsin concentrations were significantly lower in 41 patients with non septic SIRS (333.5
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pg/mL, p<0.05) [22]. Interestingly, presepsin concentrations from these patients did not differ from 22 normal participants (294.2 pg/mL) and 128 controls (190 pg/mL) [22]. In 83 SIRS compared to 106 septic patients, presepsin had a good sensitivity but a mediocre (61.9%) specificity to detect infection at a cutoff 600 pg/mL [33]. As CD14 is present at the circulating monocytes membrane, it could be suggested that white blood cell count could influence presepsin levels. However, it has been established that presepsin levels were not correlated to the leucocytes count [37]. Interestingly, several studies compared levels of presepsin in septic patients with positive and negative blood culture. Patients with bacteremia had higher concentrations of presepsin [7, 43]. In one study, only PCT showed a significant 13
ACCEPTED MANUSCRIPT difference between Gram-positive and Gram-negative blood culture results, with higher levels in the latter (p=0,008) [43]. Neither presepsin nor PCT could
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differenciate infection due to S. aureus from infection due to E. coli. However,
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presepsin was found to be significantly higher in patients with candidemia compared
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to patients with negative blood culture [43]. This observation supports a potential influence of the nature of the etiological agent on presepsin response, and an association of presepsin release and the burden of the host invasion by
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microorganisms. As suggested by studies in non-septic patients, performance of
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presepsin may decrease in patients with kidney injury, especially in those with lower glomerular function [3].
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In a recent prospective multicentre observational study (191 patients), presepsin in
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association to procalcitonin had a higher diagnostic accuracy for discriminating SIRS
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from sepsis, in comparison to presepsin or procalcitonin alone [47].
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4.3. Accuracy for prognosis A gradual increase in presepsin levels has been associated with the burden and severity of infection. More precisely, in a study that included 170 patients, the mean presepsin concentrations were 721 pg/mL for local infections, 818 pg/mL for sepsis and 1993 pg/mL for severe sepsis [25]. Notably presepsin concentrations were higher in case of very severe infection [25]. These results have been reproduced in a series of studies, listed in Table 2. Presepsin showed substantial ability to detect severe sepsis and septic shock [27]. Combining presepsin to usual severity scoring systems improved their performance to detect more severely ill patients [27]. Presepsin has also the capacity to predict mortality. Performances of presepsin to 14
ACCEPTED MANUSCRIPT determine risk of death are close to PCT and vary between studies [27, 33]. Some reports show a modest sensitivity and specificity of the test [27]. Presepsin slightly
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improved MEDS and APACHE2 performance to predict d-28 mortality. Appraisal of
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mortality seems of interest for the first few days after the beginning of the infection
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and less relevant for mid-term evaluation [33, 42]. Very recently, presepsin levels were shown to be correlated with severity of sepsis during follow-up [44]. Correlation of presepsin level and SOFA score increased with the elapsed time, and was highest
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at day 7; the same observation was done for prognostic accuracy of presepsin for 28-
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day mortality [47]. Prognosis and severity of infection might be assessed more
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accurately by measuring prespesin level during the early days of sepsis.
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ACCEPTED MANUSCRIPT 5. Conclusion and perspectives Presepsin may have an interest for early diagnosis and prognostic assessment of
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patients with systemic infections. This biomarker shows high specificity, and results
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from experimental and clinical studies are reinforcing the proof of concept.
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Performances place presepsin at the level of PCT who is used as a comparator. Therefore comparing PCT and presepsin to determine which biomarker (or which
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combination) has the best characteristics at bedside is mandatory. In comparison to PCT, significance of presepsin elevation is easy to understand, as it results from a
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dose-response mechanism of the host-pathogen interaction. As suggested by scientific literature, presepsin increases with every type of bacteria and fungi. This is
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understandable, as molecular mechanisms that involve CD14 allow innate immune
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response against most microorganisms and therefore lead to presepsin release.
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Using a biomarker of infection is futile in case of direct access to bacteria (such as urinary tract infection, meningitis). Conversely, when diagnosis of infection is unclear, the use of biomarkers can be suggested. Future developments of presepsin will
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probably use clinical models with a Bayesian approach to ascertain the additional value of the biomarker at bedside.
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ACCEPTED MANUSCRIPT 6. Acknowledgements We thank Akli Bouaziz (Nephrotek Laboratories) and Dr Ralf Thomae (Mitsubishi
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Chemical Europe GmbH) for providing support in collecting scientific data on
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presespin.
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Januzzi JL, van Kimmenade R, Lainchbury J, Bayes-Genis A, Ordonez-Llanos
J, Santalo-Bel M, Pinto YM, Richards M. NT-proBNP testing for diagnosis and shortterm prognosis in acute destabilized heart failure: an international pooled analysis of
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K, Plebani M, Biasucci LM, Tubaro M, Collinson P, Venge P, Hasin Y, Galvani M,
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Koenig W, Hamm C, Alpert JS, Katus H, Jaffe AS; Study Group on Biomarkers in Cardiology of ESC Working Group on Acute Cardiac Care. How to use high-
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sensitivity cardiac troponins in acute cardiac care. Eur Heart J 2012;33:2252-7. Palmiere C, Mussap M, Bardy D, Cibecchini F, Mangin P. Diagnostic value of
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soluble CD14 subtype (sCD14-ST) presepsin for the post-mortem diagnosis of sepsis-related fatalities. Int J Legal Med 2013; 127:799-808. Masson S, Caironi P, Spanuth E, Thomae R, Panigada M, Sangiorgi G,
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Fumagalli R, Mauri T, Isgrò S, Fanizza C, Romero M, Tognoni G, Latini R, Gattinoni
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L. Presepsin (soluble CD14 subtype) and procalcitonin levels for mortality prediction in sepsis ; data from the Albumin Italian Outcome Sepsis trial. Crit Care 2014;18:R6. [43]
Rabensteiner J, Skvarc M, Hoenigl M, Osredkar J, Prueller F, Reichsoellner
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M, Krause R, Raggam RB. Diagnostic and prognostic potential of presepsin in Emergency Department patients presenting with systemic inflammatory response syndrome. J Infect 2014;69:627-30. [44]
Endo S, Suzuki Y, Takahashi G, Shozushima T, Ishikura H, Murai A, Nishida
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Liu B, Yin Q, Chen YX, Zhao YZ, Li CS. Role of Presepsin (sCD14-ST) and
the CURB65 scoring system in predicting severity and outcome of communityacquired pneumonia in an emergency department. Respir Med 2014;108:1204-13. 23
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Nakamura A, Wada H, Ikejiri M, Hatada T, Sakurai H, Matsushima Y, Nishioka
J, Maruyama K, Isaji S, Takeda T, Nobori T. Efficacy of procalcitonin in the early
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diagnosis of bacterial infections in a critical care unite. Shock 2009;31:591.
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Presepsin in the prognosis of infectious diseases and diagnosis of infectious disseminated intravascular coagulation: A prospective, multicentre, observational study. Eur J Anaesthesiol 2014; in press
Poggi C, Bianconi T, Gozzini E, Generoso M, Dani C. Presepsin for the
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[48]
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Detection of Late-Onset Sepsis in Preterm Newborns. Pediatrics 2015;135 :68-75.
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ACCEPTED MANUSCRIPT Table 1. Control presepsin values in healthy volunteers, patients without SIRS and patients with SIRS without infection. Population
No
Presepsin (pg/mL)
Author [ref.]
119
range 60-365, med 160
Manufacturer data
20
mean 123 (SD 67,6)
Okamura et al. [7]
75
mean 21.8 (SD 8,45)
22
mean 294.2 (SD 121,4)
47
mean 200 [IQR149-275]
100
mean 130 (25 -75 perc. 104-179)
Liu et al. [27]
54
med 202 [IQR 167-266]
Chenevier-Gobeaux et al. [28]
60
med 216 (IQR 146-350)
Behnes et al. [29]
25
mean 92.74 (SD 21.43)
Kweon et al. [30]
SC R
NU
th
Yaegashi et al. [22] Shozushima et al. [25] Claessens et al. [26]
D
MA
th
IP
T
Healthy volunteers :
TE
Patients without SIRS : 144
med 442 [IQR 337-562]
<70yrs
22
med 300 [IQR 201-457]
122
med 470 [IQR 380-601]
26
mean 643, med 578
Mussap et al. [31]
60
med 454 (IQR 262-569.5)
Malickova et al. [32]
80
mean 81,3* (SD 49,5)
Yaegashi et al. [22]
41
mean 333.5 (SD 130,6)
Shozushima et al. [25]
179
mean 212 (IQR. 143-300)
Liu et al. [27]
9
med 393 (IQR 249-745)
Behnes et al. [29]
20
mean 421.83 (SD 338.21)
Kweon et al. [30]
83
mean 2516.4 (95%CI 1360.3-3672.4)
Ulla et al. [33]
39
mean 503 (SD 464)
Ishikura et al. [34]
189
mean 606 (SD 494)
Romualdo et al. [35]
11
med 332 (2.5-95.5 perc. 64-1523)
Cakır Madenci et al. [36]
>70yrs Preterm neonates
AC
Preterm females
CE P
Total
Chenevier-Gobeaux et al. [28]
Patients with SIRS :
Burn
25
ACCEPTED MANUSCRIPT Footnote: SIRS : systemic inflammation response syndrome; med : median ;IQR :
AC
CE P
TE
D
MA
NU
SC R
IP
T
interquartile range ; SD : standard deviation ; perc. : percentile. * results in ng/mL.
26
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Table 2. Synoptic presentation of presepsin values and main results of studies on presepsin. Setting
Population (n)
Presepsin (pg/mL)
Okamura et al. [7]
NA
Reference population (n=20)
mean 123 (SD 67,6)
Patients with bacteremia (n=20)
mean 2363 (SD 2161)
Reference population (n=75)
mean 21,8ng/mL (SD 8,45)
SIRS (n=80)
mean 81,3ng/mL (SD 49,5)
Systemic infection (n=66)
mean 220,7ng/mL (SD 142,8)
Reference population (n=22)
mean 294,2 (SD 121,4)
(Infection + sepsis) vs. (SIRS + reference population) :
SIRS (n=41)
mean 333,5 (SD 130,6)
PSEP AUC 0,845 ; threshold = 399 pg/mL
ED/ICU
[25]
IP
mean 721 (SD 611,3)
Systemic infection (n=87)
Main results P<0.0001
Systemic infection vs. (SIRS + reference population) PSEP AUC 0,817
PCT AUC 0.666
mean 817,9 (SD 572,7) mean 1992,9 (SD 1505,2)
CE P
Severe sepsis (n=14)
mean 130 (IQR 104-179)
mean 212 (IQR 143-300)
PSEP AUC 0.820; threshold = 317 pg/ml: Se=70.8%
mean 325 (IQR 210-480)
Sp=85.8%, PPV=93.2% NPV=51.6%
Severe sepsis (n=210)
mean 787 (IQR 464-1249)
Septic shock (n=98)
mean 1084 (IQR 695-2365)
PCT 0.741 (95%CI 0.703-0.779)
Healthy volunteers (n=100) SIRS (n=179) Sepsis (n=372)
AC
ED
CR
US
Local infection (n=28)
Liu et al. [27]
MA N
Shozushima et al.
ED/ICU
TE D
Yaegashi et al. [22]
T
Auteur [réf.]
Infection vs. (healthy volunteers + SIRS):
Sepsis vs. (severe sepsis + septic shock):
PSEP AUC 0.840 (95%CI 0.809-0.872); threshold = 349 pg/mL APACHE II 0.744 (95%CI 0.706-0.782) PSEP+APACHE II 0.858 (95%CI 0.829-0.887)
27
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d-28 mortality in septic patients:
APACHE II 0.722 (95%CI 0.681-0.763) PSEP+APACHE II 0.734 (95%CI 0.693-0.775)
SIRS (n=9)
med 393 (IQR 249-745)
PSEP AUC 0.80 (95%CI 0.73-0.86); threshold = 700
Sepsis (n=5)
med 362 (IQR 249-745)
pg/mL: Se=91% Sp=77% PPV=74% NPV=92%
Severe sepsis (n=28)
med 947 (IQR 523-2486)
PCT AUC 0.83 (95%CI 0.77-0.90)
Sepsis (n=25) Severe sepsis (n=22) Septic shock (n=26)
mean 92.74 (SD 21.43)
CE P
Controls (n=25) SIRS (n=20)
Severe sepsis and septic shock vs. others:
med 2330 (IQR 1181-5219)
AC
ED
pg/mL
med 216 (IQR 146-350)
Septic shock (n=74) Kweon et al. [30]
PSEP AUC 0.658 (95%CI 0.614-0.703) ; threshold = 556
Control (n=60)
MA N
ICU
TE D
Behnes et al. [29]
US
CR
IP
T
PCT 0.679 (95%CI 0.636-0.722)
Infection vs. no infection:
mean 421.83 (SD 338.21)
PSEP AUC 0.937; threshold = 430 pg/mL Se=87.7%
mean 875.8 (SD 591.63)
Sp=82.2%
mean 1452.23 (SD 729.82)
PCT AUC 0.915; threshold = 1 ng/mL Se=86.3%
mean 1869.58 (SD 1467.42)
Sp=86.7% PSEP to predict APACHEII increase : P>0.05 PSEP to predict d30 mortality : P>0.005
Ulla et al. [33]
ED
SIRS (n=83)
mean 2516.4 (95%CI 1360.3-3672.4)
Sepsis (n=55)
mean 2866.7 (95%CI 1579-4154)
PSEP threshold = 600pg/mL: Se=78.95% Sp=61.9%
Severe sepsis/septic shock (n=51)
mean 3167.1 (95%CI 1686.5-4647.7)
Sepsis:
d-60 in hospital mortality in septic patients:
28
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PSEP 4,232.4 vs.3,451.2pg/mL, P=0.04
No infection and SIRS (n=39)
mean 503 (SD 464)
Infection (n=43) :
mean 3290 (SD 4620)
IP
ED
CR
Ishikura et al. [34]
T
PCT 17.12 vs. 9.59 ng/mL, P=0.87
US
. Sepsis (n=8) . Severe sepsis (n=14)
Romualdo et al. [35]
ED
SIRS without bacteremia (n=189)
Burn
AC
Cakır Madenci et al. [36]
Infection vs. no infection:
PSEP AUC 0.887; threshold = 647pg/mL Se=93% Sp=76.3% PCT AUC 0.904
DIC vs. no DIC :
PSEP AUC 0.808; threshold = 899pg/mL Se=83.3% Sp=78.3% PCT AUC 0.785
mean 606 (SD 494)
PSEP AUC 0.75; threshold = 729 pg/mL Se=81.1%
mean 1219 (SD 2188)
Sp=63% LR+=2.19 LR-=0.3
CE P
SIRS with bacteremia (n=37)
TE D
MA N
. Septic shock (n=21)
PCT AUC 0.783; threshold = 0.45 ng/mL Se=75.7% Sp=64% LR+=2.1 LR-=0.38
Burn without sepsis (n=11)
med 332 (2.5-95.5 perc. 64-1523)
PSEP to detect infection vs. no infection : P<0.0001
Burn and sepsis (n=26)
med 847 (2.5-95.5 perc. 207-12364)
PCT to detect infection vs. no infection : P=0.0012 PSEP to predict mortality : P<0.0001 PCT to predict mortality : P=0.0021
Palmiere et al. [41]
Masson et al. [42]
Post-
Non septic death (n=10)
med 670, range 180-4890
PSEP threshold = 600pg/mL: Se=0,94 Sp=0.83 AUC
mortem
Septic death (n=19)
med 4420, range 92-8960
0.81
ICU
Severe sepsis / septic shock
PSEP kinetics survivor/non survivor (d1, d2, d7)
29
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med 1184 (IQR 875-2113)
P=0.03
. non survivor (n=50)
med 2269 (IQR 1171-4300)
d28 mortality :
non adjusted OR 1.73 (95%CI 1.32-2.27) per unit adjusted OR 1.54 (95%CI 1.12-2.12) per unit
d90 mortality :
non adjusted OR 1.50 (95%CI 1.18-1.91) per unit adjusted OR 1.29 (95%CI 0.96-1.76) per unit
med 931 (IQR 500-1722)
Gram-positive bacteremia (n=102)
med 1078 (IQR 670-2422)
PSEP AUC 0.6 (95%CI 0.517-0.684)
Gram-negative bacteremia (n=124)
med 1295 (IQR 777-2654)
PCT AUC 0.693 (95%CI 0.617-0.768)
med 2293 (IQR 804-3027)
Gram-positive vs. Gram-negative PCT, p=0.008
Candidemia (n=15)
TE D
Negative blood culture (n=59)
CE P
ED
AC
Rabensteiner et al. [43]
MA N
US
CR
IP
T
. Survivor (n=50)
Bacteraemia vs negative blood culture:
Candidemia vs. negative blod culture, PSEP p=0.038
Admission to ICU :
PSEP AUC 0.645 (95%CI 0.565-0.725) PCT AUC 0.612 (95%CI 0.529-0.694)
H48 mortality:
PSEP AUC 0.619 (95%CI 0.442-0.795) PCT AUC 0.709 (95%CI 0.557-0.861)
d30 mortality:
PSEP AUC 0.65 (95%CI 0.557-0.742) PCT AUC 0.583 (95%CI 0.497-0.668)
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d90 mortality:
ED /ICU
Patients with infection (n=53)
med 1523 (IQR 1014-2615)
CR
Endo et al. [44]
IP
T
PSEP AUC 0.659 (95%CI 0.581-0.737)
US
. Sepsis (n=14) . Severe sepsis (n=19)
Liu et al. [45]
TE D
MA N
. Septic shock (n=20)
CAP (n=359)
ICU
d0 levels of biomarkers:
PSEP, CRP, PCT, IL6 : not associated with SOFA / APACHEII
Kinetics (d0,d3,d7) of biomarkers:
PSEP : no decrease if unfavorable SOFA / APACHEII CRP,
PCT,
IL6:
decrease
regardless
of
SOFA/APACHEII
med 689 (IQR 395.5-1225.5)
ARDS : OR 1 (95%CI 1-1), P=0.708
AC
Nakamura et al. [46]
med 400 (IQR 231.5-691.5)
CE P
Severe CAP (n=214)
PCT AUC 0.577 (95%CI 0.502-0.653)
PSEP to predict adverse outcome:
DIC : OR 1 (95%CI 1-1.001), P=0.001 Severe CAP : OR 1 (95%CI 1-1.001), P=0.614 d28 mortality : OR 1 (95%CI 1-1.001), P=0.006
Non acute kidney injury
sepsis in non acute kidney injury:
. SIRS without infection (n=75)
med 300 (range 86-4374)
AUC 0.784 (95%CI 0.683-0.86)
. Sepsis (n=37)
med 831 (range 187-9960)
Risk
sepsis in risk, injury and failure combined:
AUC 0.698 (95%CI 0.593-0.786)
. SIRS without infection (n=23)
med 467 (range 71–3361)
. Sepsis (n=27)
med 924 (range 290–16759)
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med 517 (range 144–1197)
. Sepsis (n=27)
med 1451 (range 237–4200)
IP
. SIRS without infection (n=9)
med 1535 (range 454–8516)
. Sepsis (n=27)
med 1523 (range 293–16764)
Infectious
disseminated
NA
Preterm newborns with late-onset
CE P
sepsis (n=19)
Preterm newborns non infected controls (n=21)
med 1295 (p<0.0001 vs. controls)
med 562
Sepsis vs SIRS:
(PSEP+PCT) AUC = 0.91 PSEP AUC = 0.89 PCT AUC = 0.85
Late-onset sepsis:
PSEP AUC 0,972; threshold = 885 ng/L (Se94%, Sp100%)
AC
NA
TE D
intravascular coagulation (n=191)
Poggi et al. [48]
US
. SIRS without infection (n=15)
MA N
NA
CR
Failure
Takahashi et al. [47]
T
Injury
32
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Footnote: NA: not available; ED: department of emergency medicine; ICU: intensive care unit; IQR: Interquartile range; SIRS:
IP
T
systemic inflammation response syndrome; PSEP: presepsin; PSEP: presepsin; PCT: procalcitonin; DIC: disseminated
CR
intravascular coagulation; ARDS: acute respiratory distress syndrome; SOFA: sequential organ failure assessment score; APACHE
US
II: acute physiology and chronic health evaluation score; med: median; IQR: interquartile range; SD: standard deviation; perc.:
MA N
percentile; AUC: area under the ROC curve; 95%CI: 95% confidence interval; Se: sensitivity; Sp: specificity; PPV: positive
AC
CE P
TE D
predictive value; NPV: negative predictive value; LR+: positive likelihood ratio; LR-: negative likelihood ratio. * results in ng/mL.
33
AC
CE P
TE D
MA N
US
CR
IP
T
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Figure 1. Shematic production of presepsin. TLR: Toll-like-receptor; LPS: lipopolysaccharides ; LBP: LPS-binding protein; MD2: molecular dynamic-2; PSEP : presepsin. 34
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IP
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Presepsin (sCD14-ST) to detect sepsis: review and perspectives of a biomarker derived from innate immune response
US
CR
Camille Chenevier-Gobeaux (1), Didier Borderie (1, 2), Nicolas Weiss (3), Thomas Mallet-Coste (3), Yann-Erick Claessens (3).
MA N
Highlights o Presepsin appears as an emergent biomarker of infection.
TE D
o Recent data support presepsin use at bedside.
CE P
o Presepsin may have an interest for early diagnosis of sepsis.
AC
o Presepsin may have an interest for prognostic assessment of sepsis.
35