Markers for predicting severity

Abstract

Methods of determining the severity of an infectious disease, including ruling in sepsis, based on expression level of ANG-2.

Description

[0001] MARKERS FOR PREDICTING SEVERITY

[0002] RELATED APPLICATION

[0003] This application claims the benefit of priority of U.S. Provisional Patent Application No. 63 / 792,382 filed on April 22, 2025, the contents of which are incorporated herein by reference in their entirety.

[0004] FIELD AND BACKGROUND OF THE INVENTION

[0005] The present invention, in some embodiments thereof, relates to the identification of signatures and determinants associated with determining or predicting severity of bacterial and viral infections.

[0006] Risk assessment is one of the most important tasks in management of infectious disease patients. Complement to determining infection etiology, predicting patient prognosis may affect various aspects of patient management including treatment, diagnostic tests (e.g., microbiology, blood chemistry, radiology etc.), monitoring and admission. Timely identification of patients with higher chance for poor prognosis may result in more aggressive patient management procedures including for example, intensive care unit (ICU) admission, advanced therapeutics, invasive diagnostics or surgical intervention, which could reduce complications and mortality. Conversely, timely identification of patients with lower chance for poor prognosis may result in less aggressive patient management procedures such as discontinuation of drugs or treatment, discharge, etc.

[0007] Additional background art includes WO 2013 / 117746, WO 2016 / 024278, W02018 / 060998, W02018 / 060999 and W02024 / 018470.

[0008] SUMMARY OF THE INVENTION

[0009] According to an aspect of the invention there is provided a method of determining the severity of an infectious disease in a subject comprising:

[0010] (a) measuring, in a blood sample of the subject, an expression level of Angiogpoietin-2 (ANG-2);

[0011] (b) generating a score on the basis of the expression level, wherein the score incorporates at least one additional feature selected from the group consisting of age, number of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology; and

[0012] (c) determining the severity of the infectious disease based on the score, thereby determining the severity of the infectious disease of the subject. According to embodiments of the invention, the determining comprises predicting the likelihood of severity.

[0013] According to embodiments of the invention, the determining comprises predicting the likelihood of non-severity.

[0014] According to embodiments of the invention, the comorbidities are selected from the group consisting of hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD.

[0015] According to embodiments of the invention, the score incorporates an indicator of viral etiology.

[0016] According to embodiments of the invention, the score incorporates at least one parameter set forth in Tables B or C.

[0017] According to embodiments of the invention, the score incorporates a clinical index selected from the group consisting of NEWS, NEWS 2, MEWS APACHE I, APACHE II, APACHE III, CURB-65, SMART-COP, SAPS II, SAPS III, SIRS, Shock Index, Phoenix Sepsis Score, ESI, PIM2, CMM, SOFA, qSOFA, MPM, RIFLE, CP, MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukee criteria and Ranson criteria.

[0018] According to embodiments of the invention, the clinical index is NEWS or qSOFA,

[0019] According to embodiments of the invention, the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

[0020] According to embodiments of the invention, the score provides an indication of the likelihood of at least one of the following outcomes:

[0021] (a) respiratory failure within three days from blood draw;

[0022] (b) septic shock within three days from blood draw;

[0023] (c) renal failure within three days from blood draw; or

[0024] (d) mortality within 14 days from blood draw.

[0025] According to embodiments of the invention, an increase in an expression of each of the ANG-2 above a corresponding expression level in a control sample is indicative of a higher severity of the infectious disease.

[0026] According to embodiments of the invention, the method further comprises measuring an expression of at least one additional protein selected from the group consisting of Interferon gamma- induced protein 10 (IP- 10), Interleukin 1 receptor- like 1 (ST2), Tumor necrosis factorinducible gene 14 protein (TSG-14), Advanced glycosylation end product- specific receptor (RAGE), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor receptor superfamily member 10B (DR5), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) and Mid- regional proadrenomedullin (MR-proADM) and incorporating the expression into the score.

[0027] According to embodiments of the invention, the at least one additional protein is IP- 10.

[0028] According to embodiments of the invention, the weight of the IP- 10 in the score is increased on inclusion of a positive indicator of the viral etiology.

[0029] According to embodiments of the invention, the expression of no more than four of the at least one additional protein is incorporated into the score.

[0030] According to embodiments of the invention, the severity is stratified according to at least three levels.

[0031] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0032] According to embodiments of the invention, the subject does not show symptoms of an infectious disease.

[0033] According to embodiments of the invention, the subject does not have a chronic non- infectious disease.

[0034] According to embodiments of the invention, the blood sample is whole blood or a fraction thereof.

[0035] According to embodiments of the invention, the fraction comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

[0036] According to embodiments of the invention, the fraction comprises serum or plasma.

[0037] According to an aspect of the invention there is provided a method of treating a subject having an infectious disease comprising:

[0038] (a) determining the severity of the infection according to the methods described herein; and

[0039] (b) treating the subject according to the diagnosis of the infection.

[0040] According to embodiments of the invention, when a severe infection is ruled in, at least one of the following treatments is used: hospitalization, placement in intensive care, mechanical ventilation; non-invasive ventilation, ECMO, renal replacement therapy, cardiac catheterization, Antibiotic treatment, vasopressor therapy, oxygen therapy, surgical intervention, anti-viral drug, immunomodulators drugs, monoclonal antibodies, infusion of blood products, glucocorticoid therapy and / or treatment of last resort.

[0041] According to embodiments of the invention, when respiratory failure is ruled in for the subject, the subject is treated using Invasive Mechanical Ventilation (IMV). According to embodiments of the invention, when septic shock is ruled in for the subject, the subject is administered with a vasopressor.

[0042] According to embodiments of the invention, when renal organ failure is ruled in for the subject, the subject is treated with Renal Replacement Therapy (RRT).

[0043] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0044] According to embodiments of the invention, the symptoms comprise fever.

[0045] According to an aspect of the invention there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0046] (a) measuring an expression level of ANG-2 in a blood sample of the suspect subject; and

[0047] (b) ruling in the sepsis or septic shock when the expression level of ANG-2 is above a predetermined amount.

[0048] According to an aspect of the invention there is provided a method of ruling out sepsis or septic shock in a suspect subject comprising:

[0049] (a) measuring an expression level of ANG-2 in a blood sample of the suspect subject; and

[0050] (b) ruling out the sepsis or septic shock when the expression level of ANG-2 is below a predetermined amount.

[0051] According to embodiments of the invention, the suspect subject has a fever.

[0052] According to embodiments of the invention, the suspect subject has a qSOFA score > 2.

[0053] According to embodiments of the invention, the suspect subject has a qSOFA score < 2.

[0054] According to embodiments of the invention, the suspect subject fulfils at least one criteria of SIRS (Systemic Inflammatory Response Syndrome).

[0055] According to embodiments of the invention, the method further comprises measuring an expression of at least one additional protein selected from the group consisting of ST2, IP- 10, Tumor necrosis factor- inducible gene 14 protein (TSG-14), Advanced glycosylation end productspecific receptor (RAGE), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor receptor superfamily member 10B (DR5), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) and MR-proADM.

[0056] Unless otherwise defined, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and / or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.

[0057] DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

[0058] The present invention, in some embodiments thereof, relates to the identification of signatures and determinants associated with predicting or determining severity of bacterial and viral infections.

[0059] Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details set forth in the following description or exemplified by the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.

[0060] Through extensive clinical studies, the present inventors have identified a particular protein present in the blood, whose level serves as a highly accurate marker for predicting disease severity - ANG-2. Using machine learning, the present inventors have developed an algorithm that considers the expression of this protein together with other parameters to generate a score that enables users to easily assess the severity of the infection and make appropriate prognosis, diagnosis and treatment decisions. Prediction of severity may be carried out in the absence of a confirmed diagnosis of an infection and in the absence of knowledge of the source of the infection.

[0061] Whilst further reducing the invention to practice, the present inventors uncovered that ANG-2 is capable of independently ruling in and ruling out sepsis (or septic shock) in patients with a high degree of accuracy, and ruling in and ruling out severe outcome for suspected sepsis patients.

[0062] Thus, according to another aspect of the invention, there is provided a method of determining the severity of an infectious disease in a subject comprising:

[0063] (a) measuring, in a blood sample of the subject, an expression level of Angiogpoietin-2 (ANG-2);

[0064] (b) generating a score on the basis of the expression level, wherein the score incorporates at least one additional feature selected from the group consisting of age, number of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology; and

[0065] (c) determining the severity of the infectious disease based on the score, thereby determining the severity of the infectious disease of the subject.

[0066] Information regarding ANG-2 and other relevant protein markers which may also be incorporated into the score are provided in Table A, herein below (based on release 2025_01 of UniProtKB, published on Wed Feb 05 2025). Table A

[0067] In one embodiment, the expression level of ANG-2 is used to rule in a severe infection or rule in a non-severe infection. Additionally, or alternatively, the expression level of ANG-2 is used to rule out a severe infection or rule out a non-severe infection. The expression level of ANG- 2 is increased in severe infection as compared to non-severe infection as further detailed herein below. In some embodiments, the expression level of ANG-2 used to rule in a severe viral infection or rule out a severe viral infection.

[0068] Additionally, or alternatively, the expression level ANG-2 is used to rule in a non- severe viral infection or rule out a non- severe viral infection.

[0069] In some embodiments, the expression level of ANG-2 is used to rule in a severe bacterial infection or rule out a severe bacterial infection.

[0070] Additionally, or alternatively, the expression level of ANG-2 is used to rule in a non-severe bacterial infection or rule out a non-severe bacterial infection. When the level of ANG-2 is above a predetermined amount, a severe bacterial or viral infection may be ruled in.

[0071] The predetermined level is the amount (i.e., level or concentration) of (or a function of the amount of) the protein in a control sample derived from one or more subjects who do not have an infection (i.e., healthy, and or non-infectious individuals) or who do not have a severe infection (i.e., subjects who have a non-severe infection). In a further embodiment, such subjects are monitored and / or periodically retested for a diagnostically relevant period of time (“longitudinal studies”) following such test to verify continued absence of infection. Such period of time may be one day, two days, two to five days, five days, five to ten days, ten days, or ten or more days from the initial testing date for determination of the reference value. Furthermore, retrospective measurement of protein levels in properly banked historical subject samples may be used in establishing these reference values, thus shortening the study time required.

[0072] A reference value can also comprise the amounts of proteins derived from subjects who show an improvement as a result of treatments and / or therapies for the infection. A reference value can also comprise the amounts of proteins derived from subjects who have confirmed infection by known techniques.

[0073] According to another embodiment, when the expression level of ANG-2 is below about 1800 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for ANG-2 that may be used below which a severe infection is ruled out include below about 2646 pg / ml, below about 2300 pg / ml, below about 2000 pg / ml or below about 1800 pg / ml.

[0074] Other exemplary thresholds for ANG-2 that may be used below which a severe infection is ruled out include below about 1500 pg / ml, below about 1300 pg / ml, below about 1100 pg / ml or below about 900 pg / ml.

[0075] According to another embodiment, when the expression level of ANG-2 is above about 5000 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for ANG-2 that may be used above which a severe infection is ruled in include above about 7,000 pg / ml, above about 8,000 pg / ml or above about 9,000 pg / ml. Other exemplary thresholds for ANG-2 that may be used above which a severe infection is ruled in include above about 6695 pg / ml, above about 7500 pg / ml, above about 7800 pg / ml, above about 8500 pg / ml, above about 9500 pg / ml, above about 10,000 pg / ml, above about 15,000 pg / ml.

[0076] According to still another embodiment, when the expression level of ANG-2 is increased by at least two fold or 1.9 fold over the baseline of ANG-2 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0077] For all the aspects described herein, the term “determining the severity” refers to assignment of the severity of the disease which may in one embodiment, relate to the probability to experience certain adverse events (e.g. death, hospitalization or admission to ICU) to an individual. Thus, the determination / classification may also be used to prognose the outcome of a patient with an infectious disease. Classifying the severity of the disease may be affected on a binary level (severe / non- severe) or may be effected on non-binary level (e.g. based on numerical values, such as severity categories 1, 2, 3, 4, 5 etc.).

[0078] According to a specific embodiment, a severe infectious disease is one in which at least one of the following outcomes is predicted to be required for treatment or to occur:

[0079] (a) respiratory failure within three days from blood draw;

[0080] (b) septic shock within three days from blood draw;

[0081] (c) renal failure within three days from blood draw; or

[0082] (d) mortality within 14 days from blood draw.

[0083] According to a specific embodiment, determination of severity of the infectious disease (or likelihood of outcome) is affected on the basis of a score which is categorized into 2, 3, 4, 5 or more discrete interpretation bins. The bins may represent different levels of risk based on the likelihood of meeting one or more of the above-mentioned outcomes.

[0084] The number of bins may be selected such that the kit has a rule-out threshold of equal or greater than 90 % sensitivity and a rule-in threshold of equal or greater than 80 % specificity.

[0085] According to a particular embodiment, the score is categorized into 5 bins. For example, the rule out sensitivity may be 97 %, 90% and the rule-in specificity may be 95 %, 80 %.

[0086] The bins may serve as risk stratification categories, helping clinicians interpret the severity of a patient's condition. Such risk stratification categories may serve for guiding treatment, as further described herein below.

[0087] In one embodiment, a higher bin number corresponds to an increased probability of experiencing one or more of these severe outcomes. In another embodiment, a lower bin number corresponds to an increase probability of experiencing one or more of these severe outcomes. This type of stratification allows for more actionable decision-making, guiding interventions based on risk level.

[0088] In another embodiment, the severity can be classified according to the WHO ordinal scale of disease stratification, NEWS (National Early Warning Score), NEWS2, SOFA (Sequential Organ Failure Assessment) score, qSOFA (Quick SOFA) and SIRS score,

[0089] In one embodiment, the term “severe” refers to an infection that will have at least one of the following outcomes: will require vasopressor therapy, will require intubation with mechanical ventilation, will require non-invasive ventilation, will be admitted to the intensive care unit and / or predicted to die within 14 days from blood draw.

[0090] In one embodiment, the prediction is accurate on the same day as blood draw.

[0091] In another embodiment, the prediction of severity is accurate on the day after blood draw.

[0092] In still another embodiment, the prediction of severity is accurate for the second and third day following blood draw.

[0093] In still another embodiment, the prediction of severity is accurate from the fourth day following blood draw. This provides particularly useful information since it predicts a longer term prognosis of the subject.

[0094] The term “non- severe”, in one embodiment, refers to an infection that will not require vasopressor therapy, will not require intubation with mechanical ventilation, will not require non- invasive ventilation, will not require admission to the intensive care unit and / or will not cause death within 14 days of blood draw.

[0095] It will be appreciated that the score may incorporate the expression level of different blood proteins including but not limited to Tumor necrosis factor- inducible gene 14 protein (TSG-14), Advanced glycosylation end product- specific receptor (RAGE), Interleukin-6 (IE-6), Interleukin- 10 (IE- 10), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF) -related apoptosis inducing ligand (TRAIL) and MR-proADM. Details of the above-described markers may be found in Table A and in PCT Application No. W02024 / 018470, the contents of which are incorporated herein by reference.

[0096] According to a particular embodiment, the score incorporates the expression level of at least one of IP- 10, ST2, IL- 10, IL-6, TRAIL, CRP or DR5.

[0097] When the expression level of ST2 is below about 28,000 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for ST2 that may be used below which a severe infection is ruled out include below about 23,000, below about 22,000 pg / ml, below about 20,000 pg / ml or below about 15,000 pg / ml. Other exemplary thresholds for ST2 that may be used below which a severe infection is ruled out include below about 21,000 pg / ml, below about 18,000 pg / ml, below about 16,000 pg / ml or below about 14,000 pg / ml.

[0098] According to another embodiment, when the expression level of IP- 10 is below about 100 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for IP- 10 that may be used below which a severe infection is ruled out include below about 95 pg / ml, below about 90 pg / ml, below about 85 pg / ml or below about 80 pg / ml.

[0099] According to another embodiment, when the expression level of ST2 is above about 140,000 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for ST2 that may be used above which a severe infection is ruled in include above about 138, 000 pg / ml, above about 150,000 pg / ml, above about 170,000 pg / ml or above about 200,000 pg / ml.

[0100] Other exemplary thresholds for ST2 that may be used above which a severe infection is ruled in include above about 180,000 pg / ml, above about 230,000 pg / ml, above about 390,000 pg / ml, above about 500,000 pg / ml, above about 770,000 pg / ml.

[0101] According to still another embodiment, when the expression level of ST2 is increased by at least three or four fold over the baseline of ST2 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0102] According to another embodiment, when the expression level of IP- 10 is above about 1000 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for IP- 10 that may be used above which a severe infection is ruled in include above about 1050 pg / ml, above about 1100 pg / ml or above about 1200 pg / ml.

[0103] According to still another embodiment, when the expression level of IP- 10 is increased by at least 4 fold over the baseline of IP- 10 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0104] According to another embodiment, when the expression level of DR5 is below about 145 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for DR5 that may be used below which a severe infection is ruled out include below about 120 pg / ml, below about 110 pg / ml or below about 100 pg / ml.

[0105] According to another embodiment, when the expression level of IL- 10 is below about 7 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for IL- 10 that may be used below which a severe infection is ruled out include below about 5 pg / ml, 4 pg / ml, below about 3 pg / ml or below about 2 pg / ml. According to another embodiment, when the expression level of IL-6 is below about 12 pg / ml, a severe infectious disease is ruled out. Other exemplary thresholds for IL-6 that may be used below which a severe infection is ruled out include below about 9.5 pg / ml, below about 9.0 pg / ml, below about 8.5 pg / ml or below about 8 pg / ml.

[0106] Another exemplary threshold for IL-6 that may be used below which a severe infection is ruled out is below about 40 pg / ml.

[0107] Other exemplary thresholds for IL-6 that may be used below which a severe infection is ruled out include below about 7 pg / ml, below about 6 pg / ml, below about 5 pg / ml or below about 4 pg / ml.

[0108] According to another embodiment, when the expression level of DR5 is above about 315 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for DR5 that may be used above which a severe infection is ruled in include above about 300 pg / ml, above about 350 pg / ml or above about 400 pg / ml.

[0109] According to still another embodiment, when the expression level of DR5 is increased by at least 1.8 fold over the baseline of DR5 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0110] According to another embodiment, when the expression level of IL- 10 is above about 68 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for IL- 10 that may be used above which a severe infection is ruled in include above about 50 pg / ml, above about 55 pg / ml or above about 60 pg / ml or above about 44 pg / ml.

[0111] Other exemplary thresholds for IL- 10 that may be used above which a severe infection is ruled in include above about 40 pg / ml, above about 70 pg / ml, above about 80 pg / ml, above about 90 pg / ml, above about 100 pg / ml, above about 110 pg / ml.

[0112] According to still another embodiment, when the expression level of IL- 10 is increased by at least three fold over the baseline of IL- 10 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0113] According to another embodiment, when the expression level of IL-6 is above about 230 pg / ml, a severe infectious disease is ruled in. Other exemplary thresholds for IL-6 that may be used above which a severe infection is ruled in include above about 240 pg / ml, above about 245 pg / ml or above about 250 pg / ml. Other exemplary thresholds for IL-6 that may be used above which a severe infection is ruled in include above about 56 pg / ml, above about 260 pg / ml, above about 280 pg / ml, above about 300 pg / ml, above about 350 pg / ml, above about 400 pg / ml, above about 500 pg / ml.

[0114] According to still another embodiment, when the expression level of IL-6 is increased by at least two fold or by 4.5 fold over the baseline of IL-6 (e.g. when the subject has a non-severe infection, or when the subject is healthy or when the subject is non-infectious), a severe infection may be ruled in.

[0115] Additional factors that can be incorporated into the score for classifying severity include epidemiological and demographic information, clinical data, symptom assessment, radiology and imaging data, medication data, procedural data, dynamic and time-series data and traditional laboratory results.

[0116] Exemplary factors that can be incorporated into the score for determining / predicting severity of infection include at least one of the following:

[0117] 1. number of comorbidities (e.g. the number of diseases selected from the group consisting of hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD),

[0118] 2. heart rate,

[0119] 3. mean arterial pressure (e.g. a weighted average of systolic and diastolic blood pressure),

[0120] 4. respiratory rate,

[0121] 5. indicator of a viral infection etiology,

[0122] 6. indicator of a bacterial infection etiology,

[0123] 7. Number of SIRS criteria met

[0124] 8. Risk assessment scores: indicator of meeting two or more SIRS, qSOFA, ESI, Shock index and CURB -65 criteria,

[0125] 9. NEWS / NEWS2 clinical score

[0126] 10. indicator on the source of infection (e.g., when subject is known to have a lower respiratory tract infection).

[0127] 11. Complete blood count

[0128] 12. Metabolic panel

[0129] 13. Blood gases

[0130] 14. Patient medical history including the need for past ventilation / ICU admission

[0131] 15. Need for recent hospitalization

[0132] 16. Imaging data According to a particular embodiment ANG-2 is measured in combination with IP- 10. With respect to the indicator as to whether a subject has a viral etiology, the present inventors contemplate that the weight of IP- 10 in the score may increase upon input that the infection of the subject is of a viral etiology, as compared to a lack of knowledge as to the etiology of the disease or compared to a situation whereby it is known that the infection of the subject is of a bacterial etiology.

[0133] Additional factors that can be incorporated into the score are summarized in Table B or C, herein below.

[0134] In one embodiment at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 of the clinical parameters disclosed in Tables B or C are combined with the above disclosed signature for predicting severity.

[0135] Table B

[0136]

[0137] Table C Table D, herein below indicates the association of exemplary clinical parameters with severity.

[0138] Table D

[0139] According to a specific embodiment, the above disclosed scores (i.e., based on the ANG- 2 and the at least one additional feature selected from the group consisting of age, number of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology) are used to provide a risk assessment of the subject.

[0140] The term “risk assessment” refers to assignment of a likelihood to experience certain adverse events (e.g., death, hospitalization, acute organ failure or admission to ICU) to an individual. Hereby, the individual may preferably be accounted to a certain risk category, wherein categories comprise for instance high risk versus low risk, or risk categories based on numeral values, such as risk category 1, 2, 3, etc.

[0141] The risk assessment may be made in the hospital, for example in the emergency department of a hospital and may be part of a triaging of the subject. On the basis of the expression level of at least one of the above disclosed proteins, a decision may be made on which patient to attend to first.

[0142] Emergency departments (ED) are progressively overwhelmed by patients with both urgent and non-urgent problems. This leads to overfilled ED waiting rooms with long waiting times, detrimental outcomes and unsatisfied patients. As a result, patients needing urgent care may not be treated in time, whereas patients with non-urgent problems may unnecessarily receive expensive and dispensable treatments. Time to effective treatment is among the key predictors for outcomes across different medical conditions. For these reasons, the present inventors propose expression analysis of the presently disclosed proteins in a risk stratification system in the ED as an initial triage of medical patients.

[0143] Thus, for example, the levels of ANG-2 may be used together with triage systems for patient and resources allocation such as Emergency Severity Index (ESI), Electronic triage tools such as EPIC, vital signs (heart and respiratory rate, temperature, 02 saturation, general appearance), SIRS, qSOFA, SOFA, Manchester Triage System (MTS), NEWS, NEWS2, MEWS, APACHE II, Glasgow Coma Scale (GCS), Charlson Comorbidity Index (CCI), Mortality in Emergency Department Sepsis (MEDS) Score, EMR sepsis alert, Phoenix Sepsis Score, CURB-65 or Canadian Triage Acuity Scale (CT AS).

[0144] In another embodiment, the risk assessment is made in the intensive care unit, ward, Stepdown unit or post-OP of a hospital.

[0145] The risk measurement may be used to determine a management course for the patient. The risk measurement may aid in selection of treatment priority and also site-of-care decisions (i.e. outpatient vs. inpatient management) and early identification and organization of post-acute care needs.

[0146] When a patient has been assessed as being at high risk, the management course is typically more aggressive than if he had not been assessed as being at high risk. Thus, treatment options such as mechanical ventilation, life support, vasopressor or Inotropic support, catheterization, renal replacement therapies, supportive care (e.g., oxygen, fluids, etc.), initiation of sepsis bundle / treatment protocols, start antibiotic treatment or broad spectrum Abx, hemofiltration non-invasive high monitoring, invasive and continuous monitoring, sedation, intensive care admission, surgical intervention, drug of last resort, referral to other medical center, initiation of treatment bundles such as SEP-1, treatment with Steroids and hospital admittance may be selected which may otherwise not have been considered the preferred method of treatment if the patient had not been assessed as being at high risk.

[0147] The risk analysis may be carried out together with at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine or at least ten parameters of a clinical index of the subject and providing a risk score based on the clinical index.

[0148] In one embodiment, the risk analysis is carried out together with all the parameters of a clinical index of the subject.

[0149] Exemplary clinical indices include but are not limited to Acute Physiology and Chronic Health Evaluation (APACHE II) as a measure of how likely is the patient to make it out of intensive care unit; Simplified Acute Physiology (SAP) score; Glasgow Coma Score (GCS) as an assessment of consciousness; Sequential Organ Failure Assessment (SOFA) score as an assessment of person's organ function or rate of failure; qSOFA (Quick SOFA) Score for Sepsis- identifies high-risk patients for in-hospital mortality with suspected infection outside the ICU; CURB-65 Score for Pneumonia Severity (confusion, uremia, respiratory rate, blood pressure, age > 65 years) - estimates mortality of community-acquired pneumonia to help determine inpatient vs. outpatient treatment; National Early Warning Score (NEWS)- determines the degree of illness of a patient and prompts critical care intervention; Modified Early Warning Score (MEWS) for Clinical Deterioration- determines the degree of illness of a patient National Early Warning Score (NEWS) 2- Determines the degree of illness of a patient and prompts critical care intervention; EMR sepsis alert- an automated notification within electronic medical records that monitors patient data for signs of sepsis, such as abnormal vital signs or lab results. When specific criteria indicating potential sepsis are met, it alerts healthcare providers to prompt early intervention; SIRS score; Pneumonia Severity Index (PSI); Charlson Comorbidity Index; Apgar Assessment of a newborn's adjustment to life; Pain perception profile; visual analogue scale (VAS); quality of life metrics such as EDLQ, SF36; depression scale such as CES-D; impact of event scale (IES); or thrombosis risk assessment, or trend therein, or combination of above.

[0150] According to one embodiment, the clinical index is NEWS, NEWS 2 and MEWS.

[0151] According to a particular embodiment, the clinical index is Acute Physiology and Chronic Health Evaluation II (APACHE II). This system is an example of a severity of disease classification system that uses a point score based upon initial values of 12 routine physiologic measurements that include: temperature, mean arterial pressure, pH arterial, heart rate, respiratory rate, AaDO2 or PaO2, sodium, potassium, creatinine, hematocrit, white blood cell count, and Glasgow Coma Scale. These parameters are measured during the first 24 hours after admission and utilized in addition to information about previous health status (recent surgery, history of severe organ insufficiency, immunocompromised state) and baseline demographics such as age. An integer score from 0 to 71 is calculated wherein higher scores correspond to more severe disease and a higher risk of death.

[0152] Many other predictive models have been developed for various purposes which are contemplated by the present invention. Such predictive models are used for determining population-based outcome risks. By way of illustration and not as a limitation, a partial list of predictive models comprises SAPS II expanded and predicted mortality, SAPS II and predicted mortality, APACHE I-IV and predicted mortality, SOFA (Sequential Organ Failure Assessment), MODS (Multiple Organ Dysfunction Score), ODIN (Organ Dysfunctions and / or Infection), MPM (Mortality Probability Model), MPM II LODS (Logistic Organ Dysfunction System), TRIOS (Three days Recalibrated ICU Outcome Score), EUROSCORE (cardiac surgery), ONTARIO (cardiac surgery), Parsonnet score (cardiac-surgery), System 97 score (cardiac surgery), QMMI score (coronary surgery), Early mortality risk in redocoronary artery surgery, MPM for cancer patients, POSSUM (Physiologic and Operative Severity Score for the enumeration of Mortality and Morbidity) (surgery, any), Portsmouth POSSUM (surgery, any), IRISS score: graft failure after lung transplantation, Glasgow Coma Score, ISS (Injury Severity Score), RTS (Revised Trauma Score), TRISS (Trauma Injury Severity Score), ASCOT (A Severity Characterization Of Trauma), 24 h-ICU Trauma Score, TISS (Therapeutic Intervention Scoring System), TISS-28 (simplified TISS), PRISM (Pediatric RISk of Mortality), P-MODS (Pediatric Multiple Organ Dysfunction Score), DORA (Dynamic Objective Risk Assessment), PELOD (Pediatric Logistic Organ Dysfunction), PIM II (Paediatric Index of Mortality II), PIM (Paediatric Index of Mortality), CRIB II (Clinical Risk Index for Babies), CRIB (Clinical Risk Index for Babies), SNAP (Score for Neonatal Acute Physiology), SNAP-PE (SNAP Perinatal Extension), SNAP II and SNAPPE II, MSSS (Meningococcal Septic Shock Score), GMSPS (Glasgow Meningococcal Septicaemia Prognostic Score), Rotterdam Score (meningococcal septic shock), Children's Coma Score (Raimondi), Paediatric Coma Scale (Simpson & Reilly), and Pediatric Trauma Score, Rochester criteria, Philadelphia Criteria, Milwaukee criteria, the last three being specific to neonatal fever / sepsis. Of course, the above list of quality of care metrics directed to health risk to the patient is not limiting, and other miscellaneous scores and assessments known in the medical field can be used.

[0153] Classification of subjects into subgroups (e.g. severe / non-severe; high risk, low risk etc.) as performed in aspects of the present invention is preferably done with an acceptable level of clinical or diagnostic accuracy. An "acceptable degree of diagnostic accuracy" is herein defined as a test or assay (such as the test used in some aspects of the invention) in which the AUC (area under the ROC curve for the test or assay) is at least 0.60, desirably at least 0.65, more desirably at least 0.70, preferably at least 0.75, more preferably at least 0.80, and most preferably at least 0.85.

[0154] By a "very high degree of diagnostic accuracy" it is meant a test or assay in which the AUC (area under the ROC curve for the test or assay) is at least 0.75, 0.80, desirably at least 0.85, more desirably at least 0.875, preferably at least 0.90, more preferably at least 0.925, and most preferably at least 0.95.

[0155] Alternatively, the methods may be used to rule in or rule out severity with at least 75% total accuracy, more preferably 80%, 85%, 90%, 95%, 97%, 98%, 99% or greater total accuracy.

[0156] Alternatively, the methods predict the correct management or treatment with an MCC larger than 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 or 1.0.

[0157] On the basis of the classification of the infection, clinical decisions may be made.

[0158] According to some embodiments of the invention, the method further comprises informing the subject of results of the classification.

[0159] As used herein the phrase “informing the subject” refers to advising the subject that based on the diagnosis the subject should seek a suitable treatment regimen. Once the diagnosis and / or likelihood of severe outcome and / or prognosis is determined, the results can be recorded in the subject’s medical file, which may assist in guiding patient management, selecting a treatment regimen and / or determining prognosis of the subject.

[0160] Examples of clinical decisions that may be made in light of a severe classification include oxygen therapy, non-invasive ventilation, mechanical ventilation, invasive monitoring, continuous monitoring, inotropic or vasopressor support, renal replacement therapy, cytokine blood purification, last-resort drug, sedation, intensive care admission, admission to the step-down unit, surgical intervention, hospital admittance, anti-viral drug, antibiotic treatment, anti-viral regimen, anti-fungal drug, fluid resuscitation, vasoactive drugs, immunomodulators drugs, monoclonal antibodies, infusion of blood products, immune-globulin treatment, glucocorticoid therapy, extracorporeal membrane oxygenation, kidney replacement therapy.

[0161] An example of a clinical decision that may be made in light of a non-severe classification may be discharge or refer to a low monitoring setting, remote monitoring, discharge from hospital / outpatient management, discontinuation of drugs or treatment protocols (e.g. 1 hour sepsis bundle).

[0162] • The antiviral drug may be selected from the group consisting of Remdesivir, Ribavirin, Adefovir, Tenofovir, Acyclovir, Brivudin, Cidofovir, Fomivirsen, Foscarnet, Ganciclovir, Penciclovir, Amantadine, Rimantadine, Zanamivir, Molnupiravir, Paxlovid, Oseltamivir phosphate, Ivermectin, Interferon beta, Interferon alfa, Interferon lambda, Nitazoxanide, Hydroxychloroquine, Peramivir, Baloxavir marboxil, Entecavir, lamivudine and Telbivudine.

[0163] • Also contemplated are plasma treatments from infected persons who survived and / or antiHIV drugs such as lopinavir and ritonavir, as well as chloroquine.

[0164] • Specific examples for drugs that are routinely used for the treatment of COVID- 19 include, but are not limited to, Eopinavir / Ritonavir, Nucleoside analogues, Neuraminidase inhibitors, Remdesivir, polypeptide (EK1), abidol, RNA synthesis inhibitors (such as TDF, 3TC), anti-inflammatory drugs (such as hormones and other molecules), Monoclonal antibodies (Ixagevimab plus Cilgavimab (Evusheld), Adrecizumab, Procizumab, Tixagevimab plus cilgavimab (Evusheld)), Chinese traditional medicine, such ShuFengJieDu Capsules and Lianhuaqingwen Capsule, could be the drug treatment options for COVID 19.

[0165] If a severe bacterial infection is ruled in, the subject may be treated with an antibiotic or other antibacterial agents.

[0166] As used herein, the term "antibiotic agent" refers to a group of chemical substances, isolated from natural sources or derived from antibiotic agents isolated from natural sources, having a capacity to inhibit growth of, or to destroy bacteria. Examples of antibiotic agents include, but are not limited to; Amikacin; Amoxicillin; Ampicillin; Azithromycin; Azlocillin; Aztreonam; Aztreonam; Carbenicillin; Cefaclor; Cefepime; Cefetamet; Cefinetazole; Cefixime; Cefonicid; Cefoperazone; Cefotaxime; Cefotetan; Cefoxitin; Cefpodoxime; Cefprozil; Cefsulodin; Ceftazidime; Ceftizoxime; Ceftriaxone; Cefuroxime; Cephalexin; Cephalothin; Cethromycin; Chloramphenicol; Cinoxacin; Ciprofloxacin; Clarithromycin; Clindamycin; Cioxacillin; Co- amoxiclavuanate; Dalbavancin; Daptomycin; Dicloxacillin; Doxycycline; Enoxacin; Erythromycin estolate; Erythromycin ethyl succinate; Erythromycin glucoheptonate; Erythromycin lactobionate; Erythromycin stearate; Erythromycin; Fidaxomicin; Fleroxacin; Gentamicin; Imipenem; Kanamycin; Lomefloxacin; Loracarbef; Methicillin; Metronidazole; Mezlocillin; Minocycline; Mupirocin; Nafcillin; Nalidixic acid; Netilmicin; Nitrofurantoin; Norfloxacin; Ofloxacin; Oxacillin; Penicillin G; Piperacillin; Retapamulin; Rifaxamin, Rifampin; Roxithromycin; Streptomycin; Sulfamethoxazole; Teicoplanin; Tetracycline; Ticarcillin; Tigecycline; Tobramycin; Trimethoprim; Vancomycin; combinations of Piperacillin and Tazobactam; and their various salts, acids, bases, and other derivatives. Anti-bacterial antibiotic agents include, but are not limited to, aminoglycosides, carbacephems, carbapenems, cephalosporins, cephamycins, fluoroquinolones, glycopeptides, lincosamides, macrolides, monobactams, penicillins, quinolones, sulfonamides, and tetracyclines.

[0167] Antibacterial agents also include antibacterial peptides. Examples include but are not limited to abaecin; andropin; apidaecins; bombinin; brevinins; buforin II; CAP18; cecropins; ceratotoxin; defensins; dermaseptin; dermcidin; drosomycin; esculentins; indolicidin; LL37; magainin; maximum H5; melittin; moricin; prophenin; protegrin; and or tachyplesins.

[0168] If a severe infection is ruled in, the subject may be treated with an immunomodulatory drugs. As used herein, the term "immunomodulatory drug" refers to a group of chemical substances, isolated from natural sources or derived from immunomodulatory agents isolated from natural sources, having the capacity to modulate the immune system's response by enhancing or suppressing its activity. Examples of antibiotic immunomodulatory include, but are not limited to; Thalidomide (Thalomid), Lenalidomide (Revlimid), Pomalidomide (Pomalyst / Imnovid), Interferon Alfa, Interferon Beta (Avonex, Betaseron, Rebif), Interferon Gamma- lb (Actimmune), Glatiramer Acetate (Copaxone), Fingolimod (Gilenya), Teriflunomide (Aubagio), Dimethyl Fumarate (Tecfidera), Natalizumab (Tysabri), Vedolizumab (Entyvio), Ustekinumab (Stelara), Secukinumab (Cosentyx), Adalimumab (Humira), Etanercept (Enbrel), Infliximab (Remicade), Rituximab (Rituxan / MabThera), Abatacept (Orencia), Tocilizumab (Actemra / RoActemra), Anakinra (Kineret), Baricitinib (Olumiant), Tofacitinib (Xeljanz), Upadacitinib (Rinvoq), Belimumab (Benlysta), Eculizumab (Soliris), Alemtuzumab (Campath / Lemtrada), Ocrelizumab (Ocrevus), Ipilimumab (Yervoy), Nivolumab (Opdivo), Pembrolizumab (Keytruda), Atezolizumab (Tecentriq), Daratumumab (Darzalex), Siltuximab (Sylvant), Ixekizumab (Taltz), Guselkumab (Tremfya), Sarilumab (Kevzara), Dupilumab (Dupixent), Mepolizumab (Nucala), Reslizumab (Cinqair / Cinqaero), Benralizumab (Fasenra), Omalizumab (Xolair), Basiliximab (Simulect), Belatacept (Nulojix), Canakinumab (Haris), Denosumab (Prolia / Xgeva), Tildrakizumab (Ilumya), Risankizumab (Skyrizi), Pimecrolimus (Elidel), Tacrolimus (Prograf / Protopic), Cyclosporine (Neoral / Sandimmune), Sirolimus (Rapamune), Everolimus (Zortress / Certican), Azathioprine (Imuran), Methotrexate, Mycophenolate Mofetil (CellCept), Leflunomide (Arava), Cyclophosphamide, Hydroxychloroquine (Plaquenil), Sulfasalazine, Bortezomib (Velcade), Carfilzomib (Kyprolis), Ixazomib (Ninlaro), Blinatumomab (Blincyto), Romidepsin (Istodax), Rilonacept (Arcalyst), Emapalumab (Gamifant), Anifrolumab (Saphnelo), Ozanimod (Zeposia), Siponimod (Mayzent), Cladribine (Mavenclad), Diroximel Fumarate (Vumerity), Luspatercept (Reblozyl), Satralizumab (Enspryng), Efgartigimod (Vyvgart), Sutimlimab (Enjaymo), Peginterferon Beta-la (Plegridy), Ofatumumab (Kesimpta), Sipuleucel-T (Provenge), Voclosporin (Lupkynis), and Avacopan (Tavneos).

[0169] If a severe infection is ruled in or vascular dysfunction is diagnosed, the subject may be treated with vasoactive drugs. As used herein, the term "vasoactive drug" refers to a group of chemical substances, isolated from natural sources or derived from vasoactive agents isolated from natural sources, having the capacity to affect the tone and diameter of blood vessels, thereby influencing blood pressure and blood flow. Examples of vasoactive drugs include, but are not limited to; Epinephrine (Adrenaline), Norepinephrine (Noradrenaline, Levophed), Dopamine, Dobutamine, Phenylephrine, Isoproterenol (Isoprenaline), Vasopressin (Antidiuretic Hormone, ADH), Angiotensin II (Giapreza), Midodrine, Methyldopa, Clonidine, Terbutaline, Oxymetazoline, Xylometazoline, Desmopressin (DDAVP), Histamine Phosphate, Octopamine, Phenylpropanolamine, Pseudoephedrine, Amphetamine and derivatives (e.g., Dextroamphetamine, Methamphetamine), Methylphenidate, Tyramine, Serotonin (5- Hydroxytryptamine) and analogs like Sumatriptan, Dihydroergotamine, Ergotamine, Droxidopa (Northera), Phenelzine, Tranylcypromine, Levodopa, and Atomoxetine (Strattera).

[0170] Once the classifications are made, additional tests may be made in order to corroborate the result or to further classify the infectious agent.

[0171] Examples of such tests include PCR analysis, sequencing analysis, viral culture, antibody or antigen testing.

[0172] Particular actions that may be carried out once a severe bacterial infection is ruled in are summarized below: Blood Cultures and Antibiotic Susceptibility Testing (AST): Obtain blood cultures to identify the causative organism and perform AST to tailor antibiotic therapy effectively.

[0173] Optimized Antibiotic Therapy: Use the tool's risk assessment to select the most effective antibiotics, adjust dosages, or switch to broader- spectrum agents as needed.

[0174] Enhanced Source Control: Prompt initiation of procedures to eliminate the infection source, such as drainage or debridement.

[0175] Diagnostic Imaging: Order targeted imaging studies to locate occult bacterial sources based on risk indicators.

[0176] Infection Isolation Protocols: Implement appropriate isolation measures to prevent nosocomial spread.

[0177] Particular actions that may be carried out once a severe viral infection is ruled in are summarized below:

[0178] Viral Panel Testing: Order comprehensive viral panels to identify the specific viral pathogen involved.

[0179] Treatment with Immunomodulators: Initiate immunomodulatory therapies when appropriate to modulate the immune response to the viral infection.

[0180] Antiviral Treatment Initiation: Start antiviral medications promptly when the tool indicates a high risk of viral infection.

[0181] Avoidance of Unnecessary Antibiotics: Reduce antibiotic usage to prevent resistance and side effects when bacterial infection is unlikely.

[0182] Supportive Care Enhancement: Focus on symptom management, hydration, and monitoring for viral complications.

[0183] Public Health Reporting: Notify public health authorities if a contagious viral pathogen is suspected.

[0184] Particular actions that may be carried out once death is predicted are summarized below:

[0185] Aggressive Management Strategies: Intensify therapeutic interventions for patients at high risk of mortality.

[0186] Early Palliative Care Consultation: Engage palliative care services to support patient and family needs.

[0187] Ethical Decision-Making Support: Facilitate discussions about goals of care and advanced directives.

[0188] Particular actions that may be carried out once ICU admission is predicted are summarized below: Proactive ICU Transfer: Expedite admission to intensive care for patients identified as high risk.

[0189] Resource Allocation: Allocate critical care resources efficiently based on risk stratification.

[0190] Enhanced Monitoring: Implement continuous monitoring protocols in the ED while awaiting ICU transfer.

[0191] Particular actions that may be carried out once Invasive mechanical ventilation (IMV) is predicted are summarized below:

[0192] Blood Gas Analysis: Perform arterial blood gas (ABG) tests to assess oxygenation and ventilation status, guiding respiratory support decisions.

[0193] Continuous Monitoring: Implement continuous monitoring of vital signs, oxygen saturation, and end-tidal CO2 to detect early signs of deterioration.

[0194] Early Airway Management: Prepare for potential intubation by assembling necessary equipment and personnel ahead of time.

[0195] Preventative Respiratory Support: Initiate non-invasive ventilation methods when appropriate to delay or prevent the need for IMV.

[0196] Respiratory Therapy Consultation: Involve respiratory specialists early to optimize ventilation strategies and weaning protocols.

[0197] Particular actions that may be carried out once shock is predicted are summarized below:

[0198] Rapid Hemodynamic Support: Begin aggressive fluid resuscitation and vasopressor therapy promptly.

[0199] Advanced Monitoring Techniques: Use central venous pressure monitoring or other invasive methods to guide therapy.

[0200] Multidisciplinary Team Activation: Assemble a team including cardiology and critical care specialists.

[0201] When the time to outcome is predicted for the same day, the following actions may be taken:

[0202] Sepsis Bundle Activation: Immediately initiate sepsis bundle protocols, which may include early administration of broad- spectrum antibiotics, rapid fluid resuscitation, lactate measurement, and source control measures.

[0203] Immediate Intervention Protocols: Prioritize these patients for the fastest possible diagnostic testing and treatment initiation.

[0204] Frequent Clinical Reassessments: Increase the frequency of vital sign monitoring and patient evaluations to quickly identify any changes in condition. Emergency Response Activation: Alert rapid response or code teams to be on standby for potential critical interventions.

[0205] When the time to outcome is predicted for between 2-14 days, the following actions may be taken:

[0206] Ongoing Monitoring: Maintain regular monitoring of vital signs, laboratory results, and clinical observations to detect any signs of improvement or deterioration over this period.

[0207] Repetitive Assessment with Risk Tool: Perform serial assessments using your risk assessment tool at scheduled intervals to track changes in the patient's risk status.

[0208] Adjust Treatment Plans Accordingly: Use insights from repetitive assessments to modify treatment strategies, such as adjusting medications or initiating new interventions.

[0209] Early Detection of Complications: Continuous monitoring allows for prompt identification of potential complications, enabling timely interventions.

[0210] Patient and Family Education: Provide guidance on symptoms to watch for and instructions on when to seek immediate medical attention.

[0211] Care Coordination: Collaborate with multidisciplinary teams, including specialists, nursing staff, and outpatient services, to ensure comprehensive care throughout the extended timeframe.

[0212] Particular action that may be carried out once septic shock is predicted is treatment with vasopressors.

[0213] Particular action that may be carried out once septic shock is predicted is to initiate the sepsis bundle.

[0214] Other actions that may be carried out once septic shock is predicted are as follows:

[0215] • Early antibiotic administration: Initiate within the first hour of recognizing sepsis.

[0216] • Fluid resuscitation protocols: Employ dynamic hemodynamic assessment to guide therapy.

[0217] • Early initiation of vasopressor support: Use agents like norepinephrine or vasopressin if needed.

[0218] • Rapid source control: Identify and manage the infection source promptly.

[0219] • Use of MABs targeting endotoxins: e.g. edobacomab

[0220] Particular action that may be carried out once renal organ failure is predicted is to initiate Renal replacement therapy.

[0221] Other actions that may be carried out once organ failure is predicted are as follows:

[0222] • Organ supportive therapy: Provide interventions like dialysis for kidney failure or mechanical ventilation for respiratory failure. • Serial monitoring: Regularly assess organ-specific laboratory values to detect deterioration.

[0223] • Preventive strategies: Implement measures to protect at-risk organs, such as nephroprotective protocols.

[0224] • Assess need for ECMO (Extracorporeal Membrane Oxygenation): Evaluate extracorporeal membrane oxygenation for severe cardiac or respiratory failure.

[0225] • Use of targeted therapies, including MABs: For example, vilobelimab.

[0226] Particular action that may be carried out once respiratory failure is predicted is to initiate Invasive Mechanical Ventilation (IMV).

[0227] Other actions that may be carried out once respiratory failure is predicted are set forth below:

[0228] • Early use of non-invasive ventilation: Utilize CPAP or BiPAP to support breathing.

[0229] • Prone positioning: Apply for patients at risk of acute respiratory distress syndrome (ARDS).

[0230] • High-flow nasal cannula (HFNC / Vapoterm): Use to prevent intubation in patients with hypoxemia.

[0231] • Continuous monitoring: Perform pulse oximetry and frequent arterial blood gas (ABG) measurements.

[0232] • Intubation and mechanical ventilation: Proceed if non-invasive methods are insufficient.

[0233] • Treatment with immunomodulators: Administer agents like dexamethasone to reduce inflammation.

[0234] • Consider MABs for specific respiratory conditions: For instance, benralizumab has been identified as a potential treatment for asthma and COPD exacerbations.

[0235] Particular actions that may be carried out once the risk of mortality is ruled in include the following:

[0236] • Early aggressive management: Implement protocols like early goal-directed therapy and the Sep-1 bundle to address sepsis and related conditions promptly.

[0237] • Advance care planning discussions: Engage in multidisciplinary rounds with specialists to align treatment with patient goals.

[0238] • Palliative care consultation: Initiate when appropriate to manage symptoms and improve quality of life.

[0239] • Consult ICU for admission: Evaluate the need for intensive care unit admission based on patient severity. • Consider prophylactic anticoagulation: Administer to prevent thromboembolic events in high-risk patients.

[0240] • Administer broad-spectrum antibiotics: Provide as indicated to combat potential infections.

[0241] • Use of monoclonal antibodies: For example, afelimomab, an anti-TNFa monoclonal antibody, has shown a modest mortality benefit in patients with severe sepsis and elevated interleukin-6 levels.

[0242] A “subject” in the context of the present invention may be a mammal (e.g. human, dog, cat, horse, cow, sheep, pig or goat). According to another embodiment, the subject is a bird (e.g. chicken, turkey, duck or goose). According to a particular embodiment, the subject is a human. The subject may be male or female. The subject may be an adult (e.g. older than 18, 21, or 22 years) or a child (e.g. younger than 18, 21 or 22 years or between 3 months and 18 years). In another embodiment, the subject is an adolescent (between 12 and 21 years), an infant (29 days to less than 2 years of age) or a neonate (birth through the first 28 days of life). In still another embodiment, the subject is over 60, 70 or even 80. In still another embodiment, the subject is under 45, between 45-65 or between 65-80.

[0243] The subject of this aspect of the present invention may have symptoms of an infection.

[0244] Exemplary symptoms include, but are not limited to fever, headache, cough, runny nose, chills, muscle aches, loss of taste and / or loss of smell.

[0245] According to a particular embodiment the subject has diabetes.

[0246] According to another embodiment, the subject has cancer.

[0247] According to still another embodiment, the subject has been diagnosed as hypertensive.

[0248] According to other embodiments, the subject is obese, has chronic kidney disease and / or is diagnosed as having COPD.

[0249] According to a particular embodiment, measuring the determinants (i.e. proteins) described herein above is carried out no more than 24 hours following the start of symptoms, no more than 36 hours following the start of symptoms, no more than 48 hours following the start of symptoms, no more than 72 hours following the start of symptoms, no more than 96 hours following the start of symptoms, no more than 1 week following the start of symptoms, or no more than 2 weeks following the start of symptoms.

[0250] According to a particular embodiment, blood is drawn no more than 24 hours following the start of symptoms, no more than 36 hours following the start of symptoms, no more than 48 hours following the start of symptoms, no more than 72 hours following the start of symptoms, no more than 96 hours following the start of symptoms, no more than 1 week following the start of symptoms, or no more than 2 weeks following the start of symptoms.

[0251] In another embodiment, blood is drawn on the same day the patient reaches a severe outcome, one day / 2-3 days / 4-14 days before the patient reaches a severe outcome.

[0252] According to another embodiment, the subject is asymptomatic.

[0253] It will be appreciated, whether symptomatic or asymptomatic, the subject may or may not be contagious.

[0254] In one embodiment, the subject does not have a chronic non-infectious disease such as cancer, a chronic immune disorder or a chronic inflammatory disorder.

[0255] In another embodiment, the subject does not have a coronary disease.

[0256] In one embodiment, the subject is hospitalized.

[0257] In another embodiment, the subject is non-hospitalized.

[0258] According to one embodiment, the subject is suspected of suffering from (or is confirmed as having) SIRS without infection, sepsis, severe sepsis or septic shock.

[0259] Sepsis is a life-threatening condition that is caused by dysregulated response to an infection. The early diagnosis of sepsis is essential for clinical intervention before the disease rapidly progresses beyond initial stages to the more severe stages, such as severe sepsis or septic shock, which are associated with high mortality.

[0260] According to one embodiment, sepsis may be diagnosed as the presence of SIRS criteria in the presence of a known infection. SIRS may be defined as 2 or more of the following variables: fever of more than 38°C (100.4°F) or less than 36°C (96.8°F); heart rate of more than 90 beats per minute; respiratory rate of more than 20 breaths per minute or arterial carbon dioxide tension (PaCO2) of less than 32 mm Hg; abnormal white blood cell count (>12,000 / pL or < 4,000 / pL or >10% immature [band] forms).

[0261] In another embodiment, sepsis is diagnosed in a subject suspected of having an infection and which fulfils 2 or more of the three criteria:

[0262] Respiratory rate greater or equal to 22 / min;

[0263] Altered mentation (e.g. a Glasgow coma score of less than 15);

[0264] Systolic blood pressure lower than or equal to_l OOmmHg.

[0265] Further criteria for diagnosing sepsis are disclosed in Singer et al. 2016, 315(8):801-810 JAMA.

[0266] According to yet another aspect there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0267] (a) measuring an expression level of ANG-2 in a blood sample of the subject; and (b) ruling in the sepsis or septic shock when the expression level of ANG-2 is above a predetermined amount.

[0268] Septic shock is a subset of sepsis in which underlying circulatory and cellular / metabolic abnormalities are profound enough to substantially increase mortality.

[0269] Subjects who are suspected of having sepsis or septic shock typically show signs of infection (e.g. a fever), signs of systemic inflammation, signs of organ dysfunction and / or symptoms of septic shock (e.g. persisting hypotension requiring vasopressors to maintain MAP >65 mm Hg and having a serum lactate level >2 mmol / L (18 mg / dL) despite adequate volume resuscitation).

[0270] In one embodiment, the method is carried out on a subject having ESI<=3, CURB-65>=1 or NEWS>=5.

[0271] In another embodiment, the method is carried out on a subject having a qSOFA score > 2 The qSOFA score consists of three items: Respiratory rate >22 breaths / min, Altered mental status (Glasgow Coma Scale < 15) and Systolic BP <100 mmHg. Details about qSOFA score may be found at mdcalcdot(dot)com / calc / 2654 / qsofa-quick-sofa-score-sepsis.

[0272] In another embodiment, the method is carried out on a subject having a qSOFA score < 2.

[0273] In still another embodiment, the method is carried out on a subject who fulfils at least one or at least two criteria of SIRS (Systemic Inflammatory Response Syndrome). SIRS includes the following criteria: Temperature >38°C or <36°C, Heart rate >90 bpm, Respiratory rate >20 breaths / min or PaCCE <32 mmHg and WBC >12,000 / mm3, <4,000 / mm3, or >10% immature forms. For additional details see for example mdcalcdot(dot)com / calc / 1096 / sirs-sepsis-septic- shock-criteria.

[0274] Ruling in of sepsis or septic shock may be carried out by measuring, in addition to ANG- 2, expression levels of additional proteins, including but not limited to ST2, IP- 10, Tumor necrosis factor- inducible gene 14 protein (TSG-14), Advanced glycosylation end product- specific receptor (RAGE), Interleukin-6 (IE-6), Interleukin- 10 (IE- 10), Tumor necrosis factor receptor superfamily member 10B (DR5), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) and MR- proADM.

[0275] The method further contemplates measuring an expression of ST2 and IP- 10 and generating a score on the basis of an expression of said ST2, ANG-2 and said IP- 10, wherein the score is indicative of a likelihood of sepsis and / or septic shock.

[0276] For any of the aspects disclosed herein, the term “measuring” or “measurement,” or alternatively “detecting” or “detection,” means assessing the presence, absence, quantity or amount (which can be an effective amount) of the determinant within a clinical or subject-derived sample, including the derivation of qualitative or quantitative concentration levels of such determinants.

[0277] Methods of measuring the level of protein determinants are well known in the art and include, e.g., immunoassays based on antibodies to proteins, aptamers or molecular imprints.

[0278] Protein determinants can be detected in any suitable manner, but are typically detected by contacting a sample from the subject with an antibody, which binds the protein determinant and then detecting the presence or absence of a reaction product. The antibody may be monoclonal, polyclonal, chimeric, or a fragment of the foregoing, and the step of detecting the reaction product may be carried out with any suitable immunoassay.

[0279] In one embodiment, the antibody which specifically binds the determinant is attached (either directly or indirectly) to a signal producing label, including but not limited to a radioactive label, an enzymatic label, a hapten, a reporter dye or a fluorescent label.

[0280] Immunoassays carried out in accordance with some embodiments of the present invention may be homogeneous assays or heterogeneous assays. In a homogeneous assay the immunological reaction usually involves the specific antibody (e.g., anti- determinant antibody), a labeled analyte, and the sample of interest. The signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labeled analyte. Both the immunological reaction and detection of the extent thereof can be carried out in a homogeneous solution. Immunochemical labels, which may be employed, include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.

[0281] In a heterogeneous assay approach, the reagents are usually the sample, the antibody, and means for producing a detectable signal. Samples as described above may be used. The antibody can be immobilized on a support, such as a bead (such as protein A and protein G agarose beads), plate, pipette tip or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase.

[0282] The support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal. The signal is related to the presence of the analyte in the sample. Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels. For example, if the antigen to be detected contains a second binding site, an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step. The presence of the detectable group on the solid support indicates the presence of the antigen in the test sample. Examples of suitable immunoassays are oligonucleotides, immunoblotting, immunofluorescence methods, immunoprecipitation, chemiluminescence methods, electrochemiluminescence (ECL) or enzyme-linked immunoassays.

[0283] Those skilled in the art will be familiar with numerous specific immunoassay formats and variations thereof which may be useful for carrying out the method disclosed herein. See generally E. Maggio, Enzyme-Immunoassay, (1980) (CRC Press, Inc., Boca Raton, Fla.); see also U.S. Pat. No. 4,727,022 to Skold et al., titled “Methods for Modulating Ligand-Receptor Interactions and their Application,” U.S. Pat. No. 4,659,678 to Forrest et al., titled “Immunoassay of Antigens,” U.S. Pat. No. 4,376,110 to David et al., titled “Immunometric Assays Using Monoclonal Antibodies,” U.S. Pat. No. 4,275,149 to Litman et al., titled “Macromolecular Environment Control in Specific Receptor Assays,” U.S. Pat. No. 4,233,402 to Maggio et al., titled “Reagents and Method Employing Channeling,” and U.S. Pat. No. 4,230,767 to Boguslaski et al., titled “Heterogenous Specific Binding Assay Employing a Coenzyme as Label.” The determinant can also be detected with antibodies using flow cytometry. Those skilled in the art will be familiar with flow cytometric techniques which may be useful in carrying out the methods disclosed herein (Shapiro 2005). These include, without limitation, Cytokine Bead Array (Becton Dickinson) and Luminex technology.

[0284] According to a specific embodiment, ST2 (and other additional proteins measured together with ST2) is detected by lateral flow immunoassay.

[0285] This is a technology which allows rapid measurement of analytes at the point of care (POC) and its underlying principles are described below. According to one embodiment, LFIA is used in the context of a hand-held device.

[0286] The technology is based on a series of capillary beds, such as pieces of porous paper or sintered polymer. Each of these elements has the capacity to transport fluid (e.g., urine) spontaneously. The first element (the sample pad) acts as a sponge and holds an excess of sample fluid. Once soaked, the fluid migrates to the second element (conjugate pad) in which the manufacturer has stored the so-called conjugate, a dried format of bio-active particles (see below) in a salt-sugar matrix that contains everything to guarantee an optimized chemical reaction between the target molecule (e.g., an antigen) and its chemical partner (e.g., antibody) that has been immobilized on the particle's surface. While the sample fluid dissolves the salt-sugar matrix, it also dissolves the particles and in one combined transport action the sample and conjugate mix while flowing through the porous structure. In this way, the analyte binds to the particles while migrating further through the third capillary bed. This material has one or more areas (often called test lines) where a capture antibody has been immobilized by the manufacturer. By the time the sample-conjugate mix reaches these lines, analyte has been bound on the particle and the 'capture' antibody binds the complex.

[0287] After a while, when more and more fluid has passed the test lines, particles accumulate and the line-area changes color. Typically, there are at least two lines: one (the control) that captures the labeled detection conjugate, independent of analyte presence, and thereby shows that reaction conditions and technology worked fine, the second contains a specific capture molecule and only captures those particles onto which an analyte molecule has been immobilized. After passing these reaction zones the fluid enters the final porous material, the wick (absorbent pad), that simply acts as a waste container. Lateral Flow Tests can operate as either competitive or sandwich assays.

[0288] Different formats may be adopted in LFIA. Strips used for LFIA contain four main components. A brief description of each is given before describing format types.

[0289] Sample application pad: It is made of cellulose and / or glass fiber and sample is applied on this pad to start assay. Its function is to transport the sample to other components of lateral flow test strip (LFTS). The sample pad must enable smooth, continuous, and uniform transport of the sample. Sample application pads are sometimes designed to pretreat the sample before its transportation. This pretreatment may include separation of sample components, removal of interferences, adjustment of pH, etc.

[0290] Conjugate pad: It is the place where labeled biorecognition molecules are dispensed. Material of conjugate pad should immediately release labeled conjugate upon contact with moving liquid sample. Labeled conjugate should stay stable over entire life span of lateral flow strip. Any variations in dispensing, drying or release of conjugate can change results of assay significantly. Poor preparation of labeled conjugate can adversely affect sensitivity of assay. Glass fiber, cellulose, polyesters and some other materials are used to make conjugate pad for LFIA. Nature of conjugate pad material has an effect on release of labeled conjugate and sensitivity of assay.

[0291] Nitrocellulose membrane: It is highly critical in determining sensitivity of LFIA. Nitrocellulose membranes are available in different grades. Test and control lines are drawn over this piece of membrane. An ideal membrane should provide support and good binding to capture probes (antibodies, aptamers etc.). Nonspecific adsorption over test and control lines may affect results of assay significantly, thus a good membrane will be characterized by lesser non-specific adsorption in the regions of test and control lines. Wicking rate of nitrocellulose membrane can influence assay sensitivity. These membranes are easy to use, inexpensive, and offer high affinity for proteins and other biomolecules. Proper dispensing of bioreagents, drying and blocking play a role in improving sensitivity of assay. Adsorbent pad: It works as sink at the end of the strip. It also helps in maintaining flow rate of the liquid over the membrane and stops back flow of the sample. Adsorbent capacity to hold liquid can play an important role in results of assay.

[0292] All these components are fixed or mounted over a backing card. Materials for backing card are highly flexible because they have nothing to do with LFIA except providing a platform for proper assembling of all the components. Thus, backing card serves as a support and it makes easy to handle the strip.

[0293] Major steps in LFIA are (i) preparation of antibody against target analyte (ii) preparation of label (iii) labeling of biorecognition molecules (iv) assembling of all components onto a backing card after dispensing of reagents at their proper pads (v) application of sample and obtaining results.

[0294] Sandwich format: In a typical format, label (Enzymes or nanoparticles or fluorescence dyes) coated antibody or aptamer is immobilized at conjugate pad. This is a temporary adsorption which can be flushed away by flow of any buffer solution. A primary antibody or aptamer against target analyte is immobilized over test line. A secondary antibody or probe against labeled conjugate antibody / aptamer is immobilized at control zone.

[0295] Sample containing the analyte is applied to the sample application pad and it subsequently migrates to the other parts of strip. At conjugate pad, target analyte is captured by the immobilized labeled antibody or aptamer conjugate and results in the formation of labeled antibody conjugate / analyte complex. This complex now reaches at nitrocellulose membrane and moves under capillary action. At test line, label antibody conjugate / analyte complex is captured by another antibody which is primary to the analyte. Analyte becomes sandwiched between labeled and primary antibodies forming labeled antibody conjugate / analyte / primary antibody complex. Excess labeled antibody conjugate will be captured at control zone by secondary antibody. Buffer or excess solution goes to absorption pad. Intensity of color at test line corresponds to the amount of target analyte and is measured with an optical strip reader or visually inspected. Appearance of color at control line ensures that a strip is functioning properly.

[0296] Competitive format: Such a format suits best for low molecular weight compounds which cannot bind two antibodies simultaneously. Absence of color at test line is an indication for the presence of analyte while appearance of color both at test and control lines indicates a negative result. Competitive format has two layouts. In the first layout, solution containing target analyte is applied onto the sample application pad and prefixed labeled biomolecule (antibody / aptamer) conjugate gets hydrated and starts flowing with moving liquid. Test line contains pre-immobilized antigen (same analyte to be detected) which binds specifically to label conjugate. Control line contains pre-immobilized secondary antibody which has the ability to bind with labeled antibody conjugate. When liquid sample reaches at the test line, pre-immobilized antigen will bind to the labeled conjugate in case target analyte in sample solution is absent or present in such a low quantity that some sites of labeled antibody conjugate were vacant. Antigen in the sample solution and the one which is immobilized at test line of strip compete to bind with labeled conjugate. In another layout, labeled analyte conjugate is dispensed at conjugate pad while a primary antibody to analyte is dispensed at test line. After application of analyte solution a competition takes place between analyte and labeled analyte to bind with primary antibody at test line.

[0297] Multiplex detection format: Multiplex detection format is used for detection of more than one target species and assay is performed over the strip containing test lines equal to number of target species to be analyzed. It is highly desirable to analyze multiple analytes simultaneously under same set of conditions. Multiplex detection format is very useful in clinical diagnosis where multiple analytes which are inter-dependent in deciding about the stage of a disease are to be detected. Lateral flow strips for this purpose can be built in various ways i.e., by increasing length and test lines on conventional strip, making other structures like stars or T-shapes. Shape of strip for LFIA will be dictated by number of target analytes. Miniaturized versions of LFIA based on microarrays for multiplex detection of DNA sequences have been reported to have several advantages such as less consumption of test reagents, requirement of lesser sample volume and better sensitivity.

[0298] Antibodies can be conjugated to a solid support suitable for a diagnostic assay (e.g., beads such as magnetic beads, protein A or protein G agarose, microspheres, plates, slides, pipette tip or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding. Antibodies as described herein may likewise be conjugated to detectable labels or groups such as radiolabels (e.g.,35S,125I,131I), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine) in accordance with known techniques.

[0299] In particular embodiments, the antibodies of the present invention comprise monoclonal antibodies.

[0300] In other embodiments, the antibodies of the present invention comprise polyoclonal antibodies.

[0301] Suitable sources for antibodies for the detection of determinants include commercially available sources such as, for example, Abazyme, Abnova, AssayPro, Affinity Biologicals, AntibodyShop, Aviva bioscience, Biogenesis, Biosense Laboratories, Calbiochem, Cell Sciences, Chemicon International, Chemokine, Clontech, Cytolab, DAKO, Diagnostic BioSystems, eBioscience, Endocrine Technologies, Enzo Biochem, Eurogentec, Fusion Antibodies, Genesis Biotech, GloboZymes, Haematologic Technologies, Immunodetect, Immunodiagnostik, Immunometrics, Immunostar, Immunovision, Biogenex, Invitrogen, Jackson ImmunoResearch Laboratory, KMI Diagnostics, Koma Biotech, LabFrontier Life Science Institute, Lee Laboratories, Lifescreen, Maine Biotechnology Services, Mediclone, MicroPharm Ltd., ModiQuest, Molecular Innovations, Molecular Probes, Neoclone, Neuromics, New England Biolabs, Novocastra, Novus Biologicals, Oncogene Research Products, Orbigen, Oxford Biotechnology, Panvera, PerkinElmer Life Sciences, Pharmingen, Phoenix Pharmaceuticals, Pierce Chemical Company, Polymun Scientific, Polysiences, Inc., Promega Corporation, Proteogenix, Protos Immunoresearch, QED Biosciences, Inc., R&D Systems, Repligen, Research Diagnostics, Roboscreen, Santa Cruz Biotechnology, Seikagaku America, Serological Corporation, Serotec, SigmaAldrich, StemCell Technologies, Synaptic Systems GmbH, Technopharm, Terra Nova Biotechnology, TiterMax, Trillium Diagnostics, Upstate Biotechnology, US Biological, Vector Laboratories, Wako Pure Chemical Industries, and Zeptometrix. However, the skilled artisan can routinely make antibodies, against any of the polypeptide determinants described herein.

[0302] The presence of a label can be detected by inspection, or a detector which monitors a particular probe or probe combination is used to detect the detection reagent label. Typical detectors include spectrophotometers, phototubes and photodiodes, microscopes, scintillation counters, cameras, film and the like, as well as combinations thereof. Those skilled in the art will be familiar with numerous suitable detectors that are widely available from a variety of commercial sources and may be useful for carrying out the method disclosed herein. Commonly, an optical image of a substrate comprising bound labeling moieties is digitized for subsequent computer analysis. See generally The Immunoassay Handbook [The Immunoassay Handbook. Third Edition. 2005].

[0303] Antibodies suitable for specifically detecting ST2 include Recombinant Rabbit anti-human monoclonal antibody to ST2 (ab259721) (Abeam), Mouse anti-human monoclonal antibody to ST2 / IL-33R Antibody, Clone # 97203, (MAB523) (biotechne® R&D Systems), IL-33R (ST2) Mouse anti-human Monoclonal Antibody to ST2 (IL-33R), Clone hIL33Rcap, eBioscience™ Catalog # 17-9338-42 (invitrogen).

[0304] Antibodies suitable for specifically detecting ANG-2 include Mouse anti-human monoclonal antibody to Angiopoietin-2, Clone # 85816, (MAB098) (biotechne® R&D Systems), Recombinant rabbit anti-human monoclonal antibody to Angiopoietin 2 / ANG-2 (ab285368) (Abeam), Rabbit anti-human polyclonal antibody to Angiopoietin 2, Catalog # PA5-27297, (Invitrogen).

[0305] Antibodies suitable for specifically detecting DR5 include Rabbit anti-human polyclonal antibody to DR5 (ab8416) (Abeam), Mouse anti-human monoclonal antibody to DR5, eBioscience™ Catalog # 12-9908-42 (Invitrogen), Recombinant rabbit anti-human monoclonal antibody to DR5, clone JAO3-38, Catalog # MA5-32693 (Invitrogen), Mouse anti-human monoclonal IgGl antibody to DR5, Catalog # sc- 166624, (Santa Cruz).

[0306] Antibodies suitable for specifically detection IL-6 inlude but are not limited to Mouse antihuman monoclonal antibody to IL-6 (MAB2063) (biotechne® R&D Systems)., Mouse anti-human monoclonal antibody to IL-6, Clone 5IL6, Catalog # M620, (Invitrogen) and Mouse anti-human monoclonal antibody to IL-6, clone OTI3G9, (TA500067) (OriGene).

[0307] Antibodies suitable for detecting IL- 10 include Recombinant Rabbit anti-human monoclonal Antibody to IL- 10 (ab244835) (abeam); Mouse anti-human monoclonal antibody to IL-10, Clone # 127107, (MAB2172) (biotechne® R&D Systems); and Rat anti-human monoclonal antibody to IL- 10, Clone JES3-9D7, eBioscience™, Catalog # 14-7108-81 (Invitrogen).

[0308] Antibodies suitable for measuring TRAIL include without limitation: Mouse, Monoclonal (55B709-3) IgG (Thermo Fisher Scientific); Mouse, Monoclonal (2E5) IgGl (Enzo Lifesciences); Mouse, Monoclonal (2E05) IgGl; Mouse, Monoclonal (M912292) IgGl kappa (My BioSource); Mouse, Monoclonal (IIIF6) IgG2b; Mouse, Monoclonal (2E1-1B9) IgGl (EpiGentek); Mouse, Monoclonal (RIK-2) IgGl, kappa (BioLegend); Mouse, Monoclonal M181 IgGl (Immunex Corporation); Mouse, Monoclonal VI10E IgG2b (Novus Biologicals); Mouse, Monoclonal MAB375 IgGl (R&D Systems); Mouse, Monoclonal MAB687 IgGl (R&D Systems); Mouse, Monoclonal HS501 IgGl (Enzo Lifesciences); Mouse, Monoclonal clone 75411.11 Mouse IgGl (Abeam); Mouse, Monoclonal T8175-50 IgG (X-Zell Biotech Co); Mouse, Monoclonal 2B2.108 IgGl; Mouse, Monoclonal B-T24 IgGl (Cell Sciences); Mouse, Monoclonal 55B709.3 IgGl (Thermo Fisher Scientific); Mouse, Monoclonal D3 IgGl (Thermo Fisher Scientific); Goat, Polyclonal C19 IgG; Rabbit, Polyclonal H257 IgG (Santa Cruz Biotechnology); Mouse, Monoclonal 500-M49 IgG; Mouse, Monoclonal 05-607 IgG; Mouse, Monoclonal B-T24 IgGl (Thermo Fisher Scientific); Rat, Monoclonal (N2B2), IgG2a, kappa (Thermo Fisher Scientific); Mouse, Monoclonal (1A7-2B7), IgGl (Genxbio); Mouse, Monoclonal (55B709.3), IgG (Thermo Fisher Scientific); Mouse, Monoclonal B-S23* IgGl (Cell Sciences), Human TRAIL / TNFSF10 MAb (Clone 75411), Mouse IgGl (R&D Systems); Human TRAIL / TNFSF10 MAb (Clone 124723), Mouse IgGl (R&D Systems) and Human TRAIL / TNFSF10 MAb (Clone 75402), Mouse IgGl (R&D Systems). Antibodies suitable for measuring IP- 10 include without limitation: Mouse anti-human CXCL10 (IP- 10) Monoclonal Antibody (Cat. No. 524401) (BioLegend), Rabbit anti-human CXCL10 (IP- 10) polyclonal Antibody (ab9807) (Abeam), Mouse anti-human CXCL10 (IP- 10) Monoclonal Antibody (4D5) (MCA1693) (Bio-Rad), Goat anti-human CXCL10 (IP-10) Monoclonal Antibody (PA5-46999) (Invitrogen), Mouse anti-human CXCL10 (IP- 10) Monoclonal Antibody (MA5-23819) (Invitrogen).

[0309] Antibodies suitable for measuring CRP include without limitation: Rabbit anti-Human C- Reactive Protein / CRP polyclonal antibody (ab31156) (Abeam), Sheep anti-Human C-Reactive Protein / CRP Polyclonal antibody (AF1707) (R&D Systems), rabbit anti-Human C-Reactive Protein / CRP Polyclonal antibody (C3527) (Sigma-Aldrich), Mouse anti-Human C-Reactive Protein / CRP monoclonal antibody (C1688) (MilliporeSigma).

[0310] A “sample” in the context of the present invention is a biological sample isolated from a subject and can include, by way of example and not limitation, whole blood, serum, plasma, saliva, mucus, breath, urine, CSF, sputum, sweat, stool, hair, seminal fluid, biopsy, rhinorrhea, tissue biopsy, cytological sample, platelets, reticulocytes, leukocytes, epithelial cells, or whole blood cells.

[0311] In a particular embodiment, the sample is a blood sample - e.g., serum, plasma, or whole blood. The sample may be a venous sample, peripheral blood mononuclear cell sample or a peripheral blood sample. In one embodiment, the sample comprises white blood cells including for example granulocytes, lymphocytes and / or monocytes. In one embodiment, the sample is depleted of red blood cells.

[0312] The subject is typically suffering from a bacterial or viral infection.

[0313] The bacterial or viral infection may be an acute or chronic infection.

[0314] A chronic infection is an infection that develops slowly and lasts a long time. Viruses that may cause a chronic infection include Hepatitis C and HIV. One difference between acute and chronic infection is that during acute infection the immune system often produces IgM+ antibodies against the infectious agent, whereas the chronic phase of the infection is usually characteristic of IgM- / IgG+ antibodies. In addition, acute infections cause immune mediated necrotic processes while chronic infections often cause inflammatory mediated fibrotic processes and scaring (e.g. Hepatitis C in the liver). Thus, acute and chronic infections may elicit different underlying immunological mechanisms.

[0315] According to a particular embodiment, the infection that is diagnosed is an acute infection.

[0316] Exemplary viral diseases which may be diagnosed according to the methods described herein are summarized in Table E. Table E

[0317]

[0318] According to a specific embodiment, the viral disease is COVID- 19.

[0319] Exemplary virus-causing families are summarized in Table F, herein below. Table F

[0320] According to another specific embodiment, the virus is Human metapneumovirus, Bocavirus or Enterovirus.

[0321] According to another specific embodiment, the virus is RSV, Flu A, Flu B, HCoV or SARS- Cov-2.

[0322] Examples of coronaviruses include: human coronavirus 229E, human coronavirus OC43, SARS-CoV, HCoV NE63, HKU1, MERS-CoV and SARS-CoV-2.

[0323] According to a particular embodiment, the coronavirus is SARS-CoV-2.

[0324] Bacterial infections which may be ruled in according to embodiments of the invention may be the result of gram-positive, gram-negative bacteria or atypical bacteria.

[0325] The term "Gram-positive bacteria" refers to bacteria that are stained dark blue by Gram staining. Gram-positive organisms are able to retain the crystal violet stain because of the high amount of peptidoglycan in the cell wall.

[0326] The term "Gram-negative bacteria" refers to bacteria that do not retain the crystal violet dye in the Gram staining protocol.

[0327] The term "Atypical bacteria" are bacteria that do not fall into one of the classical "Gram" groups. They are usually, though not always, intracellular bacterial pathogens. They include, without limitations, Mycoplasmas spp., Legionella spp. Rickettsiae spp., and Chlamydiae spp.

[0328] In order to diagnose infections (e.g., determine severity, predict severity), using more than one protein determinant, the threshold levels provided herein above may be used. Alternatively, scores based on the amounts of these proteins may be generated which take into account the weights of each of the proteins, as further described herein below.

[0329] Preferably the combinations which are tested to classify the infectious disease (i.e. incorporated into the score) do not exceed 50, 40, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3 markers (e.g. protein expression levels). In another embodiment, no more than 40 protein markers are incorporated into the score for the classification. In another embodiment, no more than 30 protein markers are incorporated into the score for the classification. In another embodiment, no more than 20 protein markers are incorporated into the score for the classification. In another embodiment, no more than 10 protein markers are incorporated into the score for the classification. In another embodiment, no more than 9 protein markers are incorporated into the score. In another embodiment, no more than 8 protein markers are incorporated into the score. In another embodiment, no more than 7 protein markers are incorporated into the score for the classification. In another embodiment, no more than 6 protein markers are incorporated into the score, for the classification. In another embodiment, no more than 5 protein markers are incorporated into the score for the classification. In another embodiment, no more than 4 protein markers incorporated into the score for the classification. In another embodiment, no more than 3 protein markers are incorporated into the score for the classification.

[0330] Performance and Accuracy Measures of the Invention.

[0331] The performance and thus absolute and relative clinical usefulness of the invention may be assessed in multiple ways as noted above. Amongst the various assessments of performance, some aspects of the invention are intended to provide accuracy in clinical diagnosis and prognosis. The accuracy of a diagnostic or prognostic test, assay, or method concerns the ability of the test, assay, or method to distinguish between subjects having an infection is based on whether the subjects have, a “significant alteration” (e.g., clinically significant and diagnostically significant) in the levels of a determinant. By “effective amount” it is meant that the measurement of an appropriate number of determinants (which may be one or more) to produce a “significant alteration” (e.g. level of expression or activity of a determinant) that is different than the predetermined cut-off point (or threshold value) for that determinant (s) and therefore indicates that the subject has an infection for which the determinant (s) is an indication. The difference in the level of determinant is preferably statistically significant. As noted below, and without any limitation of the invention, achieving statistical significance, and thus the preferred analytical, diagnostic, and clinical accuracy, may require that combinations of several determinants be used together in panels and combined with mathematical algorithms in order to achieve a statistically significant determinant index.

[0332] In the categorical diagnosis of a disease state, changing the cut point or threshold value of a test (or assay) usually changes the sensitivity and specificity, but in a qualitatively inverse relationship. Therefore, in assessing the accuracy and usefulness of a proposed medical test, assay, or method for assessing a subject’s condition, one should always take both sensitivity and specificity into account and be mindful of what the cut point is at which the sensitivity and specificity are being reported because sensitivity and specificity may vary significantly over the range of cut points. One way to achieve this is by using the Matthews correlation coefficient (MCC) metric, which depends upon both sensitivity and specificity. Use of statistics such as area under the ROC curve (AUC), encompassing all potential cut point values, is preferred for most categorical risk measures when using some aspects of the invention, while for continuous risk measures, statistics of goodness-of-fit and calibration to observed results or other gold standards, are preferred.

[0333] By predetermined level of predictability it is meant that the method provides an acceptable level of clinical or diagnostic accuracy. Using such statistics, an “acceptable degree of diagnostic accuracy”, is herein defined as a test or assay (such as the test used in some aspects of the invention for determining the clinically significant presence of determinants, which thereby indicates the presence of an infection type and / or the severity of the infection) in which the AUC (area under the ROC curve for the test or assay) is at least 0.60, desirably at least 0.65, more desirably at least 0.70, preferably at least 0.75, more preferably at least 0.80, and most preferably at least 0.85.

[0334] By a “very high degree of diagnostic accuracy”, it is meant a test or assay in which the AUC (area under the ROC curve for the test or assay) is at least 0.75, 0.80, desirably at least 0.85, more desirably at least 0.875, preferably at least 0.90, more preferably at least 0.925, and most preferably at least 0.95.

[0335] Alternatively, the methods predict the presence or absence of an infection or severity of infection with at least 75% total accuracy, more preferably 80%, 85%, 90%, 95%, 97%, 98%, 99% or greater total accuracy.

[0336] Alternatively, the methods predict the presence of a bacterial infection or response to therapy or severity of bacterial infection with at least 75% sensitivity, more preferably 80%, 85%, 90%, 95%, 97%, 98%, 99% or greater sensitivity.

[0337] Alternatively, the methods predict the presence of a viral infection or response to therapy or severity of viral infection with at least 75% specificity, more preferably 80%, 85%, 90%, 95%, 97%, 98%, 99% or greater specificity. Alternatively, the methods predict the presence or absence of an infection or response to therapy with an MCC larger than 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 or 1.0.

[0338] In general, alternative methods of determining diagnostic accuracy are commonly used for continuous measures, when a disease category has not yet been clearly defined by the relevant medical societies and practice of medicine, where thresholds for therapeutic use are not yet established, or where there is no existing gold standard for diagnosis of the pre-disease. For continuous measures of risk, measures of diagnostic accuracy for a calculated index are typically based on curve fit and calibration between the predicted continuous value and the actual observed values (or a historical index calculated value) and utilize measures such as R squared, Hosmer- Lemeshow P-value statistics and confidence intervals. It is not unusual for predicted values using such algorithms to be reported including a confidence interval (usually 90% or 95% CI) based on a historical observed cohort’s predictions, as in the test for risk of future breast cancer recurrence commercialized by Genomic Health, Inc. (Redwood City, California).

[0339] In general, by defining the degree of diagnostic accuracy, i.e., cut points on a ROC curve, defining an acceptable AUC value, and determining the acceptable ranges in relative concentration of what constitutes an effective amount of the determinants of the invention allows for one of skill in the art to use the determinants to identify, diagnose, or prognose subjects with a pre-determined level of predictability and performance.

[0340] Furthermore, other unlisted biomarkers will be very highly correlated with the determinants (for the purpose of this application, any two variables will be considered to be “very highly correlated” when they have a Coefficient of Determination (A2) of 0.5 or greater). Some aspects of the present invention encompass such functional and statistical equivalents to the aforementioned determinants. Furthermore, the statistical utility of such additional determinants is substantially dependent on the cross-correlation between multiple biomarkers and any new biomarkers will often be required to operate within a panel in order to elaborate the meaning of the underlying biology.

[0341] Construction of determinant Panels

[0342] Groupings of determinants can be included in “panels”, also called "determinantsignatures", "determinant signatures", or "multi-determinant signatures." A “panel” within the context of the present invention means a group of biomarkers (whether they are determinants, clinical parameters, or traditional laboratory risk factors) that includes one or more determinants. A panel can also comprise additional biomarkers, e.g., clinical parameters, traditional laboratory risk factors, known to be present or associated with infection, in combination with a selected group of the determinants listed herein. As noted above, many of the individual determinants, clinical parameters, and traditional laboratory risk factors listed, when used alone and not as a member of a multi-biomarker panel of determinants, have little or no clinical use in reliably distinguishing individual normal subjects, subjects at risk for having an infection (e.g., bacterial, viral or co-infection), or severity of infection and thus cannot reliably be used alone in classifying any subject between those states. Even where there are statistically significant differences in their mean measurements in each of these populations, as commonly occurs in studies which are sufficiently powered, such biomarkers may remain limited in their applicability to an individual subject, and contribute little to diagnostic or prognostic predictions for that subject. A common measure of statistical significance is the p- value, which indicates the probability that an observation has arisen by chance alone; preferably, such p-values are 0.05 or less, representing a 5% or less chance that the observation of interest arose by chance. Such p-values depend significantly on the power of the study performed.

[0343] Despite this individual determinant performance, and the general performance of formulas combining only the traditional clinical parameters and few traditional laboratory risk factors, the present inventors have noted that certain specific combinations of two or more determinants can also be used as multi-biomarker panels comprising combinations of determinants that are known to be involved in one or more physiological or biological pathways, and that such information can be combined and made clinically useful through the use of various formulae, including statistical classification algorithms and others, combining and in many cases extending the performance characteristics of the combination beyond that of the individual determinants. These specific combinations show an acceptable level of diagnostic accuracy, and, when sufficient information from multiple determinants is combined in a trained formula, they often reliably achieve a high level of diagnostic accuracy transportable from one population to another.

[0344] The general concept of how two less specific or lower performing determinants are combined into novel and more useful combinations for the intended indications, is a key aspect of some embodiments of the invention. Multiple biomarkers can yield significant improvement in performance compared to the individual components when proper mathematical and clinical algorithms are used; this is often evident in both sensitivity and specificity, and results in a greater AUC or MCC. Significant improvement in performance could mean an increase of 1%, 2%, 3%, 4%, 5%, 8%, 10% or higher than 10% in different measures of accuracy such as total accuracy, AUC, MCC, sensitivity, specificity, PPV or NPV. Secondly, there is often novel unperceived information in the existing biomarkers, as such was necessary in order to achieve through the new formula an improved level of sensitivity or specificity. This hidden information may hold true even for biomarkers which are generally regarded to have suboptimal clinical performance on their own. In fact, the suboptimal performance in terms of high false positive rates on a single biomarker measured alone may very well be an indicator that some important additional information is contained within the biomarker results - information which would not be elucidated absent the combination with a second biomarker and a mathematical formula.

[0345] On the other hand, it is often useful to restrict the number of measured diagnostic determinants (e.g., protein markers), as this allows significant cost reduction and reduces required sample volume and assay complexity. Accordingly, even when two signatures have similar diagnostic performance (e.g., similar AUC or sensitivity), one which incorporates less proteins could have significant utility and ability to reduce to practice. For example, a signature that includes 5 proteins compared to 10 proteins and performs similarly has many advantages in real world clinical setting and thus is desirable. Therefore, there is value and invention in being able to reduce the number of proteins incorporated in a signature while retaining similar levels of accuracy. In this context similar levels of accuracy could mean plus or minus 1%, 2%, 3%, 4%, 5%, 8%, or 10% in different measures of accuracy such as total accuracy, AUC, MCC, sensitivity, specificity, PPV or NPV; a significant reduction in the number of proteins of a signature includes reducing the number of proteins by 2, 3, 4, 5, 6, 7, 8, 9, 10 or more than 10 proteins.

[0346] Several statistical and modeling algorithms known in the art can be used to both assist in determinant selection choices and optimize the algorithms combining these choices. Statistical tools such as factor and cross -biomarker correlation / covariance analyses allow more rationale approaches to panel construction. Mathematical clustering and classification tree showing the Euclidean standardized distance between the determinants can be advantageously used. Pathway informed seeding of such statistical classification techniques also may be employed, as may rational approaches based on the selection of individual determinants based on their participation across in particular pathways or physiological functions.

[0347] Ultimately, formula such as statistical classification algorithms can be directly used to both select determinants and to generate and train the optimal formula necessary to combine the results from multiple determinants into a single index. Often, techniques such as forward (from zero potential explanatory parameters) and backwards selection (from all available potential explanatory parameters) are used, and information criteria, such as AIC or BIC, are used to quantify the tradeoff between the performance and diagnostic accuracy of the panel and the number of determinants used. The position of the individual determinant on a forward or backwards selected panel can be closely related to its provision of incremental information content for the algorithm, so the order of contribution is highly dependent on the other constituent determinants in the panel. Construction of Clinical Algorithms

[0348] Any formula may be used to combine determinant results into indices useful in the practice of the invention. As indicated above, and without limitation, such indices may indicate, among the various other indications, the probability, likelihood, absolute or relative risk, time to or rate of conversion from one to another disease states, or make predictions of future biomarker measurements of infection. This may be for a specific time period or horizon, or for remaining lifetime risk, or simply be provided as an index relative to another reference subject population.

[0349] Although various preferred formula are described here, several other model and formula types beyond those mentioned herein and in the definitions above are well known to one skilled in the art. The actual model type or formula used may itself be selected from the field of potential models based on the performance and diagnostic accuracy characteristics of its results in a training population. The specifics of the formula itself may commonly be derived from determinant results in the relevant training population. Amongst other uses, such formula may be intended to map the feature space derived from one or more determinant inputs to a set of subject classes (e.g. useful in predicting class membership of subjects as normal, having an infection), to derive an estimation of a probability function of risk using a Bayesian approach, or to estimate the class-conditional probabilities, then use Bayes’ rule to produce the class probability function as in the previous case.

[0350] Preferred formulas include the broad class of statistical classification algorithms, and in particular the use of discriminant analysis. The goal of discriminant analysis is to predict class membership from a previously identified set of features. In the case of linear discriminant analysis (LDA), the linear combination of features is identified that maximizes the separation among groups by some criteria. Features can be identified for LDA using an eigengene based approach with different thresholds (ELDA) or a stepping algorithm based on a multivariate analysis of variance (MANOVA). Forward, backward, and stepwise algorithms can be performed that minimize the probability of no separation based on the Hotelling-Lawley statistic.

[0351] Eigengene-based Linear Discriminant Analysis (ELDA) is a feature selection technique developed by Shen et al. (2006). The formula selects features (e.g. biomarkers) in a multivariate framework using a modified eigen analysis to identify features associated with the most important eigenvectors. “Important” is defined as those eigenvectors that explain the most variance in the differences among samples that are trying to be classified relative to some threshold.

[0352] A support vector machine (SVM) is a classification formula that attempts to find a hyperplane that separates two classes. This hyperplane contains support vectors, data points that are exactly the margin distance away from the hyperplane. In the likely event that no separating hyperplane exists in the current dimensions of the data, the dimensionality is expanded greatly by projecting the data into larger dimensions by taking non-linear functions of the original variables (Venables and Ripley, 2002). Although not required, filtering of features for SVM often improves prediction. Features (e.g., biomarkers) can be identified for a support vector machine using a nonparametric Kruskal-Wallis (KW) test to select the best univariate features. A random forest (RF, Breiman, 2001) or recursive partitioning (RPART, Breiman et al., 1984) can also be used separately or in combination to identify biomarker combinations that are most important. Both KW and RF require that a number of features be selected from the total. RPART creates a single classification tree using a subset of available biomarkers.

[0353] Other formula may be used in order to pre-process the results of individual determinant measurements into more valuable forms of information, prior to their presentation to the predictive formula. Most notably, normalization of biomarker results, using either common mathematical transformations such as logarithmic or logistic functions, as normal or other distribution positions, in reference to a population’s mean values, etc. are all well known to those skilled in the art. Of particular interest are a set of normalizations based on clinical-determinants such as time from symptoms, gender, race, or sex, where specific formula are used solely on subjects within a class or continuously combining a clinical-determinants as an input. In other cases, analyte-based biomarkers can be combined into calculated variables which are subsequently presented to a formula.

[0354] In addition to the individual parameter values of one subject potentially being normalized, an overall predictive formula for all subjects, or any known class of subjects, may itself be recalibrated or otherwise adjusted based on adjustment for a population's expected prevalence and mean biomarker parameter values, according to the technique outlined in D'Agostino et al., (2001) JAMA 286: 180-187, or other similar normalization and recalibration techniques. Such epidemiological adjustment statistics may be captured, confirmed, improved and updated continuously through a registry of past data presented to the model, which may be machine readable or otherwise, or occasionally through the retrospective query of stored samples or reference to historical studies of such parameters and statistics. Additional examples that may be the subject of formula recalibration or other adjustments include statistics used in studies by Pepe, M.S. et al., 2004 on the limitations of odds ratios; Cook, N.R., 2007 relating to ROC curves. Finally, the numeric result of a classifier formula itself may be transformed post-processing by its reference to an actual clinical population and study results and observed endpoints, in order to calibrate to absolute risk and provide confidence intervals for varying numeric results of the classifier or risk formula. Some determinants may exhibit trends that depend on the patient age (e.g. the population baseline may rise or fall as a function of age). One can use an 'Age dependent normalization or stratification' scheme to adjust for age related differences. Performing age dependent normalization, stratification or distinct mathematical formulas can be used to improve the accuracy of determinants for differentiating between different types of infections. For example, one skilled in the art can generate a function that fits the population mean levels of each determinant as function of age and use it to normalize the determinant of individual subjects’ levels across different ages. Another example is to stratify subjects according to their age and determine age specific thresholds or index values for each age group independently.

[0355] In the context of the present invention the following statistical terms may be used:

[0356] “TP” is true positive, means positive test result that accurately reflects the tested-for activity. For example in the context of the present invention a TP, is for example but not limited to, truly classifying a bacterial infection as such.

[0357] “TN” is true negative, means negative test result that accurately reflects the tested-for activity. For example in the context of the present invention a TN, is for example but not limited to, truly classifying a viral infection as such.

[0358] “FN” is false negative, means a result that appears negative but fails to reveal a situation. For example in the context of the present invention a FN, is for example but not limited to, falsely classifying a bacterial infection as a viral infection.

[0359] “FP” is false positive, means test result that is erroneously classified in a positive category. For example in the context of the present invention a FP, is for example but not limited to, falsely classifying a viral infection as a bacterial infection.

[0360] “Sensitivity” is calculated by TP / (TP+FN) or the true positive fraction of disease subjects.

[0361] “Specificity” is calculated by TN / (TN+FP) or the true negative fraction of non-disease or normal subjects.

[0362] "Total accuracy" is calculated by (TN + TP) / (TN + FP +TP + FN).

[0363] “Positive predictive value” or “PPV” is calculated by TP / (TP+FP) or the true positive fraction of all positive test results. It is inherently impacted by the prevalence of the disease and pre-test probability of the population intended to be tested.

[0364] “Negative predictive value” or “NPV” is calculated by TN / (TN + FN) or the true negative fraction of all negative test results. It also is inherently impacted by the prevalence of the disease and pre-test probability of the population intended to be tested. See, e.g., O’Marcaigh AS, Jacobson RM, “Estimating The Predictive Value Of A Diagnostic Test, How To Prevent Misleading Or Confusing Results,” Clin. Ped. 1993, 32(8): 485-491, which discusses specificity, sensitivity, and positive and negative predictive values of a test, e.g., a clinical diagnostic test.

[0365] "MCC" (Mathews Correlation coefficient) is calculated as follows: MCC = (TP * TN - FP * FN) / {(TP + FN) * (TP + FP) * (TN + FP) * (TN + FN)}A0.5 where TP, FP, TN, FN are true- positives, false-positives, true-negatives, and false-negatives, respectively. Note that MCC values range between -1 to +1, indicating completely wrong and perfect classification, respectively. An MCC of 0 indicates random classification. MCC has been shown to be a useful for combining sensitivity and specificity into a single metric (Baldi, Brunak et al. 2000). It is also useful for measuring and optimizing classification accuracy in cases of unbalanced class sizes (Baldi, Brunak et al. 2000).

[0366] Often, for binary disease state classification approaches using a continuous diagnostic test measurement, the sensitivity and specificity is summarized by a Receiver Operating Characteristics (ROC) curve according to Pepe et al., “Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic, Prognostic, or Screening Marker,” Am. J. Epidemiol 2004, 159 (9): 882-890, and summarized by the Area Under the Curve (AUC) or c-statistic, an indicator that allows representation of the sensitivity and specificity of a test, assay, or method over the entire range of test (or assay) cut points with just a single value. See also, e.g., Shultz, “Clinical Interpretation Of Laboratory Procedures,” chapter 14 in Teitz, Fundamentals of Clinical Chemistry, Burtis and Ashwood (eds.), 4thedition 1996, W.B. Saunders Company, pages 192-199; and Zweig et al., “ROC Curve Analysis: An Example Showing The Relationships Among Serum Lipid And Apolipoprotein Concentrations In Identifying Subjects With Coronory Artery Disease,” Clin. Chem., 1992, 38(8): 1425-1428. An alternative approach using likelihood functions, odds ratios, information theory, predictive values, calibration (including goodness-of-fit), and reclassification measurements is summarized according to Cook, “Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction,” Circulation 2007, 115: 928-935.

[0367] “Accuracy” refers to the degree of conformity of a measured or calculated quantity (a test reported value) to its actual (or true) value. Clinical accuracy relates to the proportion of true outcomes (true positives (TP) or true negatives (TN) versus misclassified outcomes (false positives (FP) or false negatives (FN)), and may be stated as a sensitivity, specificity, positive predictive values (PPV) or negative predictive values (NPV), Mathews correlation coefficient (MCC), or as a likelihood, odds ratio, Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC) among other measures.

[0368] A “score” “formula,” “algorithm,” or “model” is any mathematical equation, algorithmic, analytical or programmed process, or statistical technique that takes one or more continuous or categorical inputs (herein called “parameters”) and calculates an output value, sometimes referred to as an “index” or “index value”. Non-limiting examples of “formulas” include sums, ratios, and regression operators, such as coefficients or exponents, biomarker value transformations and normalizations (including, without limitation, those normalization schemes based on clinical- determinants, such as gender, age, or ethnicity), rules and guidelines, statistical classification models, machine learning algorithms, and neural networks trained on historical populations. Of particular use in combining determinants are linear and non-linear equations and statistical classification analyses to determine the relationship between levels of determinants detected in a subject sample and the subject’s probability of having an infection or a certain type of infection. In panel and combination construction, of particular interest are structural and syntactic statistical classification algorithms, and methods of index construction, utilizing pattern recognition features, including established techniques such as cross-correlation, Principal Components Analysis (PCA), factor rotation, Logistic Regression (LogReg), Linear Discriminant Analysis (LDA), Eigengene Linear Discriminant Analysis (ELD A), Support Vector Machines (SVM), Ensemble methods such as Random Forest (RF), Recursive Partitioning Tree (RPART), as well as other related decision tree classification techniques, Shrunken Centroids (SC), StepAIC, Instance-based Learning methods such as K-Nearest Neighbors, Boosting, Tree-based methods such as Decision Trees, Neural Networks methods such as single-layer network, multi-layer network and Deep Learning, Bayesian classifiers such as Naive Bayes and Bayesian Networks, and Hidden Markov Models, among others. Other techniques may be used in survival and time to event hazard analysis, including Proportional hazards models such as the Cox model, Weibull, Kaplan-Meier and Greenwood models well known to those of skill in the art. Many of these techniques are useful either combined with a determinant selection technique, such as forward selection, backwards selection, or stepwise selection, complete enumeration of all potential panels of a given size, genetic algorithms, embedded methods such as the least absolute shrinkage and selection operator or the LASSO method, or they may themselves include biomarker selection methodologies in their own technique. These may be coupled with information criteria, such as Akaike’s Information Criterion (AIC) or Bayes Information Criterion (BIC), in order to quantify the tradeoff between additional biomarkers and model improvement, and to aid in minimizing overfit. The resulting predictive models may be validated in other studies, or cross-validated in the study they were originally trained in, using such techniques as Bootstrap, Leave-One-Out (LOO) and k-Fold cross- validation where k is a positive integer such as 5 (5-Fold CV) or 10 (10-Fold CV). At various steps, false discovery rates may be estimated by value permutation according to techniques known in the art. A “health economic utility function” is a formula that is derived from a combination of the expected probability of a range of clinical outcomes in an idealized applicable patient population, both before and after the introduction of a diagnostic or therapeutic intervention into the standard of care. It encompasses estimates of the accuracy, effectiveness and performance characteristics of such intervention, and a cost and / or value measurement (a utility) associated with each outcome, which may be derived from actual health system costs of care (services, supplies, devices and drugs, etc.) and / or as an estimated acceptable value per quality adjusted life year (QALY) resulting in each outcome. The sum, across all predicted outcomes, of the product of the predicted population size for an outcome multiplied by the respective outcome’s expected utility is the total health economic utility of a given standard of care. The difference between (i) the total health economic utility calculated for the standard of care with the intervention versus (ii) the total health economic utility for the standard of care without the intervention results in an overall measure of the health economic cost or value of the intervention. This may itself be divided amongst the entire patient group being analyzed (or solely amongst the intervention group) to arrive at a cost per unit intervention, and to guide such decisions as market positioning, pricing, and assumptions of health system acceptance. Such health economic utility functions are commonly used to compare the cost-effectiveness of the intervention, but may also be transformed to estimate the acceptable value per QALY the health care system is willing to pay, or the acceptable cost-effective clinical performance characteristics required of a new intervention.

[0369] For diagnostic (or prognostic) interventions of the invention, as each outcome (which in a disease classifying diagnostic test may be a TP, FP, TN, or FN) bears a different cost, a health economic utility function may preferentially favor sensitivity over specificity, or PPV over NPV based on the clinical situation and individual outcome costs and value, and thus provides another measure of health economic performance and value which may be different from more direct clinical or analytical performance measures. These different measurements and relative trade-offs generally will converge only in the case of a perfect test, with zero error rate (a.k.a., zero predicted subject outcome misclassifications or FP and FN), which all performance measures will favor over imperfection, but to differing degrees.

[0370] “Analytical accuracy” refers to the reproducibility and predictability of the measurement process itself, and may be summarized in such measurements as coefficients of variation (CV), Pearson correlation, and tests of concordance and calibration of the same samples or controls with different times, users, equipment and / or reagents. These and other considerations in evaluating new biomarkers are also summarized in Vasan, 2006.

[0371] “Performance” is a term that relates to the overall usefulness and quality of a diagnostic or prognostic test, including, among others, clinical and analytical accuracy, other analytical and process characteristics, such as use characteristics (e.g., stability, ease of use), health economic value, and relative costs of components of the test. Any of these factors may be the source of superior performance and thus usefulness of the test, and may be measured by appropriate “performance metrics,” such as AUC and MCC, time to result, shelf life, etc. as relevant.

[0372] By “statistically significant”, it is meant that the alteration is greater than what might be expected to happen by chance alone (which could be a “false positive”). Statistical significance can be determined by any method known in the art. Commonly used measures of significance include the p-value, which presents the probability of obtaining a result at least as extreme as a given data point, assuming the data point was the result of chance alone. A result is often considered highly significant at a p-value of 0.05 or less.

[0373] Kits

[0374] Some aspects of the invention also include a determinant-detection reagent such as antibodies packaged together in the form of a kit. The kit may contain in separate containers antibodies (either already bound to a solid matrix or packaged separately with reagents for binding them to the matrix), control formulations (positive and / or negative), and / or a detectable label such as fluorescein, green fluorescent protein, rhodamine, cyanine dyes, Alexa dyes, luciferase, radiolabels, among others. The detectable label may be attached to a secondary antibody which binds to the Fc portion of the antibody which recognizes the determinant. Instructions (e.g., written, tape, VCR, CD-ROM, etc.) for carrying out the assay may be included in the kit.

[0375] The kits of this aspect of the present invention may comprise additional components that aid in the detection of the determinants such as enzymes, salts, buffers etc. necessary to carry out the detection reactions.

[0376] For example, determinant detection reagents (e.g. antibodies) can be immobilized on a solid support such as a porous strip or an array to form at least one determinant detection site. The measurement or detection region of the porous strip may include a plurality of sites. A test strip may also contain sites for negative and / or positive controls. Alternatively, control sites can be located on a separate strip from the test strip. Optionally, the different detection sites may contain different amounts of immobilized detection reagents, e.g., a higher amount in the first detection site and lesser amounts in subsequent sites. Upon the addition of test sample, the number of sites displaying a detectable signal provides a quantitative indication of the amount of determinants present in the sample. The detection sites may be configured in any suitably detectable shape and are typically in the shape of a bar or dot spanning the width of a test strip. Polyclonal antibodies for measuring determinants include without limitation antibodies that were produced from sera by active immunization of one or more of the following: Rabbit, Goat, Sheep, Chicken, Duck, Guinea Pig, Mouse, Donkey, Camel, Rat and Horse.

[0377] Examples of detection agents, include without limitation: scFv, dsFv, Fab, sVH, F(ab')2, Cyclic peptides, Haptamers, A single-domain antibody, Fab fragments, Single-chain variable fragments, Affibody molecules, Affilins, Nanofitins, Anticalins, Avimers, DARPins, Kunitz domains, Fynomers and Monobody.

[0378] In particular embodiments, the kit does not comprise a number of antibodies that specifically recognize more than 50, 20 15, 10, 9, 8, 7, 6, 5 or 4 polypeptides.

[0379] In other embodiments, the array of the present invention does not comprise a number of antibodies that specifically recognize more than 50, 20 15, 10, 9, 8, 7, 6, 5 or 4 polypeptides.

[0380] In another embodiment, the kit comprises at least one antibody which binds specifically to ANG-2 and one that binds specifically to ST2, IP- 10, IE- 10, DR5, IL-6, TRAIL or any combination thereof. The kit may further comprise antibodies which specifically detect CRP.

[0381] A machine-readable storage medium can comprise a data storage material encoded with machine-readable data or data arrays which, when using a machine programmed with instructions for using the data, is capable of use for a variety of purposes. Measurements of effective amounts of the biomarkers of the invention and / or the resulting evaluation of risk from those biomarkers can be implemented in computer programs executing on programmable computers, comprising, inter alia, a processor, a data storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. Program code can be applied to input data to perform the functions described above and generate output information. The output information can be applied to one or more output devices, according to methods known in the art. The computer may be, for example, a personal computer, microcomputer, or workstation of conventional design.

[0382] Each program can be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. The language can be a compiled or interpreted language. Each such computer program can be stored on a storage media or device (e.g., ROM or magnetic diskette or others as defined elsewhere in this disclosure) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein. The health-related data management system used in some aspects of the invention may also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform various functions described herein.

[0383] The polypeptide determinants of the present invention, in some embodiments thereof, can be used to generate a “reference determinant profile” of those subjects who do not have an infection. The determinants disclosed herein can also be used to generate a “subject determinant profile” taken from subjects who have an infection. The subject determinant profiles can be compared to a reference determinant profile to diagnose or identify subjects with an infection. The subject determinant profile of different infection types can be compared to diagnose or identify the type of infection. The reference and subject determinant profiles of the present invention, in some embodiments thereof, can be contained in a machine-readable medium, such as but not limited to, analog tapes like those readable by a VCR, CD-ROM, DVD-ROM, USB flash media, among others. Such machine-readable media can also contain additional test results, such as, without limitation, measurements of clinical parameters and traditional laboratory risk factors. Alternatively or additionally, the machine-readable media can also comprise subject information such as medical history and any relevant family history. The machine-readable media can also contain information relating to other disease-risk algorithms and computed indices such as those described herein.

[0384] As used herein the term “about” refers to ± 10 %.

[0385] The terms "comprises", "comprising", "includes", "including", “having” and their conjugates mean "including but not limited to".

[0386] The term “consisting of’ means “including and limited to”.

[0387] The term "consisting essentially of" means that the composition, method or structure may include additional ingredients, steps and / or parts, but only if the additional ingredients, steps and / or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.

[0388] As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a compound" or "at least one compound" may include a plurality of compounds, including mixtures thereof.

[0389] Throughout this application, various embodiments of this invention may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0390] Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases “ranging / ranges between” a first indicate number and a second indicate number and “ranging / ranges from” a first indicate number “to” a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.

[0391] As used herein the term "method" refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the chemical, pharmacological, biological, biochemical and medical arts.

[0392] As used herein, the term “treating” includes abrogating, substantially inhibiting, slowing or reversing the progression of a condition, substantially ameliorating clinical or aesthetical symptoms of a condition or substantially preventing the appearance of clinical or aesthetical symptoms of a condition.

[0393] It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[0394] Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.

[0395] It is the intent of the applicant(s) that all publications, patents and patent applications referred to in this specification are to be incorporated in their entirety by reference into the specification, as if each individual publication, patent or patent application was specifically and individually noted when referenced that it is to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting. In addition, any priority document(s) of this application is / are hereby incorporated herein by reference in its / their entirety.

[0396] Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples.

[0397] EXAMPLES

[0398] Reference is now made to the following examples, which together with the above descriptions illustrate some embodiments of the invention in a non limiting fashion.

[0399] Generally, the nomenclature used herein and the laboratory procedures utilized in the present invention include molecular, biochemical, microbiological and recombinant DNA techniques. Such techniques are thoroughly explained in the literature. See, for example, "Molecular Cloning: A laboratory Manual" Sambrook et al., (1989); "Current Protocols in Molecular Biology" Volumes I-III Ausubel, R. M., ed. (1994); Ausubel et al., "Current Protocols in Molecular Biology", John Wiley and Sons, Baltimore, Maryland (1989); Perbal, "A Practical Guide to Molecular Cloning", John Wiley & Sons, New York (1988); Watson et al., "Recombinant DNA", Scientific American Books, New York; Birren et al. (eds) "Genome Analysis: A Laboratory Manual Series", Vols. 1-4, Cold Spring Harbor Laboratory Press, New York (1998); methodologies as set forth in U.S. Pat. Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and 5,272,057; "Cell Biology: A Laboratory Handbook", Volumes I-III Cellis, J. E., ed. (1994); "Culture of Animal Cells - A Manual of Basic Technique" by Freshney, Wiley-Liss, N. Y. (1994), Third Edition; "Current Protocols in Immunology" Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds), "Basic and Clinical Immunology" (8th Edition), Appleton & Lange, Norwalk, CT (1994); Mishell and Shiigi (eds), "Selected Methods in Cellular Immunology", W. H. Freeman and Co., New York (1980); available immunoassays are extensively described in the patent and scientific literature, see, for example, U.S. Pat. Nos. 3,791,932; 3,839,153; 3,850,752; 3,850,578; 3,853,987; 3,867,517; 3,879,262; 3,901,654; 3,935,074; 3,984,533; 3,996,345; 4,034,074; 4,098,876; 4,879,219; 5,011,771 and 5,281,521; "Oligonucleotide Synthesis" Gait, M. J., ed. (1984); “Nucleic Acid Hybridization" Hames, B. D., and Higgins S. J., eds. (1985); "Transcription and Translation" Hames, B. D., and Higgins S. J., eds. (1984); "Animal Cell Culture" Freshney, R. I., ed. (1986); "Immobilized Cells and Enzymes" IRL Press, (1986); "A Practical Guide to Molecular Cloning" Perbal, B., (1984) and "Methods in Enzymology" Vol. 1-317, Academic Press; "PCR Protocols: A Guide To Methods And Applications", Academic Press, San Diego, CA (1990); Marshak et al., "Strategies for Protein Purification and Characterization - A Laboratory Course Manual" CSHL Press (1996); all of which are incorporated by reference as if fully set forth herein. Other general references are provided throughout this document. The procedures therein are believed to be well known in the art and are provided for the convenience of the reader. All the information contained therein is incorporated herein by reference.

[0400] EXAMPLE 1

[0401] ANG-2 together with different parameters were tested in order to determine the best combination for determining the severity of an infectious disease.

[0402] The different parameters included: age, number of comorbidities, respiratory rate, viral etiology and bacterial etiology, qSOFA score, SIRS score and NEWS score.

[0403] General cohort 1 - adults

[0404] Inclusion criteria:

[0405] Suspected acute infection patients

[0406] • Over 18 years of age

[0407] • Clinical suspicion of acute infection as defined by the attending physician, based on clinical presentation.

[0408] Exclusion criteria:

[0409] Suspected acute infection patients:

[0410] Patients fulfilling the following criteria were not eligible for inclusion in this study:

[0411] • HIV, HBV, active HCV or active Tuberculosis infection (self-declared or known from medical records)

[0412] • Pregnancy- self reported or medically confirmed

[0413] Patients fulfilling the following criteria are not eligible for inclusion in this study:

[0414] • Episode of infection in the last 2 weeks

[0415] • Major trauma and\or burns and\or surgery in the last 2 weeks

[0416] • HIV, HBV, active HCV or active Tuberculosis infection (self-declared or known from medical records)

[0417] • Elective surgery patients

[0418] • Pregnancy- self reported or medically confirmed

[0419] Protein screening:

[0420] Protein screening was performed using either one of the 2 commercially available multiplex immunoassays: Human Magnetic Luminex® Assays and RayBiotech Custom Quantibody® Human Arrays, or a multiplex flex assay developed at MeMed. Briefly, the in-house multiplex assay included 3 proteins (TRAIL, CRP and IP- 10) which were measured using the commercially available MeMed BV® test and additional 6 proteins, measured on the MeMed Key® using 2 different assay cartridges developed for the study. In total, 9 proteins were measured providing absolute protein concentrations. Study cohort included 1939 patients, out of which 306 severe and 1633 non-severe patients. Table 1: Demographics:

[0421] Table 2 Adjudication:

[0422] Table 3: Source of infection:

[0423] The general adult cohort was divided into particular sub-cohorts depending on relevant data for different analyses.

[0424] Sub-cohort 1: Sub-cohort 6: N=866, patients with available comorbidities data

[0425] Sub-cohort 2: Sub-cohort 6: N=899, patients with lower respiratory traction infection (LRTI) Sub-cohort 3: N=l,614, patients with available qSOFA score data

[0426] Sub-cohort 4: N=l,582, patients with available SIRS score data

[0427] Sub-cohort 5: N=556, patients with available pathogen data

[0428] Sub-cohort 6: N=l,470, patients with available respiratory rate data

[0429] Sub-cohort 7: N=l,501, patients with available NEWS data

[0430] Sub-cohort 8: N=l,802, patients with outcome shock data

[0431] Sub-cohort 9: N=l,685 patients with predictive outcome in day 2-3

[0432] Sub-cohort 10: N=l,694, patients with predictive outcome within 24 hours

[0433] Disease etiology was established by applying an expert panel adjudication process or according to the clinical file.

[0434] All patients had a blood sample taken during their ED visit or hospitalization course. Comparisons between the patient groups were carried out for identifying differential markers in blood serum or plasma.

[0435] Severe patients were defined as those who died within 14 days from blood draw, or met any of the following outcomes within 3 days from blood draw:

[0436] 1. Vasopressor therapy or fluid resuscitation (a proxy for septic shock);

[0437] 2. Intubation with mechanical ventilation (IMV, also known as Invasive Mechanical Ventilation); or

[0438] 3. Renal replacement therapy (RRT).

[0439] Measures of biomarker performance:

[0440] • Performance measures for differentiating between severe and non-severe groups included area under the receiver operating characteristic curve (AUC).

[0441] • Performance was benchmarked against potential other combinations of biomarkers and standard of care (SOC) solutions.

[0442] • The biomarker was combined with additional features to improve overall prediction performance and compared to alternative combinations.

[0443] • The analysis also aimed to predict additional clinical endpoints, providing a more comprehensive risk assessment for patient stratification.

[0444] RESULTS

[0445] Combining ANG-2 with patient age outperforms other marker combinations in assessing disease severity, as summarized in Table 4. The analysis was carried out in general cohort 1. Table 4

[0446] Combining ANG-2 with patient comorbidities (i.e. number of diseases) outperforms other marker combinations in assessing disease severity, as summarized in Table 5. Diseases included hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD. The analysis was carried out in sub-cohort 1.

[0447] Table 5

[0448] Combining ANG-2 with a positive or negative ruling of lower respiratory tract infection outperforms other marker combinations in assessing disease severity, as summarized in Table 6. The analysis was carried out in sub-cohort 2.

[0449] Table 6

[0450] Combining the ANG-2 with qSOFA score outperforms other marker combinations in assessing disease severity, as summarized in Table 7. The analysis was carried out in sub-cohort 3. Table 7

[0451] Combining the ANG-2 with SIRS score outperforms other marker combinations in assessing disease severity, as summarized in Table 8. The analysis was carried out in sub-cohort 4. Table 8

[0452] Combining ANG-2 with pathogen data (viral or bacterial etiology) outperforms other marker combinations in assessing disease severity, as summarized in Table 9, herein below. The analysis was carried out in sub-cohort 5. Table 9

[0453] Combining ANG-2 with patient respiratory rate outperforms other marker combinations in assessing disease severity, as summarized in Table 10. The analysis was carried out in sub-cohort 6. Table 10

[0454] Combining the ANG-2 with NEWS score outperforms other marker combinations in assessing disease severity, as summarized in Table 11. The analysis was carried out in sub-cohort 7. Table 11

[0455] ANG-2 alone outperformed other markers in predicting ICU as an endpoint, as summarized in Table 12. The analysis was carried out in general cohort 1.

[0456] Table 12

[0457] ANG-2 outperformed other markers in assessing the risk of septic shock, as summarized in Table 13. The analysis was carried out in sub-cohort 8. Table 13

[0458] ANG-2 outperformed other markers in predicting outcome in day 2-3 from blood draw, as summarized in Table 14. The analysis was carried out in sub-cohort 9.

[0459] Table 14

[0460] ANG-2 outperformed other markers in predicting outcome within 24 hours from blood draw, as summarized in Table 15. The analysis was carried out in sub-cohort 10.

[0461] Table 15

[0462] Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims. It is the intent of the applicant(s) that all publications, patents and patent applications referred to in this specification are to be incorporated in their entirety by reference into the specification, as if each individual publication, patent or patent application was specifically and individually noted when referenced that it is to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting. In addition, any priority document(s) of this application is / are hereby incorporated herein by reference in its / their entirety.

Claims

WHAT IS CLAIMED IS:

1. A method of determining the severity of an infectious disease in a subject comprising:(a) measuring, in a blood sample of the subject, an expression level of Angiogpoietin-2 (ANG-2);(b) generating a score on the basis of said expression level, wherein the score incorporates at least one additional feature selected from the group consisting of age, number of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology; and(c) determining the severity of the infectious disease based on said score, thereby determining the severity of the infectious disease of the subject.

2. The method of claim 1, wherein the determining comprises predicting the likelihood of severity.

3. The method of claim 1, wherein said comorbidities are selected from the group consisting of hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD.

4. The method of claim 1, wherein the score incorporates an indicator of viral etiology.

5. The method of any one of claims 1-4, wherein the score incorporates at least one parameter set forth in Tables B or C.

6. The method of any one of claims 1-4, wherein the score incorporates a clinical index selected from the group consisting of NEWS, NEWS 2, MEWS APACHE I, APACHE II, APACHE III, CURB-65, SMART-COP, SAPS II, SAPS III, SIRS, Shock Index, Phoenix Sepsis Score, ESI, PIM2, CMM, SOFA, qSOFA, MPM, RIFLE, CP, MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukee criteria and Ranson criteria.

7. The method of claim 6, wherein the clinical index is NEWS or qSOFA.

8. The method of any one of claims 1-6, wherein the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

9. The method of any one of claims 1-8, wherein the score provides an indication of the likelihood of at least one of the following outcomes:(a) respiratory failure within three days from blood draw;(b) septic shock within three days from blood draw;(c) renal failure within three days from blood draw; or(d) mortality within 14 days from blood draw.

10. The method of any one of claims 1-9, wherein an increase in an expression of each of said ANG-2 above a corresponding expression level in a control sample is indicative of a higher severity of the infectious disease.

11. The method of any one of claims 1-10, further comprising measuring an expression of at least one additional protein selected from the group consisting of Interferon gamma-induced protein 10 (IP- 10), Interleukin 1 receptor-like 1 (ST2), Tumor necrosis factor-inducible gene 14 protein (TSG-14), Advanced glycosylation end product- specific receptor (RAGE), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor receptor superfamily member 10B (DR5), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) and Mid-regional proadrenomedullin (MR-proADM) and incorporating the expression into the score.

12. The method of claim 11, wherein said at least one additional protein is IP- 10.

13. The method of claim 12, wherein a weight of said IP-10 in the score is increased on inclusion of a positive indicator of said viral etiology.

14. The method of any one of claims 11-13, wherein said expression of no more than four of said at least one additional protein is incorporated into the score.

15. The method of any one of claims 1-14, wherein the severity is stratified according to at least three levels.

16. The method of any one of claims 1-15, wherein the subject shows symptoms of an infectious disease.

17. The method of any one of claims 1-15, wherein the subject does not show symptoms of an infectious disease.

18. The method of any one of claims 1-15, wherein the subject does not have a chronic non-infectious disease.

19. The method of any one of claims 1-18, wherein the blood sample is whole blood or a fraction thereof.

20. The method of claim 19, wherein said fraction comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

21. The method of claim 19, wherein said fraction comprises serum or plasma.

22. A method of treating a subject having an infectious disease comprising:(a) determining the severity of the infection according to any one of claims 1-21; and(b) treating the subject according to the diagnosis of the infection.

23. The method of claim 22, wherein when a severe infection is ruled in, at least one of the following treatments is used: hospitalization, placement in intensive care, mechanical ventilation; non-invasive ventilation, ECMO, renal replacement therapy, cardiac catheterization, Antibiotic treatment, vasopressor therapy, oxygen therapy, surgical intervention, anti-viral drug, immunomodulators drugs, monoclonal antibodies, infusion of blood products, glucocorticoid therapy and / or treatment of last resort.

24. The method of claim 22, wherein when respiratory failure is ruled in for the subject, the subject is treated using Invasive Mechanical Ventilation (IMV).

25. The method of claim 22, wherein when septic shock is ruled in for the subject, the subject is administered with a vasopressor.

26. The method of claim 22, wherein when renal organ failure is ruled in for the subject, the subject is treated with Renal Replacement Therapy (RRT).

27. The method of claim 22, wherein said subject shows symptoms of an infectious disease.

28. The method of claim 27, wherein said symptoms comprise fever.

29. A method of ruling in sepsis or septic shock in a suspect subject comprising:(a) measuring an expression level of ANG-2 in a blood sample of the suspect subject; and(b) ruling in the sepsis or septic shock when the expression level of ANG-2 is above a predetermined amount.

30. A method of ruling out sepsis or septic shock in a suspect subject comprising:(a) measuring an expression level of ANG-2 in a blood sample of the suspect subject; and(b) ruling out the sepsis or septic shock when the expression level of ANG-2 is below a predetermined amount.

31. The method of claim 29 or 30, wherein the suspect subject has a fever.

32. The method of claim 29 or 30, wherein the suspect subject has a qSOFA score > 2.

33. The method of claim 29 or 30, wherein the suspect subject has a qSOFA score < 2.

34. The method of claim 29 or 30, wherein the suspect subject fulfils at least one criteria of SIRS (Systemic Inflammatory Response Syndrome).

35. The method of any one of claims 29-34, further comprising measuring an expression of at least one additional protein selected from the group consisting of ST2, IP- 10, Tumor necrosis factor- inducible gene 14 protein (TSG-14), Advanced glycosylation end productspecific receptor (RAGE), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor receptor superfamily member 10B (DR5), soluble urokinase plasminogen activator receptor (suPAR), C-Reactive protein (CRP), Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) and MR-proADM.

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