Markers for diagnosing infections

Abstract

A method of determining the severity of the disease, in a subject comprising measuring an expression level of at least one protein selected from the group consisting of IP- 10, IL-6, IL- 10, DR5, ANG-2 and ST2 in a sample of the subject; and determining the severity of the disease based on said expression level. Kits for carrying out diagnosis are also disclosed.

Description

[0001] MARKERS FOR DIAGNOSING INFECTIONS

[0002] REEATED APPLICATION

[0003] This application claims the benefit of priority of U.S. Provisional Patent Application Nos. 63 / 699,205 filed on September 26, 2024 and 63 / 792,372 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 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 and WO2018 / 060999.

[0008] SUMMARY OF THE INVENTION

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

[0010] (a) measuring an expression level of a combination of at least three proteins in a blood sample of the subject, the combination comprising:

[0011] (i) Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2); and

[0012] (ii) at least one protein selected from the group consisting of Interferon gamma- induced protein 10 (IP- 10), Interleukin- 10 (IL- 10), Interleukin-6 (IL-6), Tumor necrosis factor ligand superfamily member 10 (TRAIL) and Tumor necrosis factor receptor superfamily member 10B (DR5); and

[0013] (b) diagnosing the infectious disease based on the expression level, thereby diagnosing the infectious disease of the subject. According to embodiments of the invention, the combination comprises ST2.

[0014] According to embodiments of the invention, the combination comprises ST2 and IP- 10.

[0015] According to embodiments of the invention, two of the proteins of the combination are set forth in a row of Table 36.

[0016] According to embodiments of the invention,

[0017] (i) when the expression level of ANG-2 is at least 2 fold higher than a level in a control sample, a severe infectious disease is ruled in;

[0018] (ii) when the expression level of ST2 is at least 3 fold higher than a level in a control sample, a severe infectious disease is ruled in;

[0019] (iii) when the expression level of IL-6 is at least 4.5 fold higher than a level in a control sample, a severe infectious disease is ruled in;

[0020] (iv) when the expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infectious disease is ruled in;

[0021] (v) when the expression level of IP- 10 is at least 4 fold higher than a level in a control sample, a severe infectious disease is ruled in and / or

[0022] (vi) when the expression level of IL- 10 is at least 3 fold higher than a level in a control sample, a severe infectious disease is ruled in.

[0023] According to embodiments of the invention:

[0024] (i) when the expression level of ANG-2 is below about 1800 pg / ml, a severe infectious disease is ruled out;

[0025] (ii) when the expression level of ST2 is below about 28,000 pg / ml, a severe infectious disease is ruled out;

[0026] (iii) when the expression level of IL-6 is below 12 pg / ml, a severe infectious disease is ruled out;

[0027] (iv) when the expression level of DR5 is below about 145 pg / ml, a severe infectious disease is ruled out;

[0028] (v) when the expression level of IP- 10 is below about 100 pg / ml, a severe infectious disease is ruled out; and / or

[0029] (vi) when the expression level of IL- 10 is below about 7 pg / ml, a severe infectious disease is ruled out.

[0030] According to embodiments of the invention:

[0031] (i) when the expression level of ANG-2 is above about 5000 pg / ml, a severe infectious disease is ruled in; (ii) when the expression level of ST2 is above about 140,000 pg / ml, a severe infectious disease is ruled in;

[0032] (iii) when the expression level of IL-6 is above 230 pg / ml, a severe infectious disease is ruled in;

[0033] (iv) when the expression level of DR5 is above 315 pg / ml, a severe infectious disease is ruled in;

[0034] (v) when the expression level of IP- 10 is above 1000 pg / ml, a severe infectious disease is ruled in; and / or

[0035] (vi) when the expression level of IL- 10 is above 35 pg / ml, a severe infectious disease is ruled in.

[0036] According to embodiments of the invention, the combination of proteins in set forth in Table 35.

[0037] According to embodiments of the invention, the diagnosing comprises determining the severity of the infection.

[0038] According to embodiments of the invention, the diagnosing comprises:

[0039] (i) predicting a severity on the same day as blood draw;

[0040] (ii) predicting a severity on a day following blood draw;

[0041] (iii) predicting a severity two-three days following blood draw; or

[0042] (iv) predicting a severity 4-14 days following blood draw.

[0043] According to an aspect of the invention, there is provided a method of determining severity of an infectious disease of a subject, comprising measuring the amount of Tumor necrosis factor receptor superfamily member 10B (DR5) and the amount of at least one protein determinant selected from the group consisting of Interferon gamma- induced protein 10 (IP- 10), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor ligand superfamily member 10 (TRAIL), Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2) in a blood sample of the subject, wherein a combined amount of the DR5 and the protein determinant is indicative of the severity of the infectious disease.

[0044] According to embodiments of the invention, when the amount of DR5 is above 315 pg / ml, a severe infectious disease is ruled in.

[0045] According to embodiments of the invention, when the expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infectious disease is ruled in.

[0046] According to another aspect of the invention there is provided a method of determining severity of an infectious disease of a subject, comprising measuring the amount of at least one protein set forth in Table A in a blood sample of the subject and measuring at least one clinical parameter set forth in Table B or Table C, wherein a combination of the amount of the at least one protein and the clinical parameter is indicative of the severity of the infection.

[0047] According to embodiments of the invention, the at least one protein is ST2.

[0048] According to embodiments of the invention, the at least one protein is at least two proteins set forth in a row of Table 36.

[0049] According to embodiments of the invention, the method further comprises measuring at least one clinical parameter set forth in Table B or C.

[0050] According to embodiments of the invention, the method further comprises measuring all the components of 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, PIM2, CMM, SOFA, qSOFA, MPM, RIFLE, CP, MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukee criteria and Ranson score.

[0051] According to embodiments of the invention, the infection is a viral infection.

[0052] According to embodiments of the invention, the infection is a bacterial infection.

[0053] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0054] According to embodiments of the invention, the subject does not show symptoms of an infectious disease.

[0055] According to embodiments of the invention, the subject does not have a chronic non- infectious disease.

[0056] According to embodiments of the invention, the blood sample is whole blood or a fraction thereof.

[0057] According to embodiments of the invention, the fraction comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

[0058] According to embodiments of the invention, the fraction comprises serum or plasma.

[0059] According to embodiments of the invention, the level of no more than 10 proteins is used to diagnose the infection.

[0060] According to embodiments of the invention, no more than 6 proteins are measured to diagnose the infection.

[0061] According to still another aspect of the invention there is provided a kit for diagnosing an infection comprising detection reagents which specifically detect a combination of proteins set forth in Table 35.

[0062] According to embodiments of the invention, at least one of the proteins is ST2. According to embodiments of the invention, the kit further comprises detection reagents which specifically detect CRP.

[0063] According to embodiments of the invention, the detection reagents are antibodies.

[0064] According to embodiments of the invention, at least one of the antibodies is attached to a detectable moiety.

[0065] According to embodiments of the invention, at least one of the antibodies is a monoclonal antibody.

[0066] According to embodiments of the invention, at least one of the antibodies is attached to a solid support.

[0067] According to embodiments of the invention, the kit comprises detection reagents that specifically detect no more than 10 protein markers.

[0068] According to embodiments of the invention, the kit comprises detection reagents that specifically detect no more than 6 protein markers.

[0069] According to an aspect of the invention, there is provided a method of treating a subject having an infectious disease comprising:

[0070] (a) determining the severity of the infection according to the method disclosed herein; and

[0071] (b) treating the subject according to the diagnosis of the infection.

[0072] 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, kidney replacement therapy and / or treatment of last resort.

[0073] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0074] According to embodiments of the invention, the symptoms comprise fever.

[0075] According to an aspect of the invention there is provided a method of determining the severity of an infectious disease in a subject comprising:

[0076] (a) measuring, in a blood sample of the subject, an expression level of:

[0077] (i) Interleukin 1 receptor-like 1 (ST2);

[0078] (ii) Angiogpoietin-2 (ANG-2); and

[0079] (iii) Interferon gamma-induced protein 10 (IP- 10):

[0080] (b) generating a score on the basis of the expression level; and (c) determining the severity of the infectious disease based on the score, thereby determining the severity of the infectious disease of the subject.

[0081] According to embodiments of the invention, 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.

[0082] 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.

[0083] According to embodiments of the invention, the score incorporates an indicator of viral etiology.

[0084] According to embodiments of the invention, the weight of IP- 10 in the score is increased on inclusion of a positive indicator of the viral etiology.

[0085] According to embodiments of the invention, the score incorporates at least one parameter set forth in Tables B or C.

[0086] 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.

[0087] According to embodiments of the invention, the clinical index is NEWS or qSOFA.

[0088] According to embodiments of the invention, the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

[0089] According to embodiments of the invention, the score provides an indication of the likelihood of at least one of the following outcomes:

[0090] (a) respiratory failure within three days from blood draw;

[0091] (b) septic shock within three days from blood draw;

[0092] (c) renal failure within three days from blood draw; or

[0093] (d) mortality within 14 days from blood draw.

[0094] According to embodiments of the invention, the increase in an expression of each of the ANG-2, the ST2 and the IP- 10 above a corresponding expression level in a control sample is indicative of a higher severity of the infectious disease.

[0095] 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 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.

[0096] 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.

[0097] According to embodiments of the invention, the severity is stratified according to at least three levels.

[0098] According to an aspect of the invention there is provided a method of determining the severity of an infectious disease in a subject comprising:

[0099] (a) measuring, in a blood sample of the subject, an expression level of ST2;

[0100] (b) measuring an additional feature selected from the group consisting of age, number of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology;

[0101] (c) generating a score on the basis of the expression level and the additional feature; and

[0102] (d) determining the severity of the infectious disease based on the score, thereby determining the severity of the infectious disease of the subject.

[0103] 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.

[0104] According to embodiments of the invention, the score incorporates at least one additional parameter set forth in Tables B or C.

[0105] 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.

[0106] According to embodiments of the invention, the clinical index is NEWS or qSOFA.

[0107] According to embodiments of the invention, the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

[0108] 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 ANG-2, 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 and incorporating the expression into the score.

[0109] According to embodiments of the invention, the expression of no more than six of the at least one additional protein is incorporated into the score.

[0110] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0111] According to embodiments of the invention, the subject does not show symptoms of an infectious disease.

[0112] According to embodiments of the invention, the subject does not have a chronic non- infectious disease.

[0113] According to embodiments of the invention, the blood sample is whole blood or a fraction thereof.

[0114] According to embodiments of the invention, the fraction comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

[0115] According to embodiments of the invention, the fraction comprises serum or plasma.

[0116] According to embodiments of the invention, the method further comprises displaying the score on a display.

[0117] According to an aspect of the invention there is provided a method of treating a subject having an infectious disease comprising:

[0118] (a) determining the severity of the infection according to the methods described herein; and

[0119] (b) treating the subject according to the diagnosis of the infection.

[0120] 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, fluid resuscitation, oxygen therapy, surgical intervention, anti-viral drug, immunomodulators drugs, monoclonal antibodies, infusion of blood products, glucocorticoid therapy and / or treatment of last resort.

[0121] According to embodiments of the invention, when respiratory failure is ruled in for the subject, the subject is treated using Invasive Mechanical Ventilation (IMV).

[0122] According to embodiments of the invention, when septic shock is ruled in for the subject, the subject is administered with a vasopressor. According to embodiments of the invention, when renal failure is ruled in for the subject, the subject is treated with Renal Replacement Therapy (RRT).

[0123] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0124] According to embodiments of the invention, the symptoms comprise fever.

[0125] According to an aspect of the invention there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0126] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0127] (b) ruling in the sepsis or septic shock when the expression level of ST2 is above a predetermined amount.

[0128] According to an aspect of the invention there is provided a method of ruling out sepsis or septic shock in a suspect subject comprising:

[0129] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0130] (b) ruling out the sepsis or septic shock when the expression level of ST2 is below a predetermined amount.

[0131] According to embodiments of the invention, the suspect subject has a fever.

[0132] According to embodiments of the invention, the suspect subject has a qSOFA score > 2.

[0133] According to embodiments of the invention, the suspect subject has a qSOFA score < 2.

[0134] According to embodiments of the invention, the suspect subject fulfils at least one criterion of SIRS (Systemic Inflammatory Response Syndrome).

[0135] 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 ANG-2, 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.

[0136] According to embodiments of the invention, the method further comprises measuring an expression of ANG-2 and IP- 10 and generating a score on the basis of an expression of the ST2, the ANG-2 and the IP- 10, wherein the score is indicative of a likelihood of sepsis.

[0137] According to an aspect of the invention there is provided a method of ruling in respiratory failure comprising:

[0138] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and (b) ruling in the respiratory failure when the expression level of ST2 is above a predetermined amount.

[0139] According to an aspect of the invention there is provided a method of treating a subject with an infectious disease comprising:

[0140] (a) ruling in respiratory failure according to claim 44; and

[0141] (b) treating the subject using Invasive Mechanical Ventilation (IMV).

[0142] According to embodiments of the invention, the method further comprises measuring an expression level of ANG-2 and the IP- 10.

[0143] According to an aspect of the invention there is provided a method of ruling in renal failure comprising:

[0144] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0145] (b) ruling in the renal failure when the expression level of ST2 is above a predetermined amount.

[0146] According to an aspect of the invention there is provided a method of treating a subject with an infectious disease comprising:

[0147] (a) ruling in renal failure according to the methods described herein; and

[0148] (b) treating the subject using Renal Replacement Therapy (RRT).

[0149] According to embodiments of the invention, the method further comprises measuring an expression level of ANG-2 and the IP- 10.

[0150] According to still another aspect, there is provided a method of diagnosing an infection or a disease associated with an infection in a subject comprising:

[0151] (a) measuring an expression level of a combination of at least three proteins in a blood sample of the subject, the combination comprising:

[0152] (i) Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2); and

[0153] (ii) at least one protein selected from the group consisting of Interferon gammainduced protein 10 (IP-10), Interleukin- 10 (IL-10), Interleukin-6 (IL-6), Tumor necrosis factor ligand superfamily member 10 (TRAIL) and Tumor necrosis factor receptor superfamily member 10B (DR5); and

[0154] (b) diagnosing the infection or the disease associated with the infection of the subject based on the expression level.

[0155] According to embodiments of the invention, the combination comprises ANG-2, ST2 and optionally IP- 10.

[0156] According to embodiments of the invention, two of the proteins of the combination are set forth in a row of Table 36. According to embodiments of the invention, the expression level of ANG-2 is at least 2 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;

[0157] (ii) when the expression level of ST2 is at least 3 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;

[0158] (iii) when the expression level of IL-6 is at least 4.5 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;

[0159] (iv) when the expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;

[0160] (v) when the expression level of IP- 10 is at least 4 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in and / or

[0161] (vi) when the expression level of IL- 10 is at least 3 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in.

[0162] According to embodiments of the invention:

[0163] (i) when the expression level of ANG-2 is above about 5000 pg / ml, a severe infection or a disease associated with an infection is ruled in;

[0164] (ii) when the expression level of ST2 is above about 140,000 pg / ml, a severe infection or a disease associated with an infection is ruled in;

[0165] (iii) when the expression level of IL-6 is above 230 pg / ml, a severe infection or a disease associated with an infection is ruled in;

[0166] (iv) when the expression level of DR5 is above 315 pg / ml, a severe infection or a disease associated with an infection is ruled in;

[0167] (v) when the expression level of IP- 10 is above 1000 pg / ml, a severe infection or a disease associated with an infection is ruled in; and / or

[0168] (vi) when the expression level of IL- 10 is above 35 pg / ml, a severe infection or a disease associated with an infection is ruled in.

[0169] According to embodiments of the invention, the combination of proteins is set forth in Table 35.

[0170] According to embodiments of the invention, the diagnosing comprises predicting the likelihood of disease progression.

[0171] According to embodiments of the invention, the diagnosing comprises:

[0172] (i) predicting a severity on the same day as blood draw;

[0173] (ii) predicting a severity on a day following blood draw;

[0174] (iii) predicting a severity two-three days following blood draw; or (iv) predicting a severity 4-14 days following blood draw.

[0175] According to still another aspect, there is provided a method of determining severity of an infection or a disease associated with an infection of a subject, comprising measuring the amount of Tumor necrosis factor receptor superfamily member 10B (DR5) and the amount of at least one protein determinant selected from the group consisting of Interferon gamma-induced protein 10 (IP- 10), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor ligand superfamily member 10 (TRAIL), Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2) in a blood sample of the subject, wherein a combined amount of the DR5 and the protein determinant is indicative of the severity of the infection or the disease associated with the infection.

[0176] According to embodiments of the invention, the amount of DR5 is above 315 pg / ml, a severe infection or disease associated with the infection is ruled in and / or when the expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infection or disease associated with the infection is ruled in.

[0177] According to still another aspect, there is provided a method of determining severity of infection or disease associated with the infection of a subject, comprising measuring the amount of at least one protein set forth in Table A in a blood sample of the subject and measuring at least one clinical parameter set forth in Table B or Table C, wherein a combination of the amount of the at least one protein and the clinical parameter is indicative of the severity of the infection or disease associated with the infection.

[0178] According to embodiments of the invention, the at least one protein is ST2.

[0179] According to embodiments of the invention, the at least one protein is at least two proteins set forth in a row of Table 36.

[0180] According to embodiments of the invention, the method further comprises measuring at least one clinical parameter set forth in Table B or C.

[0181] According to embodiments of the invention, the method further comprises measuring all the components of 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, PIM2, CMM, SOFA, qSOFA, MPM, RIFLE, CP, MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukee criteria and Ranson score.

[0182] According to still another aspect, there is provided a method of determining the severity of an infection or a disease associated with the infection in a subject comprising:

[0183] (a) measuring, in a blood sample of the subject, an expression level of:

[0184] (i) Interleukin 1 receptor- like 1 (ST2);

[0185] (ii) Angiogpoietin-2 (ANG-2); and (iii) Interferon gamma- induced protein 10 (IP- 10):

[0186] (b) generating a score on the basis of the expression level; and

[0187] (c) determining the severity of the infection or the disease associated with the infection of the subject based on the score.

[0188] According to embodiments of the invention, the determining the severity comprises ruling in a severe infection or disease associated with the infection.

[0189] According to embodiments of the invention, the determining the severity comprises ruling in a severe infection or disease associated with the infection.

[0190] According to embodiments of the invention, 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.

[0191] 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.

[0192] According to embodiments of the invention, the score incorporates an indicator of viral etiology.

[0193] According to embodiments of the invention, the weight of IP- 10 in the score is increased on inclusion of a positive indicator of the viral etiology.

[0194] According to embodiments of the invention, the score incorporates at least one parameter set forth in Tables B or C.

[0195] 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.

[0196] According to embodiments of the invention, the clinical index is NEWS or qSOFA.

[0197] According to embodiments of the invention, the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

[0198] According to embodiments of the invention, the score provides an indication of the likelihood of at least one of the following outcomes:

[0199] (a) respiratory failure within three days from blood draw;

[0200] (b) septic shock within three days from blood draw;

[0201] (c) renal failure within three days from blood draw; or

[0202] (d) mortality within 14 days from blood draw. According to embodiments of the invention, the increase in an expression of each of the ANG-2, the ST2 and the IP- 10 above a corresponding expression level in a control sample is indicative of a higher severity of the infection or the disease associated with an infection.

[0203] 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 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.

[0204] 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.

[0205] According to embodiments of the invention, the severity is stratified according to at least three levels.

[0206] According to embodiments of the invention, the method further comprises displaying the score on a display.

[0207] According to still another aspect, there is provided a method of determining the severity of an infection or a disease associated with the infection in a subject comprising:

[0208] (a) measuring, in a blood sample of the subject, an expression level of ST2;

[0209] (b) measuring an additional feature selected from the group consisting of age, number or type of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology;

[0210] (c) generating a score on the basis of the expression level and the additional feature; and

[0211] (d) determining the severity of the infection or the disease associated with the infection based on the score, thereby determining the severity of the infection or the disease associated with an infection of the subject.

[0212] 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.

[0213] According to embodiments of the invention, the subject is not diagnosed as having sepsis or septic shock.

[0214] According to embodiments of the invention, the subject is a child or neonate.

[0215] According to embodiments of the invention, the score incorporates at least one additional parameter set forth in Tables B or C. 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.

[0216] According to embodiments of the invention, the clinical index is NEWS or qSOFA.

[0217] According to embodiments of the invention, the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

[0218] 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 ANG-2, 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 and incorporating the expression into the score.

[0219] According to embodiments of the invention, the expression of no more than six of the at least one additional protein is incorporated into the score.

[0220] According to embodiments of the invention, the infection is a viral infection.

[0221] According to embodiments of the invention, the infection is a bacterial infection.

[0222] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0223] According to embodiments of the invention, the subject does not show symptoms of an infectious disease.

[0224] According to embodiments of the invention, the subject does not have a chronic non- infectious disease.

[0225] According to still another aspect, there is provided a method of treating a subject having an infection or disease associated with the infection comprising:

[0226] (a) determining the severity of the infection or disease associated with the infection according to any one of claims 1-52; and

[0227] (b) treating the subject according to the diagnosis of the infection or disease associated with the infection.

[0228] 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, glucocorticoid therapy and / or treatment of last resort.

[0229] According to embodiments of the invention, when the respiratory failure is ruled in for the subject, the subject is treated using Invasive Mechanical Ventilation (IMV); when septic shock is ruled in for the subject, the subject is administered with a vasopressor; and / or. when renal failure is ruled in for the subject, the subject is treated with Renal Replacement Therapy (RRT).

[0230] According to embodiments of the invention, the subject shows symptoms of an infectious disease.

[0231] According to embodiments of the invention, the symptoms comprise fever.

[0232] According to still another aspect, there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0233] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0234] (b) ruling in the sepsis or septic shock when the expression level of ST2 is above a predetermined amount.

[0235] According to still another aspect, there is provided a method of ruling out sepsis or septic shock in a suspect subject comprising:

[0236] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0237] (b) ruling out the sepsis or septic shock when the expression level of ST2 is below a predetermined amount.

[0238] According to embodiments of the invention, the suspect subject has a fever.

[0239] According to embodiments of the invention, the suspect subject has a qSOFA score > 2.

[0240] According to embodiments of the invention, the suspect subject has a qSOFA score < 2.

[0241] According to embodiments of the invention, the suspect subject fulfils at least one criterion of SIRS (Systemic Inflammatory Response Syndrome).

[0242] 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 ANG-2, 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. According to embodiments of the invention, the method further comprises measuring an expression of ANG-2 and IP- 10 and generating a score on the basis of an expression of the ST2, the ANG-2 and the IP- 10, wherein the score is indicative of a likelihood of sepsis.

[0243] According to still another aspect, there is provided a method of ruling in respiratory failure comprising:

[0244] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0245] (b) ruling in the respiratory failure when the expression level of ST2 is above a predetermined amount.

[0246] According to another aspect, there is provided a method of treating a subject with an infection or a disease associated with an infection comprising:

[0247] (a) ruling in respiratory failure as described herein; and

[0248] (b) treating the subject using Invasive Mechanical Ventilation (IMV).

[0249] According to embodiments of the invention, the method further comprises measuring an expression level of ANG-2 and IP- 10.

[0250] According to still another aspect, there is provided a method of ruling in renal failure comprising:

[0251] (a) measuring an expression level of ST2 in a blood sample of the suspect subject; and

[0252] (b) ruling in the renal failure when the expression level of ST2 is above a predetermined amount.

[0253] According to still another aspect, there is provided a method of treating a subject with an infection or a disease associated with an infection comprising:

[0254] (a) ruling in renal failure as described herein; and

[0255] (b) treating the subject using Renal Replacement Therapy (RRT).

[0256] According to embodiments of the invention, the method further comprises measuring an expression level of ANG-2 and IP- 10.

[0257] 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. BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0258] Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

[0259] In the drawings:

[0260] FIGs. 1A-F illustrate exemplary graphic displays which can be used to signal to a user the severity of an infection.

[0261] FIG. 2 illustrates an exemplary graphic user interphase (GUI) for distinguishing between severe and non-severe infections according to an embodiment of the present invention.

[0262] FIG. 3 illustrates an exemplary graphic user interphase (GUI) for distinguishing between severe and non-severe infections according to an embodiment of the present invention.

[0263] FIG. 4 illustrates an exemplary graphic user interphase (GUI) for distinguishing between severe and non-severe infections and further for distinguishing between a bacterial and viral infection according to an embodiment of the present invention.

[0264] DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

[0265] The present invention, in some embodiments thereof, relates to the identification of signatures and determinants associated with bacterial and viral infections.

[0266] 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.

[0267] Differentiating between bacterial and viral infections is a daily clinical challenge. Recent publications have shown that the host response to severe infection display an inflammatory ‘bacterial’ pattern, regardless of the underlying infectious etiology, even at the case of an underlying viral infection (Tang, B.M., Nature Communications 10, 3422. doi: 10.1038 / s41467- 019-11249-y; Dunning, J., et al Nature Immunology 19(6):625-635. doi: 10.1038 / s41590-018- 0111-5).

[0268] By carrying out large clinical studies, the present inventors have now discovered unique proteins present in the blood which serve as markers of infection severity. The present inventors propose diagnosing subjects and making appropriate treatment decisions based on the expression level of such markers. The predictive methods proposed herein are etiology agnostic - i.e. it is not necessary to know the source of the infection or have a definitive diagnosis of infection.

[0269] Whilst further reducing the invention to practice, the present inventors uncovered combinations of such markers which are able to classify infections in terms of severity with a very high degree of accuracy. Such proteins can be combined with additional protein determinants which are able to distinguish between bacterial and viral infections. This enables a highly detailed diagnosis of infections in a relatively short amount of time.

[0270] One particular combination of proteins was shown to be particularly accurate for predicting disease severity. These proteins are: Interleukin 1 receptor-like 1 (ST2); Angiogpoietin-2 (ANG- 2); and Interferon gamma-induced protein 10 (IP-10). Using machine learning, the present inventors have developed an algorithm that considers the expression of each of these proteins. This algorithm generates a score that enables users to easily assess the severity of the infection and make appropriate prognosis, diagnosis and treatment decisions. The present inventors showed that this signature outperformed other markers combinations for determining severity in patients with COVID- 19, diabetes, hypertensive, chronic heart failure, malignancy and immunocompromised patients.

[0271] Thus, according to an aspect of the present invention there is provided a method of diagnosing an infection or disease associated with the infection in a subject comprising:

[0272] (a) measuring an expression level of a combination of at least three proteins in a blood sample of the subject, the combination comprising:

[0273] (i) Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2); and

[0274] (ii) at least one protein selected from the group consisting of Interferon gammainduced protein 10 (IP-10), Interleukin- 10 (IL-10), Interleukin-6 (IL-6), Tumor necrosis factor ligand superfamily member 10 (TRAIL) and Tumor necrosis factor receptor superfamily member 10B (DR5); and

[0275] (b) diagnosing the infection or disease associated with the infection based on the expression level.

[0276] Whilst further reducing the invention to practice, the present inventors uncovered that ST2 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. ST2 was shown to be a particularly accurate marker in predicting a severe outcome in pediatric patients (e.g., predicting organ support outcome). Additional protein determinants may be used in conjunction with ST2 to increase the accuracy of the diagnosis. Furthermore, the present inventors have shown that expression levels of ST2 alone are very accurate for prognosing the severity of infections or diseases associated with infections. In particular, ST2 was shown to be more accurate than other markers for determining severity of an infection in pediatric patients, patients with COVID- 19, hypertensive and potentially immunocompromised patients.

[0277] Thus, according to another aspect of the invention, there is provided a method of determining the severity of an infection or disease associated with the infection in a subject comprising:

[0278] (a) measuring, in a blood sample of the subject, an expression level of ST2;

[0279] (b) measuring an additional feature selected from the group consisting of age, number and / or type of patient comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology;

[0280] (c) generating a score on the basis of the expression level and the additional feature; and

[0281] (c) determining the severity of the infectious disease based on the score, thereby determining the severity of the infection or disease associated with the infection of the subject.

[0282] The term “diagnosing an infection”, or “diagnosing a disease associated with an infection” as used herein refers to determining a severity of the infection or disease associated with the infection, monitoring infection progression, predicting a likelihood of severe outcome, determining prognosis, forecasting an outcome of an infection and / or determining prospects of recovery.

[0283] It will be appreciated that when the diagnosing is used for predicting a likelihood of severe outcome, the patient being analyzed is not in a state which is classified as “severe”. Thus, for example, the patient is classified as being critically ill. For example, the patient is not in need of invasive mechanical ventilation, vasopressor administration and / or renal replacement therapy.

[0284] In a particular embodiment, the diagnosing is carried out in patients with suspected of an acute infection or suspected sepsis. The source of the infection does not need to be known. The diagnosing may be used to predict the likelihood of disease progression in such patients.

[0285] According to an embodiment of this aspect of the present invention, the diagnosing comprises predicting or classifying a severity of the infection or disease associated with the infection.

[0286] The subject is typically suffering from a bacterial or viral infection (although it will be appreciated that a definitive diagnosis is not a prerequisite for carrying out the method.

[0287] The bacterial or viral infection may be an acute or chronic infection. According to a particular embodiment, the subject is suffering from an infectious disease. Examples of such diseases are described herein below.

[0288] According to another embodiment, the subject is suffering from (or suspected of suffering) from a disease associated with an infection e.g. sepsis, as further described below. Information regarding particularly relevant protein markers which may be used for diagnosing (and more specifically for determining severity) is provided in Table A, herein below

[0289] (based on release 2025_01 of UniProtKB, published on Wed Feb 05 2025).

[0290] Table A For example, the protein markers disclosed in Table A may be used to rule in a severe infection or rule in that a disease associated with an infection (e.g. sepsis) will be severe or rule in a non-severe infection or rule in that a disease associated with the infection (e.g. sepsis) will be non- severe. Each of the markers in Table A (except for TRAIL) are increased in severe infection as compared to non-severe infection as further detailed herein below.

[0291] Additionally, or alternatively, the protein markers disclosed in Table A may be used to rule out a severe infection or rule out a severe disease associated with an infection (e.g., sepsis) will be severe or rule out that an infection will be non-severe or rule out that a disease associated with the infection (e.g. sepsis) will be non-severe.

[0292] In some embodiments, at least one of the protein markers disclosed in Table A may be used to rule in a severe viral infection or rule out a severe viral infection.

[0293] Additionally, or alternatively, at least one of the protein markers disclosed in Table A may be used to rule in a non- severe viral infection or rule out a non-severe viral infection.

[0294] In some embodiments, at least one of the protein markers disclosed in Table A may be used to rule in a severe bacterial infection or rule out a severe bacterial infection.

[0295] Additionally, or alternatively, at least one of the proteins disclosed in Table A may be used to rule in a non-severe bacterial infection or rule out a non-severe bacterial infection. When the level of any of the above disclosed proteins (except for TRAIL) are above a predetermined amount, the likelihood of severity is increased. When the level of TRAIL is below a predetermined amount, the likelihood of severity is increased.

[0296] 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.

[0297] 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. According to another embodiment, when the expression level of ANG-2 is below about 1800 pg / ml, the likelihood of a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out. Other exemplary thresholds for ANG-2 that may be used below which a severe infection or disease associated with infection (e.g. sepsis) 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.

[0298] 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.

[0299] According to another embodiment, when the expression level of ST2 is below about 28,000 pg / ml, the likelihood of a severe infection is ruled out. Other exemplary thresholds for ST2 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0300] 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.

[0301] According to another embodiment, when the expression level of DR5 is below about 145 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out. Other exemplary thresholds for DR5 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis)is ruled out include below about 120 pg / ml, below about 110 pg / ml or below about 100 pg / ml.

[0302] According to another embodiment, when the expression level of IL- 10 is below about 7 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out. Other exemplary thresholds for IL- 10 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out include below about 5 pg / ml, 4 pg / ml, below about 3 pg / ml or below about 2 pg / ml.

[0303] According to another embodiment, when the expression level of IL-6 is below about 12 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out. Other exemplary thresholds for IL-6 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0304] Another exemplary threshold for IL-6 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out is below about 40 pg / ml. Other exemplary thresholds for IL-6 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis)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.

[0305] According to another embodiment, when the expression level of IP- 10 is below about 100 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled out. Other exemplary thresholds for IP- 10 that may be used below which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0306] According to another embodiment, when the expression level of ANG-2 is above about 5000 pg / ml, a severe infection 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.

[0307] Other exemplary thresholds for ANG-2 that may be used above which a severe infection or a disease associated with infection (e.g. sepsis) 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.

[0308] 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 or a severe disease associated with infection (e.g. sepsis) may be ruled in.

[0309] According to another embodiment, when the expression level of DR5 is above about 315 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in. Other exemplary thresholds for DR5 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in include above about 300 pg / ml, above about 350 pg / ml or above about 400 pg / ml.

[0310] 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 or a disease associated with infection (e.g. sepsis) may be ruled in.

[0311] According to another embodiment, when the expression level of ST2 is above about 140,000 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in. Other exemplary thresholds for ST2 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in include above about 138, 000 pg / ml, above aboutl50,000 pg / ml, above about 170,000 pg / ml or above about 200,000 pg / ml. Other exemplary thresholds for ST2 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0312] 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 or a severe disease associated with infection (e.g. sepsis) may be ruled in.

[0313] According to another embodiment, when the expression level of IL- 10 is above about 68 pg / ml, a severe infection or a severe response to a disease associated with infection (e.g. sepsis) is ruled in. Other exemplary thresholds for IL- 10 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0314] Other exemplary thresholds for IL- 10 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0315] 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 or a severe disease associated with infection (e.g. sepsis) may be ruled in.

[0316] According to another embodiment, when the expression level of IL-6 is above about 230 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in. Other exemplary thresholds for IL-6 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in include above about 240 pg / ml, above about 245 pg / ml or above about 250 pg / ml.

[0317] Other exemplary thresholds for IL-6 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) 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.

[0318] 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 or a severe disease associated with infection (e.g. sepsis) may be ruled in. According to another embodiment, when the expression level of IP- 10 is above about 1000 pg / ml, a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in. Other exemplary thresholds for IP- 10 that may be used above which a severe infection or a severe disease associated with infection (e.g. sepsis) is ruled in include above about 1050 pg / ml, above about 1100 pg / ml or above about 1200 pg / ml.

[0319] 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 or a severe disease associated with infection (e.g. sepsis) may be ruled in.

[0320] For all the aspects described herein, the term “classifying 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 classification may also be used to prognose the outcome of a patient with an infectious disease. Classifying the severity of the disease may be effected 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.).

[0321] 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 / occur:

[0322] (a) respiratory failure within three days from blood draw;

[0323] (b) septic shock within three days from blood draw;

[0324] (c) renal failure within three days from blood draw; or

[0325] (d) mortality within 14 days from blood draw.

[0326] In one embodiment, the severity can be classified according to the WHO ordinal scale of disease stratification, NEWS (National Early Warning Score), SOFA (Sequential Organ Failure Assessment) score and qSOFA (Quick SOFA) Score for Sepsis.

[0327] In one embodiment, the prediction is accurate on the same day as blood draw.

[0328] In another embodiment, the prediction of severity is accurate on the day after blood draw.

[0329] In still another embodiment, the prediction of severity is accurate for the second and third day following blood draw.

[0330] 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.

[0331] The term “non-severe”, in one embodiment, refers to an infection or a disease associated with infection (e.g. sepsis) that will not require vasopressor therapy, will not require intubation with mechanical ventilation, will not require non-invasive ventilation, will not be admitted to the intensive care unit and / or will not be predicted to die within 14 days.

[0332] Particular combinations of the above disclosed markers that have shown a very high degree of accuracy in determining / predicting severity of infection or disease associated with infection (e.g. sepsis) include ANG-2 and IP- 10; ST2 and IP- 10; and ANG-2 and ST2.

[0333] The following triplets are contemplated for diagnosing severity of infections or diseases associated with infection (e.g. sepsis) (or predicting a severe outcome): ST2, IP- 10 and ANG-2; ST2, IP- 10 and TRAIL; ST2, IP- 10 and IL-6; ST2, IP- 10 and IL- 10; ST2, IP- 10 and DR5; ST2, ANG-2 and TRAIL; ST2, ANG-2 and IL-6; ST2, ANG-2 and IL- 10; ST2, ANG-2 and DR5; ST2, TRAIL and IL-6; ST2, TRAIL and IL- 10; ST2, TRAIL and DR5; ANG-2, IL-6 and IL- 10; ANG- 2, IL-6 and DR5; ANG-2, TRAIL and IL- 10; ANG-2, TRAIL and IL-6; ANG-2, TRAIL and DR5.

[0334] Exemplary combinations include: ST2, IP- 10, ANG-2 and IL- 10; ST2, IP- 10, ANG-2 and IL-6; ST2, IP- 10, TRAIL and ANG-2; ST2, TRAIL, IP- 10 and CRP; ST2, ANG-2, DR5 and IL- 6; ST2, ANG-2, DR5 and IL- 10; ST2, ANG-2, TRAIL and IL-6; ST2, ANG-2, TRAIL and IL- 10; ST2, IL-6, TRAIL and DR5; ST2, IL-6, TRAIL and IL- 10; ST2, IL-6, TRAIL and IP- 10; ST2, ANG-2, TRAIL and IP-10; ST2, ANG-2, TRAIL and DR5; ST2, IP-10, TRAIL, ANG-2 and IL- 6; ST2, IP- 10, TRAIL, ANG-2 and IL- 10; ST2, TRAIL, IP- 10, CRP and ANG-2; ST2, TRAIL, IP- 10, CRP and IL- 10; ST2, TRAIL, IP- 10, CRP and IL-6; ST2, TRAIL, ANG-2, DR5 and IL-6; ST2, TRAIL, ANG-2, DR5 and IL-10; ST2, IP-10, ANG-2, DR5 and IL-6; ST2, IP-10, ANG-2, DR5 and IL- 10.

[0335] According to a specific embodiment, the following combination is contemplated - ST2, ANG-2 and IP- 10. This combination is referred to herein as the “signature”.

[0336] As shown in Table 63, the signature is more effective than other protein signatures in ruling in a severe infection on the same day, and predicting one day and 2-3 days following blood draw. In addition, it is effective at predicting death at days 4-14 following blood draw. Furthermore, as shown in Table 65, the signature is more effective than other standard of care (SOC) tools in ruling in a severe infection on the same day, one day and 2-3 days following blood draw. In addition, it is effective at predicting death at days 4-14 following blood draw. Thus, the signature may be considered as time to outcome (TTO) agnostic.

[0337] In one embodiment, the expression level of each of the markers of the signature is used to rule in, (or predict) a severe infection or disease associated with infection (e.g. sepsis) or rule in (or predict) a non-severe infection or disease associated with infection (e.g. sepsis). Additionally, or alternatively, each of the markers is used to rule out a severe infection or disease associated with infection (e.g. sepsis) (or predict the absence of a severe infection or disease associated with infection (e.g. sepsis)) or rule out a non-severe infection or disease associated with infection (e.g. sepsis) (or predict the absence of a non-severe infection or disease associated with infection (e.g. sepsis)). Each of the markers of the signature are increased in severe infection as compared to non-severe infection as further detailed herein below.

[0338] In some embodiments, the expression level of each of the markers of the signature are used to rule in a severe viral infection (or predict a severe viral infection) or rule out a severe viral infection (or predict the absence of a severe viral infection).

[0339] Additionally, or alternatively, the expression level of each of the markers of the signature is used to rule in (or predict a future presence of) a non- severe viral infection or rule out (or predict a future absence of) a non-severe viral infection.

[0340] In some embodiments, the expression level of each of the markers of the signature is used to rule in (or predict a future presence of) a severe bacterial infection or rule out (or predict a future absence of) a severe bacterial infection.

[0341] Additionally, or alternatively, the markers of the signature are used to rule in (or predict a future presence of) a non-severe bacterial infection or rule out (or predict a future absence of) a non-severe bacterial infection. When the level of any of the markers is above a predetermined amount, a severe infection may be ruled in / predicted.

[0342] According to embodiments of the invention, the expression levels of the markers disclosed herein (e.g., those of the signature) are used to generate a score.

[0343] According to a specific embodiment, determination of severity (or prediction thereof) of the infectious disease 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.

[0344] 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.

[0345] 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 %.

[0346] 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.

[0347] 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.

[0348] In one embodiment, the output is presented graphically. In another embodiment, the output is presented numerically (e.g. as a probability). In another embodiment, the output is generated using a color index (for example in a bar display) where one color indicates high likelihood of severe outcome and another color low likelihood of severe outcome. The strength of the color or the actual color correlates with the probability of severe outcomes. An example of a suitable graphic display is presented in Figures 1A-F. FIG. 1A illustrates an embodiment in which the graphic display includes a bar display in which one end of the bar (the left end in the present example) corresponds to no likelihood of severe outcome and is colored by a first color, the other end of the bar (the right end in the present example) corresponds to 100% likelihood of severe outcome and is colored by a second color, where the color varies gradually from the first to the second color over the bar. FIG. IB illustrates an embodiment in which the graphic display includes a bar display with two distinct segment, where a first segment indicates low likelihood of severe outcome and a second segment indicates high likelihood of severe outcome. FIG. 1C illustrates an embodiment in which the graphic display includes a bar display with three distinct segment, where a first segment indicates very low likelihood of severe outcome, a second segment indicates low likelihood of severe outcome and a third segment indicates high likelihood of severe outcome. FIG. ID illustrates an embodiment in which the graphic display includes a bar display with three distinct segments, where a first segment indicates low likelihood of severe outcome, a second segment indicates moderate likelihood of severe outcome and a third segment indicates very high likelihood of severe outcome. FIG. IE illustrates an embodiment in which the graphic display includes a bar display with four distinct segment, where a first segment indicates very low likelihood of severe outcome, a second segment indicates low likelihood of severe outcome, a third segment indicates moderate likelihood of severe outcome and a fourth segment indicates a very high likelihood of severe outcome. FIG. IF illustrates an embodiment in which the graphic display includes a bar display with five distinct segments, where a first segment indicates very low likelihood of severe outcome, a second segment indicates low likelihood of severe outcome, a third segment indicates moderate likelihood of severe outcome, a fourth segment indicates a high likelihood of severe outcome and a fifth segment indicates very high likelihood of severe outcome. Exemplary graphical user interfaces which can be used in order to indicate likelihood of severity are described herein below.

[0349] According to a particular embodiment, the score incorporates the expression level of the signature and at least one of IL- 10, IL-6, TRAIL, CRP or DR5. Exemplary factors that can be combined with the signature (e.g. incorporated into the score) or combined with individual markers or combinations of two of the markers of the signature for determining / predicting severity of infection or disease associated with infection (e.g. sepsis) include at least one of the following:

[0350] 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)

[0351] 2. Weighted comorbidity burden (e.g., Charlson Comorbidity Index score)

[0352] 3. Age

[0353] 4. Heart rate

[0354] 5. Mean arterial pressure (e.g., a weighted average of systolic and diastolic blood pressure)

[0355] 6. Systolic Blood Pressure

[0356] 7. Diastolic Blood Pressure

[0357] 8. Respiratory rate

[0358] 9. Blood Oxygen Saturation

[0359] 10. Immunodeficiency

[0360] 11. Indicator of a viral infection etiology

[0361] 12. Indicator of a bacterial infection etiology

[0362] 13. Number of SIRS criteria met

[0363] 14. Risk assessment scores: indicator of meeting two or more SIRS, qSOFA, SOFA, ESI, Shock index, MEWS and CURB -65 criteria

[0364] 15. NEWS / NEWS2 clinical score

[0365] 16. Indicator on the source of infection (e.g., when subject is known to have a lower respiratory tract infection).

[0366] 17. Complete blood count

[0367] 18. Metabolic panel

[0368] 19. Blood gases

[0369] 20. Patient medical history including the need for past ventilation / ICU admission / admissions within last month

[0370] 21. Need for recent hospitalization / prior sepsis related hospitalization

[0371] 22. Hospital / ER Ratio

[0372] 23. Imaging data 24. presence of a particular comorbidity (e.g. presence of one of the following diseases - COVID- 19, hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD).

[0373] Additional factors that can be incorporated into the score for diagnosing infection and in particular for classifying severity or predicting 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, as summarized in Table B or C, herein below.

[0374] 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.

[0375] In one embodiment at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 of the clinical parameters disclosed in Tables B or C are combined with at least one (e.g. ST2), at least two (e.g. ST2 and ANG-2 or ST2 and IP-10) or at least three of the proteins disclosed in Table A (e.g. each of the proteins of the signature) for determining / predicting severity.

[0376] In one embodiment at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 of the clinical parameters disclosed in Tables B or C are combined with the two proteins disclosed in Table 36 for determining / predicting severity.

[0377] In still another embodiment at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,

[0378] 18, 19, 20 of the clinical parameters disclosed in Tables B or C are combined with the three proteins disclosed in any row of Table 35 (e.g., the proteins of the signature) for determining / predicting severity. Other marker combinations which can be combined with any number of clinical parameters disclosed in Tables B or C include: ST2+ANG-2+IP-10+ MR-pro- ADM; ST2+PCT+ MR-pro-ADM; ANG-2+ PCT+ MR-pro-ADM; IP- 10+ PCT+ MR-pro-ADM; ST2+ANG-2+ PCT+ MR-pro-ADM;

[0379] Table B

[0380]

[0381] Table C

[0382] Table D, herein below indicates the association of exemplary clinical parameters with severity.

[0383] Table D

[0384] According to a specific embodiment, the above disclosed protein levels (either alone, as single markers or in combinations, such as those of the signature) are used to provide a risk assessment of the subject.

[0385] The term “risk assessment” refers to as assignment of a probability 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.

[0386] 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.

[0387] 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.

[0388] Thus, for example, the proteins described herein (e.g. at least one of ANG-2 or ST2, or the proteins of the signature) 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 (CTAS).

[0389] In another embodiment, the risk assessment is made in the intensive care unit of a hospital, Step-down unit or post-OP of a hospital.

[0390] 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.

[0391] 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, 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.

[0392] When a patient has been assessed as being at low risk, the management course is typically less aggressive than if he had not been assessed as being at low risk. Thus, treatment options such as taking off mechanical ventilation, taking off life support, vasopressor or Inotropic support, removal of catheterization, removal of supportive care (e.g., oxygen, fluids, etc.), termination of sepsis bundle / treatment protocols, stop antibiotic treatment or broad spectrum Abx, stop hemofiltration non-invasive high monitoring, stop invasive and continuous monitoring, sedation, taking out of intensive care admission, stopping drug of last resort, and release from hospital 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 low risk.

[0393] 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.

[0394] In one embodiment, the risk analysis is carried out together with all the parameters of a clinical index of the subject.

[0395] Exemplary clinical indices include but are not limited to Acute Physiology and Chronic Health Evaluation (APACHE II) as a measure of how likely 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- 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 interventionand; 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.

[0396] According to one embodiment, the clinical index is NEWS, NEWS 2 and MEWS.

[0397] 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 additional 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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. 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. On the basis of the classification of the infection, clinical decisions may be made.

[0402] According to some embodiments of the invention, the method further comprises informing the subject of results of the classification.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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).

[0407] 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.

[0408] Also contemplated are plasma treatments from infected persons who survived and / or antiHIV drugs such as lopinavir and ritonavir, as well as chloroquine.

[0409] 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. If a severe bacterial infection is ruled in, the subject may be treated with an antibiotic or other antibacterial agents.

[0410] 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.

[0411] 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.

[0412] If a severe infection is ruled in, the subject may be treated with an immunomodulatory drug.

[0413] 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).

[0414] 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). Once the classifications are made, additional tests may be made in order to corroborate the result or to further classify the infectious agent.

[0415] Examples of such tests include PCR analysis, sequencing analysis, viral culture, antibody or antigen testing.

[0416] Particular actions that may be carried out once a severe bacterial infection is ruled in are summarized below:

[0417] Blood Cultures and Antibiotic Susceptibility Testing (AST): Obtain blood cultures to identify the causative organism and perform AST to tailor antibiotic therapy effectively.

[0418] 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.

[0419] Enhanced Source Control: Prompt initiation of procedures to eliminate the infection source, such as drainage or debridement.

[0420] Diagnostic Imaging: Order targeted imaging studies to locate occult bacterial sources based on risk indicators.

[0421] Infection Isolation Protocols: Implement appropriate isolation measures to prevent nosocomial spread.

[0422] Particular actions that may be carried out once a severe viral infection is ruled in are summarized below:

[0423] Viral Panel Testing: Order comprehensive viral panels to identify the specific viral pathogen involved.

[0424] Treatment with Immunomodulators: Initiate immunomodulatory therapies when appropriate to modulate the immune response to the viral infection.

[0425] Antiviral Treatment Initiation: Start antiviral medications promptly when the tool indicates a high risk of viral infection.

[0426] Avoidance of Unnecessary Antibiotics: Reduce antibiotic usage to prevent resistance and side effects when bacterial infection is unlikely.

[0427] Supportive Care Enhancement: Focus on symptom management, hydration, and monitoring for viral complications.

[0428] Public Health Reporting: Notify public health authorities if a contagious viral pathogen is suspected.

[0429] Particular actions that may be carried out once death is predicted are summarized below:

[0430] Aggressive Management Strategies: Intensify therapeutic interventions for patients at high risk of mortality. Early Palliative Care Consultation: Engage palliative care services to support patient and family needs.

[0431] Ethical Decision-Making Support: Facilitate discussions about goals of care and advanced directives.

[0432] Particular actions that may be carried out once ICU admission is predicted are summarized below:

[0433] Proactive ICU Transfer: Expedite admission to intensive care for patients identified as high risk.

[0434] Resource Allocation: Allocate critical care resources efficiently based on risk stratification.

[0435] Enhanced Monitoring: Implement continuous monitoring protocols in the ED while awaiting ICU transfer.

[0436] Particular actions that may be carried out once Invasive mechanical ventilation (IMV) is predicted are summarized below:

[0437] Blood Gas Analysis: Perform arterial blood gas (ABG) tests to assess oxygenation and ventilation status, guiding respiratory support decisions.

[0438] Continuous Monitoring: Implement continuous monitoring of vital signs, oxygen saturation, and end-tidal CO2 to detect early signs of deterioration.

[0439] Early Airway Management: Prepare for potential intubation by assembling necessary equipment and personnel ahead of time.

[0440] Preventative Respiratory Support: Initiate non-invasive ventilation methods when appropriate to delay or prevent the need for IMV.

[0441] Respiratory Therapy Consultation: Involve respiratory specialists early to optimize ventilation strategies and weaning protocols.

[0442] Particular actions that may be carried out once shock is predicted are summarized below:

[0443] Rapid Hemodynamic Support: Begin aggressive fluid resuscitation and vasopressor therapy promptly.

[0444] Advanced Monitoring Techniques: Use central venous pressure monitoring or other invasive methods to guide therapy.

[0445] Multidisciplinary Team Activation: Assemble a team including cardiology and critical care specialists.

[0446] When the time to outcome is predicted for the same day, the following actions may be taken: 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.

[0447] Immediate Intervention Protocols: Prioritize these patients for the fastest possible diagnostic testing and treatment initiation.

[0448] Frequent Clinical Reassessments: Increase the frequency of vital sign monitoring and patient evaluations to quickly identify any changes in condition.

[0449] Emergency Response Activation: Alert rapid response or code teams to be on standby for potential critical interventions.

[0450] When the time to outcome is predicted for between 2-14 days, the following actions may be taken:

[0451] Ongoing Monitoring: Maintain regular monitoring of vital signs, laboratory results, and clinical observations to detect any signs of improvement or deterioration over this period.

[0452] 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.

[0453] Adjust Treatment Plans Accordingly: Use insights from repetitive assessments to modify treatment strategies, such as adjusting medications or initiating new interventions.

[0454] Early Detection of Complications: Continuous monitoring allows for prompt identification of potential complications, enabling timely interventions.

[0455] Patient and Family Education: Provide guidance on symptoms to watch for and instructions on when to seek immediate medical attention.

[0456] Care Coordination: Collaborate with multidisciplinary teams, including specialists, nursing staff, and outpatient services, to ensure comprehensive care throughout the extended timeframe.

[0457] Particular action that may be carried out once septic shock is predicted is treatment with vasopressors.

[0458] Particular action that may be carried out once septic shock is predicted is to initiate the sepsis bundle.

[0459] Other actions that may be carried out once septic shock is predicted are as follows:

[0460] • Early antibiotic administration: Initiate within the first hour of recognizing sepsis.

[0461] • Fluid resuscitation protocols: Employ dynamic hemodynamic assessment to guide therapy.

[0462] • Early initiation of vasopressor support: Use agents like norepinephrine or vasopressin if needed.

[0463] • Rapid source control: Identify and manage the infection source promptly. • Use of MABs targeting endotoxins: e.g. edobacomab

[0464] Particular action that may be carried out once renal failure or Acute Kidney Injury (AKI) is predicted is to initiate Renal replacement therapy.

[0465] Other actions that may be carried out once organ failure is predicted are as follows:

[0466] • Organ supportive therapy: Provide interventions like dialysis for kidney failure or mechanical ventilation for respiratory failure.

[0467] • Serial monitoring: Regularly assess organ- specific laboratory values to detect deterioration.

[0468] • Preventive strategies: Implement measures to protect at-risk organs, such as nephroprotective protocols.

[0469] • Assess need for ECMO (Extracorporeal Membrane Oxygenation): Evaluate extracorporeal membrane oxygenation for severe cardiac or respiratory failure.

[0470] • Use of targeted therapies, including MABs: For example, vilobelimab.

[0471] Particular action that may be carried out once respiratory failure is predicted is to initiate Invasive Mechanical Ventilation (IMV).

[0472] Other actions that may be carried out once respiratory failure is predicted are set forth below:

[0473] • Early use of non-invasive ventilation: Utilize CPAP or BiPAP to support breathing.

[0474] • Prone positioning: Apply for patients at risk of acute respiratory distress syndrome (ARDS).

[0475] • High-flow nasal cannula (HFNC / Vapoterm): Use to prevent intubation in patients with hypoxemia.

[0476] • Continuous monitoring: Perform pulse oximetry and frequent arterial blood gas (ABG) measurements.

[0477] • Intubation and mechanical ventilation: Proceed if non-invasive methods are insufficient.

[0478] • Treatment with immunomodulators: Administer agents like dexamethasone to reduce inflammation.

[0479] • Consider MABs for specific respiratory conditions: For instance, benralizumab has been identified as a potential treatment for asthma and COPD exacerbations.

[0480] Particular actions that may be carried out once the risk of mortality is ruled in include the following:

[0481] • Early aggressive management: Implement protocols like early goal-directed therapy and the Sep-1 bundle to address sepsis and related conditions promptly. • Advance care planning discussions: Engage in multidisciplinary rounds with specialists to align treatment with patient goals.

[0482] • Palliative care consultation: Initiate when appropriate to manage symptoms and improve quality of life.

[0483] • Consult ICU for admission: Evaluate the need for intensive care unit admission based on patient severity.

[0484] • Consider prophylactic anticoagulation: Administer to prevent thromboembolic events in high-risk patients.

[0485] • Administer broad-spectrum antibiotics: Provide as indicated to combat potential infections.

[0486] • 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.

[0487] 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 13, 18, 21 or 22 years). For example, the subject may be between 3 months and 13 years of age. 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.

[0488] The subject of this aspect of the present invention may have symptoms of an infection.

[0489] Exemplary symptoms include, but are not limited to fever, headache, cough, runny nose, chills, muscle aches, loss of taste and / or loss of smell.

[0490] According to a particular embodiment the subject has diabetes.

[0491] According to another embodiment, the subject has cancer.

[0492] According to still another embodiment, the subject has been diagnosed as hypertensive.

[0493] According to other embodiments, the subject is obese, has chronic kidney disease and / or is diagnosed as having COPD.

[0494] 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.

[0495] 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.

[0496] 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.

[0497] According to another embodiment, the subject is asymptomatic.

[0498] It will be appreciated, whether symptomatic or asymptomatic, the subject may or may not be contagious.

[0499] 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.

[0500] In another embodiment, the subject does not have a coronoary disease.

[0501] 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.

[0502] In one embodiment, the subject is hospitalized.

[0503] In another embodiment, the subject is non-hospitalized.

[0504] According to yet another aspect there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0505] (a) measuring an expression level of ST2 in a blood sample of the subject; and

[0506] (b) ruling in the sepsis or septic shock when the expression level of ST2 is above a predetermined amount.

[0507] According to yet another aspect there is provided a method of ruling in sepsis or septic shock in a suspect subject comprising:

[0508] (a) measuring an expression level of ST2, ANG-2 and IP- 10 in a blood sample of the subject; and

[0509] (b) ruling in the sepsis or septic shock when the expression level of ST2, ANG-2 and IP- 10 is above a predetermined amount.

[0510] Septic shock is a subset of sepsis in which underlying circulatory and cellular / metabolic abnormalities are profound enough to substantially increase mortality.

[0511] 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).

[0512] In one embodiment, the method is carried out on a subject having ESI<=3, CURB-65>=1 or NEWS>=5.

[0513] In another embodiment, the test 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 mdcalc(dot)com / calc / 2654 / qsofa-quick-sofa-score-sepsis.

[0514] In another embodiment, the test is carried out on a subject having a qSOFA score < 2.

[0515] In still another embodiment, the test 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 PaCCh <32 mmHg and WBC >12,000 / mm3, <4,000 / mm3, or >10% immature forms. For additional details see for example mdcalc(dot)com / calc / 1096 / sirs-sepsis-septic-shock- criteria.

[0516] Ruling in of sepsis or septic shock may be carried out by measuring, in addition to ST2, expression levels of additional proteins, including but not limited to ANG-2, 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.

[0517] It will be appreciated that the signature described herein above is particularly useful for ruling in sepsis and / or septic shock. Thus, the method contemplates measuring an expression of ST2, ANG-2 and IP- 10 and generating a score on the basis of an expression of the ST2, ANG-2 and the IP- 10, wherein the score is indicative of a likelihood of sepsis and / or septic shock.

[0518] 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.

[0519] 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).

[0520] In another embodiment, sepsis is diagnosed in a subject suspected of having an infection and which fulfils two or more of the three criteria:

[0521] Respiratory rate greater or equal to 22 / min;

[0522] Altered mentation (e.g., a Glasgow coma score of less than 15);

[0523] Systolic blood pressure lower than or equal to_100mmHg.

[0524] Further criteria for diagnosing sepsis are disclosed in Singer et al. 2016, 315(8):801-810 JAMA.

[0525] 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.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] 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. 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.

[0530] 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.

[0531] 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.

[0532] According to a specific embodiment, the proteins (e.g., ST2, ANG-2 and IP-10) are detected using lateral flow immunoassay.

[0533] 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. 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.

[0534] 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.

[0535] 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.

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] 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.

[0542] 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.

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] In particular embodiments, the antibodies of the present invention comprise monoclonal antibodies.

[0548] In other embodiments, the antibodies of the present invention comprise polyoclonal antibodies.

[0549] 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.

[0550] 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 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].

[0551] 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).

[0552] 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).

[0553] 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).

[0554] 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).

[0555] 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).

[0556] 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 Ml 81 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).

[0557] 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).

[0558] 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 (Cl 688) (MilliporeSigma).

[0559] 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, fraction of whole blood, capillary blood, serum, plasma, saliva, mucus, breath, urine, cerebral spinal fluid, tears, interstitial fluid, mucus, nasal mucus, amniotic fluid, sample collected by a nasal swab, or the like, sputum, sweat, stool, hair, seminal fluid, biopsy, rhinorrhea, tissue biopsy, cytological sample, platelets, reticulocytes, leukocytes, epithelial cells, or whole blood cells.

[0560] 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.

[0561] 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.

[0562] According to a particular embodiment, the infection that is diagnosed is an acute infection.

[0563] Exemplary viral diseases which may be diagnosed according to the methods described herein are summarized in Table E. Table E

[0564]

[0565] According to a specific embodiment, the viral disease is COVID- 19.

[0566] Exemplary virus-causing families are summarized in Table F, herein below.

[0567] Table F

[0568] According to another specific embodiment, the virus is Human metapneumovirus, Bocavirus or Enterovirus.

[0569] According to another specific embodiment, the virus is RSV, Flu A, Flu B, HCoV or SARS- Cov-2.

[0570] Examples of coronaviruses include: human coronavirus 229E, human coronavirus OC43, SARS-CoV, HCoV NE63, HKU1, MERS-CoV and SARS-CoV-2. According to a particular embodiment, the coronavirus is SARS-CoV-2.

[0571] 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.

[0572] 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.

[0573] The term "Gram- negative bacteria" refers to bacteria that do not retain the crystal violet dye in the Gram staining protocol.

[0574] 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.

[0575] In order to diagnose infections (e.g. determine 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.

[0576] Preferably the combinations which are tested to classify the infectious disease do not exceed 50, 40, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3, or 2 markers. In another embodiment, no more than 40 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 30 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 20 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 10 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 9 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 8 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 7 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 6 protein markers are analyzed in a single test / analysis, for the classification. In another embodiment, no more than 5 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 4 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 3 protein markers are analyzed in a single test / analysis for the classification. In another embodiment, no more than 2 protein markers are analyzed in a single test / analysis for the classification. Performance and Accuracy Measures of the Invention.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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).

[0585] 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. 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.

[0586] Construction of determinant Panels

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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.

[0594] Construction of Clinical Algorithms

[0595] 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.

[0596] 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. 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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.

[0601] Some determinants may exhibit trends that depends on the patient age (e.g. the population baseline may rise or fall as a function of age). One can use a '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.

[0602] In the context of the present invention the following statistical terms may be used:

[0603] “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.

[0604] “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. “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.

[0605] “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.

[0606] “Sensitivity” is calculated by TP / (TP+FN) or the true positive fraction of disease subjects.

[0607] “Specificity” is calculated by TN / (TN+FP) or the true negative fraction of non-disease or normal subjects.

[0608] "Total accuracy" is calculated by (TN + TP) / (TN + FP +TP + FN).

[0609] “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.

[0610] “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.

[0611] "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).

[0612] 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.

[0613] “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.

[0614] A “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, 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 (ELDA), Support Vector Machines (SVM), Random Forest (RF), Recursive Partitioning Tree (RPART), as well as other related decision tree classification techniques, Shrunken Centroids (SC), StepAIC, Kth-Nearest Neighbor, Boosting, Decision Trees, Neural Networks, Bayesian Networks, and Hidden Markov Models, among others. Other techniques may be used in survival and time to event hazard analysis, including Cox, 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, 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 10-Fold cross-validation (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.

[0615] 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.

[0616] “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.

[0617] “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.

[0618] 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.

[0619] Kits

[0620] 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. 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] In one embodiment, the kit comprises at least three antibodies which recognize a combination of at least 3 different proteins, namely ST2, ANG-2 and IP- 10.

[0627] In one embodiment, the kit comprises at least three antibodies which recognize a combination of at least 3 different proteins, the combination being set forth in Table 35.

[0628] In one embodiment, the kit comprises at least one antibody which binds specifically to ST2 and one that binds specifically to IP- 10.

[0629] In another embodiment, the kit comprises at least one antibody which binds specifically to ST2 and one that binds specifically to ANG-2, IE- 10, DR5, IE-6, TRAIL or any combination thereof. The kit may further comprise antibodies which specifically detect CRP. 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.

[0630] 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.

[0631] 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.

[0632] As mentioned herein above, the present inventors contemplate computer-implemented methods for generating a graphical scale on a graphical user interface (GUI) indicative of likelihood of a severe and / or non-severe outcome of an infectious disease.

[0633] The method comprises: displaying on a display device a graphical user interface (GUI) optionally and preferably having a calculation activation control; receiving values of biomarkers in the blood of a subject; automatically calculating a score based on the values; generating on the GUI a graphical scale indicative of likelihoods for severe and / or non- severe outcome of an infectious disease; and generating a mark on the scale at a location corresponding to the score.

[0634] In some embodiments of the present invention the graphical scale or the mark are generated responsively to an activation of the calculation activation control by a user. In some embodiments of the present invention the graphical scale or the mark are generated automatically immediately after the values of biomarkers are received. In some embodiments of the present invention the graphical scale is generated before the values of biomarkers are received or, if employed, before activation of the calculation activation control by a user, and the mark is generated automatically immediately after the values of biomarkers are received.

[0635] FIGs. 2 and 3 are screenshots of exemplary graphical user interfaces (GUI) suitable for receiving user input in a computer-implemented method for analyzing biological data in order to determine severity of an infection.

[0636] The GUI may comprise a calculation activation control 10, that may be in the form of a button control. The GUI may also comprise a plurality of expression value input fields 12, wherein each expression value input field is configured for receiving from a user an expression value of a biomarker (e.g., polypeptide or RNA) in the blood of a subject, wherein a combination of the biomarkers is informative about the severity of an infectious disease. Exemplary polypeptides that can be used as markers include ST2, ANG-2 and IP- 10. Other signatures that may be used in order to determine severity of infection are disclosed in W02024 / 018470, the contents of which are incorporated herein by reference. The user feeds into the input fields the values of the biomarkers (e.g., expression value of the polypeptides). Alternatively, the values can be received by establishing a communication between the computer and an internal or external machine that measures the values. In these embodiments, it is not necessary for the user to manually feed the expression values into the input fields. In some embodiments, the GUI comprises a communication control 14, e.g., in the form of a button control, wherein the communication with the external machine is in response to an activation of the communication control by the user.

[0637] The computer calculates a score based on the combined expression values as received. Optionally, this is responsive to an activation of by the user. Alternatively, the mark is generated automatically immediately after the values of biomarkers are received. The score can be the likelihood of a severe and / or non-severe outcome. Optionally, the computer can calculate a score 32 for each individual biomarker value.

[0638] A graphical display can be generated on the GUI, to indicate severity of the infection. In one embodiment, the graphical display is a graduated color index such as that portrayed in FIG. 1A. Alternatively, the graphical display can be divided into a number of subsections, each subsection corresponding to a particular likelihood. It will be appreciated that the graphical display can also be a scale without color or a number without a scale.

[0639] For example, when the display is divided into two subsections, one subsection may indicate a low likelihood of severe outcome and the other subsection may indicate a high likelihood of severe outcome (see for example FIG. IB).

[0640] When the display is divided into three subsections, one subsection may indicate a very low likelihood of severe outcome, the second may indicate a low likelihood of severe outcome and the third subsection may indicate a high likelihood of severe outcome (see for example FIG. 1C). Alternatively, one subsection may indicate a low likelihood of severe outcome, the second may indicate a moderate likelihood of severe outcome and the third subsection may indicate a very high likelihood of severe outcome (see for example FIG. ID).

[0641] When the display is divided into four subsections, one subsection may indicate a very low likelihood of severe outcome, the second may indicate a low likelihood of severe outcome, the third subsection may indicate a moderate likelihood of severe outcome and the fourth may indicate a very high likelihood of severe outcome (see for example FIG. IE).

[0642] When the display is divided into five subsections, one subsection may indicate a very low likelihood of severe outcome, the second may indicate a low likelihood of severe outcome, the third subsection may indicate a moderate likelihood of severe outcome, the fourth may indicate a high likelihood of severe outcome and the fifth may indicate a very high likelihood of severe outcome (see for example FIG. IF).

[0643] The graphical display can include a first end, identified as corresponding to a severe infection, and a second end, identified as corresponding to a non-severe infection. Once the score is calculated, a mark 16 can optionally and preferably be made on the graphical scale at a location corresponding to the calculated likelihood. FIGs. 1A-F show optional graphical displays after the values have been fed into the input fields. FIG. 3 shows a mark 16 on scale 20 at a location that corresponds to a high likelihood that the infection is severe. Optionally, the GUI also displays the calculated score numerically (see FIGs. 2 and 3). Optionally, the GUI displays the calculated score numerically without a color bar (see FIG. 2).

[0644] The GUI optionally and preferably includes one or more additional controls 22 and 24 that may be in the form of button controls. For example, control 22 can instruct the computer to clear the input fields 12 when the user activates the control 22. This allows the user to feed values that correspond to a different sample. In some embodiments, the GUI also generates an output 26 that summarizes the results of the previous samples. Control 24 can instruct the computer to clear the input fields 12 as well as the output 26. This allows the user to begin a new run (optionally with multiple samples) without logging out of the GUI.

[0645] In some embodiments of the present invention, the GUI also includes a report screen that displays the results of previous experiments, for example, in response to a date based request.

[0646] In some embodiments, the GUI also provides information (e.g. graphically) as to the likelihood of having a bacterial or viral infections - see FIG. 4. This may be carried out on the basis of expression of a different set of markers, including but not limited to IP- 10 and TRAIL.

[0647] Thus, the GUI may include one graphical representation 28 with regards severity of infection and another graphical representation 30 with regards source of infection (e.g. bacterial vs. viral).

[0648] As used herein the term “about” refers to ± 10 %.

[0649] The terms "comprises", "comprising", "includes", "including", “having” and their conjugates mean "including but not limited to".

[0650] The term “consisting of’ means “including and limited to”.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] EXAMPLES

[0662] 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.

[0663] 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.

[0664] EXAMPLE 1

[0665] STUDY DETAILS

[0666] Inclusion criteria:

[0667] Suspected acute infection patients

[0668] • Over 18 years of age

[0669] • Clinical suspicion of acute infection as defined by the attending physician, based on clinical presentation.

[0670] Healthy individuals

[0671] • Over 18 years of age

[0672] • No clinical suspicion of acute infection

[0673] Exclusion criteria:

[0674] Suspected acute infection patients:

[0675] Patients fulfilling the following criteria were not eligible for inclusion in this study:

[0676] • HIV, HBV, active HCV or active Tuberculosis infection (self-declared or known from medical records)

[0677] • Pregnancy- self reported or medically confirmed

[0678] Healthy individuals

[0679] Patients fulfilling the following criteria are not eligible for inclusion in this study:

[0680] • Episode of infection in the last 2 weeks

[0681] • Major trauma and\or burns and\or surgery in the last 2 weeks

[0682] • HIV, HBV, active HCV or active Tuberculosis infection (self-declared or known from medical records)

[0683] Elective surgery patients

[0684] Pregnancy- self reported or medically confirmed

[0685] Protein screening: Protein screening was performed using either one of the 3 available multiplex immunoassays: Human Magnetic Luminex® Assays, RayBiotech Custom Quantibody® Human Arrays, or a multiplex assay developed at MeMed.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 1778 patients, out of which 286 severe and 1492 non-severe patients. Table 1: Demographics:

[0686] Table 2 Adjudication:

[0687] *Viral COVID is a subset of Viral Table 3: Source of infection:

[0688] Disease etiology was established by applying an expert panel adjudication process or according to the clinical file.

[0689] 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.

[0690] 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:

[0691] Vasopressor therapy (a proxy for septic shock);

[0692] Intubation with mechanical ventilation (IMV, also known as Invasive Mechanical Ventilation);

[0693] Admission to an intensive care unit (ICU);

[0694] Renal replacement therapy (RRT); and / or

[0695] Admission to a stepdown unit (SDU).

[0696] Measures of biomarker performance:

[0697] Performance measures for differentiating between severe and non-severe groups included area under the receiver operating characteristic curve (AUC) and / or sensitivity (for detecting severe patients) and specificity, at 2 cutoffs:

[0698] Rule-out cutoff: determined based on required sensitivity of 95%

[0699] Rule-in cutoff: determined based on required specificity of 85%

[0700] Performance of combinations of multiple markers is based on the probabilities from a logistic regression model.

[0701] RESULTS

[0702] The following tables (Tables 4- 22) summarize the results of relevant proteins in terms of their ability to either rule in or rule out a severe infection using particular cut-offs: Table 4: Entire cohort:

[0703] Table 5: Time to meet the severe outcome- same day as blood draw: Table 6: Time to meet the severe outcome- one day following blood draw:

[0704]

[0705] Table 7: Time to meet the severe outcome- 2-3 days following blood draw:

[0706] Table 8: Time to meet the severe outcome- 4-14 days following blood draw:

[0707] Table 9: Severe outcome- death within the 14 days following blood draw:

[0708] Table 10: Severe outcome- admittance to an Intensive Care Unit (ICU) within 3 days following blood draw: Table 11: Severe outcome- shock within 3 days following blood draw:

[0709] Table 12: Severe outcome- invasive Mechanical Ventilation (IMV) within 3 days following blood: Table 13: Specific age group- patients whose age is below 45 years:

[0710] Table 14: Specific age group- patients whose age is greater than or equal to 45 years and below 65 years:

[0711] Table 15: Specific age group- patients whose age is greater than or equal to 65 years and below 80 years:

[0712] Table 16: Specific age group- patients whose age is greater than or equal to 80 years:

[0713] Table 17: Sex- male patients:

[0714] Table 18: Sex- female patients:

[0715] Table 19: Patients with a viral etiology

[0716] Table 20: Patients with a bacterial etiology

[0717] Table 21: Severe patients with a viral etiology Table 22: Severe patients with a bacterial etiology

[0718] Tables 23-26 summarize the markers with the highest performances (ROC AUC) for determining severity in subgroups of subjects or using different severity outcomes: Table 23 Table 24

[0719] Table 25 Table 26

[0720] Tables 27-34 summarize combinations of markers (pairs) with the highest performances (ROC AUC) for determining severity in subgroups of subjects or using different severity outcomes: Table 27

[0721] Table 28 Table 29

[0722] Table 30

[0723] Table 32

[0724] Table 33 Table 35 summarizes combinations of markers (triplets) with high performances for determining severity (having an AUC of 0.79 or above):

[0725] Table 35 Table 36 summarizes combinations of markers (pairs) with high performances for determining severity:

[0726] Table 36 EXAMPLE 2

[0727] Combinations of different markers were tested in order to determine the best combination for determining the severity of an infectious disease.

[0728] The different markers included: ST2, ANG-2, IP- 10, RAGE, CRP, IL-6, IL- 10, DR5 and TRAIL.

[0729] General cohort 1 - adults

[0730] Inclusion criteria:

[0731] Suspected acute infection patients

[0732] • Over 18 years of age

[0733] • Clinical suspicion of acute infection or sepsis as defined by the attending physician, based on clinical presentation.

[0734] Exclusion criteria:

[0735] Suspected acute infection patients:

[0736] Patients fulfilling the following criteria were not eligible for inclusion in this study:

[0737] • HIV, HBV, active HCV or active Tuberculosis infection (self-declared or known from medical records)

[0738] • Pregnancy- self reported or medically confirmed

[0739] Protein screening:

[0740] Protein screening was performed using either one of the 3 available multiplex immunoassays: Human Magnetic Luminex® Assays, RayBiotech Custom Quantibody® Human Arrays, or a multiplex assay developed at MeMed.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.

[0741] Table 37: Demographics:

[0742] Table 38 Adjudication of disease etiology:

[0743] Table 39: Source of infection:

[0744] The general adult cohort (General cohort 1) was divided into particular sub-cohorts depending on relevant data for different analyses.

[0745] Sub-cohort 1: N=556, patients with available pathogen data

[0746] Sub-cohort 2: N=l,501, patients with available NEWS data Sub-cohort 3: N=l,582, patients with available SIRS score data

[0747] Sub-cohort 4: N=l,614, patients with available qSOFA score data

[0748] Sub-cohort 5: N=l,587, patients with available Heart rate data

[0749] Sub-cohort 6: N=866, patients with available comorbidities data

[0750] Sub-cohort 7: N=370, patients with available sepsis diagnosis data Sub-cohort 8: N=l,739, patients meeting the IMV outcome compared with non-severe patients

[0751] Sub-cohort 9: N=l,837, patients meeting an organ failure outcome compared with non- severe patients Disease etiology was established by applying an expert panel adjudication process or according to the clinical file.

[0752] 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.

[0753] 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:

[0754] 1. Vasopressor therapy or fluid resuscitation (a proxy for septic shock);

[0755] 2. Intubation with mechanical ventilation (IMV, also known as Invasive Mechanical Ventilation); or

[0756] 3. Renal replacement therapy (RRT).

[0757] Measures of biomarker performance:

[0758] • Performance measures for differentiating between severe and non-severe groups included area under the receiver operating characteristic curve (AUC).

[0759] • Performance of combinations of multiple markers is based on a logistic regression model.

[0760] • Performance was benchmarked against potential other combinations of biomarkers and standard of care (SOC) solutions.

[0761] • A biomarker signature was combined with additional features to improve overall prediction performance and compared to alternative combinations.

[0762] • The analysis also aimed to predict additional clinical endpoints, providing more comprehensive risk assessment for patient stratification.

[0763] RESULTS

[0764] ST2, ANG-2 and IP-10 signature for determining severity of infectious disease

[0765] The combination ST2, ANG-2 and IP- 10 outperformed all other combinations shown in Table 40 for determining severity of the infectious disease, in terms of AUC (the AUC was higher than the highest AUC of the other marker combinations shown by a difference of 0.04). The analysis was carried out in general cohort 1.

[0766] Table 40

[0767] The signature (ST2, ANG-2, IP- 10) outperformed other standard-of-care tools such as clinical scores in assessing disease severity, when evaluated on the entire general cohort or on the sub-cohorts with available data on each clinical score, as illustrated in Table 41.

[0768] Table 41

[0769] The signature (ST2, ANG-2, IP- 10) outperformed other standard-of-care assays such as lactate, Procalcitonin, IL-6, suPAR, Presepsin, sTREM-1, MR-proADM assessing disease severity, when evaluated on the entire general cohort or on the sub-cohorts with available data on each assay as illustrated in Table 42.

[0770] Table 42

[0771] Combining the signature (ST2, ANG-2, IP- 10) with pathogen data (viral or bacterial etiology) outperforms other marker combinations in assessing disease severity, as summarized in Table 43, herein below. The analysis was carried out in sub-cohort 1.

[0772] Table 43

[0773] Combining the signature (ST2, ANG-2, IP- 10) with NEWS score outperforms other marker combinations in assessing disease severity, as summarized in Table 44. The analysis was carried out in sub-cohort 2.

[0774] Table 44

[0775] Combining the signature (ST2, ANG-2, IP- 10) with SIRS score outperforms other marker combinations in assessing disease severity, as summarized in Table 45. The analysis was carried out in sub-cohort 3.

[0776] Table 45

[0777] Combining the signature (ST2, ANG-2, IP- 10) with qSOFA score outperforms other marker combinations in assessing disease severity, as summarized in Table 46. The analysis was carried out in sub-cohort 4.

[0778] Table 46

[0779] Combining the signature (ST2, ANG-2, IP- 10) with patient heart rate outperforms other marker combinations in assessing disease severity, as summarized in Table 47. The analysis was carried out in sub-cohort 5.

[0780] Table 47

[0781] Combining the signature (ST2, ANG-2, IP- 10) with patient comorbidities (i.e. number of diseases) outperforms other marker combinations in assessing disease severity, as summarized in Table 48. Diseases included hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD. The analysis was carried out in sub-cohort 6.

[0782] Table 48

[0783] Combining the signature (ST2, ANG-2, IP- 10) with patient age outperforms other marker combinations in assessing disease severity, as summarized in Table 49. The analysis was carried out in general cohort 1.

[0784] Table 49

[0785] ST2 for determining severity of infectious disease in adult patients

[0786] ST2 AUC outperformed other standard-of-care tools such as clinical scores (age shock index, NEWS, SIRS, qSOFA, ESI and Shock index) in assessing disease severity (analysis carried out on general cohort 1). In addition, ST2 AUC outperformed other standard-of-care assays including lactate, MR-proADM, IL-6, PCT, suPAR, Presepsin and sTREM-1. ST2 combined with pathogen data (viral or bacterial etiology) outperformed other markers in assessing disease severity, as summarized in Table 50. The analysis was carried out in subcohort 1.

[0787] Table 50

[0788] ST2 combined with patient comorbidities outperformed other markers in assessing disease severity, as summarized in Table 51. Diseases included hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD. The analysis was carried out in sub-cohort 6. Table 51

[0789] ST2 combined with SIRS score outperformed other markers in assessing disease severity, as summarized in Table 52. The analysis was carried out in sub-cohort 3. Table 52

[0790] ST2 combined with heart rate outperformed other markers in assessing disease severity, as summarized in Table 53. The analysis was carried out in sub-cohort 5. Table 53

[0791] ST2 combined with patient age outperformed other markers in assessing disease severity, as summarized in Table 54. The analysis was carried out in general cohort 1.

[0792] Table 54

[0793] Diagnosis of sepsis

[0794] The signature (ST2, ANG-2, IP- 10) outperformed other marker combinations in diagnosing sepsis, as summarized in Table 55. The analysis was carried out in sub-cohort 7. Table 55

[0795] ST2 alone outperformed other marker combinations in diagnosing sepsis, as summarized in Table 56. The analysis was carried out in sub-cohort 7.

[0796] Table 56 Ruling in respiratory failure and renal failure

[0797] ST2 outperformed other markers in ruling in respiratory failure, as summarized in Table 57 and 58 and renal failure as summarized in Table 59 and 60. The analyses were carried out in sub-cohort 8 and sub-cohort 9, respectively.

[0798] Table 57

[0799] Table 58

[0800] Table 59

[0801] Table 60

[0802] ICU Endpoint I l l

[0803] ST2 outperformed other markers in ruling in ICU admittance, as summarized in Table 61, herein below. The signature (ST2, ANG-2, IP- 10) outperformed other standard-of-care assays in assessing ICU admission as summarized in Table 62, herein below. The analysis was carried out in general cohort 1.

[0804] Table 61

[0805] Table 62

[0806] ST2, ANG-2 and IP-10 signature performance as a function of time Table 63, herein below presents the AUC values of the ST2, ANG-2 and IP-10 signature compared to other triplet signatures across various time frames, evaluating its ability to differentiate non- severe patients from severe patients who met the severe outcome within each specific time frame. The results demonstrate that the ST2, ANG-2 and IP- 10 signature outperforms alternative triplets across all time frames.

[0807] Table 63

[0808] Tables 64 and 65, herein below presents the AUC values of the ST2, ANG-2 and IP-10 signature compared to qSOFA clinical score across various time frames, evaluating its ability to differentiate non- severe patients from severe patients who met the severe outcome within each specific time frame.

[0809] The results demonstrate that the ST2, ANG-2 and IP- 10 signature outperforms qSOFA across all time frames. Table 64

[0810] Table 65

[0811] EXAMPLE 3

[0812] An expanded dataset (1,951 patients) was analyzed to determine the accuracy of the signature (ST2, ANG-2 and IP- 10) for predicting severity outcome in specific subgroups of patients, as summarized in Table 66. A patient was labeled severe if at least one of the following outcomes occurred - IMV, shock, RRT within 3 days, or death within 14 days.

[0813] Table 66

[0814] RESULTS ST2 outperformed other markers in distinguishing between severe and non-severe outcome in COVID patients as shown in Table 67. Using the signature ST2, ANG-2 and IP-10, an AUC of 0.84 was obtained.

[0815] Table 67

[0816] ST2 outperformed other markers in distinguishing between severe and non-severe outcome in hypertensive patients as shown in Table 68. Using the signature ST2, ANG-2 and IP-10, an AUC of 0.79 was obtained. Table 68

[0817] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between COVID patients who reached a severe outcome and patients who did not, as shown in Table 69. Table 69

[0818] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between potentially immunocompromised patients who reached a severe outcome and patients who did not, as shown in Table 70. Table 70

[0819] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between diabetic patients who reached a severe outcome and patients who did not, as shown in Table 71. Table 71

[0820] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between hypertensive patients who reached a severe outcome and patients who did not, as shown in Table 72. Table 72

[0821] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between patients with chronic heart failure who reached a severe outcome and patients who did not, as shown in Table 73. Table 73

[0822] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between patients with a malignancy who reached a severe outcome and patients who did not, as shown in Table 74. Table 74

[0823] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between obese patients who reached a severe outcome and patients who did not, as shown in Table 75. Table 75

[0824] The ST2, ANG-2 and IP- 10 signature outperformed other markers combinations in distinguishing between patients having COPD who reached a severe outcome and patients who did not, as shown in Table 76. Table 76

[0825] EXAMPLE 4

[0826] A pediatric dataset (648 patients, as summarized in Table 77) was analyzed to determine the accuracy of predicting severity outcome. The definition of the codes A, B, D, E and F is in Table 78.

[0827] Table 77 Outcome information was gathered at multiple timepoints, listed below in chronological order (from earliest to latest):

[0828] 1. Baseline

[0829] 2. First Research Blood (FRB)

[0830] • Protein markers were measured at FRB draw

[0831] 3. One day after FRB (FRB + Id)

[0832] 4. Any later time

[0833] The severe outcomes recorded included various organ support treatments, and death. Organ support treatments included the following: Inotropes administration, Intubation with mechanical ventilation, Extracorporeal membrane oxygenation (ECMO), and Renal replacement therapy. A patient positive for any of these severe outcomes at a certain timepoint was considered severe at that timepoint; otherwise, the patient was considered non-severe at that timepoint.

[0834] Clinical trajectories were defined based on the severity status at the various timepoints, and are summarized in Table 80. Each patient was assigned to one of the clinical trajectories.

[0835] Two analyses were performed:

[0836] 1. Comparing each of the Severe trajectories A, B, or E separately to the Non-severe trajectory (C)

[0837] 2. Comparing all Severe trajectories combined (A, B, D, E and F) to the Non-severe trajectory (C)

[0838] Table 78 summarizes the definition of the clinical trajectories.

[0839] Table 78 RESULTS

[0840] ST2 showed the strongest association with severe outcomes across the clinical trajectories, compared to other markers measured as shown in Table 79.

[0841] Table 79

[0842] Furthermore, as shown in Table 80, ST2 was strongly associated with severe outcomes when comparing all Severe trajectories combined to the Non-severe trajectory.

[0843] Table 80 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.

[0844] 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 diagnosing an infection or a disease associated with an infection in a subject comprising:(a) measuring an expression level of a combination of at least three proteins in a blood sample of the subject, said combination comprising:(i) Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2); and(ii) at least one protein selected from the group consisting of Interferon gammainduced protein 10 (IP-10), Interleukin- 10 (IL-10), Interleukin-6 (IL-6), Tumor necrosis factor ligand superfamily member 10 (TRAIL) and Tumor necrosis factor receptor superfamily member 10B (DR5); and(b) diagnosing the infection or the disease associated with the infection of the subject based on said expression level.

2. The method of claim 1, wherein said combination comprises ANG-2, ST2 and optionally IP- 10.

3. The method of claim 1 , wherein said combination of at least three proteins comprise combination set forth in a row of Table 36.

4. The method of claim 1, wherein:(i) when said expression level of ANG-2 is at least 2 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;(ii) when said expression level of ST2 is at least 3 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;(iii) when said expression level of IL-6 is at least 4.5 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;(iv) when said expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in;(v) when said expression level of IP- 10 is at least 4 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in and / or(vi) when said expression level of IL- 10 is at least 3 fold higher than a level in a control sample, a severe infection or a disease associated with an infection is ruled in.

5. The method of claim 1, wherein:(i) when said expression level of ANG-2 is above about 5000 pg / ml, a severe infection or a disease associated with an infection is ruled in;(ii) when said expression level of ST2 is above about 140,000 pg / ml, a severe infection or a disease associated with an infection is ruled in;(iii) when said expression level of IL-6 is above 230 pg / ml, a severe infection or a disease associated with an infection is ruled in;(iv) when said expression level of DR5 is above 315 pg / ml, a severe infection or a disease associated with an infection is ruled in;(v) when said expression level of IP- 10 is above 1000 pg / ml, a severe infection or a disease associated with an infection is ruled in; and / or(vi) when said expression level of IL- 10 is above 35 pg / ml, a severe infection or a disease associated with an infection is ruled in.

6. The method of any one of claims 1-5, wherein said combination of proteins is set forth in Table 35.

7. The method of any one of claims 1-6, wherein said diagnosing comprises predicting the likelihood of disease progression.

8. The method of claim 1, wherein said diagnosing comprises:(i) predicting a severity on the same day as blood draw;(ii) predicting a severity on a day following blood draw;(iii) predicting a severity two-three days following blood draw; or(iv) predicting a severity 4-14 days following blood draw.

9. A method of determining severity of an infection or a disease associated with an infection of a subject, comprising measuring the amount of Tumor necrosis factor receptor superfamily member 10B (DR5) and the amount of at least one protein determinant selected from the group consisting of Interferon gamma- induced protein 10 (IP- 10), Interleukin-6 (IL-6), Interleukin- 10 (IL- 10), Tumor necrosis factor ligand superfamily member 10 (TRAIL), Angiogpoietin-2 (ANG-2) and / or Interleukin 1 receptor-like 1 (ST2) in a blood sample of the subject, wherein a combined amount of said DR5 and said protein determinant is indicative of the severity of the infection or the disease associated with the infection.

10. The method of claim 9, wherein when said amount of DR5 is above 315 pg / ml, a severe infection or disease associated with the infection is ruled in and / or when said expression level of DR5 is at least 1.8 fold higher than a level in a control sample, a severe infection or disease associated with the infection is ruled in.

11. A method of determining severity of infection or disease associated with the infection of a subject, comprising measuring the amount of at least one protein set forth in Table A in a blood sample of the subject and measuring at least one clinical parameter set forth in Table B or Table C, wherein a combination of the amount of said at least one protein and the clinical parameter is indicative of the severity of the infection or disease associated with the infection.

12. The method of claim 11, wherein said at least one protein is ST2.

13. The method of claim 11, wherein said at least one protein is at least two proteins set forth in a row of Table 36.

14. The method of any one of claims 1-10, further comprising measuring at least one clinical parameter set forth in Table B or C.

15. The method of any one of claims 1-10, further comprising measuring all the components of 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, PIM2, CMM, SOFA, qSOFA, MPM, RIFLE, CP, MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukee criteria and Ranson score.

16. A method of determining the severity of an infection or a disease associated with the infection in a subject comprising:(a) measuring, in a blood sample of the subject, an expression level of:(i) Interleukin 1 receptor- like 1 (ST2);(ii) Angiogpoietin-2 (ANG-2); and(iii) Interferon gamma- induced protein 10 (IP- 10):(b) generating a score on the basis of said expression level; and(c) determining the severity of the infection or the disease associated with the infection of the subject based on said score.

17. The method of claim 16, wherein the determining the severity comprises ruling in a severe infection or disease associated with the infection.

18. The method of claim 16, wherein the determining the severity comprises ruling in a severe infection or disease associated with the infection.

19. The method of any one of claims 16-18, 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.

20. The method of claim 19, wherein said comorbidities are selected from the group consisting of hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD.

21. The method of claim 19, wherein the score incorporates an indicator of viral etiology.

22. The method of claim 21, wherein a weight of IP- 10 in the score is increased on inclusion of a positive indicator of said viral etiology.

23. The method of any one of claims 16-22, wherein the score incorporates at least one parameter set forth in Tables B or C.

24. The method of any one of claims 16-22, 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.

25. The method of claim 24, wherein the clinical index is NEWS or qSOFA.

26. The method of any one of claims 16-24, wherein the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

27. The method of any one of claims 16-26, 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.

28. The method of any one of claims 16-27, wherein an increase in an expression of each of said ANG-2, said ST2 and said IP- 10 above a corresponding expression level in a control sample is indicative of a higher severity of the infection or the disease associated with an infection.

29. The method of any one of claims 1-28, further comprising measuring an expression of at least one additional protein selected from the group consisting of 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.

30. The method of claim 29, wherein said expression of no more than four of said at least one additional protein is incorporated into the score.

31. The method of any one of claims 16-30, wherein the severity is stratified according to at least three levels.

32. The method of any one of claims 16-31, further comprising displaying said score on a display.

33. A method of determining the severity of an infection or a disease associated with the infection in a subject comprising:(a) measuring, in a blood sample of the subject, an expression level of ST2;(b) measuring an additional feature selected from the group consisting of age, number or type of comorbidities, heart rate, mean arterial pressure, respiratory rate, viral etiology and bacterial etiology;(c) generating a score on the basis of said expression level and said additional feature; and(d) determining the severity of the infection or the disease associated with the infection based on said score, thereby determining the severity of the infection or the disease associated with an infection of the subject.

34. The method of claim 33, wherein said comorbidities are selected from the group consisting of hypertension, diabetes, chronic heart failure, malignancy, obesity, chronic kidney disease and COPD.

35. The method of claims 33 or 34 wherein the subject is not diagnosed as having sepsis or septic shock.

36. The method of any one of claims 33-35, wherein the subject is a child or neonate.

37. The method of any one of claims 33-36, wherein the score incorporates at least one additional parameter set forth in Tables B or C.

38. The method of any one of claims 33-37, 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.

39. The method of claim 38, wherein the clinical index is NEWS or qSOFA.

40. The method of any one of claims 33-39, wherein the score incorporates a number of Systemic Inflammatory Response Syndrome (SIRS) criteria met.

41. The method of any one of claims 33-40, further comprising measuring an expression of at least one additional protein selected from the group consisting of ANG-2, 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 and incorporating the expression into the score.

42. The method of claim 41, wherein said expression of no more than six of said at least one additional protein is incorporated into the score.

43. The method of any one of claims 1-42, wherein the infection is a viral infection.

44. The method of any one of claims 1-42, wherein the infection is a bacterial infection.

45. The method of any one of claims 1-44, wherein the subject shows symptoms of an infectious disease.

46. The method of any one of claims 1-44, wherein the subject does not show symptoms of an infectious disease.

47. The method of any one of claims 1-46, wherein the subject does not have a chronic non-infectious disease.

48. The method of any one of claims 1-47, wherein the blood sample is whole blood, capillary blood, or a fraction thereof.

49. The method of claim 48, wherein said fraction comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

50. The method of claim 48, wherein said fraction comprises serum or plasma.

51. The method of any one of claims 1-47, wherein the level of no more than 10 proteins is used to diagnose the infection.

52. The method of any one of claims 1-47, wherein no more than 6 proteins are measured to diagnose the infection.

53. A kit for diagnosing an infection or disease associated with the infection comprising detection reagents which specifically detect a combination of proteins set forth in Table 35.

54. The kit of claim 53, wherein at least one of said proteins is ST2.

55. The kit of any one of claims 53-54, further comprising detection reagents which specifically detect CRP.

56. The kit of any one of claims 53-55, wherein said detection reagents are antibodies.

57. The kit of claim 56, wherein at least one of said antibodies is attached to a detectable moiety.

58. The kit of claims 56 or 57, wherein at least one of said antibodies is a monoclonal antibody.

59. The kit of any one of claims 56-58, wherein at least one of said antibodies is attached to a solid support.

60. The kit of any one of claims 53-59, wherein said kit comprises detection reagents that specifically detect no more than 10 protein markers.

61. The kit of any one of claims 53-59, wherein said kit comprises detection reagents that specifically detect no more than 6 protein markers.

62. A method of treating a subject having an infection or disease associated with the infection comprising:(a) determining the severity of the infection or disease associated with the infection according to any one of claims 1-52; and(b) treating the subject according to the diagnosis of the infection or disease associated with the infection.

63. The method of claim 62, 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, glucocorticoid therapy and / or treatment of last resort.

64. The method of claim 62, wherein when respiratory failure is ruled in for the subject, the subject is treated using Invasive Mechanical Ventilation (IMV); when septic shock is ruled in for the subject, the subject is administered with a vasopressor; and / or. when renal failure is ruled in for the subject, the subject is treated with Renal Replacement Therapy (RRT).

65. The method of claim 62, wherein said subject shows symptoms of an infectious disease.

66. The method of claim 65, wherein said symptoms comprise fever.

67. A method of ruling in sepsis or septic shock in a suspect subject comprising:(a) measuring an expression level of ST2 in a blood sample of the suspect subject; and(b) ruling in the sepsis or septic shock when the expression level of ST2 is above a predetermined amount.

68. A method of ruling out sepsis or septic shock in a suspect subject comprising:(a) measuring an expression level of ST2 in a blood sample of the suspect subject; and(b) ruling out the sepsis or septic shock when the expression level of ST2 is below a predetermined amount.

69. The method of claim 67 or 68, wherein the suspect subject has a fever.

70. The method of claim 67 or 68, wherein the suspect subject has a qSOFA score > 2.

71. The method of claim 67 or 68, wherein the suspect subject has a qSOFA score < 2.

72. The method of claim 67 or 68, wherein the suspect subject fulfils at least one criterion of SIRS (Systemic Inflammatory Response Syndrome).

73. The method of any one of claims 67-72, further comprising measuring an expression of at least one additional protein selected from the group consisting of ANG-2, 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.

74. The method of any one of claims 67-72, further comprising measuring an expression of ANG-2 and IP- 10 and generating a score on the basis of an expression of said ST2, said ANG-2 and said IP- 10, wherein the score is indicative of a likelihood of sepsis.

75. A method of ruling in respiratory failure comprising:(a) measuring an expression level of ST2 in a blood sample of the suspect subject; and(b) ruling in the respiratory failure when the expression level of ST2 is above a predetermined amount.

76. A method of treating a subject with an infection or a disease associated with an infection comprising:(a) ruling in respiratory failure according to claim 75; and(b) treating the subject using Invasive Mechanical Ventilation (IMV).

77. The method of claims 75 or 76, further comprising measuring an expression level of ANG-2 and IP- 10.

78. A method of ruling in renal failure comprising:(a) measuring an expression level of ST2 in a blood sample of the suspect subject; and(b) ruling in the renal failure when the expression level of ST2 is above a predetermined amount.

79. A method of treating a subject with an infection or a disease associated with an infection comprising:(a) ruling in renal failure according to claim 78; and(b) treating the subject using Renal Replacement Therapy (RRT).

80. The method of claims 78 or 79, further comprising measuring an expression level of ANG-2 and IP- 10.

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