Presepsin marker panel for early detection of sepsis

Abstract

The present invention relates to the field of diagnosis.Specifically, the present invention relates to a method for assessing a subject suspected of infection, comprising the steps of: determining the amount of a first biomarker in a sample of the subject, the first biomarker being presepsin; determining the amount of a second biomarker in a sample of the subject, the second biomarker being selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), comparing the amount of the biomarker with a standard for the biomarker and / or calculating a score for assessing the subject suspected of infection based on the amount of the biomarker; and assessing the subject based on the comparison and / or the calculation. The present invention also relates to the use of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), or a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, for assessing a subject suspected of infection. Furthermore, the present invention further relates to a computer-implemented method for assessing a subject suspected of infection, and an apparatus and a kit for assessing a subject suspected of infection.

Description

[Technical field]

[0001] The present invention relates to the field of diagnosis.Specifically, the present invention relates to a method for assessing a subject suspected of infection, comprising the steps of determining the amount of a first biomarker in a sample of the subject, said first biomarker being presepsin; determining the amount of a second biomarker in a sample of the subject, said second biomarker being selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), comparing the amount of the biomarker with a standard for said biomarker and / or calculating a score for assessing the subject suspected of infection based on the amount of the biomarker; and assessing the subject based on the comparison and / or calculation. The present invention also relates to the use of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), or a detection agent that specifically binds to said first biomarker and a detection agent that specifically binds to said second biomarker, for assessing a subject suspected of infection.Furthermore, the present invention relates to a computer-implemented method for assessing a subject suspected of infection, and an apparatus and a kit for assessing a subject suspected of infection. [Background technology]

[0002] Infections, particularly those that occur in patients with more severe signs and symptoms, such as those presenting to an emergency department, can develop into more life-threatening medical conditions, including systemic inflammatory response syndrome (SIRS) and sepsis.

[0003] According to the Sepsis-3 definition, sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Because sepsis develops rapidly, early recognition is important to initiate correct therapeutic measures, including appropriate antibiotic therapy within the first hour of management and hospitalization of septic patients, as well as initiating resuscitation with intravenous fluids and vasoactive drugs (Sepsis Campaign Guidelines 2016). Every hour of delay is associated with a progressive increase in morbidity and mortality.

[0004] The diagnosis of sepsis is based on clinical signs and symptoms that are non-specific and can be easily overlooked. Thus, patients are often misdiagnosed and the severity of the disease can be underestimated. So far, there is no gold standard for the diagnosis of sepsis in general, especially in the emergency department. In high-income countries, c-reactive protein (CRP), procalcitonin (PCT) and white blood cell (WBC) counts are often used in emergency rooms for the detection of patients with bloodstream infections at risk of developing sepsis, along with lactate values ​​for the detection of septic shock. In low-income countries, the diagnosis is mainly based on clinical signs and symptoms, and occasionally SIRS and SOFA criteria. However, the latest guidelines do not list any biomarkers for diagnosing sepsis, other than lactate (except for clinical chemistry, BGE and the hematological component of the SOFA score). PCT is only recommended to potentially ease antibiotic therapy, but with moderate evidence. The limitations of PCT in sepsis diagnosis are mainly its moderate sensitivity and specificity.

[0005] WO 2007 / 009071 discloses a method for diagnosing an inflammatory response in a subject based on sFlt-1. The disclosed method further comprises analyzing the level of at least one of VEGF, PlGF, TNF-α, IL-6, D-dimer, P-selectin, ICAM-I, VCAM-I, Cox-2, or PAI-I.

[0006] EP 2174143 discloses an in vitro method for the prognosis of patients with a primary non-infectious disease, which comprises determining the level of procalcitonin.

[0007] A number of markers have been suggested to be useful in detecting or diagnosing sepsis. These include PCT, presepsin, GDF-15, sFLT, inflammatory markers such as CRP or interleukins, or markers specific for organ failure, among many others (e.g., Spanuth, 2014, Comparison of sCD14-ST (presepsin) with eight biomarkers in predicting mortality in patients hospitalized with acute heart failure, 2014 AACC Annual Meeting Abstracts. B-331; van Engelen, 2018, Crit Care Clin 34(1):139-152).

[0008] WO 2015 / 031996 discloses biomarkers for the early determination of serious or life-threatening responses to disease and / or treatment responses.

[0009] However, there remains a need for biomarkers that allow reliable and early assessment of patients who exhibit signs and symptoms of infection. Summary of the Invention

[0010] Therefore, the present invention provides means and methods that meet these needs.

[0011] The present invention provides a method for assessing a subject suspected of infection, comprising: (a) determining the amount of a first biomarker in a sample from a subject, wherein the first biomarker is presepsin; (b) determining the amount of a second biomarker in the subject's sample, wherein the second biomarker is selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein); (c) comparing the amount of the biomarker with a standard of said biomarker and / or calculating a score for assessing the subject as suspected of being infected based on the amount of the biomarker; and (d) assessing the subject based on the comparisons and / or calculations performed in step (c). The present invention relates to a method comprising the steps of: DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] As used in this specification and claims, it should be understood that "a" or "an" can mean one or more, depending on the context in which it is used. Thus, for example, reference to "an" item can mean that at least one item can be utilized.

[0013] When used below, the terms "have", "comprise" or "include" or any grammatical variants thereof are used in a non-exclusive manner. These terms may therefore refer both to the situation in which the entity described in this context has no further features other than those introduced by these terms, and to the situation in which one or more further features are present. As an example, the expressions "A has B", "A comprises B" and "A includes B" can all refer to the situation in which, apart from B, no other elements are present in A (i.e., A consists solely and exclusively of B), as well as to the situation in which, apart from B, one or more further elements are present in the entity A, such as element C, elements C and D, or even further elements. The term "comprising" has a restrictive meaning in the sense of "consisting of", also encompassing embodiments in which only the mentioned items are present.

[0014] Furthermore, when used hereinafter, the terms "particularly", "more particularly", "typically" and "more typically" or similar terms are used with additional / alternative features without limiting the possibility of substitution. Thus, features introduced by these terms are additional / alternative features and are not intended to limit the scope of the claims in any way. The invention may be implemented by using alternative features, as would be understood by a person skilled in the art. Similarly, features introduced by "in an embodiment of the invention" or similar expressions are intended to be additional / alternative features, without any limitation on alternative embodiments of the invention, without any limitation on the scope of the invention, and without any limitation on the possibility of combining the features so introduced with other additional / alternative or non-additional / alternative features of the invention.

[0015] Furthermore, as used herein, the term "at least one" is understood to mean that one or more of the items followed by this term can be used according to the present invention. For example, when this term indicates that at least one sampling unit should be used, this may be understood as one sampling unit or two or more sampling units, i.e., two, three, four, five, or any other number. Depending on the item to which the term refers, a person skilled in the art will understand which upper limit, if any, the term can refer to.

[0016] As used herein, the term "about" means that there is an interval of precision that can achieve the technical effect for any number listed after the term. Thus, "about" as referred to herein preferably refers to the exact numerical value or a range of ±20%, preferably ±15%, more preferably ±10%, or even more preferably ±5% of the exact numerical value.

[0017] Moreover, the terms "first," "second," "third," etc. in the specification and claims are used to distinguish between similar elements and are not necessarily intended to describe a sequential or chronological order.

[0018] The method of the invention may consist of the above steps or may include additional steps, such as a step for further evaluating the assessment obtained in step (d), a step for recommending a therapeutic measure, such as a treatment. Furthermore, the method of the invention may include a step prior to step (a), such as a step relating to the pre-treatment of the sample. However, it is preferably envisaged that the above-mentioned method is an ex vivo method that does not require any steps performed on the human or animal body. Furthermore, the method may be supported by automation. Typically, the determination of the biomarkers may be supported by a robotic device, and the comparison and assessment may be supported by a data processing device, such as a computer.

[0019] As used herein, the term "assessing" refers to assessing whether a subject suffers from sepsis, whether a subject is at risk of suffering from sepsis, whether a subject shows symptoms of deterioration in terms of overall health, or in terms of sepsis or the signs and symptoms associated with sepsis and / or infection.Accordingly, as used herein, assessing includes diagnosing sepsis, predicting the risk of developing sepsis, and / or predicting any deterioration in the health of a subject, particularly in terms of the signs and symptoms associated with sepsis and / or infection.

[0020] Typically, the assessment referred to by the present invention is an assessment of the risk of developing sepsis (hence, a prediction of the risk of developing sepsis). Alternatively, the assessment is a prediction of the risk of the subject's (health) condition worsening. Furthermore, it will be understood that when the risk of developing sepsis or the risk of the health condition worsening is predicted, the prediction is typically made within a prediction window. More typically, the prediction window is preferably about 8 hours, about 10 hours, about 12 hours, about 16 hours, about 20 hours, about 24 hours, about 48 hours, particularly at least about 48 hours after the sample is obtained. Furthermore, the risk of developing sepsis can be predicted preferably within 24 or 48 hours after the test sample is obtained.

[0021] In one embodiment, the risk of developing sepsis within 24 hours is predicted. In another embodiment, the risk of developing sepsis within 48 hours is predicted. The 48 hour period was tested in the Examples section.

[0022] In yet another embodiment, the assessment is a prediction of the risk of the subject's (health) condition worsening in the future.The term "worsening condition" of a subject suspected of suffering from an infectious disease and / or suffering from an infectious disease is well understood by those skilled in the art.This term typically relates to the worsening condition that can eventually lead to further medication or other intervention.

[0023] Preferably, if the subject's condition deteriorates, if the subject's disease severity increases, if the subject's antibiotic therapy is intensified, if the subject is admitted to an ICU or another unit for a higher level of care, if the subject requires emergency surgery, if the subject dies in the hospital, if the subject dies within 30 days after admission, if the subject is readmitted within 30 days after discharge, if the subject experiences organ dysfunction or failure, e.g., as measured by SOFA score, and / or if the subject requires organ support.

[0024] One of skill in the art will appreciate when a subject's condition does not worsen. Typically, a subject's condition does not worsen if the subject does not have the results described in the previous paragraph.

[0025] In one embodiment, a subject's condition deteriorates if the subject has one or more of the following outcomes: the subject is admitted to the ICU, the subject dies in the hospital, the subject dies within 30 days of admission, and / or the subject is readmitted within 30 days of discharge.

[0026] In one embodiment, predicting the risk of the subject's condition worsening is predicting the risk of the subject's antibiotic therapy being intensified.

[0027] In one embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the subject's risk of being admitted to an ICU. Thus, it is assessed whether the subject is at risk of being admitted to an ICU.

[0028] In another embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the subject's risk of dying during hospitalization. Thus, it is assessed whether the subject is at risk of dying during hospitalization.

[0029] In yet another embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the subject's risk of death within 30 days of admission. Thus, it is assessed whether the subject is at risk of dying within 30 days of admission to the hospital.

[0030] In yet another embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the subject's risk of readmission within 30 days after discharge. Thus, it is assessed whether the subject is at risk of being readmitted within 30 days after discharge.

[0031] In yet another embodiment, the prediction of the risk of the subject's condition worsening is the prediction of the risk of the subject experiencing organ dysfunction or insufficiency. Organ dysfunction and insufficiency can be assessed, for example, through SOFA score. Thus, the present invention further relates to the prediction of the risk of the subject's SOFA score increasing or not increasing (after the test sample is obtained). If the SOFA score increases (for example, by at least one, at least two, at least three, or at least four points, etc.), the condition is considered to be worsening. In contrast, if the SOFA score does not increase (if the subject does not have the highest SOFA score), the condition usually does not worsen. The prediction window can be the prediction window described above for the prediction of the risk of developing sepsis.

[0032] The Sequential Organ Failure Assessment (SOFA) is a validated score that combines clinical assessments and laboratory measurements that quantitatively describe organ dysfunction / failure. Respiratory, coagulation, hepatic, cardiovascular, central nervous system and renal dysfunction are scored individually and summed up to a SOFA score ranging from 0 to 24. Preferably, the SOFA score is determined as described in Vincent 1996 (Vincent et al. Intensive Care Med. 1996 Jul;22(7):707-10. doi:10.1007 / BF01709751. PMID:8844239.).

[0033] In yet another embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the risk of the subject needing organ support, such as a prediction of the risk of the subject needing vasoactive therapy, hemodynamic support (e.g., by ventilation or by extracorporeal membrane oxygenation), oxygenation, and / or renal replacement therapy. The prediction window may be, for example, the prediction window described above for predicting the risk of developing sepsis within 24 or 48 hours after the sample is obtained.

[0034] In one embodiment, the term "assessment" refers to the diagnosis of sepsis. Thus, a subject suspected of infection is diagnosed as suffering from sepsis or not. Preferably, assessment refers to the early detection of sepsis.

[0035] As will be understood by those skilled in the art, the assessment made according to the present invention, although preferred, may not be correct for 100% of the subjects usually examined. This term typically requires that the statistically significant portion of the subjects can be accurately assessed. Whether a portion is statistically significant can be determined by those skilled in the art without further difficulty using various well-known statistical evaluation tools, such as determining confidence intervals, determining p-values, Student's t-test, Mann-Whitney test, etc. Details can be found in Dowdy and Wearden, Statistics for Research, John Wiley and Sons, New York 1983. The typically assumed confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%. The p-value is typically 0.2, 0.1, 0.05.

[0036] As used herein, the term "subject" refers to an animal, preferably a mammal, more typically a human. The subject investigated by the method of the present invention shall be a subject suspected of infection. As used herein, the term "suspected of infection" means that the subject shows clinical parameters, signs and / or symptoms of infection. Thus, the subject according to the present invention is typically a subject suffering from or suspected of suffering from an infectious disease. Typically, the subject is a subject presenting to an emergency department. Advantageously, the sample is obtained at the time of presentation. Preferably, the sample is obtained at the time of presentation at the emergency department. However, the sample may also be obtained at the time of presentation at a primary care physician.

[0037] As used herein, the term "sample" refers to any sample that contains the first, second and / or third biomarkers referred to herein under physiological conditions. More typically, the sample is a body fluid sample, such as a blood sample or a sample derived therefrom, a urine sample, a saliva sample, a lymph sample, etc. Most typically, the sample is a blood sample or a sample derived therefrom. Thus, the sample may be a blood, serum or plasma sample. A blood sample typically includes a capillary, venous or arterial blood sample.

[0038] In one embodiment, the sample is an interstitial fluid sample.

[0039] The term "sepsis" is well known in the art. As used herein, this term refers to life-threatening organ dysfunction caused by dysregulated host response to infection. The definition of sepsis can be found, for example, in Singer et al. (Sepsis-3: The Third International Consensus Definitions for Sepsis and Septic Shock. JAMA 2016;315:801-819), which is incorporated by reference in its entirety. Preferably, the term "sepsis" refers to sepsis according to the definition of Sepsis-3 disclosed in Singer et al. (cited above).

[0040] Typically, the subject to be tested is suspected of suffering from an infectious disease. The term "infection" is well understood by those skilled in the art. As used herein, the term "infection" preferably refers to the invasion of the subject's body tissue by disease-causing microorganisms, their proliferation, and the reaction of the subject's tissue to the microorganisms. In one embodiment, the infection is a bacterial infection. Thus, the subject is suspected of suffering from a bacterial infection.

[0041] As described elsewhere herein, the present invention allows early identification of at-risk patients. Thus, in one embodiment of the prediction described herein, the subject being tested is not suffering from sepsis at the time the sample is obtained. In a particularly preferred embodiment, the subject being tested is preferably not suffering from septic shock at the time the sample is obtained. The term "septic shock" is defined in Singer et al. (supra). Thus, if the following criteria are met, the subject is suffering from septic shock. Sepsis, i.e. suspected / documented infection and a change in total SOFA score of ≥2 points as a result of infection and persistent hypotension requiring vasopressors to maintain MAP ≥ 65 mmHg despite adequate volume resuscitation, and with a serum lactate level > 2 mmol / L (18 mg / dL).

[0042] It is further envisaged that the subjects being tested may or may not be infected with SARS-CoV-2.

[0043] As used herein, the term "determining" refers to the qualitative and quantitative determination of the biomarker referred to in accordance with the present invention, i.e., the term encompasses the determination of the presence or absence or the determination of the absolute or relative amount of said biomarker. As used herein, the term "amount" refers to the absolute amount of the compound referred to herein, the relative amount or concentration of the compound, as well as any value or parameter that can be correlated therewith or derived therefrom. Such values ​​or parameters include intensity signal values ​​from any specific physical or chemical property obtained from the compound by direct measurement, such as intensity values ​​of mass spectrum or NMR spectrum. In addition, all values ​​or parameters obtained by indirect measurement as specified elsewhere herein are included, such as response levels determined from a biological readout system in response to a compound or intensity signal obtained from a specifically bound ligand. It should be understood that values ​​that correlate with the above-mentioned amount or parameter can also be obtained by any standard mathematical operation. When the biomarker is an enzyme, such as alanine aminotransferase (ALAT) or aspartate aminotransferase (AST or ASAT), the term "amount" can also include the activity of the enzyme.

[0044] The determination of the amount in the methods of the invention can be carried out by any technique that allows detecting the presence or amount of said second molecule upon release from said first molecule. Suitable techniques will depend on the nature of the molecule and the characteristics of the biomarker and are discussed in more detail elsewhere herein.

[0045] Typically, the amount of the biomarkers referred to in accordance with the present invention can be determined by immunoassays using sandwich, competitive, or other assay formats. The assay generates a signal indicative of the presence or absence or amount of the biomarker. Further suitable methods include measuring a physical or chemical property specific to the biomarker, such as its exact molecular mass or NMR spectrum. The methods preferably include biosensors, optical devices coupled with immunoassays, biochips, analytical devices such as mass spectrometers, NMR analyzers, surface plasmon resonance measuring instruments or chromatography devices. Furthermore, the methods include microplate ELISA-based methods, fully automated or robotic immunoassays (e.g. available from Roche). Suitable measurement methods according to the present invention may also include precipitation (particularly immunoprecipitation), electrochemiluminescence (electrogenerated chemiluminescence), RIA (radioimmunoassay), ELISA (enzyme-linked immunosorbent assay), electrochemiluminescence sandwich immunoassay (ECLIA), dissociation-enhanced lanthanide fluoroimmunoassay (DELFIA), scintillation proximity assay (SPA), turbidimetry, nephelometry, latex-enhanced nephelometry or nephelometry, or solid-phase immunoassay. There are further methods known in the art, such as gel electrophoresis, 2D gel electrophoresis, SDS-polyacrylamide gel electrophoresis (SDS-PAGE) or Western blotting. More typically, the techniques specifically envisaged for determining the biomarkers referred to herein are described in the accompanying examples below.

[0046] The biomarkers determined according to the present invention are well known in the art. Moreover, methods for determining the amount of biomarkers are known. For example, biomarkers can be measured as described in the Examples section (see Example 1). Some of the biomarkers tested are enzymes (such as aspartate aminotransferase). The amount of these biomarkers can also be determined by determining the activity of the enzyme in the sample.

[0047] The biomarker presepsin is also known as "soluble CD14 subtype" or "sCD14-ST" and is derived from sCD14 (soluble CD14) and exists in at least two forms of high molecular weight (49 kDa and 55 kDa), of which sCD14-ST is a fragment. Proteolysis of sCD14 leads to the formation of presepsin. Markers are well known in the art, see for example the review by Erenler et al. (Presepsin (sCD14-ST) as a biomarker of sepsis in clinical practice and in emergency department: a mini review. 2015 J Lab Med 39: 367-372), which is incorporated herein by reference. Preferably, an antibody is available that specifically binds to presepsin without binding to sCD14 (see, for example, Okamura Y, Yokoi H. Development of a point-of-care assay system for measurement of presepsin (sCD14-ST). Clin Chim Acta. 2011; 412 (23-24): 2157-61).

[0048] The term "growth differentiation factor-15" or "GDF-15" refers to a polypeptide that is a member of the transforming growth factor (TGF)-cytokine superfamily. The terms polypeptide, peptide and protein are used interchangeably throughout this specification. GDF-15 was originally cloned as macrophage inhibitory cytokine 1, and was subsequently identified as placental transforming growth factor-15, placental bone morphogenetic protein, nonsteroidal anti-inflammatory drug-activated gene 1, and prostate-derived factor (Bootcov loc cit; Hromas, 1997 Biochim Biophys Acta 1354:40-44; Lawton 1997, Gene 203:17-26; Yokoyama-Kobayashi 1997, J Biochem (Tokyo), 122:622-626; Paralkar 1998, J Biol Chem 273:13760-13767). The amino acid sequence of GDF-15 is disclosed in WO 99 / 06445, WO 00 / 70051, WO 2005 / 113585, etc., Bottner 1999, Gene 237:105-111, Bootcov supra, Tan loc.cit., Baek 2001, Mol Pharmacol 59:901-908, Hromas supra, Paralkar loc cit, and Morrish 1996, Placenta 17:431-441.

[0049] Insulin-like growth factor binding protein 7 (=IGFBP7) is a modular glycoprotein of 30 kDa known to be secreted by endothelial cells, vascular smooth muscle cells, fibroblasts and epithelial cells (Ono, Y., et al., Biochem Biophys Res Comm 202 (1994) 1490-1496). Preferably, the term "IGFBP7" refers to human IGFBP7. The sequence of the protein is well known in the art and can be accessed, for example, via GenBank (NP_001240764.1).

[0050] Aspartate aminotransferase (AST or ASAT) catalyzes the transamination of L-aspartate to α-ketoglutarate, forming L-glutamate and oxalacetate. The oxalacetate formed is reduced to malate by malate dehydrogenase (MDH) with the concomitant oxidation of reduced nicotinamide adenine dinucleotide (NADH). The change in absorbance over time due to the conversion of NADH to NAD is directly proportional to AST activity and can be measured, for example, using a dichroic (340, 700 nm) kinetic technique.

[0051] The marker, cystatin C (CysC), is well known in the art. Cystatin C is encoded by the CST3 gene and is produced at a constant rate by all nucleated cells, and the production rate in humans is remarkably constant throughout life. Elimination from the circulation is almost entirely by glomerular filtration. For this reason, serum concentrations of cystatin C are independent of muscle mass and sex in the age range of 1 to 50 years. Cystatin C in plasma and serum has therefore been proposed as a more sensitive marker for GFR. The sequence of the human cystatin C polypeptide can be assessed by Genbank (see, for example, accession number NP_000090.1). Biomarkers can be determined by particle-enhanced immunoturbidimetric assays. Human cystatin C aggregates with latex particles coated with anti-cystatin C antibodies. The aggregates are detected with a turbidimeter.

[0052] sTREM-1 or soluble TREM1 (or STREM1) is the soluble form of TREM-1 (triggering receptor-1 expressed on myeloid cells). Thus, the term refers to the non-cell-bound form of TREM-1. TREM-1 is an immune receptor known to be expressed on neutrophils and monocytes / macrophages. TREM-1 is a recently discovered member of the immunoglobulin superfamily involved in the innate immune response. TREM-1 is a monomeric protein of approximately 30 kD that is synthesized as a 234 amino acid precursor with a 16 amino acid signal peptide, a 184 amino acid extracellular domain, a 29 amino acid transmembrane domain and a short cytoplasmic domain of 5 amino acids. During infection, receptor expression is altered and sTREM-1 is released. Thus, sTREM-1 (17 kDa) is a soluble form of TREM-1 that is released from the membrane of activated phagocytes, and typically the term "sTREM-1" encompasses all naturally occurring cleaved or released forms that have at least the extracellular portion of TREM-1.

[0053] The marker "creatinine" is well known in the art. In muscle metabolism, creatinine is endogenously synthesized from creatine and creatine phosphate. Under conditions of normal renal function, creatinine is excreted by glomerular filtration. Determination of creatinine is performed for the diagnosis and monitoring of acute and chronic renal diseases and for monitoring renal dialysis. Creatinine concentration in urine can be used as a reference value for the excretion of certain analytes (albumin, α-amylase). Creatinine can be determined as described by Popper et al. (Popper H et al. Biochem Z 1937;291:354), Seelig and Wust (Seelig HP, Wust H. Arztl Labor 1969;15:34) or Bartels (Bartels H et al. Clin Chim Acta 1972;37:193). For example, sodium hydroxide and picric acid are added to the sample to initiate the formation of creatinine-picric acid complex. In alkaline solutions, creatinine forms a yellow-orange complex with picrate, the intensity of which is directly proportional to the creatinine concentration and can be measured photometrically.

[0054] As used herein, the term "soluble Flt-1" or "sFlt-1" (abbreviation for "soluble fms-like tyrosine kinase-1") preferably refers to a polypeptide that is a soluble form of the VEGF receptor Flt1. sFlt-1 was identified in conditioned culture medium of human umbilical vein endothelial cells. The endogenous soluble Flt1 (sFlt-1) receptor is chromatographically and immunologically similar to recombinant human sFlt-1 and binds [125I]VEGF with comparable high affinity. Human sFlt-1 has been shown to form a VEGF-stabilized complex with the extracellular domain of KDR / Flk-1 in vitro. Preferably, sFlt-1 refers to human sFlt-1 as described in Kendall 1996, Biochem Biophs Res Commun 226(2):324-328 (for amino acid sequences see also, e.g., P17948, GI:125361 for human and BAA 24499.1, GI:2809071 for mouse sFlt-1).

[0055] Pancreatic stone protein (abbreviated as PSP) is a protein secreted by the pancreas, Lithostatin-1-alpha islet cell regenerating factor (ICRF) or Langerhans islet regenerating protein (REG). In humans, the PSP polypeptide is encoded by the REG1A gene as a single polypeptide of 144 amino acids, which is further cleaved by trypsin to generate a 133 amino acid protein that is O-linked glycosylated on threonine 27. The amino acid sequence of human PSP can be accessed via UniProt (see P05451(REG1A_HUMAN)).

[0056] In the method of the invention, a third biomarker may be determined. In particular, in step (b) of the method of the invention, (i) if the amount of GDF-15 is determined as the second biomarker, the method further comprises determining the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or (ii) If the amount of cystatin C is determined as the second biomarker, the method further comprises determining the amount of aspartate aminotransferase as a third biomarker.

[0057] Thus, the present invention relates to the determination of at least two biomarkers (i.e. the first and second biomarkers referred to herein) or at least three biomarkers (i.e. the first, second and third biomarkers referred to herein).

[0058] The first biomarker is presepsin. The second biomarker is selected from GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein).

[0059] In one embodiment, the second biomarker is GDF-15. In another embodiment, the second biomarker is cystatin C. In another embodiment, the second biomarker is creatinine. In another embodiment, the second biomarker is sFlt1. In another embodiment, the second biomarker is IGFPB7. In another embodiment, the second biomarker is sTREM1. In another embodiment, the second biomarker is PSP.

[0060] Where GDF-15 is the second marker, the method may further comprise determining the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker.

[0061] In one embodiment, presepsin, GDF-15 and sFlt-1 are determined.

[0062] In another embodiment, presepsin, GDF-15 and IGFBP7 are determined.

[0063] In another embodiment, presepsin, GDF-15 and sTREM1 are determined.

[0064] When the amount of cystatin C is determined as the second biomarker, the method may further include determining the amount of aspartate aminotransferase (ASAT) as a third biomarker. Thus, presepsin, cystatin C and ASAT are determined.

[0065] It should be understood that the present invention is not limited to the above markers, rather, the present invention may involve determining additional markers.

[0066] As used herein, the term "criterion" refers to an amount or value that allows a subject to be assigned to either a group of subjects suffering from or at risk of developing a disease or condition, or a group of subjects not suffering from or at risk of developing said disease or condition. Such a criterion can be a threshold amount that separates these groups from each other. Thus, a criterion is intended to be an amount or score that allows a subject to be assigned to a group of subjects, whether suffering from or at risk of developing a disease or condition. A criterion is intended to be an amount or score that allows a subject to be assigned to a group of subjects suffering from or at risk of developing sepsis (within the above-mentioned prediction window, such as within about 48 hours).

[0067] The appropriate threshold amount for separating two groups can be calculated without further ado by the statistical test mentioned elsewhere herein based on the amount of biomarker from either the subject or subject group known to suffer from or at risk of developing disease or condition, or the subject or subject group known not to suffer from or at risk of developing disease or condition.The reference amount applicable to individual subjects may vary according to various physiological parameters such as age, sex, or subpopulation.

[0068] Typically, the reference is a reference for each biomarker derived from at least one subject known to be at risk of developing sepsis, and preferably an amount for each biomarker that is essentially the same as or similar to the corresponding reference is shown for a subject at risk of developing sepsis, and an amount for each biomarker that differs from the corresponding reference is shown for a subject not at risk of developing sepsis.

[0069] Also, typically the standards are standards for each biomarker derived from at least one subject known to be not at risk of developing sepsis, and preferably amounts for each biomarker that are essentially identical or similar to the corresponding standard are shown for subjects not at risk of developing sepsis, while amounts for each biomarker that differ from the corresponding standard are shown for subjects at risk of developing sepsis.

[0070] The term "at least one subject" refers to one subject or multiple subjects, for example, at least 10, 50, 100, 200, or 1000 subjects.

[0071] In one embodiment, an amount of the biomarker greater than the reference level indicates a subject at risk (e.g., of developing sepsis), and an amount of the biomarker less than the reference level indicates a subject not at risk.

[0072] Reference amounts can in principle be calculated for a cohort of subjects based on the mean or average value of a given parameter, such as a biomarker amount, by applying standard statistical methods. Whether a test, particularly a method aimed at diagnosing an event, is accurate or not is best described by its receiver operating characteristics (ROC) (see, in particular, Zweig 1993, Clin. Chem. 39:561-577). The ROC graph is a plot of all sensitivity / specificity pairs resulting from continuously varying the decision threshold over the entire range of observed data. The clinical performance of a diagnostic method depends on its accuracy, i.e., its ability to correctly assign subjects to a certain prognosis or diagnosis. The ROC plot shows the overlap between the two distributions by plotting sensitivity versus 1-specificity for the entire range of thresholds suitable for making the distinction. The y-axis is the sensitivity, or true positive rate, defined as the ratio of the number of true positive test results to the product of the number of true positive test results and the number of false negative test results. This is also called positivity in the presence of a disease or condition. The y-axis is calculated only from the affected subgroup. On the x-axis is the false positive rate, or 1-specificity, which is defined as the ratio of the number of false positive results to the product of the number of true negative and false positive results. The x-axis is an index of specificity, calculated only from the unaffected subgroup. The true positive rate and the false positive rate are calculated completely separately by using the test results from the two different subgroups, so the ROC plot is independent of the prevalence of the event in the cohort. Each point on the ROC plot represents a sensitivity / specificity pair that corresponds to a particular decision threshold. A test with perfect discrimination (no overlap between the two distributions of results) would have an ROC plot that passes through the upper left corner, with a true positive rate of 1.0, or 100% (perfect sensitivity) and a false positive rate of 0 (perfect specificity). The theoretical plot for a test with no discrimination (the distribution of results for the two groups is identical) would be a 45° diagonal line from the lower left corner to the upper right corner. Most plots fall between these two extremes. If the ROC plot falls entirely below the 45° diagonal, this is easily corrected by swapping the criteria for "positive rate" from "higher" to "lower" and vice versa.Qualitatively, the closer the plot is to the upper left corner, the higher the accuracy of the entire test. Depending on the desired confidence interval, a threshold value is derived from the ROC curve to allow diagnosis or prediction of a given event with an appropriate balance of sensitivity and specificity, respectively. Therefore, the criteria used in the aforementioned method of the present invention, i.e., the threshold value that allows distinguishing between subjects at risk and those not at risk, can usually be generated by establishing the ROC of the cohort as described above and deriving the threshold amount therefrom. Depending on the desired sensitivity and specificity of the diagnostic method, the ROC plot allows appropriate threshold values ​​to be derived. It will be understood that optimal sensitivity is desired to exclude subjects at high risk or affected by disease (i.e., exclude), while optimal specificity is assumed to exclude subjects at high risk or affected by disease (i.e., exclude).

[0073] Step c) of the method of the present invention comprises comparing the amount of the biomarkers (i.e., the first biomarker, the second biomarker and optionally the third biomarker) with a standard for said biomarkers and / or calculating a score for assessing the subject suspected of infection based on the amount of the biomarkers.

[0074] Thus, the amounts of the first biomarker, the second biomarker, and optionally the third biomarker can be compared to a standard for the first biomarker, a standard for the second biomarker, and optionally a standard for the third biomarker, respectively.

[0075] Alternatively, a score can be calculated based on the amount of biomarkers, i.e., the amount of the first biomarker, the second biomarker, and optionally the third biomarker. The score allows for the assessment of subjects suspected of infection, such as to predict the risk of developing sepsis. Optionally, the score can be compared to a suitable reference score.

[0076] As used herein, the term "comparing" includes comparing the amount of the determined biomarker with a standard, as referred to herein. It should be understood that comparison as used herein refers to any kind of comparison made between an amount value and a standard. However, it should be understood that preferably, values ​​of the same type are compared with each other, e.g., if absolute amounts are determined and compared in the method of the present invention, the standard is also an absolute amount, if relative amounts are determined and compared in the method of the present invention, the standard is also a relative amount, etc. Alternatively, as used herein, the term "comparing" includes comparing the calculated score with a suitable standard core. The comparison can be performed manually or computer-assisted. The amount value and the standard can, for example, be compared with each other, and the comparison can be performed automatically by a computer program that executes an algorithm for the comparison. The computer program that performs the evaluation provides the desired assessment in a suitable output format.

[0077] As mentioned above, it is also envisaged to calculate a score (particularly a single score), i.e. a single score, based on the amount of the first and second biomarkers, or the first, second or third biomarker, and compare this score to a reference score. Preferably, the score is based on the amount of the first and second biomarkers in a sample from the subject, and if the amount of the third biomarker is determined, it is based on the amount of the first, second and third biomarkers in a sample from the subject.

[0078] The calculated score combines information on the amount of at least two or three biomarkers. Moreover, in the score, the biomarkers are preferably weighted according to their contribution to the establishment of the evaluation. Thus, the values ​​of individual markers are usually weighted, and the weighted values ​​are used to calculate the score. The appropriate coefficients (weights) can be determined by the skilled person without further difficulty. The score can also be calculated from a decision tree or a set (ensemble) of decision trees trained on at least two biomarkers. Based on the combination of biomarkers applied in the method of the present invention, the weights of individual biomarkers as well as the structure of the decision tree can be different.

[0079] The score can be considered as a classification parameter for assessing the subject described herein. In particular, it allows a person to provide an assessment based on a single score. The reference score is preferably a value, in particular a cut-off value that allows an assessment of a subject suspected of infection as described herein. Preferably, the reference is a single value. Thus, a person does not need to interpret the entire information regarding the amount of each biomarker. Using the scoring system described herein, advantageously, values ​​of different dimensions or units of biomarkers can be used, since the values ​​are mathematically converted into scores. Thus, for example, absolute concentration values ​​can be combined with scores with peak area ratios. The applied reference score can be selected based on the desired sensitivity or the desired specificity. How to select an appropriate reference score is well known in the art.

[0080] Advantageously, in the study on which the present invention is based, it was found that the combination of a first biomarker with a second biomarker, preferably a third biomarker, allows for a reliable and early assessment of patients showing signs and symptoms of infection. For example, the assessment of the subject can be performed within 5 hours after the test sample is obtained. In the study, patients presenting in the emergency department with medical (non-surgical) emergencies were investigated. For this purpose, the patients were subdivided into those with a high probability of sepsis and those without sepsis who were suspected of having an infection. The amounts of the various biomarkers were determined, and the biomarkers were analyzed and mathematically combined by logistic regression analysis. The area under the receiver operating characteristic (AUC) was used to evaluate the performance of the biomarkers. The AUC value is the mathematical integer of the function f(x) in the interval [a][b]. The AUC was also investigated for biomarker pairs and triplets. Combinations of biomarkers that show an improved AUC over the AUC of the best single biomarker were identified. The results are described in the attached examples below.

[0081] In particular, when these patients are admitted to, for example, an emergency unit, early assessment of the risk of developing severe complications such as sepsis, SIRS, or a general deterioration in overall health dictates the initiation of therapeutic measures, including drug administration, physical or other therapeutic interventions, and / or hospitalization. These therapeutic measures may include, among others, for example, rapid administration of broad-spectrum antibiotics, fluid resuscitation, vasoactive drug therapy, mechanical ventilation, other organ support (e.g., continuous hemofiltration, extracorporeal membrane oxygenation). Triage to higher levels of care (e.g., intensive care unit, intermediate care unit) is also included as a therapeutic measure. If there is no risk of severe complications, the patient can be discharged home and managed in an outpatient setting or admitted to the hospital with a lower level of care (e.g., general ward). The present invention allows patients to be assessed early by biomarker determination, thus preventing life-threatening events. The biomarker pairs and triplets identified in the studies underlying the present invention are a reliable basis for medical decisions, and the assessment can be performed in a time- and cost-effective manner.

[0082] Thus, the method of the present invention may further comprise recommending or initiating an appropriate therapeutic measure. Typically, the appropriate therapeutic measure is selected from medical guidelines or recommendations for the management of sepsis, such as the International Guidelines for the Management of Sepsis and Septic Shock (Intensive Care Med, 2017). For example, the therapeutic measure may be treatment of sepsis or further diagnostic investigation or other aspects of care required by the medical practitioner.

[0083] In one embodiment, the therapeutic measures recommended or initiated if a patient is assessed as being at risk are selected from the following: Administration of empirical broad-spectrum therapy, typically with at least one broad-spectrum antibiotic, such as a cephalosporin, a beta-lactam / beta-lactamase inhibitor (e.g., piperacillin), or a carbapenem, depending on the organisms considered likely pathogens and their antibiotic susceptibility. Fluid resuscitation administration of one or more vasoconstrictors, such as administration of norepinephrine; and • Administration of one or more corticosteroids, such as administration of hydrocortisone.

[0084] The definitions given herein above apply mutatis mutandis below.

[0085] The present invention also provides a computer-implemented method for assessing a subject suspected of infection, comprising: (a) receiving an amount value of a first biomarker in a sample from a subject, the first biomarker being presepsin; (b) receiving a value of the amount of a second biomarker in the subject's sample, wherein the second biomarker is selected from GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein) (such as NTproBNP or BNP); (c) comparing the value of the amount of the biomarker with a standard of said biomarker and / or calculating a score for assessing the subject suspected of infection based on the amount of the biomarker; and (d) assessing the subject based on the comparisons and / or calculations performed in step (c). The present invention relates to a computer-implemented method,

[0086] As used herein, the term "computer-implemented" means that the method is carried out in an automated manner on a data processing unit, typically included in a computer or similar data processing device. The data processing unit shall receive the amount values ​​of the biomarkers. Such values ​​may be amounts, relative amounts, or any other calculated values ​​reflecting the amounts as detailed elsewhere herein. It should therefore be understood that the above-mentioned methods do not require the determination of the amounts of the biomarkers, but rather use amount values ​​that have already been determined.

[0087] Typically, in step (b) of the process, (i) if a value of the amount of GDF-15 is received as the second biomarker, the method further comprises receiving a value of the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or (ii) if the amount value of cystatin C is received as the second biomarker, then receiving the amount value of aspartate aminotransferase as a third biomarker.

[0088] The present invention also in principle contemplates a computer program, a computer program product or a computer-readable storage medium in which said computer program is operably embedded, the computer program comprising instructions which, when executed on a data processing device or a computer, carry out the method of the present invention as specified above. - a computer or computer network comprising at least one processor, the processor being configured to execute a method according to one of the embodiments described herein. - a computer-loadable data structure configured to perform a method according to one of the embodiments described in this specification when executed on a computer. - a computer script, the computer program being adapted to carry out the method of one of the embodiments described herein while the program is running on a computer, - a computer program comprising program means for carrying out the method according to one of the embodiments described herein when the computer program is run on a computer or on a computer network. A computer program comprising program means according to any of the preceding embodiments stored on a computer readable storage medium. - a storage medium on which a data structure is stored and adapted to perform a method according to one of the embodiments described herein after the data structure has been loaded into a primary and / or working storage device of a computer or a computer network, a computer program product having program code means in which, or capable of being stored on a storage medium, the program code means for performing a method according to one of the embodiments described in this specification when the program code means is executed on a computer or a computer network, - a data stream signal, usually encrypted, containing data of parameters as defined elsewhere in this specification, and - a typically encrypted data stream signal containing the assessment provided by the method of the invention.

[0089] The present invention provides an apparatus for assessing a subject suspected of infection, comprising: (a) a measuring unit for determining the amount of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), in a sample from a subject, the measuring unit comprising a detection system for the first biomarker and the second biomarker; and (b) an evaluation unit operatively linked to the measurement unit, the evaluation unit comprising a database with stored references for the first and second biomarkers, preferably as specified above, and a data processor having instructions for performing a comparison of the amounts of the first and second biomarkers with the references and / or for performing a calculation of a score for assessing a subject suspected of infection based on the amounts of the biomarkers, preferably as specified above, and for assessing said subject based on the comparison, the evaluation unit being capable of automatically receiving the values ​​of the amounts of the biomarkers from the measurement unit; The present invention relates to an apparatus comprising:

[0090] As used herein, the term "apparatus" relates to a system comprising the aforementioned units operatively linked to each other to enable the determination of the amount of biomarkers and their evaluation according to the method of the present invention so as to provide an assessment.

[0091] The analytical unit typically comprises at least one reaction zone having biomarker detection agents for the first and second biomarkers, preferably the third biomarker, in immobilized form on a solid support or carrier that is brought into contact with the sample, and in which it is possible to apply conditions in the reaction zone that allow specific binding of the detection agents to the biomarkers contained in the sample.

[0092] The reaction zone may be connected to a loading zone where the sample is applied, or the sample may be applied directly. In the latter case, the sample may be actively or passively transported to the reaction zone through a connection between the loading zone and the reaction zone. Furthermore, the reaction zone shall also be connected to a detector. The connection shall be such that the detector is able to detect the binding of the biomarkers to their detection agents. The appropriate connection depends on the technique used to measure the presence or amount of the biomarkers. For example, for optical detection, the transmission of light may be required between the detector and the reaction zone, while for electrochemical determination, a fluid connection may be required, for example, between the reaction zone and an electrode.

[0093] The detector must be adapted to detect the determination of the amount of the biomarker. The determined amount can then be transmitted to an evaluation unit, which includes a data processing element such as a computer with an implemented algorithm for determining the amount present in the sample.

[0094] The processing unit referred to in accordance with the method of the present invention typically comprises a central processing unit (CPU) and / or one or more graphic processing units (GPUs) and / or one or more application specific integrated circuits (ASICs) and / or one or more tensor processing units (TPUs) and / or one or more field programmable gate arrays (FPGAs), etc. The data processing element may be, for example, a general-purpose computer or a portable computing device. It should also be understood that multiple computing devices can be used together, such as via a network or other method of transferring data, to perform one or more steps of the method disclosed herein. Exemplary computing devices include desktop computers, laptop computers, personal data assistants ("PDAs"), cellular devices, smart or mobile devices, tablet computers, servers, etc. In general, the data processing element comprises a processor capable of executing multiple instructions (such as a program of software).

[0095] The evaluation unit typically comprises or has access to a memory. The memory is a computer-readable medium and may comprise, for example, a single storage device or multiple storage devices located locally with the computing device or accessible to the computing device over a network. The computer-readable medium may be any available medium that can be accessed by the computing device, including both volatile and non-volatile media. Furthermore, the computer-readable medium may be one or both of removable and non-removable media. By way of example and not limitation, the computer-readable medium may include computer storage media. Exemplary computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or any other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other medium that can be accessed by the computing device and used to store a plurality of instructions that can be executed by the processor of the computing device.

[0096] According to an embodiment of the present disclosure, the software may include instructions that, when executed by a processor of a computing device, may perform one or more steps of the methods disclosed herein. Some of the instructions may be adapted to generate signals that control the operation of other machines, and thus may operate via those control signals to transform materials remote from the computer itself. These descriptions and representations are, for example, the means used by those skilled in the art of data processing to most effectively convey the substance of their work to others skilled in the art.

[0097] Instructions may also include algorithms, which are generally conceived to be a self-consistent sequence of steps leading to a desired result. These steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic pulses or signals that can be stored, transferred, transformed, combined, compared, and otherwise manipulated. It has proven convenient at times, primarily for reasons of common usage, to refer to these signals as values, characters, representations, numbers, or the like, in reference to the physical items or representations that such signals are embodied or represented. It should be noted, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely used as convenient labels applied to these quantities.

[0098] The evaluation unit may also include or have access to an output device. Exemplary output devices include, for example, a fax, a display, a printer, a file, etc. According to some embodiments of the present disclosure, a computing device may perform one or more steps of the methods disclosed herein and then provide output regarding the results, instructions, ratios, or other factors of the methods via the output device.

[0099] Typically, the measurement unit comprises a detection system for a third biomarker, and the database comprises stored references for a third biomarker, the third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) Aspartate aminotransferase when cystatin C is the second biomarker.

[0100] The detection system includes at least one detection agent capable of specifically detecting each of the biomarkers.

[0101] The present invention contemplates a device for assessing a subject suspected of infection, comprising an evaluation unit comprising a database with stored criteria of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), and a data processor comprising instructions for performing a comparison of the amounts of the first and second biomarker with the criteria, preferably as specified above, and for assessing the subject based on the comparison, said evaluation unit being capable of receiving the values ​​of the amounts of the biomarkers determined in a sample from the subject.

[0102] Typically, the database includes stored references for a third biomarker, the third biomarker being (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) Aspartate aminotransferase when cystatin C is the second biomarker.

[0103] The present invention relates in principle to the use of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), or a detection agent that specifically binds to said first biomarker and a detection agent that specifically binds to said second biomarker, for determining a subject suspected of infection.

[0104] As used herein, the term "detection agent" typically refers to any agent that specifically binds to a biomarker, i.e., does not cross-react with other components present in the sample. Typically, detection agents that specifically bind to biomarkers referred to herein may be antibodies, antibody fragments or derivatives, aptamers, ligands of the biomarkers, receptors of the biomarkers, enzymes known to bind and / or convert the biomarkers, or small molecules known to specifically bind to the biomarkers. For example, antibodies referred to herein as detection agents include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments capable of binding to antigens or haptens. The present invention also includes single chain antibodies and humanized hybrid antibodies in which the amino acid sequence of a non-human donor antibody exhibiting the desired antigen specificity is combined with the sequence of a human acceptor antibody. The donor sequence typically includes at least the antigen-binding amino acid residues of the donor, but may include other structurally and / or functionally related amino acid residues of the donor antibody. Such hybrids can be prepared by several methods well known in the art. Aptamer detection agents may be, for example, nucleic acid or peptide aptamers. Methods for preparing such aptamers are well known in the art. For example, random mutations can be introduced into the nucleic acid or peptide that is the basis of the aptamer. These derivatives can then be tested for binding according to screening procedures known in the art, such as phage display. Specific binding of a detection agent means that it does not substantially bind, i.e. does not cross-react, with another peptide, polypeptide or substance present in the sample being analyzed. Preferably, a specifically bound biomarker should bind with an affinity that is at least 3 times higher than any other component of the sample, more preferably at least 10 times higher, and even more preferably at least 50 times higher. Non-specific binding can be tolerated if it can still be clearly distinguished and measured, for example according to its size on Western blot or by its relatively high abundance in the sample.

[0105] The detection agent can be permanently or reversibly fused or linked to the detectable label. Suitable labels are well known to those skilled in the art. Suitable detectable labels are any labels that can be detected by suitable detection methods. Typical labels include gold particles, latex beads, acridan esters, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels (including "e.g. magnetic beads", paramagnetic and superparamagnetic labels) and fluorescent labels. Enzymatically active labels include, for example, horseradish peroxidase, alkaline phosphatase, beta-galactosidase, luciferase, and their derivatives. Suitable substrates for detection include di-amino-benzidine (DAB), 3,3'-5,5'-tetramethylbenzidine, NBT-BCIP (4-nitro blue tetrazolium chloride and 5-bromo-4-chloro-3-indolyl phosphate available as ready-made stock solutions from Roche Diagnostics), CDP-Star™ (Amersham Biosciences), ECF™ (Amersham Biosciences). Suitable enzyme-substrate combinations may result in colored reaction products, fluorescence or chemiluminescence, which can be measured according to methods known in the art (e.g., using light-sensitive film or a suitable camera system). For the measurement of enzyme reactions, the above criteria apply as well. Typical fluorescent labels include fluorescent proteins (e.g., GFP and its derivatives), Cy3, Cy5, Texas Red, fluorescein, and Alexa dyes (e.g., Alexa568). Further fluorescent labels are available, for example, from Molecular Probes (Oregon). The use of quantum dots as fluorescent labels is also contemplated. Exemplary radioactive labels include 35S, 125I, 32P, 33P, etc. Radioactive labels can be detected by any method known and appropriate, such as a light-sensitive film or a phosphor imager.Suitable labels may also be or include tags such as biotin, digoxigenin, His-Tag, glutathione-S-transferase, FLAG, GFP, myc-tag, influenza A virus hemagglutinin (HA), maltose binding protein, etc.

[0106] Detecting agents for biomarkers such as AST, ALT, bilirubin and creatinine are described in the Examples (see Example 1). When the biomarker is an enzyme such as AST or ALT, the detecting agent may be a substrate for the enzyme.

[0107] The determination of the biomarkers described herein may include mass spectrometry (MS) performed after a separation step (e.g. by LC or HPLC). Mass spectrometry as used herein encompasses all techniques that allow the determination of the molecular weight (i.e. mass) or mass variable corresponding to the compound, i.e. biomarker, determined according to the present invention. Preferably, mass spectrometry as used herein relates to GC-MS, LC-MS, direct infusion mass spectrometry, FT-ICR-MS, CE-MS, HPLC-MS, quadrupole mass spectrometry, any sequentially coupled mass spectrometry such as MS-MS or MS-MS, ICP-MS, Py-MS, TOF, or any combination approach using the aforementioned techniques. How to apply these techniques is well known to the skilled person. Moreover, suitable equipment is commercially available. More preferably, mass spectrometry as used herein relates to LC-MS and / or HPLC-MS, i.e. mass spectrometry operatively linked to a prior liquid chromatographic separation step. Preferably, the mass spectrometry is tandem mass spectrometry (also known as MS / MS). Tandem mass spectrometry, also known as MS / MS, comprises two or more mass spectrometry steps during which fragmentation occurs. In tandem mass spectrometry, there are two mass spectrometers in series connected by a collision cell. The mass spectrometer is coupled to a chromatography device. The chromatographically separated sample is fractionated and weighed in the first mass spectrometer, then fragmented with an inert gas in the collision cell, fractionated and weighed in the second mass spectrometer. The fragments are selected and weighed in the second mass spectrometer. Identification by MS / MS is more accurate.

[0108] In one embodiment, mass analysis as used herein encompasses quadrupole MS. Most preferably, said quadrupole MS is carried out as follows: a) selection of the mass / charge quotient (m / z) of ions generated by ionization in a first analytical quadrupole of a mass spectrometer, b) fragmentation of the ions selected in step a) by applying an accelerating voltage in an additional subsequent quadrupole filled with collision gas and acting as a collision chamber, c) selection of the mass / charge quotient of ions generated by the fragmentation process of step b) in the additional subsequent quadrupole. Steps a) to c) of the method are thereby carried out at least once and an analysis of the mass / charge quotient of all ions present in the mixture of substances as a result of the ionization process is carried out, whereby the quadrupole is filled with collision gas but no accelerating voltage is applied during the analysis. Details regarding said most preferred mass analysis used according to the present invention can be found in WO 2003 / 073464.

[0109] More preferably, the mass spectrometry is liquid chromatography (LC) MS, such as high performance liquid chromatography (HPLC) MS, in particular HPLC-MS / MS. As used herein, liquid chromatography refers to all techniques that allow the separation of compounds (i.e. metabolites) in a liquid or supercritical phase.

[0110] For mass spectrometry, the analytes in the sample are ionized to generate charged molecules or molecular fragments. The mass-charge of the ionized analytes, particularly the ionized biomarkers or fragments thereof, is then measured. Prior to ionization, the sample may be cleaved with a protease, such as trypsin. The protease cleaves the protein biomarkers into smaller fragments.

[0111] Thus, the mass analysis step preferably includes an ionization step in which the biomarkers to be determined are ionized. Naturally, other compounds present in the sample / eluent are also ionized. The ionization of the biomarkers can be carried out by any method considered appropriate, in particular by electron impact ionization, fast atom bombardment, electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), matrix-assisted laser desorption ionization (MALDI).

[0112] In a preferred embodiment, the ionization step (for mass spectrometry) is performed by electrospray ionization (ESI). Mass spectrometry is therefore preferably ESI-MS (or ESI-MS / MS, when performing tandem MS). Electrospray is a soft ionization method that forms ions without breaking chemical bonds.

[0113] More typically, a third biomarker or a detection agent that specifically binds to said third biomarker is further used, said third biomarker being (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) Aspartate aminotransferase when cystatin C is the second biomarker.

[0114] The present invention also relates to a kit for assessing a subject suspected of having an infection comprising a detection agent that specifically binds to a first biomarker, which is presepsin, and a detection agent that specifically binds to a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein).

[0115] As used herein, the term "kit" refers to a collection of the above-mentioned components, typically provided in separate or single containers. The container also typically contains instructions for carrying out the method of the invention. These instructions may be in the form of a manual or may be provided by a computer program code capable of carrying out or supporting the determination of the biomarkers referred to in the method of the invention when implemented in a computer or data processing device. The computer program code may be provided on a data storage medium or device, such as an optical storage medium (e.g., compact disc), or directly on the computer or data processing device, or in a downloadable form, such as a link to an accessible server or cloud. In addition, the kit may typically include standards of reference amounts of the biomarkers for calibration purposes, as described in detail elsewhere herein. The kit according to the invention may also include further components necessary for carrying out the method of the invention, such as solvents, buffers, washing solutions and / or reagents necessary for the detection of the released second molecule. Furthermore, the kit may partially or entirely include the device of the invention.

[0116] More typically, the kit further comprises a detection agent that specifically binds to a third biomarker, the third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) Aspartate aminotransferase when cystatin C is the second biomarker.

[0117] Therefore, it is to be understood that the above definitions and explanations of terms apply to all embodiments described in this specification and the appended claims. The following embodiments are specific embodiments contemplated in accordance with the present invention.

[0118] 1. A method for assessing a subject suspected of infection, comprising: (a) determining the amount of a first biomarker in a sample from a subject, wherein the first biomarker is presepsin; (b) determining the amount of a second biomarker in the subject's sample, wherein the second biomarker is selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein); (c) comparing the amount of the biomarker with a standard of said biomarker and / or calculating a score for assessing the subject as suspected of being infected based on the amount of the biomarker; and (d) assessing the subject based on the comparisons and / or calculations performed in step (c). A method comprising:

[0119] 2. In step (b), (i) if the amount of GDF-15 is determined as the second biomarker, the method further comprises determining the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or (ii) If the amount of cystatin C is determined as the second biomarker, the method of embodiment 1 further comprises determining the amount of aspartate aminotransferase as a third biomarker.

[0120] 3. The method of embodiment 1 or 2, wherein the subject is a subject presenting to an emergency department.

[0121] 4. The method according to any one of embodiments 1 to 3, wherein the assessment is an assessment of the risk of developing sepsis and / or an assessment of the risk of the subject's condition worsening.

[0122] 5. The method of any one of embodiments 1-4, wherein said references are references for each biomarker from at least one subject known to be at risk for developing sepsis, and preferably, an amount for each of the biomarkers that is essentially the same as or similar to the corresponding reference indicates a subject at risk for developing sepsis, and an amount for each of the biomarkers that is different from the corresponding reference indicates a subject not at risk for developing sepsis.

[0123] 6. The method of any one of embodiments 1-4, wherein said references are references for each biomarker from at least one subject known to be not at risk of developing sepsis, and preferably, an amount for each of the biomarkers that is essentially the same as or similar to the corresponding reference indicates a subject that is not at risk of developing sepsis, and an amount for each of the biomarkers that is different from the corresponding reference indicates a subject that is at risk of developing sepsis.

[0124] 7. The method of any one of embodiments 1-6, wherein the subject has or is suspected of having an infectious disease.

[0125] 8. The method of any one of embodiments 1 to 7, wherein the sample is a blood sample or a sample derived therefrom.

[0126] 9. The method of any one of embodiments 1 to 8, wherein the subject is a human.

[0127] 10. A computer-implemented method for assessing a subject suspected of infection, comprising: (a) receiving an amount value of a first biomarker in a sample from a subject, the first biomarker being presepsin; (b) receiving a value of the amount of a second biomarker in the subject's sample, wherein the second biomarker is selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein); (c) comparing the value of the amount of the biomarker with a standard of said biomarker and / or calculating a score for assessing the subject suspected of infection based on the amount of the biomarker; and (d) assessing the subject based on the comparisons and / or calculations performed in step (c). 4. A computer-implemented method comprising:

[0128] 11. In step (b), (i) if a value of the amount of GDF-15 is received as the second biomarker, the method further comprises receiving a value of the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or 11. The method of embodiment 10, wherein (ii) if the amount value of cystatin C is received as the second biomarker, the method further comprises receiving the amount value of aspartate aminotransferase as a third biomarker.

[0129] 12. A device for assessing a subject suspected of infection, comprising: (a) a measuring unit for determining the amount of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein) in a sample from a subject, the measuring unit comprising a detection system for the first biomarker and the second biomarker; and (b) an evaluation unit operatively coupled to the measurement unit, the evaluation unit comprising: a database with stored references for the first and second biomarkers, preferably as described in any one of embodiments 1 to 9; and a data processor having instructions for performing a comparison of the amounts of the first and second biomarkers with the references and / or for performing a calculation of a score for assessing a subject suspected of infection based on the amounts of the biomarkers, preferably as described in any one of embodiments 1 to 9, and for assessing said subject based on the comparison, the evaluation unit being capable of automatically receiving the values ​​of the amounts of the biomarkers from the measurement unit. An apparatus comprising:

[0130] 13. The measurement unit determines a third biomarker and is equipped with a detection system for the third biomarker, the database has stored references for the third biomarker, and the third biomarker is: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) When cystatin C is the second biomarker, the second biomarker is aspartate aminotransferase.

[0131] 14. The device of embodiment 12 or 13, wherein the detection system comprises at least one detection agent capable of specifically detecting each of the biomarkers.

[0132] 15. A device for assessing a subject suspected of infection, comprising an evaluation unit comprising a database with stored references of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), and a data processor, preferably as described in any one of embodiments 1 to 11, comprising instructions for performing a comparison of the amount of the first and second biomarker with the reference and for assessing the subject based on the comparison, wherein the evaluation unit is capable of receiving the value of the amount of the biomarker determined in a sample of the subject.

[0133] 16. The database comprises a stored reference of a third biomarker, the third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) When cystatin C is the second biomarker, it is aspartate aminotransferase.

[0134] 17. Use of a first biomarker that is presepsin and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), or a detection agent that specifically binds to said first biomarker and a detection agent that specifically binds to said second biomarker, to assess a subject suspected of infection.

[0135] 18. A third biomarker or a detection agent that specifically binds to the third biomarker is additionally used, and the third biomarker is (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) The use of embodiment 17, wherein when cystatin C is the second biomarker, it is aspartate aminotransferase.

[0136] 19. A kit for assessing a subject suspected of having an infection comprising a detection agent that specifically binds to a first biomarker, which is presepsin, and a detection agent that specifically binds to a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein).

[0137] 20. The method further comprises the step of detecting a detection agent that specifically binds to a third biomarker, the third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) when cystatin C is the second biomarker, it is aspartate aminotransferase.

[0138] All references cited throughout this specification are hereby incorporated by reference in their entirety and for the disclosure content specifically mentioned above. EXAMPLES

[0139] Example 1: Biomarker Determination The Elecsys® Electro-ChemiLuminescence (ECL) technology and assay method for the determination of GDF-15 are briefly described below. The concentration of GDF-15 was determined by a cobas e801 analyzer. The detection of GDF-15 by the Cobas e801 analyzer is based on the Elecsys® Electro-ChemiLuminescence (ECL) technology. Briefly, biotin-labeled and ruthenium-labeled antibodies are combined with the respective amounts of undiluted sample and incubated on the analyzer. Streptavidin-coated magnetic microparticles are then added and incubated on the device to promote the binding of the biotin-labeled immune complexes. After this incubation step, the reaction mixture is transferred to the measurement cell, where the beads are magnetically captured on the surface of the electrode. ProCell M buffer containing tripropylamine (TPA) is introduced into the measurement cell for subsequent ECL to separate the bound immunoassay complexes from the free remaining particles. The induction of a voltage between the working and counter electrodes then initiates a reaction that results in the emission of photons by the ruthenium complex and TPA. The electrochemiluminescence signal obtained by the photomultiplier tube is recorded and converted to a numerical value that indicates the concentration level of the respective analyte.

[0140] Presepsin (sCD14-ST) was measured with a commercially available chemiluminescence (CLIA) assay for presepsin (sCD14-ST), a sandwich immunoassay developed for the Pathfast CLIA Amagtration platform (LSIMedience, Japan). The assay contains magnetic beads coated with an antibody that specifically binds to presepsin (sCD14-ST) and an alkaline phosphatase (ALP)-conjugated antibody that specifically binds to presepsin (sCD14-ST). 100 μL was used from each plasma sample and measured with a Pathfast™ analyzer (Mitsubishi Chemical Europe, Germany / LSIM). Briefly, the PATHFAST Presepsin test principle is based on a non-competitive CLEIA in combination with *MAGTRATIONR® technology. During incubation of the sample with alkaline phosphatase-labeled anti-presepsin polyclonal antibody and anti-presepsin monoclonal antibody-coated magnetic particles, the presepsin in the sample binds to the anti-presepsin antibody and forms an immune complex with the enzyme-labeled antibody and antibody-coated magnetic particles. *After removing unbound material by MAGTRATIONR® technology, a chemiluminescent substrate is added. After a short incubation, the luminescence intensity generated by the enzyme reaction is measured. The luminescence intensity is related to the presepsin concentration of the sample and calculated by a standard curve. *MAGTRATION® is a B / F separation technology that washes magnetic particles in a pipette tip and is a registered trademark of Precision System Science.

[0141] SFLT-1 or sFLT-1 (soluble fms-like tyrosine kinase-1) was measured with the commercially available ECLIA assay for sFLT-1, a sandwich immunoassay developed for the cobas Elecsys® ECLIA platform (ECLIA assay from Roche Diagnostics, Germany). The assay contains a biotinylated monoclonal antibody and a rutheniumylated monoclonal antibody that specifically binds to sFLT-1. 12 μL was used from each serum sample and measured undiluted on a cobas e801 analyzer (Roche Diagnostics, Germany).

[0142] GDF15 (growth differentiation factor 15) was measured with the commercially available ECLIA assay for GDF-15, a sandwich immunoassay developed for the cobas Elecsys® ECLIA platform (ECLIA assay from Roche Diagnostics, Germany). The assay contains a biotinylated monoclonal antibody and a rutheniumylated monoclonal antibody that specifically binds to GDF-15. 21 μL was used from each serum sample, undiluted, and measured on a cobas e801 analyzer (Roche Diagnostics, Germany).

[0143] CysC2 (cystatin C) was measured with a commercially available PETIA (Particle Enhanced Immunoturbidimetric Assay) for CysC developed for the cobas® clinical chemistry analyzer platform (Roche Diagnostics, Germany). The assay contains latex particles coated with an antibody that specifically binds to CysC. When the antibody reagent and sample are mixed and incubated, the latex enhances the particles coated with anti-cystatin C antibodies in the reagent and agglutinates with human cystatin C in the sample. The degree of turbidity caused by the aggregates can be determined turbidimetrically at 546 nm, which is proportional to the amount of cystatin C in the sample. 2 μL from each serum sample was used and measured on a cobas c501 analyzer (Roche Diagnostics, Germany).

[0144] FERR (ferritin) was measured with the commercial ECLIA assay for ferritin, a sandwich immunoassay developed for the cobas Elecsys® ECLIA platform (ECLIA assay from Roche Diagnostics, Germany). The assay contains a biotinylated monoclonal antibody and a rutheniumylated monoclonal antibody that specifically bind to ferritin. 10 μL was used from each serum sample, undiluted, and measured on a cobas e801 analyzer (Roche Diagnostics, Germany).

[0145] IGFBP7 (insulin-like growth factor binding protein 7) was measured with a robust prototype ECLIA assay for IGFBP-7, a sandwich immunoassay developed in-house for the cobas Elecsys® ECLIA platform (ECLIA assay from Roche Diagnostics, Germany). The assay contains a biotinylated monoclonal antibody and a rutheniumylated monoclonal antibody that specifically binds to IGFBP-7. 10 μL was used from each serum sample, undiluted, and measured on a cobas e601 analyzer (Roche Diagnostics, Germany).

[0146] STREM1 or sTREM-1 (soluble triggering receptor 1 expressed on myeloid cells) was measured with the robust prototype ECLIA assay for sTREM-1, a sandwich immunoassay developed in-house for the cobas Elecsys® ECLIA platform (ECLIA assays from Roche Diagnostics, Germany). The assay contains biotinylated and rutheniumylated monoclonal antibodies that specifically bind to sTREM-1. 50 μL was used from each serum sample, undiluted, and measured on a cobas e601 analyzer (Roche Diagnostics, Germany).

[0147] PSP (pancreatic stone protein) was measured with the commercially available Abionic Platform (Abionic, Switzerland). A nanofluidic PSP (pancreatic stone protein) immunoassay that quantifies PSP from 30 μL EDTA plasma samples. The test principle relies on the passage of the specimen, premixed for a few seconds with a solution containing fluorescently labeled detection antibodies, through a nanometer-sized channel where anti-PSP antibodies are immobilized. These antibodies capture the PSP bound to the fluorescent detection anti-PSP antibodies. The abioSCOPE reads the fluorescence emission from the PSP sensor and uses advanced signal processing to convert the signal into a concentration, with an embedded lot-specific calibration of the assay.

[0148] KL6 (sialylated carbohydrate antigen KL-6): Sialylated carbohydrate antigen KL-6 (KL-6) in the sample agglutinates with mouse KL-6 monoclonal antibody-coated latex via an antigen-antibody reaction. The absorbance change due to this agglutination is measured to determine the level of KL-6. The reagents were from Sekisui Medical Co., Ltd. (Japan). 2.5 μL of plasma was analyzed. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0149] BILI (Bilirubin): Diazotized sulfanilic acid is formed by combining sodium nitrite and sulfanilic acid at low pH. Bilirubin (unconjugated) in the sample is solubilized by dilution in a mixture of caffeine / benzoate / acetate / EDTA. Upon addition of diazotized sulfanilic acid, solubilized bilirubin, including conjugated bilirubin (monogluconides and digluconides) and delta form 2 (biliprotein-bilirubin covalently bound to albumin), is converted to diazobilirubin, a red chromophore that absorbs at 540 nm and represents total bilirubin, which is measured using a dichroic (540, 700 nm) end point method. Sample blank correction is used.

[0150] CREJ2 (creatinine): This kinetic colorimetric assay is based on the Jaffe method. In alkaline solution, creatinine forms a picrate and a yellow-orange complex. The rate of pigment formation is proportional to the creatinine concentration in the sample. The assay uses "rate blanking" to minimize interference by bilirubin. Assay from Roche Diagnostics (Germany) 7.5 μL of plasma were used for the determination. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0151] ALAT (Alanine Aminotransferase): Alanine aminotransferase catalyzes the transamination of L-alanine to α-ketoglutarate (α-KG) to form L-glutamate and pyruvate. The pyruvate formed is reduced to lactate by lactate dehydrogenase (LDH) with the concomitant oxidation of reduced nicotinamide adenine dinucleotide (NADH). The change in absorbance is directly proportional to alanine aminotransferase activity and is measured using a dichroic (340, 700 nm) kinetic method.

[0152] ASAT (Aspartate Aminotransferase): Aspartate aminotransferase (AST) catalyzes the transamination of L-aspartate to α-ketoglutarate to form L-glutamate and oxaloacetate. The oxaloacetate formed is reduced to malate by malate dehydrogenase (MDH) with the concomitant oxidation of reduced nicotinamide adenine dinucleotide (NADH). The change in absorbance over time due to the conversion of NADH to NAD is directly proportional to AST activity and is measured using a dichroic (340, 700 nm) kinetic method.

[0153] Example 2: Analysis of patients from the triage study Triage trial, Emergency Department, Aarau Hospital, Switzerland. (Schuetz 2013, BMC Emergency Medicine, 13(1), 12).

[0154] All continuations seeking emergency department (ED) care for a medical emergency were included at ED admission.From a total of 4000 patients, a subset of patients with suspected infection at admission was selected and classified as probable sepsis cases or infection controls according to the following: ● Cases (N=64): Likely cases of sepsis that worsened / more severe within 48 hours of ED presentation and were admitted to the ICU or met the criteria from Rhee 2017, “Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014.” JAMA 318(13):1241-1249. ● Controls (N=207): Patients with suspected infection but not sepsis within 48 hours of ED presentation.

[0155] Markers were mathematically combined by logistic regression and the "area under the receiver operating characteristic" (AUC) was used as a general measure of marker performance.

[0156] Combinations of marker pairs (bivariate marker combinations) that improved AUC by at least 1 percentage point over single markers are shown in Table 1 . [Table 1]

[0157] Marker triplets (trivariate marker combinations) that showed improved AUC over bivariate marker pairs, as well as combinations of all three single markers that showed an improvement of at least one percentage point, are shown in Table 2. [Table 2]

[0158] Examples of bivariate combinations of markers that are not an improvement over a single marker are shown in Table 3. [Table 3]

Claims

1. 1. A method for assessing a subject suspected of infection, comprising: (a) determining the amount of a first biomarker in a sample from the subject, wherein the first biomarker is presepsin; (b) determining the amount of a second biomarker in the subject's sample, wherein the second biomarker is selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein); (c) comparing the amount of said biomarkers to a standard for said biomarkers and / or calculating a score for assessing said subject as suspected of infection based on the amount of said biomarkers; and (d) assessing the subject based on the comparison and / or the calculation performed in step (c). A method comprising:

2. In step (b), (i) if the amount of GDF-15 is determined as the second biomarker, the method further comprises determining the amount of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or 2. The method of claim 1, wherein (ii) if the amount of cystatin C is determined as the second biomarker, the method further comprises determining the amount of aspartate aminotransferase as a third biomarker.

3. The method of claim 1 , wherein the subject is a subject presenting to an emergency department.

4. The method of claim 1 , wherein the assessment is an assessment of the risk of developing sepsis and / or an assessment of the risk of the subject's condition worsening.

5. 2. The method of claim 1, wherein the reference is a reference for each biomarker from at least one subject known to be at risk of developing sepsis, preferably wherein an amount for each of the biomarkers that is essentially the same as or similar to the corresponding reference indicates a subject at risk of developing sepsis, and an amount for each of the biomarkers that is different from the corresponding reference indicates a subject not at risk of developing sepsis.

6. 2. The method of claim 1, wherein the reference is a reference for each biomarker from at least one subject known to be not at risk of developing sepsis, preferably wherein an amount for each of the biomarkers that is essentially the same as or similar to the corresponding reference indicates a subject that is not at risk of developing sepsis, and an amount for each of the biomarkers that is different from the corresponding reference indicates a subject that is at risk of developing sepsis.

7. 10. The method of claim 1, wherein the subject has or is suspected of having an infectious disease.

8. The method of claim 1 , wherein the sample is a blood, serum or plasma sample.

9. The method of claim 1 , wherein the subject is a human.

10. 1. A computer-implemented method for assessing a subject suspected of infection, comprising: (a) receiving an amount value of a first biomarker in a sample of the subject, wherein the first biomarker is presepsin; (b) receiving a quantity value of a second biomarker in the subject's sample, wherein the second biomarker is selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein); (c) comparing the value of the amount of the biomarker with a standard for the biomarker and / or calculating a score for assessing the subject as suspected of infection based on the amount of the biomarker; and (d) assessing the subject based on the comparison and / or the calculation performed in step (c).

4. A computer-implemented method comprising:

11. In step (b), (i) if a quantity value of GDF-15 is received as the second biomarker, the method further comprises receiving a quantity value of sFlt1, IGFBP7 or sTREM1 as a third biomarker; or 11. The method of claim 10, wherein (ii) if a value of the amount of cystatin C is received as the second biomarker, the method further comprises receiving a value of the amount of aspartate aminotransferase as a third biomarker.

12. 1. An apparatus for assessing a subject suspected of infection, comprising: (a) a measuring unit for determining the amount of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein) in a sample from said subject, said measuring unit comprising a detection system for said first biomarker and said second biomarker; and (b) an evaluation unit operatively coupled to said measurement unit, said evaluation unit comprising a database with stored references for said first and second biomarkers, preferably as claimed in any one of claims 1 to 9, and a data processor having instructions for performing a comparison of the amounts of said first and second biomarkers with references and / or for performing a calculation of a score for assessing said subject suspected of infection based on the amounts of said biomarkers, preferably as claimed in any one of claims 1 to 9, and for assessing said subject based on said comparison, said evaluation unit being capable of automatically receiving the values ​​of the amounts of said biomarkers from said measurement unit. An apparatus comprising:

13. The measurement unit determines a third biomarker and comprises a detection system for the third biomarker, the database has stored references for the third biomarker, and the third biomarker is (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or 13. The device of claim 12, wherein (ii) when cystatin C is the second biomarker, it is aspartate aminotransferase.

14. The device of claim 12 , wherein the detection system comprises at least one detection agent capable of specifically detecting each of the biomarkers.

15. 12. A device for assessing a subject suspected of infection, comprising an evaluation unit comprising a database with stored references of a first biomarker, which is presepsin, and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, Cystatin C and PSP (pancreatic stone protein), and a data processor comprising instructions for performing a comparison of the amounts of said first and second biomarker with a reference and for assessing said subject based on said comparison, preferably as claimed in any one of claims 1 to 11, wherein said evaluation unit is capable of receiving the values ​​of the amounts of said biomarkers determined in a sample of said subject.

16. The database includes a stored reference for a third biomarker, the third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or 16. The device of claim 15, wherein (ii) when cystatin C is the second biomarker, it is aspartate aminotransferase.

17. The use of i) a first biomarker which is presepsin and a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C and PSP (pancreatic stone protein), or ii) a detection agent which specifically binds to said first biomarker and a detection agent which specifically binds to said second biomarker, to assess a subject suspected of being infected.

18. A third biomarker or a detection agent that specifically binds to said third biomarker may additionally be used, said third biomarker being: (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or (ii) when cystatin C is the second biomarker, it is aspartate aminotransferase.

19. A kit for assessing a subject suspected of having an infection comprising a detection agent that specifically binds to a first biomarker, which is presepsin, and a detection agent that specifically binds to a second biomarker selected from the group consisting of GDF-15, creatinine, sFlt1, IGFBP7, sTREM1, cystatin C, and PSP (pancreatic stone protein).

20. The method further comprises the step of: detecting a detection agent that specifically binds to a third biomarker, the third biomarker being (i) if GDF-15 is the second biomarker, sFlt1, IGFBP7 or sTREM1; or 20. The kit of claim 19, wherein (ii) when cystatin C is the second biomarker, it is aspartate aminotransferase.

21. The method, device, use or kit according to any one of claims 1 to 20, wherein said assessment is an assessment of the risk of developing sepsis.

22. 22. The method, device, use or kit of claim 21, wherein the risk of developing sepsis within 48 hours is predicted.