DLL1 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 evaluating a subject suspected of having an infectious disease, comprising the steps of determining the amount of a first biomarker in a sample of the subject, the first biomarker being DLL1, determining the amount of a second biomarker in a sample of the subject, the second biomarker being GDF15, comparing the amount of the biomarker with a standard for the biomarker and / or calculating a score for evaluating the subject suspected of having an infectious disease based on the amount of the biomarker, and evaluating the subject based on the comparison and / or calculation.The present invention also relates to the use of a first biomarker being DLL1 and a second biomarker being GDF15, or a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, for evaluating a subject suspected of having an infectious disease.In addition, the present invention further relates to a computer-implemented method for evaluating a subject suspected of having an infectious disease, and a device and a kit for evaluating a subject suspected of having an infectious disease.

Description

[Technical field]

[0001] The present invention relates to the field of diagnosis.Specifically, the present invention relates to a method for evaluating a subject suspected of having an infectious disease, comprising the steps of determining the amount of a first biomarker in a sample of the subject, the first biomarker being DLL1, determining the amount of a second biomarker in a sample of the subject, the second biomarker being GDF15, comparing the amount of the biomarker with a standard for the biomarker and / or calculating a score for evaluating the subject suspected of having an infectious disease based on the amount of the biomarker, and evaluating the subject based on the comparison and / or calculation.The present invention also relates to the use of a first biomarker being DLL1 and a second biomarker being GDF15, or a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, for evaluating a subject suspected of having an infectious disease.Furthermore, the present invention further relates to a computer-implemented method for evaluating a subject suspected of having an infectious disease, and a device and a kit for evaluating a subject suspected of having an infectious disease. [Background technology]

[0002] Infections, particularly those occurring in patients with more severe signs and symptoms, such as those presenting to emergency centers, 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 a life-threatening organ dysfunction caused by a dysregulated host response to infection. Due to its rapid onset, early recognition is crucial in the management of septic patients, and initiation of correct therapeutic measures, including appropriate antibiotic therapy, and resuscitation with intravenous fluids and vasoactive drugs within 1 hour of admission is important (Surviving Sepsis Campaign Guidelines 2016). Every hour of delay is associated with a stepwise increase in morbidity and mortality.

[0004] The diagnosis of sepsis is based on clinical signs and symptoms that are non-specific and can easily be overlooked. Therefore, patients are frequently misdiagnosed and the disease severity is often underestimated. So far, there is no gold standard for diagnosing sepsis in general medicine and especially in the emergency department. In high-income countries, C-reactive protein (CRP), procalcitonin (PCT) and white blood cell (WBC) count are often used in emergency centers for the detection of patients with bloodstream infections at risk for the development of sepsis, together with lactate 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 (except for blood components of clinical chemistry, BGE and SOFA scores) besides lactate. 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, PlGF5, 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 inflammatory markers such as PCT, presepsin, GDF-15, sFLT, CRP or interleukins, among others, or markers specific for organ failure (see, e.g., Spanuth, 2014, Comparison of sCD14-ST(рresepsin) with еight biomarkers for mortality prediction in patients admitted 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 describes biomarkers for early determination of critical or life-threatening response to disease and / or treatment response.

[0009] Delta-like protein 1 (DLL1, Uniprot accession number O00548) is a 723 amino acid transmembrane cell surface protein. DLL1 is one of the four canonical ligands of the Notch receptor and binds to the extracellular domain of the Notch receptor. The Notch signaling pathway controls many aspects of embryonic development, as well as differentiation processes and tissues in multiple adult organ systems, including the hematopoietic and immune systems. Interaction between Notch receptors and DLL1 results in the cleavage of both the receptor and its ligand from the surface, generating soluble DLL1 (sDLL1).

[0010] DLL1 expression is increased in human monocytes and mouse models upon lipopolysaccharide (LPS) stimulation or bacterial infection. Induction of DLL1 expression is mediated by Toll-like receptors (TLRs), which signal indirectly through STAT3 activation triggered by cytokine receptors. (Hildebrand et al., Front. Cell. Infect. Microbiol. 8:241. doi:10.3389 / fcimb.2018.00241(2018)).

[0011] Two cohorts of patients with sepsis or septic shock were reported to have elevated plasma concentrations of DLL1 when compared with healthy controls or control patients undergoing cisceral surgery (Hildebrand et al., Front. Cell. Infect. Microbiol. 9:267. (2019); doi:10.3389 / fcimb.2019.00267).

[0012] Decker et al. reported that DLL1 levels were higher in patients with bacterial infections after liver transplantation than in those without. They analyzed 93 patients (Decker et al., Diagnostics (Basel). 2020 Oct 31; 10(11): 894. doi: 10.3390 / diagnostics10110894. PMID: 33142943; PMCID: PMC7693674).

[0013] Norum et al. reported that DLL1 plasma levels are elevated in heart transplant recipients (Norum et al., Am J Transplant. 2019 Apr;19(4):1050-1060. doi:10.1111 / ajt.15141. Epub 2018 Nov 5. PMID:30312541.

[0014] EP 3701268 discloses the use of delta-like ligand 1 protein or a nucleotide sequence encoding the delta-like ligand 1 protein as a biomarker for the in vitro diagnosis of serious infections.

[0015] However, there remains a need for biomarkers that allow reliable and early assessment of patients who present with signs and symptoms of infection. Therefore, the present invention provides means and methods that meet these needs. Summary of the Invention

[0016] The present invention provides a method for evaluating a subject suspected of having an infectious disease, comprising: (a) determining the amount of a first biomarker in a sample from a subject, the first biomarker being DLL1 (Delta-like protein 1); (b) determining the amount of a second biomarker in the subject's sample, the second biomarker being GDF15 (growth-differentiation factor-15); (c) comparing the amount of the biomarker to a standard for the biomarker and / or calculating a score for assessing the subject for suspected infection based on the amount of the biomarker; (d) evaluating the subject based on the comparison and / or calculation performed in step (c).

[0017] It should be understood that as used in this specification and claims, "a" or "an" can mean one or more, depending on the context in which it is used. Thus, for example, a reference to "an" item can mean that at least one of the item is available.

[0018] When used below, the terms "have", "comprise" or "include" or any grammatical variants thereof are used in a non-exclusive manner. Thus, these terms can refer both to the situation where no further features are present in the entity described in this context, in addition to the features introduced by these terms, and to the situation where one or more further features are present. As an example, the expressions "A has B", "A includes B" and "A contains B" can refer both to the situation where no other elements are present in A besides B (i.e., the situation where A consists only of B), and to the situation where one or more further elements are present in entity A besides B, such as elements C, elements C and D or further elements. The term "comprising" has a restrictive meaning in the sense of "consisting of", which also encompasses embodiments where only the mentioned items are present.

[0019] Furthermore, when used below, the terms "particularly", "more particularly", "typically" and "more typically" or similar terms are used with additional / alternative features without limiting the possibilities 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 using alternative features, as the skilled artisan will recognize. Similarly, features introduced by "in one embodiment of the invention" or similar expressions are intended to be additional / alternative features without limitations on alternative embodiments of the invention, without limitations on the scope of the invention, and without limitations on the possibilities of combining the features so introduced with other additional / alternative or non-additional / alternative features of the invention.

[0020] Furthermore, as used herein, the term "at least one" is understood to mean that one or more of the items mentioned following this term can be used according to the present invention. For example, when this term indicates that at least one sampling unit is used, this can 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 this term refers, a person skilled in the art can understand what upper limit, if any, the term can refer to.

[0021] As used herein, the term "about" means that for any number listed after the term, there exists an interval of precision within which the technical effect can be achieved. Thus, about as referred to herein preferably refers to the exact numerical value or a range around the exact numerical value ±20%, preferably ±15%, more preferably ±10%, or even more preferably ±5%.

[0022] Furthermore, terms such as "first," "second," and "third" in this specification and claims are used to distinguish between similar elements and are not necessarily used to describe a sequential or chronological order.

[0023] The method of the present invention may consist of the above-mentioned steps or may include additional steps, such as a step for further evaluation of the evaluation obtained in step (d) or a step for recommending a therapeutic measure, such as a treatment. Furthermore, it may include a step prior to step (a), such as a step relating to the pretreatment of the sample. However, it is preferably envisaged that the above method is an ex vivo method that does not require any steps to be 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 evaluation may be supported by a data processing device, such as a computer.

[0024] As used herein, the term "assess" refers to assessing whether a subject suffers from sepsis, whether the subject is at risk of suffering from sepsis, whether the subject shows a worsening medical condition in terms of overall health status, or in terms of sepsis or the signs and symptoms associated with sepsis and / or infection.Accordingly, as used herein, assessment includes diagnosing sepsis, predicting the risk of developing sepsis, and / or predicting any deterioration in the health status of the subject, particularly in terms of the signs and symptoms associated with sepsis and / or infection.

[0025] In one embodiment, the term "assessing" refers to diagnosing sepsis, such that a subject suspected of having an infection is diagnosed as suffering from sepsis or not.

[0026] In another embodiment, the assessment referred to according to the present invention is an assessment of the risk of developing sepsis (and thus a prediction of the risk of developing sepsis). Furthermore, when the risk of developing sepsis or the risk of a worsening health condition is predicted, it will be understood that the prediction is typically performed 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, in particular 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. In one embodiment of prediction, the subject being tested does not suffer from sepsis at the time the sample is obtained. Thus, the present invention allows for early identification of patients at risk.

[0027] In one embodiment, the risk of developing sepsis within 24 hours is predicted.

[0028] In an alternative embodiment, the risk of developing sepsis within 48 hours is predicted. The 48 hour period is evaluated in the Examples section.

[0029] In yet another embodiment, the evaluation is a prediction of the risk of the subject's (health) condition worsening in the future.The term "worsening of symptoms" of a subject suspected of and / or suffering from an infectious disease is well understood by those skilled in the art.This term typically relates to the worsening of symptoms that may ultimately lead to further medication or other intervention.

[0030] Preferably, the subject's condition worsens if the subject's disease severity increases, if the subject's antibiotic therapy is intensified, if the subject is admitted to the 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 of admission, if the subject is readmitted within 30 days of discharge, if the subject experiences organ dysfunction or failure as measured, for example, by SOFA score, and / or if the subject requires organ support.

[0031] One of skill in the art will understand when a subject's condition has not worsened. Typically, a subject's condition has not worsened when the subject does not have the outcomes described in the previous paragraph.

[0032] In one embodiment, a subject's condition worsens 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.

[0033] In one embodiment, predicting the risk of the subject's condition worsening is predicting the risk of the subject's antibiotic therapy being intensified.

[0034] 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.

[0035] In another embodiment, the prediction of the risk of the subject's condition worsening is a prediction of the subject's risk of dying in hospital. Thus, it is assessed whether the subject is at risk of dying in hospital.

[0036] 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 to the hospital. Thus, it is assessed whether the subject is at risk of dying within 30 days of admission to the hospital.

[0037] 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 evaluated whether the subject is at risk of being readmitted within 30 days after discharge.

[0038] 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 failure. Organ dysfunction and failure can be evaluated, 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). An increase in SOFA score (such as at least 1 point, at least 2 points, at least 3 points, or at least 4 points) is considered as a worsening of the condition. In contrast, when the SOFA score does not increase (the subject does not have the highest SOFA score), the condition typically does not worsen. The prediction window may be the prediction window described above for the prediction of the risk of developing sepsis.

[0039] The Sequential Organ Failure Assessment (SOFA) is a validated score that combines clinical assessment and laboratory measurements to quantitatively describe organ dysfunction / failure. Respiratory, coagulation, hepatic, cardiovascular, central nervous system and renal dysfunction are scored individually and the sum of the scores gives the SOFA score, which ranges from 0 to 24. Preferably, the SOFA score is determined as described in Vincent 1996 (Vincent et al., Intensive Care Med. 1996 July;22(7):707-10. doi:10.1007 / BF 01709751. PMID:8844239.).

[0040] 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 (such as fluid therapy), oxygenation (e.g., by ventilation or extracorporeal membrane oxygenation), and / or renal replacement therapy. The prediction window may be, for example, a prediction window as described above for predicting the risk of developing sepsis within 24 or 48 hours after the sample is obtained.

[0041] In one embodiment, the term "assessment" refers to the diagnosis of sepsis. Thus, a subject suspected of having an infection is diagnosed as suffering from sepsis or not. Preferably, assessment refers to the early detection of sepsis.

[0042] As will be understood by those skilled in the art, the evaluation performed according to the present invention, although preferred, may not usually be correct for 100% of the subjects examined. This term typically requires that the statistically significant portion of the subjects can be accurately evaluated. 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 & Sons, New York 1983. 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.

[0043] The term "subject" as used herein 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 an infectious disease. The term "suspected of an infectious disease" as used herein means that the subject exhibits clinical parameters, signs and / or symptoms of an infectious disease. Thus, a subject according to the present invention is typically a subject suffering from an infectious disease 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 consultation. Preferably, the sample is obtained at the time of consultation at the emergency department. However, the sample may also be obtained at the time of consultation with a primary care physician.

[0044] Typically, the subject to be tested is suspected of having an infectious disease. The term "infectious disease" is well understood by those skilled in the art. As used herein, the term "infectious disease" 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 infectious disease is a bacterial infection. Thus, the subject is suspected of having a bacterial infection.

[0045] The term "sample" as used herein 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, an interstitial fluid sample, a lymphatic fluid 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.

[0046] In one embodiment, the sample is an interstitial fluid sample.

[0047] 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 supra).

[0048] 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 does not suffer 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. (cited above). Thus, a subject suffers from septic shock if the following criteria are met: Sepsis, i.e. suspected / proven infection, causing a change in the total SOFA score of ≥2 points · Persistent hypotension requiring vasopressors to maintain a MAP of 65 mmHg or greater and a serum lactate level greater than 2 mmol / L (18 mg / dL) despite adequate volume resuscitation

[0049] It is further envisaged that the subjects being tested may or may not be infected with SARS-CoV-2.

[0050] The term "determining" as used herein 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.

[0051] The term "amount" as used herein refers to the absolute amount of the biomarker referred to herein, the relative amount or concentration of the compound, and any value or parameter that can be correlated therewith or derived therefrom. Such values ​​or parameters include intensity signal values ​​derived from any specific physical or chemical property obtained from the compound by direct measurement, such as intensity values ​​in mass or NMR spectra. In addition, all values ​​or parameters obtained by indirect measurement as specified elsewhere in this specification are included, such as the amount of response measured by a biological readout system in response to a compound, or the intensity signal obtained from a specifically bound ligand. It should be understood that values ​​that correlate with the above amounts or parameters can also be obtained by any standard mathematical operation.

[0052] Determining the amount in the methods of the invention may be performed by any technique that allows for detection of the presence or absence 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.

[0053] 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 weight or NMR spectrum. The methods preferably include analytical devices such as biosensors, optical devices linked to immunoassays, biochips, mass spectrometers, NMR analyzers, surface plasmon resonance measuring instruments, or chromatographic 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), nephelometry, 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 appended examples below.

[0054] The biomarkers that are determined according to the present invention are well known in the art.Furthermore, the method of determining the amount of biomarkers is well known.For example, biomarkers can be measured as described in the Examples section (see Example 1).

[0055] Delta-like proteins are single-pass transmembrane proteins known for their role in Notch signaling as homologs of the Notch Delta ligand first described in Drosophila. DLL1 (Delta-like ligand 1) polypeptide is the human homolog of the Notch Delta ligand and is a member of the delta / serrate / jagged family. It plays a role in mediating cell fate decisions during hematopoiesis. It may play a role in cell-cell communication. Synonyms for DLL1 are DELTA1, DL1, Delta or delta-like canonical Notch ligand 1.

[0056] DLL1 (UniProtKB_O00548(DLL1_HUMAN)) binds to the extracellular domain of the Notch receptor. The interaction between the Notch receptor and DLL1 generates a soluble extracellular portion of DLL1 (sDLL1) that is cleaved and released from the surface of both the receptor and its ligand. The transmembrane domain and the intracellular domain remain connected to the cell. As used herein, "DLL1" preferably refers to soluble DLL1, i.e., the released extracellular domain of DLL1.

[0057] The biomarker Mid-regional proadrenomedullin (MRproADM) is well known in the art. This biomarker has been proposed as a marker for sepsis (Christ-Crain, M., Morgenthaler, NG, Struck, J. et al. Mid-regional pro-adrenomedullin as a prognostic marker in sepsis: an observational study. Crit Care 9, R816 (2005). https: / / doi.org / 10.1186 / cc3885). MRproADM is a 48 amino acid long fragment derived from the proADM molecule, which exists in a 1:1 ratio with adrenomedullin (AM). Thus, the amount of MRproADM represents the amount and activity of adrenomedullin. AM (adrenomedullin) and PAMP (proadrenomedullin N-terminal peptide) are potent antihypertensive and vasodilator agents. Many of the actions reported are most relevant to the physiological control of fluid and electrolyte homeostasis.

[0058] 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 first 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, Bottner 1999, Gene 237:105-111, Bootcov supra, Tan supra, Baek 2001, Mol Pharmacol 59:901-908, Hromas supra, Paralkar supra, and Morrish 1996, Placenta 17:431-441.

[0059] 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. It was identified in the 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).

[0060] The marker, cystatin C, 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 quite constant throughout life. Elimination from the circulation is almost entirely via glomerular filtration. For this reason, serum concentrations of cystatin C are independent of muscle mass and gender in the age range of 1 to 50 years. Thus, cystatin C in plasma and serum has been proposed as a more sensitive marker for GFR. The sequence of human cystatin C polypeptide can be assessed using Genbank (see, for example, accession number NP_000090.1). This biomarker can be determined by particle-enhanced immunoturbidimetric assay. Human cystatin C agglutinates with latex particles coated with anti-cystatin C antibodies.

[0061] In the method of the present invention, a third biomarker may be determined. In particular, step (b) of the method of the present invention may further comprise determining the amount of sFlt1, cystatin C or MR-proADM as a third biomarker.

[0062] Thus, the present invention relates to the determination of at least two biomarkers, namely the biomarker DLL1 and the biomarker GDF15, and optionally a third biomarker.

[0063] In one embodiment, the third biomarker is sFlt1. Thus, DLL1, GDF15 and sFLT1 are determined.

[0064] In an alternative embodiment, the third biomarker is cystatin C (Cys). Thus, DLL1, GDF15 and CysC are determined.

[0065] In an alternative embodiment, the third biomarker is MR-proADM. Thus, DLL1, GDF15 and CysC are determined.

[0066] It should be understood that the present invention is not limited to the above markers. Rather, the present invention may encompass the determination of additional markers.

[0067] The term "criterion" as used herein refers to a quantity 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, the criterion shall be a quantity 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.For example, the criterion is a quantity or score that allows a subject to be assigned to a group of subjects that is at risk of developing sepsis (within the above-mentioned prediction window, for example within about 48 hours) or a group of subjects that is not at risk of developing sepsis.

[0068] The suitable threshold amount for separating the two groups can be calculated without further investigation by the statistical test mentioned elsewhere herein based on the amount of biomarker from either the subject or group of subjects known to suffer from or be at risk of developing disease or condition, or the subject or group of subjects known not to suffer from or be at risk of developing disease or condition.The reference amount applicable to each subject can vary according to various physiological parameters such as age, sex, or subpopulation.

[0069] 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 of the biomarkers that is essentially the same as or similar to the corresponding reference indicates that the subject is at risk of developing sepsis, and an amount for each of the biomarkers that differs from the corresponding reference indicates that the subject is not at risk of developing sepsis.

[0070] Also, typically the reference is a reference for each biomarker derived 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 that the subject is not at risk of developing sepsis, and an amount for each of the biomarkers that differs from the corresponding reference indicates that the subject is at risk of developing sepsis.

[0071] The term "at least one subject" refers to one subject or multiple subjects, for example, at least 10, 50, 100, 200, or 1000 subjects.

[0072] In one embodiment, an amount of the biomarker greater than the baseline for that biomarker is indicative of a subject at risk (e.g., developing sepsis within a particular time period after the sample is obtained), and an amount of the biomarker less than the baseline for that biomarker is indicative of a subject not at risk for sepsis or not suffering from sepsis.

[0073] Reference amounts can in principle be calculated for a cohort of subjects based on the mean or median value of a given parameter, such as the amount of a biomarker, by applying standard statistical methods. The accuracy of a test, particularly a method aimed at diagnosing an event, 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 the 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. On the y-axis is the sensitivity, i.e. the true positive rate, which is 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. It is calculated only from the affected subgroup. On the x-axis is the false positive rate, i.e. 1-specificity, which is defined as the ratio of the number of false positive results to the product of the number of true negative results and the number of false positive results. The x-axis is an index of specificity, calculated entirely from the unaffected subgroup. The true positive rate and the false positive rate are calculated entirely 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. An ROC plot that passes through the upper left corner, where the true positive rate is 1.0, i.e. 100% (perfect sensitivity) and the false positive rate is 0 (perfect specificity), is a test that is perfectly discriminatory (there is no overlap between the two outcome distributions). The theoretical plot of an indiscriminate test (where the distribution of outcomes for the two groups is identical) is 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 completely below the 45° diagonal, this is easily remedied by changing the criterion for "positive" from "greater than" to "less than," or vice versa.Qualitatively, the closer the plot is to the upper left corner, the higher the accuracy of the whole test. Depending on the desired confidence interval, a threshold value can be derived from the ROC curve, which allows diagnosis or prediction for a given event with an appropriate balance of sensitivity and specificity. Therefore, the criteria used in the above-mentioned method of the present invention, i.e., the threshold value that allows distinguishing subjects at risk (for example, developing sepsis) from those at no risk, can usually be generated by establishing the ROC of the cohort as described above and deriving a 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 is understood that optimal sensitivity is desired to exclude subjects as being at increased risk or suffering from a disease (i.e., rule out), whereas optimal specificity is assumed to evaluate subjects as being at increased risk or suffering from a disease (i.e., rule in).

[0074] 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 having an infection based on the amount of the biomarkers.

[0075] Thus, the amounts of the first biomarker, the second biomarker and optionally the third biomarker may be compared to a standard for the first biomarker, a standard for the second biomarker and optionally a standard for the third biomarker, respectively.

[0076] Alternatively, a score may be calculated based on the amounts of the biomarkers, i.e., the first biomarker, the second biomarker and, optionally, the third biomarker. The score allows for the assessment of a subject suspected of having an infection, such as to predict the risk of developing sepsis. Optionally, the score may be compared to a suitable reference score.

[0077] The term "comparing" as used herein includes comparing the determined amount of the biomarker referred to herein with a standard. It should be understood that comparison as used herein refers to any type 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, the term "comparing" as used herein includes comparing the calculated score with a suitable standard score. The comparison may be performed manually or computer-assisted. The amount and standard values ​​can, for example, be compared with each other, and the comparison may be performed automatically by a computer program implementing an algorithm for the comparison. The computer program performing the evaluation provides the desired assessment in a suitable output format.

[0078] As mentioned above, it is also envisaged to calculate a score (particularly a single score) based on the amounts of the first and second biomarkers, or the first, second or third biomarker, i.e. a single score, and compare this score to a reference score. Preferably, the score is based on the amounts of the first and second biomarkers in a sample from the test subject, and if the amount of the third biomarker is determined, based on the amounts of the first, second and third biomarkers in a sample from the test subject.

[0079] The calculated score combines information on the amount of at least two biomarkers (e.g., two or three biomarkers). Moreover, in the score, the biomarkers are preferably weighted according to their contribution to the establishment of an evaluation such as differentiation. Thus, the values ​​of individual markers are weighted, and the weighted values ​​are used to calculate the score. Suitable coefficients (weights) can be determined by those skilled in the art 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.

[0080] The score can be considered as a classification parameter for evaluating the subject described herein. In particular, it allows to provide an evaluation based on a single score. The reference score is preferably a value, in particular a cut-off value that allows to evaluate a subject suspected of having an infection as described herein. Preferably, the reference is a single value. Therefore, it is not necessary to interpret the entire information on the amount of each biomarker. Using the scoring system described herein, advantageously, values ​​of different dimensions or units of biomarkers may be used, since the values ​​are mathematically converted into scores. Thus, for example, absolute concentration values ​​may be combined with peak area ratios to be scored. The applied reference score may be selected based on the desired sensitivity or the desired specificity. Methods for selecting suitable reference scores are well known in the art.

[0081] Advantageously, in the study underlying the present invention, it was found that the combination of a first biomarker with a second biomarker, preferably a third biomarker, allows a reliable early assessment of patients showing signs and symptoms of infection. In the study, patients presenting to the emergency department, a medical (non-surgical) emergency, were investigated. For this purpose, the patients were further subdivided into those with a high probability of sepsis and those suspected of having an infection without sepsis. The patients suspected of having an infection were further subdivided into those whose overall condition worsened and those whose overall condition did not worsen. The deterioration was defined as the following: escalation of care (i.e. admission to the ICU), death in the hospital, death within 30 days of admission, or readmission within 30 days of discharge. The amounts of the different biomarkers were determined, the biomarkers were analyzed and mathematically combined by logistic regression. 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) within the interval [a][b]. AUC was also examined for biomarker pairs and triplets. Combinations of biomarkers that together showed improved AUC over the AUC of the best biomarker alone were identified. Results are described in the accompanying Examples below.

[0082] In particular, when these patients are seen, for example, in an emergency center, early assessment of the risk of developing severe complications such as sepsis, SIRS or overall deterioration of health is decisive for initiating therapeutic measures, including drug administration, physical or other therapeutic interventions and / or hospitalization. These therapeutic measures may include, inter alia, 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 and managed in an outpatient setting or admitted to the hospital with a lower level of care (e.g., general ward). Thanks to the present invention, patients can be evaluated early by biomarker determination, so that life-threatening developments can be prevented. The biomarker pairs and triplets identified in the studies underlying the present invention are a reliable basis for medical decisions, and the evaluation can be carried out in a time- and cost-effective manner.

[0083] Therefore, the method of the present invention may further include 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 that the practitioner considers necessary.

[0084] In one embodiment, the therapeutic measures recommended or initiated if a patient is assessed to be at risk are selected from the following: Administration of empirical broad-spectrum treatment with at least one or more broad-spectrum antibiotics, such as a cephalosporin, a beta-lactam / beta-lactamase inhibitor (e.g., piperacillin), or a carbapenem, typically depending on the organisms considered likely pathogens and 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

[0085] The definitions given herein above apply mutatis mutandis below.

[0086] The present invention also provides a computer-implemented method for evaluating a subject suspected of having an infectious disease, comprising: (a) receiving a value for the amount of a first biomarker in a sample from a subject, the first biomarker being DLL1; (b) receiving a value for the amount of a second biomarker in the subject's sample, the second biomarker being GDF15; (c) comparing the value for the amount of the biomarker with a standard for that biomarker and / or calculating a score for assessing the subject for suspected infection based on the amount of the biomarker; (d) evaluating the subject based on the comparison and / or calculation performed in step (c).

[0087] The term "computer-implemented" as used herein means that the method is carried out in an automated manner, typically on a processing unit included in a computer or similar data processing device. The data processing unit receives the values ​​of the amounts of the biomarkers. Such values ​​may be amounts, relative amounts, or any other calculated values ​​reflecting the amounts 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 values ​​for the amounts that are already predetermined.

[0088] Typically, in step (b) of the method, the method may comprise receiving a value of the amount of sFlt1, cystatin C or MR-proADM as a third biomarker.

[0089] The present invention also in principle contemplates a computer program, a computer program product, or a computer readable storage medium tangibly embodied with said computer program, the computer program comprising instructions which, when executed on a data processing device or computer, perform the inventive method as specified above. a computer or computer network comprising at least one processor, the processor being adapted to execute a method according to one of the embodiments described herein, a computer-loadable data structure adapted to carry out a method according to one of the embodiments described herein while said data structure is executed on a computer, a computer script, the computer script being adapted to carry out a method according to one of the embodiments described herein while the program is being run on a computer, a computer program comprising program means for carrying out a method according to one of the embodiments described herein while said computer program is being run on a computer or a computer network, a computer program comprising program means according to any of the preceding embodiments, the program means being stored on a computer readable storage medium; a storage medium, on which a data structure is stored and which is adapted to carry out a method according to one of the embodiments described herein after the data structure has been loaded into a main and / or working storage device of a computer or a computer network, a computer program product having program code means, which can be or are stored on a storage medium for performing a method according to one of the embodiments described herein when the program code means is executed on a computer or a computer network, a typically encrypted data stream signal containing data of the parameters defined elsewhere in this specification, and - includes a typically encrypted data stream signal containing the assessment provided by the method of the present invention.

[0090] The present invention relates to a device for evaluating a subject suspected of having an infectious disease, comprising: (a) a measuring unit for determining the amount of a first biomarker, which is DLL1, and a second biomarker, which is GDF15, in a sample of a subject, the measuring unit comprising a detection system for the first biomarker and the second biomarker; and (b) a device comprising an evaluation unit operably linked to the measurement unit, the evaluation unit preferably comprising a database having stored criteria for the first and second biomarkers specified above, and a data processor preferably comprising instructions for performing a comparison of the amounts of the first and second biomarkers specified above with the criteria and / or for performing a calculation of a score for evaluating the subject suspected of having an infection based on the amounts of the biomarkers, and for evaluating the subject based on the comparison, the evaluation unit being capable of automatically receiving values ​​for the amounts of the biomarkers from the measurement unit.

[0091] The term "device" as used herein relates to a system comprising the above-mentioned units operatively linked to each other to allow the determination of the amount of the biomarker and its evaluation according to the method of the present invention, such that an evaluation can be provided.

[0092] The analytical unit typically comprises at least one reaction zone having biomarker detection agents for the first and second biomarkers, and preferably also for a third biomarker, in immobilized form on a solid support or carrier that is brought into contact with the sample. Furthermore, in the reaction zone it is possible to apply conditions that allow specific binding of the detection agents to the biomarkers contained in the sample.

[0093] The reaction zone may allow direct sample application or may be connected to a loading zone where the sample is applied. In the latter case, the sample may be actively or passively transported to the reaction zone through the connection between the loading zone and the reaction zone. In addition, the reaction zone is also connected to a detector. The connection must be such that the detector can detect the binding of the biomarker to the detection agent. The suitable connection depends on the technique used to measure the presence or amount of the biomarker. For example, for optical detection, light transmission 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.

[0094] 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 comprises a data processing element, such as a computer, in which an algorithm for determining the amount present in the sample is implemented.

[0095] The processing unit referred to in accordance with the method of the present invention typically includes 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 may 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 includes a processor capable of executing multiple instructions (such as a program of software).

[0096] The evaluation unit typically includes a memory or has access to a memory. The memory is a computer-readable medium and may include, 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 accessible 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 without 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 cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium accessible by a computing device and capable of storing a plurality of instructions executable by the processor of the computing device.

[0097] 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 through those control signals to transform substances remote from the computer itself. These descriptions and representations are the means used by those skilled in the art of data processing to most effectively convey, for example, the substance of their work to others skilled in the art.

[0098] The instructions may also include an algorithm, which is 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 of data, 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 associated with the appropriate physical quantities and are merely used as convenient labels applied to these quantities.

[0099] 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, and a file. 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 an output regarding the results, instructions, ratios, or other factors of the method via an output device.

[0100] Typically, the measurement unit determines a third biomarker and includes a detection system for the third biomarker, and the database includes stored references for the third biomarker, the third biomarker being sFlt1, cystatin C or MR-proADM.

[0101] More typically, the detection system includes at least one detection agent capable of specifically detecting each of the biomarkers.

[0102] The present invention contemplates a device for evaluating a subject suspected of having an infectious disease, comprising an evaluation unit comprising a database with stored criteria for a first biomarker, which is DLL1, and a second biomarker, which is GDF15, and a data processor, preferably comprising instructions for performing a comparison of the amounts of the first and second biomarkers specified above with the criteria, and for evaluating the subject based on the comparison, said evaluation unit being capable of receiving the values ​​of the amounts of the biomarkers determined in the subject's sample.

[0103] Typically, the database includes stored references for a third biomarker, the third biomarker being sFlt1, cystatin C, or MR-proADM.

[0104] The present invention also relates in principle to the use of a first biomarker which is DLL1 and a second biomarker which is GDF15, or a detection agent which specifically binds to the first biomarker and a detection agent which specifically binds to the second biomarker, for evaluating a subject suspected of having an infectious disease.

[0105] The term "detection agent" as used herein 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, the 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 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 also 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. The aptamer detection agent may be, for example, a nucleic acid or peptide aptamer. Methods for preparing such aptamers are well known in the art. For example, random mutations may be introduced into the nucleic acid or peptide that is the basis for 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 at least 3 times higher than any other component of the sample, more preferably at least 10 times higher, even more preferably at least 50 times higher. Non-specific binding may be acceptable if it can still be clearly distinguished and measured, for example according to its size on a Western blot or by its relatively high abundance in the sample.

[0106] 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, β-galactosidase, luciferase, and their derivatives. Suitable substrates for detection include diaminobenzidine (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). Appropriate enzyme-substrate combinations can result in colored reaction products, fluorescence or chemiluminescence that 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. Exemplary fluorescent labels include fluorescent proteins (such as 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. Typical radioactive labels include 35S, 125I, 32P, 33P, etc. Radioactive labels can be detected by any known and appropriate method, such as a light-sensitive film or a phosphor imager. Suitable labels can 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.

[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 any sequentially coupled mass spectrometry such as GC-MS, LC-MS, direct injection mass spectrometry, FT-ICR-MS, CE-MS, HPLC-MS, quadrupole mass spectrometry, MS-MS or MS-MS, ICP-MS, Py-MS, TOF, or any combination approach using the aforementioned techniques. Methods for applying these techniques are well known to those skilled in the art. Moreover, suitable devices are 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, mass spectrometry is tandem mass spectrometry (also known as MS / MS). Tandem mass spectrometry, also known as MS / MS, involves two or more mass spectrometry steps during which fragmentation occurs. In tandem mass spectrometry, two mass spectrometers are connected in series with a collision cell. The mass spectrometers are coupled to a chromatography device. The chromatographically separated sample is selected and quantified in the first mass spectrometer, then fragmented with an inert gas in the collision cell, and one or more pieces are selected and quantified in the second mass spectrometer. The fragments are selected and quantified in the second mass spectrometer. Identification by MS / MS is more accurate.

[0108] In one embodiment, mass spectrometry as used herein encompasses quadrupole MS. Most preferably, said quadrupole MS performs the following steps: a) selection of the mass / charge ratio (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 ratio of ions generated by the fragmentation process of step b) in the additional subsequent quadrupole, whereby methods a) to c) are performed at least once and an analysis of the mass / charge ratio of all ions present in the mixture of substances as a result of the ionization process is performed, whereby the quadrupole is filled with collision gas but no accelerating voltage is applied during the analysis. Details regarding said most preferred mass spectrometry 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 subjected to cleavage with a protease, for example trypsin. The protease cleaves the protein biomarkers into smaller fragments.

[0111] Thus, the mass spectrometry step preferably includes an ionization step in which the biomarkers to be determined are ionized. Naturally, other compounds present in the sample / eluate 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). Thus, mass spectrometry is 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 the third biomarker is additionally used, the third biomarker being sFlt1, cystatin C or MR-proADM.

[0114] The present invention also relates to a kit for evaluating a subject suspected of having an infectious disease comprising a detection agent that specifically binds to a first biomarker, which is DLL1, and a detection agent that specifically binds to a second biomarker, which is GDF15.

[0115] The term "kit" as used herein 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 that, when executed on a computer or data processing device, can carry out or assist in the determination of the biomarkers referred to in the method of the invention. 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 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. In addition, it 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 sFlt1, cystatin C, or MR-proADM.

[0117] The above definitions and explanations apply mutatis mutandis below.

[0118] Determining the amount of the first, second and optionally third biomarkers mentioned herein in connection with the method of assessing a subject suspected of having an infection also allows for monitoring of the subject.

[0119] Accordingly, the present invention provides a method for monitoring a subject, comprising the steps of: (a) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of a third biomarker referred to herein (i.e., sFlt1, Cystatin C, or MR-proADM) in a first sample from the subject, and optionally calculating a first score based on the determined amounts; (b) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of a third biomarker in a second sample from the subject, and optionally calculating a second score based on the determined amounts; (c) c1) First score vs. second score, or c2) the amount of DLL1, GDF-15 and optionally a third biomarker in the second sample versus the amount of DLL1, GDF-15 and optionally a third biomarker in the first sample. and comparing As a result, The present invention relates to a method for monitoring a target.

[0120] The above method therefore includes two alternative embodiments.

[0121] According to embodiment c1), the first score is compared with the second score. This embodiment requires the calculation of the scores in steps (a) and (b).

[0122] According to embodiment c2), the amount of the biomarker in the second sample is compared with the amount of the biomarker in the first sample. This embodiment does not require the calculation of the scores in steps (a) and (b).

[0123] The term "subject" is defined above. This definition applies accordingly. Preferably, the subject is a subject suspected of having an infectious disease or a subject suffering from an infectious disease. Also preferably, the subject is a subject presenting to an emergency department.

[0124] In one embodiment, the term "monitoring a subject" refers to determining whether a patient has been successfully treated with a therapeutic treatment (as defined elsewhere herein). Thus, the term "monitoring a subject" preferably relates to assessing whether a subject responds to a therapeutic treatment as referred to herein. Preferably, a subject responds to a therapeutic treatment if the treatment improves the subject's symptoms (with respect to an infection). Preferably, a subject does not respond to a therapeutic treatment if the treatment does not improve the subject's symptoms (with respect to an infection). A therapeutic treatment is typically initiated after obtaining a first sample but before obtaining a second sample. However, it may also be initiated before obtaining a first sample.

[0125] Also preferably, the term "monitoring a subject" refers to assessing whether the subject's condition improves or worsens. Monitoring can be used for active patient management, including hospitalization, intensive care measures, and / or additional qualitative monitoring, as well as quantitative monitoring measures, i.e., determining the frequency of monitoring.

[0126] The term "sample" is defined elsewhere herein. For example, the sample may be a blood, serum or plasma sample.

[0127] The amount of the biomarker is determined in a first sample and in a second sample. In one embodiment, the first sample is obtained at the time of presentation (e.g. in the emergency department). A "second sample" is understood as a sample obtained in particular to reflect the change in the amount or score of the biomarker in the second sample relative to the amount or score of the biomarker in the second sample relative to the first score (i.e. the score of the first sample). The second sample is therefore preferably obtained after the first sample. It is understood that the second sample is obtained not too early from the first sample in order to observe a change in the score that is significant enough to allow monitoring of the patient. The second sample is therefore preferably obtained at least 4 hours, or more preferably at least 8 hours, or most preferably at least 20 hours after the first sample is obtained. In one embodiment, the second sample is obtained 8 to 30 hours, for example 12 to 26 hours, after the first sample.

[0128] Preferably, a decrease in the second score (or the amount of the biomarker in the second sample) compared to the first score (or the amount of the biomarker in the first sample) is indicative of a subject that responds to the therapeutic treatment or has improved symptoms. In contrast, an increase in the second score compared to the first score is indicative of a subject that does not respond to the therapeutic treatment or has not improved symptoms. By carrying out the above method, a decision can be made to continue, stop, or modify the therapeutic treatment in the subject.

[0129] Preferably, if the treatment improves the subject's condition, the subject responds to the therapeutic treatment.Preferably, if the treatment does not improve the subject's condition, the subject does not respond to the treatment.In this case, the treatment may expose the subject to the risk of harmful side effects without providing any significant benefit to the subject (thereby generating unnecessary medical costs).

[0130] Preferably, a decrease, more preferably a significant decrease, and most preferably a statistically significant decrease, in the second score compared to the first score is indicative of the subject responding to the therapeutic treatment.

[0131] A significant decrease is preferably a decrease in size that is considered significant for monitoring a subject. In particular, the decrease is considered statistically significant. The terms "significant" and "statistically significant" are known to those skilled in the art. Therefore, whether a decrease is significant or statistically significant can be easily determined by those skilled in the art using various well-known statistical evaluation tools. The preferred significant decrease in score shown for a subject responding to therapeutic treatment is shown herein below.

[0132] Preferably, a reduction of at least 5%, at least 10%, more preferably at least 20%, even more preferably at least 30%, and most preferably at least 40% is considered significant and thus indicative of a subject responding to a therapeutic treatment or having an improvement in its condition.

[0133] The present invention also relates to the in vitro use of i) a first biomarker which is DLL1 and a second biomarker which is GDF15 or ii) a detection agent which specifically binds to said first biomarker and a detection agent which specifically binds to said second biomarker, for monitoring a subject. Preferably, the biomarkers or detection agents are used in a first and second sample as described above.

[0134] In one embodiment, a third biomarker or a detection agent that specifically binds to the third biomarker is additionally used, the third biomarker being sFlt1, cystatin C or MR-proADM.

[0135] Therefore, it should be understood that the above definitions and explanations of terms apply to all embodiments described herein and in the appended claims.

[0136] The following embodiments are specific embodiments contemplated in accordance with the present invention.

[0137] 1. A method for evaluating a subject suspected of having an infectious disease, comprising: (a) determining the amount of a first biomarker in a sample from a subject, wherein the first biomarker is DLL1; (b) determining the amount of a second biomarker in the subject's sample, wherein the second biomarker is GDF15; (c) comparing the amount of the biomarker with a standard for that biomarker and / or calculating a score for assessing the subject for suspected infection based on the amount of the biomarker; (d) evaluating the subject based on the comparison and / or calculation performed in step (c).

[0138] 2. The method of embodiment 1, wherein step (b) further comprises determining the amount of MR-proADM, sFlt1 and / or cystatin C.

[0139] 3. The method of embodiment 1 or 2, wherein the subject is a subject presenting to an emergency department.

[0140] 4. The method of 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.

[0141] 5. The method of any one of embodiments 1-4, wherein the reference is a reference for each biomarker derived 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 that the subject is at risk for developing sepsis, and an amount for each of the biomarkers that differs from the corresponding reference indicates that the subject is not at risk for developing sepsis.

[0142] 6. The method of any one of embodiments 1-4, wherein the reference is a reference for each biomarker derived from at least one subject known to be not 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 that the subject is not at risk for developing sepsis, and an amount for each of the biomarkers that differs from the corresponding reference indicates that the subject is at risk for developing sepsis.

[0143] 7. The method of any one of embodiments 1-6, wherein the subject has or is suspected of having an infectious disease.

[0144] 8. The method of any one of embodiments 1 to 7, wherein the sample is a blood sample or a sample derived therefrom.

[0145] 9. The method of any one of embodiments 1-8, wherein the subject is a human.

[0146] 10. A computer-implemented method for evaluating a subject suspected of having an infectious disease, comprising: (a) receiving a value for the amount of a first biomarker in a sample from a subject, the first biomarker being DLL1; (b) receiving a value for the amount of a second biomarker in the subject's sample, the second biomarker being GDF15; (c) comparing the value for the amount of the biomarker with a standard for that biomarker and / or calculating a score for assessing the subject for suspected infection based on the amount of the biomarker; (d) evaluating the subject based on the comparison and / or calculation performed in step (c).

[0147] 11. The method of embodiment 10, wherein in step (b), the method further comprises receiving a value for the amount of sFlt1, cystatin C or MR-proADM as a third biomarker.

[0148] 12. A device for evaluating a subject suspected of having an infectious disease, comprising: (a) a measuring unit for determining the amount of a first biomarker, which is DLL1, and a second biomarker, which is GDF15, in a sample of a subject, the measuring unit comprising a detection system for the first biomarker and the second biomarker; and (b) an evaluation unit operably coupled to the measurement unit, the evaluation unit comprising a database having stored references for a first biomarker and a second biomarker, preferably as described in any one of embodiments 1-9, and a data processor comprising instructions for performing a comparison of the amounts of the first biomarker and the second biomarker with the reference, preferably as described in any one of embodiments 1-9, and / or for performing a calculation of a score for evaluating a subject suspected of having an infection based on the amounts of the biomarkers, and for evaluating the subject based on the comparison, the evaluation unit being capable of automatically receiving values ​​for the amounts of the biomarkers from the measurement unit.

[0149] 13. The device of embodiment 12, wherein the measuring unit determines a third biomarker and comprises a detection system for a third biomarker, and the database comprises stored standards for a third biomarker, and the third biomarker is sFlt1, cystatin C or MR-proADM.

[0150] 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.

[0151] 15. A device for evaluating a subject suspected of having an infectious disease, comprising an evaluation unit comprising a database with stored criteria for a first biomarker, which is DLL1, and a second biomarker, which is GDF15, and a data processor comprising instructions for performing a comparison of the amounts of the first and second biomarkers, preferably as specified in any one of embodiments 1 to 11, with the criteria, and for evaluating the subject based on the comparison, wherein the evaluation unit is capable of receiving the values ​​of the amounts of the biomarkers determined in a sample from the subject.

[0152] 16. The device of embodiment 15, wherein said database comprises stored references for a third biomarker, said third biomarker being sFlt1, cystatin C or MR-proADM.

[0153] 17. The use of i) a first biomarker that is DLL1 and a second biomarker that is GDF15, or ii) a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, to evaluate a subject suspected of having an infectious disease.

[0154] 18. The use according to embodiment 17, wherein a third biomarker or a detection agent that specifically binds to said third biomarker is additionally used, said third biomarker being sFlt1, cystatin C or MR-proADM.

[0155] 19. A kit for evaluating a subject suspected of having an infectious disease comprising a detection agent that specifically binds to a first biomarker, which is DLL1, and a detection agent that specifically binds to a second biomarker, which is GDF15.

[0156] 20. The kit of embodiment 19, wherein the kit further comprises a detection agent that specifically binds to a third biomarker, the third biomarker being sFlt1, cystatin C, or MR-proADM.

[0157] 21. A method for monitoring a subject, comprising: (a) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of a third biomarker referred to herein (i.e., sFlt1, Cystatin C, or MR-proADM) in a first sample from the subject, and optionally calculating a first score based on the determined amounts; (b) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of a third biomarker in a second sample from the subject, and optionally calculating a second score based on the determined amounts; (c) c1) First score vs. second score, or c2) the amount of DLL1, GDF-15 and optionally a third biomarker in the second sample versus the amount of DLL1, GDF-15 and optionally a third biomarker in the first sample. and comparing As a result, A method for monitoring a subject.

[0158] 22. The use of i) a first biomarker that is DLL1 and a second biomarker that is GDF15, or ii) a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, to monitor a subject.

[0159] 23. The method, use, device or kit according to any one of embodiments 1 to 22, wherein the assessment is a prediction of the risk of developing sepsis.

[0160] 24. The method, use, device or kit according to any one of embodiments 1 to 23, wherein the assessment is a prediction of the risk of developing sepsis.

[0161] 25. The method, use, device or kit according to any one of embodiments 1 to 24, wherein the assessment is a prediction of the risk of the subject's condition worsening.

[0162] 26. The method, use, device or kit according to embodiment 25, wherein the subject's condition worsens if: the subject's disease severity increases; the subject's antibiotic therapy is intensified; the subject is admitted to the ICU or another unit for a higher level of care; the subject requires emergency surgery; the subject dies in the hospital; the subject dies within 30 days of admission; the subject is readmitted within 30 days of discharge; the subject experiences organ dysfunction or failure, e.g. as measured by SOFA score; and / or the subject requires organ support.

[0163] 27. The method, use, device or kit of embodiment 25 or 26, wherein the subject's condition worsens 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.

[0164] All references cited throughout this specification are hereby incorporated by reference in their entirety and for the disclosure content specifically mentioned above. EXAMPLES

[0165] Example 1: Biomarker Determination The Elecsys® electrochemiluminescence (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 e 801 analyzer. The detection of GDF-15 using the cobas e 801 analyzer is based on the Elecsys® electrochemiluminescence (ECL) technology. Briefly, biotin-labeled and ruthenium-labeled antibodies are combined with the respective amounts of undiluted sample and incubated on the analyzer. Then, to promote the binding of the biotin-labeled immune complexes, streptavidin-coated magnetic microparticles are added and incubated on the device. 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. Then, in order to separate the bound immunoassay complexes from the remaining free particles, ProCell M buffer containing tripropylamine (TPA) for the subsequent ECL reaction is introduced into the measurement cell. 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 complexes and TPA. The resulting electrochemiluminescent signals are recorded by photomultiplier tubes and converted to a numerical value indicative of the concentration level of each analyte.

[0166] DLL1 was measured using a commercially available enzyme-linked immunosorbent assay (ELISA) (RayBio® Human DLL1 ELISA Kit Catalog Number: ELH-DLL1; Raybiotech, Norcross, USA). Briefly, an antibody specific for human DLL1 is coated onto a 96-well microtiter plate. DLL-1 present in the sample is bound and retained by the immobilized antibody. After washing away unbound material, a second biotinylated antibody specific for human DLL1 is pipetted into the wells and binds to the DLL1 present on the first antibody. After a further washing step, horseradish peroxidase (HRP)-conjugated streptavidin is pipetted into the wells and retained according to the amount of DLL1 present. After washing away unbound material, 3,3,5,5'-tetramethylbenzidine (TMB) is added to the wells, which in the presence of HRP forms a reaction product that can be measured by spectrophotometry.

[0167] Mid-regional pro-adrenomedullin (MRproADM) was measured using the commercially available B·R·A·H·M·S MRproADM KRYPTOR assay, a sandwich immunoassay developed for the ThermoFisher KRYPTOR platform (BRAHMS GMbH, ThermoFisher Scientific, Germany). The assay contains anti-pro-ADM sheep polyclonal antibodies conjugated with europium cryptate and anti-pro-ADM sheep polyclonal antibodies conjugated with XL665. From each plasma sample, 26 μL was used and measured undiluted on a ThermoFisher KRYPTOR analyzer (ThermoFisher Scientific, Germany).

[0168] SFLT1 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 and rutheniumylated monoclonal antibody that specifically binds to sFLT-1. 12 μL from each serum sample was used and measured undiluted on a cobas e 801 analyzer (Roche Diagnostics, Germany).

[0169] 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. Upon mixing and incubation of the antibody reagent with the sample, 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 nephelometrically at 546 nm and is proportional to the amount of cystatin C in the sample. 2 μL from each serum sample was used and measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0170] The NGAL (Neutrophil Gelatinase-Associated Lipocalin) test is a particle-enhanced turbidimetric immunoassay for the quantitative determination of NGAL by mixing 3 μL of plasma with reaction buffer R1. After a short incubation, the reaction is initiated by the addition of an immunoparticle suspension (polystyrene microparticles coated with a mouse monoclonal antibody against NGAL). Assay from Roche Diagnostics (Germany). NGAL in the sample causes agglutination of the immunoparticles. The degree of agglutination is quantified by the amount of light scattering, measured as light absorption. The NGAL concentration in the sample is determined by interpolation on an established calibration curve. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0171] FERR was measured with the commercially available 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 and rutheniumylated monoclonal antibody that specifically binds to ferritin. 10 μL was used from each serum sample and measured undiluted on a cobas e 801 analyzer (Roche Diagnostics, Germany).

[0172] KL6 (KL-6) [sialylated carbohydrate antigen KL-6]: The sialylated carbohydrate antigen KL-6 (KL-6) in the sample agglutinates with latex coated with mouse KL-6 monoclonal antibody through an antigen-antibody reaction. The absorbance change due to this agglutination is measured to determine the KL-6 level. The reagents were from Sekisui Medical Co. (Japan). 2.5 μL of plasma was analyzed. The samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0173] suPAR [soluble urokinase-type plasminogen activator receptor] is a turbidimetric immunoassay to quantitatively determine suPAR in human plasma samples. The first step of the test is the incubation of specimens of human origin (EDTA or heparin plasma) with the R1 reagent. After 5 min of incubation, the R2 reagent is added, initiating the reaction. Reaction buffer R2 is a suspension of latex particles coated with rat and mouse monoclonal antibodies against suPAR. After the addition of R2, the process of suPAR aggregation begins, and the level of accumulation is determined by the amount of scattered light during the measurement of light absorption. The concentration of suPAR in human plasma samples is determined using a linear calibration curve made before the start of the test. Reagents from ViroGates (Denmark). 10 μL of plasma were analyzed. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0174] LDHI2 [Lactate dehydrogenase]: UV assay Lactate dehydrogenase catalyzes the conversion of L-lactate to pyruvate, and NAD is reduced to NADH in this process. The initial rate of L-lactate + NAD + LDH pyruvate + NADH + H + NADH formation is directly proportional to the catalytic LDH activity. It is determined by photometrically measuring the increase in absorbance. Assay from Roche Diagnostics (Germany). 2.2 μL of plasma was analyzed. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0175] AT.pc [Antithrombin %]: kinetic colorimetric test. This test works according to the principle of the antithrombin (AT) heparin cofactor assay. Heparin and a defined amount of thrombin are added in excess to the sample. Any free antithrombin present binds to thrombin forming an inactive complex. Uninhibited thrombin liberates p-nitroaniline from the chromogenic substrate MeOCO-Gly-Pro-Arg-pNA. The remaining amount of thrombin is inversely proportional to the antithrombin content of the sample and therefore the increase in absorbance at a wavelength of 415 nm can be used to calculate the antithrombin activity. Assay from Roche Diagnostics (Germany). 1 μL of plasma was analyzed. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0176] Calprotectin [Calprotectin]: The Gentian (Norway) Calprotectin Immunoassay is a particle-enhanced turbidimetric immunoassay (PETIA) for the in vitro diagnostic testing of calprotectin in human plasma and serum samples. Samples were measured on a cobas c 501 analyzer (Roche Diagnostics, Germany).

[0177] Example 2: Analysis of Patients from the TRIAGE Study TRIAGE Study, Emergency Department, Kantonsspital Aarau, Switzerland. (Schuetz 2013, BMC emergency medicine, 13(1), 12).

[0178] All consecutive patients seeking non-surgical ED care were included at the time of ED admission.From a total of 4000 patients, we selected a subset of 600 patients with and without infection who subsequently developed sepsis, and 200 patients without infection.Patients with suspected infection at admission were classified as probable sepsis patients or infection controls according to the following: Cases (N=64): Sepsis cases likely to worsen / be more severe within 48 hours of ED presentation if admitted to ICU or met the criteria of Rhee et al. (Rhee, C., et al. (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 no sepsis within 48 hours of ED visit

[0179] Markers were mathematically combined by logistic regression and the "area under the receiver operating characteristic curve" (AUC) was used as a general measure of marker performance.

[0180] In addition to sepsis endpoints, we also assessed the endpoint of "general deterioration" (i.e., whether the patient's condition worsened independent of the sepsis diagnosis) in the population of patients with suspected infection on ED admission. Patients were classified into cases and controls according to: Cases: Deterioration was defined as the following: escalation of care (i.e., admission to an ICU) or death in the hospital, or death within 30 days of admission, or readmission within 30 days of discharge. Control: Patients with suspected infection but whose infection did not worsen

[0181] For sepsis endpoints, 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]

[0182] For sepsis endpoints, bivariate marker pairs as well as marker triplets (trivariate marker combinations) with AUCs that were at least 1 percentage point improved over all three single markers are shown in Table 2 . [Table 2]

[0183] For the worsening endpoint, combinations of marker pairs (bivariate marker combinations) that improved AUC by at least 1 percentage point over single markers are shown in Table 3 . [Table 3]

[0184] Examples of bivariate combinations of markers that are not an improvement over a single marker, i.e., have a negative AUC, are shown in Table 4 for the sepsis endpoint and in Table 5 for the exacerbation endpoint. Tables 4 and 5 show that combining sepsis markers is not trivial. [Table 4] [Table 5]

Claims

1. 1. A method for evaluating a subject suspected of having an infectious disease, comprising: (a) determining the amount of a first biomarker in a sample of the subject, wherein the first biomarker is DLL1; (b) determining the amount of a second biomarker in the subject's sample, wherein the second biomarker is GDF15; and (c) comparing the amount of said biomarker with a standard for said biomarker and / or calculating a score for assessing said subject suspected of having an infection based on the amount of said biomarker; (d) evaluating the subject based on the comparison and / or the calculation performed in step (c).

2. The method of claim 1, wherein step (b) further comprises determining the amount of MR-proADM, sFlt1 and / or cystatin C.

3. 3. The method of claim 1 or 2, wherein the subject is a subject presenting to an emergency department.

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

5. a) the subject has or is suspected of having an infectious disease; b) the sample is a blood sample or a sample derived therefrom, such as a blood, serum or plasma sample, and / or c) the subject is a human; The method according to any one of claims 1 to 4.

6. 1. A computer-implemented method for evaluating a subject suspected of having an infectious disease, comprising: (a) receiving a value for the amount of a first biomarker in the subject's sample, wherein the first biomarker is DLL1; (b) receiving a value for the amount of a second biomarker in the subject's sample, wherein the second biomarker is GDF15; and (c) comparing the value for the amount of the biomarker with a standard for the biomarker and / or calculating a score for assessing the subject suspected of having an infection based on the amount of the biomarker; (d) evaluating the object based on the comparison and / or the calculation performed in step (c).

7. 7. The method of claim 6, wherein in step (b), the method further comprises receiving a value for the amount of sFlt1, cystatin C, or MR-proADM as a third biomarker.

8. 1. A device for evaluating a subject suspected of having an infectious disease, comprising: (a) a measurement unit for determining an amount of a first biomarker, said first biomarker being DLL1, and a second biomarker, said second biomarker being GDF15, in a sample of said subject, said measurement unit comprising a detection system for said first biomarker and said second biomarker; (b) an evaluation unit operatively linked to said measurement unit, said evaluation unit comprising: a database with stored references for said first and second biomarkers, preferably as described in any one of claims 1 to 9; and a data processor comprising instructions for performing a comparison of said amounts of said first and second biomarkers with references, preferably as described in any one of claims 1 to 9, and / or for performing a calculation of a score for assessing said subject suspected of having an infection based on said amounts of said biomarkers, and for assessing said subject based on said comparison, said evaluation unit being capable of automatically receiving values ​​for said amounts of said biomarkers from said measurement unit; Including, the device.

9. The device of claim 8, wherein the measurement unit determines a third biomarker and comprises a detection system for a third biomarker, and the database comprises stored standards for a third biomarker, the third biomarker being sFlt1, cystatin C or MR-proADM.

10. The device of claim 8 or 9, wherein the detection system comprises at least one detection agent capable of specifically detecting the biomarker.

11. The use of i) a first biomarker that is DLL1 and a second biomarker that is GDF15, or ii) a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, to evaluate a subject suspected of having an infection.

12. The use according to claim 11, wherein a third biomarker or a detection agent that specifically binds to said third biomarker is additionally used, said third biomarker being sFlt1, cystatin C or MR-proADM.

13. 1. A kit for evaluating a subject suspected of having an infectious disease, comprising a detection agent that specifically binds to a first biomarker, where the first biomarker is DLL1, and a detection agent that specifically binds to a second biomarker, where the second biomarker is GDF15, and optionally the kit further comprises a detection agent that specifically binds to a third biomarker, where the third biomarker is sFlt1, cystatin C, or MR-proADM.

14. 1. A method for monitoring a subject, comprising: (a) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of a third biomarker referred to herein (i.e., sFlt1, Cystatin C, or MR-proADM) in a first sample from said subject, and optionally calculating a first score based on said determined amounts; (b) determining the amount of DLL1, the amount of GDF-15, and optionally the amount of said third biomarker in a second sample from said subject, and optionally calculating a second score based on said determined amounts; (c) c1) the first score versus the second score; or c2) the amount of DLL1, GDF-15, and optionally the third biomarker in said second sample versus the amount of DLL1, GDF-15, and optionally the third biomarker in said first sample. and comparing As a result, Monitoring the subject.

15. 1. The use of i) a first biomarker that is DLL1 and a second biomarker that is GDF15, or ii) a detection agent that specifically binds to the first biomarker and a detection agent that specifically binds to the second biomarker, for monitoring a subject suffering from or suspected of suffering from an infectious disease.

16. The use according to claim 15, wherein a third biomarker or a detection agent that specifically binds to said third biomarker is additionally used, said third biomarker being sFlt1, cystatin C or MR-proADM.

17. The method, device, use or kit according to any one of claims 1 to 16, wherein said assessment is an assessment of the risk of developing sepsis.

18. 18. The method, device, use or kit according to any one of claims 1 to 17, wherein the risk of developing sepsis within 48 hours is predicted.

19. The method, use, device or kit of any one of claims 1 to 18, wherein said assessment is a prediction of the risk of the subject's condition worsening.

20. 20. The method, use, device or kit of claim 19, wherein 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 the 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 of admission, if the subject is readmitted within 30 days of discharge, if the subject experiences organ dysfunction or failure, e.g. as measured by SOFA score, and / or if the subject requires organ assistance.

21. 21. The method, use, device or kit of claim 19 or 20, wherein the 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.

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