ANTIBIOTIC THERAPY GUIDANCE BASED ON PRO-ADM

Abstract

The invention relates to a method for antibiotic therapy guidance, stratification and/or control in a patient suspected of having an infection. In particular, the method comprises providing a sample form said patient, determining a level of proADM or fragment(s) thereof in said sample, and wherein the level of proADM or fragment(s) thereof in said sample is indicative of whether an initiation or a change of an antibiotic treatment is required. In a preferred embodiment of the invention, the method comprises additionally determining in a sample from said patient a level of PCT or fragment(s) thereof. Furthermore, the invention also relates to a kit for carrying out the method of the present invention.

Claims

1. Method for antibiotic therapy guidance, stratification and/or control in a patient suspected of having an infection, the method comprising: providing a sample form said patient, and determining a level of proADM or fragment(s) thereof in said sample, wherein the level of proADM or fragment(s) thereof in said sample is indicative of whether an initiation or a change of an antibiotic treatment is required.

2. Method according to claim 1, wherein the provided sample was isolated from the patient within 12 hours from first contact with medical personnel, preferably within 6 hours, 2 hours, 1 hour, or more preferably within 30 minutes from first contact with medical personnel.

3. Method according to claim 1, wherein the patient presents in an emergency department or a primary care unit.

4. Method according to claim 1, comprising determining the level of MR-proADM.

5. Method according to claim 1, wherein determining a level of proADM or fragment(s) thereof in said sample that is greater than the level of proADM or fragment(s) thereof in one or more control samples, such as in a group of healthy individuals, indicates that an initiation or a change of an antibiotic treatment is required.

6. Method according to claim 5, wherein the antibiotic treatment that requires initiation or change comprises an initiation of or change to intravenous antibiotic treatment.

7. Method according to claim 1, wherein a level of proADM or fragment(s) thereof in a sample equal to or above 1 nmol/L, preferably equal to or greater than 1.2 nmol/L, more preferably equal to or above 1.27 nmol/L, indicates that an initiation or a change of an antibiotic treatment is required.

8. Method according to claim 1, comprising additionally determining in a sample from said patient a level of PCT or fragment(s) thereof.

9. Method according to claim 1, wherein the level of PCT or fragment(s) thereof is determined in the same sample as the level of proADM or fragment(s) thereof.

10. Method according to claim 8, wherein a level of PCT or fragment(s) thereof is equal to or above 0.05 ng/ml, preferably equal to or above 0.1 ng/ml, more preferably equal to or above 0.12 ng/ml indicates that an initiation or a change of an antibiotic treatment is required.

11. Method according to claim 1, wherein the sample for determining proADM or fragment(s) thereof and the sample for determining PCT or fragment(s) thereof are is a bodily fluid, preferably selected from the group consisting of a blood sample, a serum sample, a plasma sample and/or a urine sample.

12. Method according to claim 1, wherein a level of proADM or fragment(s) thereof in a sample equal to or above 1 nmol/L, preferably equal to or greater than 1.2 nmol/L, more preferably equal to or above 1.27 nmol/L, and a level of PCT or fragment(s) thereof is below 0.05 nmol/L, preferably below 0.1 nmol/mL, more preferably below 0.12 nmol/L indicate that an initiation or a change of an antibiotic treatment is required.

13. Method according to claim 1, wherein said patient has not yet received antibiotic treatment.

14. Method according to claim 1, wherein said patient is receiving oral antibiotic treatment and the change of an antibiotic treatment comprises a change in the route of administration of the antibiotic treatment.

15. Method according to claim 1, comprising additionally determining one or more risk factors, such as age, gender, comorbidities and/or organ dysfunction.

16. Method according to claim 1, additionally comprising determining a level of at least one additional biomarker or fragment(s) thereof in a sample from said patient, wherein the at least one additional biomarker preferably is lactate and/or C-reactive protein, and/or determining at least one clinical score, wherein the at least one clinical score is preferably SOFA and/or qSOFA, wherein the level of the at least one additional biomarker and/or the at least one clinical score, and the level of proADM or fragment(s) thereof is indicative of whether an initiation or a change of an antibiotic treatment is required.

17. A method of treating a patient suspected of having an infection comprising administering a pharmaceutical composition comprising one or more antibiotic agents, wherein the patient is administered said composition after being identified by the method according to claim 1 as requiring an initiation or a change of an antibiotic treatment due to the levels of proADM or fragment(s) thereof in a sample obtained from said patient.

18. Method of treating a patient suspected of having an infection according to claim 17, wherein administration of the composition is initiated within 180 minutes, preferably within 120 minutes, more preferably within 60 minutes or immediately after determining the level of proADM or fragment(s) thereof in said sample.

19. Method of treating a patient suspected of having an infection according to claim 17, wherein the patient receives intravenous administration of the composition, preferably intravenous and oral administration of one or more compositions.

20. Kit for carrying out the method of claim 1, comprising detection reagents for determining the level proADM or fragment(s) thereof, and optionally additionally for determining the level of PCT or fragment(s) thereof, in a sample from a subject, and reference data, such as a reference level, corresponding to a level of proADM or fragment(s) thereof in said sample equal to or above 1 nmol/L, preferably equal to or above 1.2 nmol/L, more preferably equal to or above 1.27 nmol/L, wherein said reference data is preferably stored on a computer readable medium and/or employed in in the form of computer executable code configured for comparing the determined levels of proADM or fragment(s) thereof, and optionally additionally the determined levels of PCT or fragment(s) thereof, to said reference data.

21. A method comprising: providing a sample having a complex comprising: at least one binder to proADM or a fragment thereof, in a bodily fluid obtained from a patient suspected of having an infection, wherein: the sample has a level of proADM equal to or higher than 1.2 nmol/L.

22. A method comprising: treating a patient suspected of having an infection with an antibiotic, wherein said patient has been determined to have, in a bodily fluid sample of the patient, a level of the proADM equal to or higher than 1.2 nmol/L.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0130] The invention relates to a method for antibiotic therapy guidance, stratification and/or control in a patient suspected of having an infection. As is evident from the data presented herein, the initiation or change of an antibiotic treatment is indicated by the level of proADM or fragment(s) thereof, which provides information on potentially initiating or changing an antibiotic treatment.

[0131] In another embodiment of the invention, the decision to initiate, change or stop an antibiotic treatment can be supported by the quantification of proADM or fragment(s) thereof to predict 28 day mortality, to predict severe sepsis development within 48 hours and to predict a positive bacterial culture (blood culture).

[0132] The present invention has the following advantages over the conventional methods: the inventive methods and the kits are fast, objective, easy to use and precise for therapy guidance, stratification and/or control patients suspected of having an infection. The methods and kits of the invention relate to markers and clinical scores that are easily measurable in routine methods in hospitals, because the levels of proADM, PCT, lactate, c-reactive protein, SOFA, qSOFA, APACHE II, SAPS II can be determined in routinely obtained blood samples or further biological fluids or samples obtained from a subject.

[0133] As used herein, the “patient” or “subject” may be a vertebrate. In the context of the present invention, the term “subject” includes both humans and animals, particularly mammals, and other organisms.

[0134] In the context of the present invention, an “adverse event in the health of a patient” relates to events that indicate complications or worsening of the health state of the patient. Such adverse events include, without limitation, death of the patient, death of a patient within 28-90 days after diagnosis and treatment initiation, occurrence of an infection or a new infection, organ failure and deterioration of the patient's general clinical signs or symptoms, such as hypotension or hypertension, tachycardia or bradycardia. Furthermore, examples of adverse events include situations where a deterioration of clinical symptoms indicates the requirement for therapeutic measures, such as a focus cleaning procedure, transfusion of blood products, infusion of colloids, invasive mechanical ventilation, non-invasive mechanical ventilation, emergency surgery, organ replacement therapy, such as renal or liver replacement, and vasopressor therapy.

[0135] As used herein, a primary care unit is a doctor's practice or a health care center where day-to-day primary healthcare may be given by a health care provider to a patient. Typically the provider acts as the first contact and principal point of continuing care for patients within a healthcare system, and coordinates other specialist care that the patient may need. Patients commonly receive primary care from professionals such as a primary care physician (for example a general practitioner or family physician), a nurse practitioner (such as an adult-gerontology nurse practitioner, family nurse practitioner, or pediatric nurse practitioner), or a physician assistant. Such a professional may also be a registered nurse, a pharmacist, a clinical officer.

[0136] In the context of the present invention, an emergency department (ED), also known as an accident and emergency department, emergency room (ER), emergency ward (EW) or casualty department, is a medical treatment facility specializing in emergency medicine, which involved the acute care of patients who present without prior appointment either by their own means or by that of an ambulance. Emergency departments are usually found in hospitals or other primary care centers.

[0137] As used herein, “diagnosis” in the context of the present invention relates to the recognition and (early) detection of a clinical condition of a subject linked to an infectious disease. Also the assessment of the severity of the infectious disease may be encompassed by the term “diagnosis”.

[0138] “Prognosis” relates to the prediction of an outcome or a specific risk for a subject based on an infectious disease. This may also include an estimation of the chance of recovery or the chance of an adverse outcome for said subject.

[0139] The methods of the invention may also be used for monitoring. “Monitoring” relates to keeping track of an already diagnosed infectious disease, disorder, complication or risk, e.g. to analyze the progression of the disease or the influence of a particular treatment or therapy on the disease progression of the disease of a critically ill patient or an infectious disease in a patient.

[0140] The term “therapy monitoring” or “therapy control” in the context of the present invention refers to the monitoring and/or adjustment of a therapeutic treatment of said subject, for example by obtaining feedback on the efficacy of the therapy.

[0141] In the present invention, the terms “risk assessment” and “risk stratification” and “therapy stratification” relate to the grouping of subjects into different risk groups according to their further prognosis. Risk assessment also relates to stratification for applying preventive and/or therapeutic measures. The term “therapy stratification” in particular relates to grouping or classifying patients into different groups, such as risk groups or therapy groups that receive certain differential therapeutic measures depending on their classification. The term “therapy stratification” also relates to grouping or classifying patients with infections or having symptoms of an infectious disease into a group that are not in need to receive certain therapeutic measures.

[0142] As used herein, the term “therapy guidance” refers to application of certain therapies or medical interventions based on the value of one or more biomarkers and/or clinical parameter and/or clinical scores.

[0143] It is understood that in the context of the present invention “determining the level of proADM or fragment(s) thereof” or the like refers to any means of determining proADM or a fragment thereof. The fragment can have any length, e.g. at least about 5, 10, 20, 30, 40, 50 or 100 amino acids, so long as the fragment allows the unambiguous determination of the level of proADM or fragment thereof. In preferred aspects of the invention, “determining the level of proADM” refers to determining the level of midregional proadrenomedullin (MR-proADM). MR-proADM is a fragment and/or region of proADM.

[0144] The peptide adrenomedullin (ADM) was discovered as a hypotensive peptide comprising 52 amino acids, which had been isolated from a human phenochromocytome (Kitamura et al., 1993). Adrenomedullin (ADM) is encoded as a precursor peptide comprising 185 amino acids (“preproadrenomedullin” or “pre proADM”). An exemplary amino acid sequence of ADM is given in SEQ ID NO: 1.

TABLE-US-00001 SEQ ID NO: 1: amino acid sequence of pre-pro-ADM:   1 MKLVSVALMY LGSLAFLGAD TARLDVASEF RKKWNKWALS RGKRELRMSS  51 SYPTGLADVK AGPAQTLIRP QDMKGASRSP EDSSPDAARI RVKRYRQSMN 101 NFQGLRSFGC RFGTCTVQKL AHQIYQFTDK DKDNVAPRSK ISPQGYGRRR 151 RRSLPEAGPG RTLVSSKPQA HGAPAPPSGS APHFL

[0145] ADM comprises the positions 95-146 of the pre-proADM amino acid sequence and is a splice product thereof. “Proadrenomedullin” (“proADM”) refers to pre-proADM without the signal sequence (amino acids 1 to 21), i.e. to amino acid residues 22 to 185 of pre-proADM. “Midregional proadrenomedullin” (“MR-proADM”) refers to the amino acids 45 to 95 of pre-proADM. An exemplary amino acid sequence of MR-proADM is given in SEQ ID NO: 2.

TABLE-US-00002 SEQ ID NO: 2: amino acid sequence of MR-proADM (AS 45-92 of pre-pro-ADM): ELRMSSSYPT GLADVKAGPA QTLIRPQDMK GASRSPEDSS PDAARIRV

[0146] It is also envisaged herein that a peptide and fragment thereof of pre-proADM or MR-proADM can be used for the herein described methods. For example, the peptide or the fragment thereof can comprise the amino acids 22-41 of pre-proADM (PAMP peptide) or amino acids 95-146 of pre-proADM (mature adrenomedullin, including the biologically active form, also known as bio-ADM). A C-terminal fragment of proADM (amino acids 153 to 185 of pre proADM) is called adrenotensin. Fragments of the proADM peptides or fragments of the MR-proADM can comprise, for example, at least about 5, 10, 20, 30 or more amino acids. Accordingly, the fragment of ADM may, for example, be selected from the group consisting of MR-proADM, PAMP, adrenotensin and mature adrenomedullin, preferably herein the fragment is MR-proADM.

[0147] The determination of these various forms of ADM or proADM and fragments thereof also encompass measuring and/or detecting specific sub-regions of these molecules, for example by employing antibodies or other affinity reagents directed against a particular portion of the molecules, or by determining the presence and/or quantity of the molecules by measuring a portion of the protein using mass spectrometry.

[0148] The methods and kits of the present invention can also comprise determining at least one further biomarker, marker, clinical score and/or parameter in addition to proADM or fragments thereof.

[0149] As used herein, a parameter is a characteristic, feature, or measurable factor that can help in defining a particular system. A parameter is an important element for health- and physiology-related assessments, such as a disease/disorder/clinical condition risk, preferably organ dysfunction(s). Furthermore, a parameter is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. An exemplary parameter can be selected from the group consisting of Acute Physiology and Chronic Health Evaluation II (APACHE II), the simplified acute physiology score (SAPSII score), quick sequential organ failure assessment score (qSOFA), sequential organ failure assessment score (SOFA score), body mass index, weight, age, sex, IGS II, liquid intake, white blood cell count, sodium, potassium, temperature, blood pressure, dopamine, bilirubin, respiratory rate, partial pressure of oxygen, World Federation of Neurosurgical Societies (WFNS) grading, and Glasgow Coma Scale (GCS).

[0150] As used herein, terms such as “marker”, “surrogate”, “prognostic marker”, “factor” or “biomarker” or “biological marker” are used interchangeably and relate to measurable and quantifiable biological markers (e.g., specific protein or enzyme concentration or a fragment thereof, specific hormone concentration or a fragment thereof, or presence of biological substances or a fragment thereof) which serve as indices for health- and physiology-related assessments, such as a disease/disorder/clinical condition risk, preferably an adverse event. A marker or biomarker is defined as a characteristic that can be objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers may be measured in a sample (as a blood, plasma, urine, or tissue test).

[0151] The at least one further marker and/or parameter of said subject can be selected from the group consisting of a level of lactate in said sample, a level of procalcitonin (PCT) in said sample, the sequential organ failure assessment score (SOFA score) of said subject, the simplified acute physiology score (SAPSII) of said subject, the Acute Physiology and Chronic Health Evaluation II (APACHE II) score of said subject and a level of the soluble fms-like tyrosine kinase-1 (sFlt-1), Histone H2A, Histone H2B, Histone H3, Histone H4, calcitonin, Endothelin-1 (ET-1), Arginine Vasopressin (AVP), Atrial Natriuretic Peptide (ANP), Neutrophil Gelatinase-Associated Lipocalin (NGAL), Troponin, Brain Natriuretic Peptide (BNP), C-Reactive Protein (CRP), Pancreatic Stone Protein (PSP), Triggering Receptor Expressed on Myeloid Cells 1 (TREM1), Interleukin-6 (IL-6), Interleukin-1, Interleukin-24 (IL-24), Interleukin-22 (IL-22), Interleukin (IL-20) other ILs, Presepsin (sCD14-ST), Lipopolysaccharide Binding Protein (LBP), Alpha-1-Antitrypsin, Matrix Metalloproteinase 2 (MMP2), Metalloproteinase 2 (MMP8), Matrix Metalloproteinase 9 (MMP9), Matrix Metalloproteinase 7 (MMP7, Placental growth factor (PIGF), Chromogranin A, S100A protein, S100B protein and Tumor Necrosis Factor α (TNFα), Neopterin, Alpha-1-Antitrypsin, pro-arginine vasopressin (AVP, proAVP or Copeptin), procalcitonin, atrial natriuretic peptide (ANP, pro-ANP), Endothelin-1, E-selectin, ICAM-1, VCAM-1, IP-10, CCL1/TCA3, CCL11, CCL12/MCP-5, CCL13/MCP-4, CCL14, CCL15, CCL16, CCL17/TARC, CCL18, CCL19, CCL2/MCP-1, CCL20, CCL21, CCL22/MDC, CCL23, CCL24, CCL25, CCL26, CCL27, CCL28, CCL3, CCL3L3, CCL4, CCL4L1/LAG-1, CCL5, CCL6, CCL7, CCL8, CCL9, CX3CL1, CXCL1, CXCL10, CXCL11, CXCL12, CXCL13, CXCL14, CXCL15, CXCL16, CXCL17, CXCL2/MIP-2, CXCL3, CXCL4, CXCL5, CXCL6, CXCL7/Ppbp, CXCL9, IL8/CXCL8, XCL1, XCL2, FAM19A1, FAM19A2, FAM19A3, FAM19A4, FAM19A5, CLCF1, CNTF, IL11, IL31, IL6, Leptin, LIF, OSM, IFNA1, IFNA10, IFNA13, IFNA14, IFNA2, IFNA4, IFNA7, IFNB1, IFNE, IFNG, IFNZ, IFNA8, IFNA5/IFNaG, IFNω/IFNW1, BAFF, 4-1BBL, TNFSF8, CD40LG, CD70, CD95L/CD178, EDA-A1, TNFSF14, LTA/TNFB, LTB, TNFα, TNFSF10, TNFSF11, TNFSF12, TNFSF13, TNFSF15, TNFSF4, IL18, IL18BP, IL1A, IL1B, IL1F10, IL1F3/IL1RA, IL1F5, IL1F6, IL1F7, IL1F8, IL1RL2, IL1F9, IL33 or a fragment thereof.

[0152] As used herein, “procalcitonin” or “PCT” relates to a peptide spanning amino acid residues 1-116, 2-116, 3-116, or fragments thereof, of the procalcitonin peptide. PCT is a peptide precursor of the hormone calcitonin. Thus the length of procalcitonin fragments is at least 12 amino acids, preferably more than 50 amino acids, more preferably more than 110 amino acids. PCT may comprise post-translational modifications such as glycosylation, liposidation or derivatisation. Procalcitonin is a precursor of calcitonin and katacalcin. Thus, under normal conditions the PCT levels in the circulation are very low (<about 0.05 ng/ml).

[0153] The level of PCT in the sample of the subject can be determined by immunoassays as described herein. As used herein, the level of ribonucleic acid or deoxyribonucleic acids encoding “procalcitonin” or “PCT” can also be determined. Methods for the determination of PCT are known to a skilled person, for example by using products obtained from Thermo Fisher Scientific/B⋅R⋅A⋅H⋅M⋅S GmbH.

[0154] Lactate, or lactic acid, is an organic compound with the formula CH.sub.3CH(OH)COOH, which occurs in bodily fluids including blood. Blood tests for lactate are performed to determine the status of the acid base homeostasis in the body. Lactic acid is a product of cell metabolism that can accumulate when cells lack sufficient oxygen (hypoxia) and must turn to a less efficient means of energy production, or when a condition causes excess production or impaired clearance of lactate. Lactic acidosis can be caused by an inadequate amount of oxygen in cells and tissues (hypoxia), for example if someone has a condition that may lead to a decreased amount of oxygen delivered to cells and tissues, such as shock, septic shock or congestive heart failure, the lactate test can be used to help detect and evaluate the severity of hypoxia and lactic acidosis.

[0155] C-reactive protein (CRP) is a pentameric protein, which can be found in bodily fluids such as blood plasma. CRP levels can rise in response to inflammation. Measuring and charting CRP values can prove useful in determining disease progress or the effectiveness of treatments.

[0156] As used herein, the “sequential organ failure assessment score” or “SOFA score” is one score used to track a patient's status during the stay in an intensive care unit (ICU). The SOFA score is a scoring system to determine the extent of a person's organ function or rate of failure. The score is based on six different scores, one each for the respiratory, cardiovascular, hepatic, coagulation, renal and neurological systems. Both the mean and highest SOFA scores being predictors of outcome. An increase in SOFA score during the first 24 to 48 hours in the ICU predicts a mortality rate of at least 50% up to 95%. Scores less than 9 give predictive mortality at 33% while above 14 can be close to or above 95%.

[0157] As used herein, the quick SOFA score (qSOFA) is a scoring system that indicates a patient's organ dysfunction or mortality risk. The score is based on three criteria: 1) an alteration in mental status, 2) a decrease in systolic blood pressure of less than 100 mm Hg, 3) a respiration rate greater than 22 breaths per minute. Patients with two or more of these conditions are at greater risk of having an organ dysfunction or to die.

[0158] As used herein, “APACHE II” or “Acute Physiology and Chronic Health Evaluation II” is a severity-of-disease classification scoring system (Knaus et al., 1985). It can be applied within 24 hours of admission of a patient to an intensive care unit (ICU) and may be determined based on 12 different physiologic parameters: AaDO2 or PaO2 (depending on FiO2), temperature (rectal), mean arterial pressure, pH arterial, heart rate, respiratory rate, sodium (serum), potassium (serum), creatinine, hematocrit, white blood cell count and Glasgow Coma Scale.

[0159] As used herein, “SAPS II” or “Simplified Acute Physiology Score II” relates to a system for classifying the severity of a disease or disorder (see Le Gall J R et al., A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993; 270(24):2957-63.). The SAPS II score is made of 12 physiological variables and 3 disease-related variables. The point score is calculated from 12 routine physiological measurements, information about previous health status and some information obtained at admission to the ICU.

[0160] The SAPS II score can be determined at any time, preferably, at day 2. The “worst” measurement is defined as the measure that correlates to the highest number of points. The SAPS II score ranges from 0 to 163 points. The classification system includes the followings parameters: Age, Heart Rate, Systolic Blood Pressure, Temperature, Glasgow Coma Scale, Mechanical Ventilation or CPAP, PaO2, FiO2, Urine Output, Blood Urea Nitrogen, Sodium, Potassium, Bicarbonate, Bilirubin, White Blood Cell, Chronic diseases and Type of admission. There is a sigmoidal relationship between mortality and the total SAPS II score. The mortality of a subject is 10% at a SAPSII score of 29 points, the mortality is 25% at a SAPSII score of 40 points, the mortality is 50% at a SAPSII score of 52 points, the mortality is 75% at a SAPSII score of 64 points, the mortality is 90% at a SAPSII score of 77 points (Le Gall loc. cit.).

[0161] As used herein, the term “sample” is a biological sample that is obtained or isolated from the patient or subject. “Sample” as used herein may, e.g., refer to a sample of bodily fluid or tissue obtained for the purpose of diagnosis, prognosis, or evaluation of a subject of interest, such as a patient. Preferably herein, the sample is a sample of a bodily fluid, such as blood, serum, plasma, cerebrospinal fluid, urine, saliva, sputum, pleural effusions, cells, a cellular extract, a tissue sample, a tissue biopsy, a stool sample and the like. Particularly, the sample is blood, blood plasma, blood serum, or urine.

[0162] “Plasma” in the context of the present invention is the virtually cell-free supernatant of blood containing anticoagulant obtained after centrifugation. Exemplary anticoagulants include calcium ion binding compounds such as EDTA or citrate and thrombin inhibitors such as heparinates or hirudin. Cell-free plasma can be obtained by centrifugation of the anticoagulated blood (e.g. citrated, EDTA or heparinized blood), for example for at least 15 minutes at 2000 to 3000 g.

[0163] “Serum” in the context of the present invention is the liquid fraction of whole blood that is collected after the blood is allowed to clot. When coagulated blood (clotted blood) is centrifuged serum can be obtained as supernatant.

[0164] As used herein, “urine” is a liquid product of the body secreted by the kidneys through a process called urination (or micturition) and excreted through the urethra.

[0165] “Sepsis” in the context of the invention refers to a systemic response to infection. Alternatively, sepsis may be seen as the combination of SIRS with a confirmed infectious process or an infection. Sepsis may be characterized as clinical syndrome defined by the presence of both infection and a systemic inflammatory response (Levy M M et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med. 2003 April; 31(4):1250-6). The term “sepsis” used herein includes, but is not limited to, sepsis, severe sepsis, septic shock.

[0166] The term “sepsis” used herein includes, but is not limited to, sepsis, severe sepsis, and septic shock. Severe sepsis in refers to sepsis associated with organ dysfunction, hypoperfusion abnormality, or sepsis-induced hypotension. Hypoperfusion abnormalities include lactic acidosis, oliguria and acute alteration of mental status. Sepsis-induced hypotension is defined by the presence of a systolic blood pressure of less than about 90 mm Hg or its reduction by about 40 mm Hg or more from baseline in the absence of other causes for hypotension (e.g. cardiogenic shock). Septic shock is defined as severe sepsis with sepsis-induced hypotension persisting despite adequate fluid resuscitation, along with the presence of hypoperfusion abnormalities or organ dysfunction (Bone et al., CHEST 101(6): 1644-55, 1992).

[0167] The term sepsis may alternatively be defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. For clinical operationalization, organ dysfunction can preferably be represented by an increase in the Sequential Organ Failure Assessment (SOFA) score of 2 points or more, which is associated with an in-hospital mortality greater than 10%. Septic shock may be defined as a subset of sepsis in which particularly profound circulatory, cellular, and metabolic abnormalities are associated with a greater risk of mortality than with sepsis alone. Patients with septic shock can be clinically identified by a vasopressor requirement to maintain a mean arterial pressure of 65 mm Hg or greater and serum lactate level greater than 2 mmol/L (>18 mg/dL) in the absence of hypovolemia.

[0168] The term “sepsis” used herein relates to all possible stages in the development of sepsis.

[0169] The term “sepsis” also includes severe sepsis or septic shock based on the SEPSIS-2 definition (Bone et al., 2009). The term “sepsis” also includes subjects falling within the SEPSIS-3 definition (Singer et al., 2016). The term “sepsis” used herein relates to all possible stages in the development of sepsis.

[0170] As used herein, “infection” within the scope of the invention means a pathological process caused by the invasion of normally sterile tissue or fluid by pathogenic or potentially pathogenic agents/pathogens, organisms and/or microorganisms, and relates preferably to infection(s) by bacteria, viruses, fungi, and/or parasites. Accordingly, the infection can be a bacterial infection, viral infection, and/or fungal infection. The infection can be a local or systemic infection. For the purposes of the invention, a viral infection may be considered as infection by a microorganism.

[0171] Further, the subject suffering from an infection can suffer from more than one source(s) of infection simultaneously. For example, the subject suffering from an infection can suffer from a bacterial infection and viral infection; from a viral infection and fungal infection; from a bacterial and fungal infection, and from a bacterial infection, fungal infection and viral infection, or suffer from a mixed infection comprising one or more of the infections listed herein, including potentially a superinfection, for example one or more bacterial infections in addition to one or more viral infections and/or one or more fungal infections.

[0172] As used herein “infectious disease” comprises all diseases or disorders that are associated with bacterial and/or viral and/or fungal infections.

[0173] According to the present invention, critically ill patients, such as septic patients may need a very strict control, with respect of vital functions and/or monitoring of organ protection and may be under medical treatment.

[0174] In the context of the present invention, the term “medical treatment” or “treatment” comprises various treatments and therapeutic strategies, which comprise, without limitation, anti-inflammatory strategies, administration of ADM-antagonists such as therapeutic antibodies, si-RNA or DNA, the extracorporal blood purification or the removal of harmful substances via apheresis, dialyses, adsorbers to prevent the cytokine storm, removal of inflammatory mediators, plasma apheresis, administration of vitamins such as vitamin C, antibiotic treatment, fluid therapy, apheresis and measures for organ protection.

[0175] In a preferred embodiment, the term “medical treatment” or “treatment” comprises antibiotic treatment such as intraveneous antibiotic, oral antibiotics or topical antibiotics.

[0176] In a more preferred embodiment, the term “medical treatment” or “treatment” comprises intravenously applied antibiotic treatment.

[0177] Additionally, medical treatments of the present invention comprise, without limitation, stabilization of the blood clotting, iNOS inhibitors, anti-inflammatory agents like hydrocortisone, sedatives and analgetics as well as insulin.

[0178] “Fluid management” refers to the monitoring and controlling of the fluid status of a subject and the administration of fluids to stabilize the circulation or organ vitality, by e.g. oral, enteral or intravenous fluid administration. It comprises the stabilization of the fluid and electrolyte balance or the prevention or correction of hyper- or hypovolemia as well as the supply of blood products.

[0179] In the case of critical illness, such as sepsis or severe infections it is very important to have an early diagnosis as well a prognosis and risk assessment for the outcome of a patient to find the optimal therapy and management. The therapeutic approaches need to be very individual and vary from case to case. A therapeutic monitoring is needed for a best practice therapy and is influenced by the timing of treatment, the use of combined therapies and the optimization of drug dosing. A wrong or omitted therapy or management will increase the mortality rate hourly.

[0180] The term “comorbidity” in the context of the present invention refers to any further pathology or disease of the patient of the method of the invention that may be present in addition to a suspected infection or sepsis. Such comorbidities may comprise, without limitation, cardiovascular disease, atrial fibrillation, flutter, congestive heart failure, COPD, asthma, lung fibrosis, asbestosis, pulmonary disease, immunodeficiency, diabetes, renal disease, hypertension, stroke, transient ischemic attack (TIA), dementia, anaemia, thrombosis, rheumatic disease, neuromuscular disease, malignancy or cancer.

[0181] A medical treatment of the present invention may be an antibiotic treatment, wherein one or more “antibiotics” or “antibiotic agents” may be administered if an infection has been diagnosed or symptoms of an infectious disease have been determined.

[0182] Antibiotics or antibiotic agents according to the present invention also encompass potentially the anti-fungal or anti-viral compounds used to treat a diagnosed infection or sepsis. The antibiotic agents commonly applied in the treatment of any given infection, as separated into the classes of pathogen are:

[0183] Gram positive coverage: Penicillins, (ampicillin, amoxicillin), penicillinase resistant, (Dicloxacillin, Oxacillin), Cephalosporins (1st and 2nd generation), Macrolides (Erythromycin, Clarithromycin, Azithromycin), Quinolones (gatifloxacin, moxifloxacin, levofloxacin), Vancomycin, Sulfonamide/trimethoprim, Clindamycin, Tetracyclines, Chloramphenicol, Linezolid, Synercid.

[0184] Gram negative coverage: Broad spectrum penicillins (Ticarcillin, clavulanate, piperacillin, tazobactam), Cephalosporins (2nd, 3rd, and 4th generation), Aminoglycosides, Macrolides, Azithromycin, Quinolones (Ciprofloxacin), Monobactams (Azetreonam), Sulfonamide/trimethoprim, Carbapenems (Imipenem), Chloramphenicol.

[0185] Pseudomonas coverage: Ciprofloxacin, Aminoglycosides, Some 3rd generation cephalosporins, 4th generation cephalosporins, Broad spectrum penicillins, Carbapenems.

[0186] Further antibiotic agents include for example Bensylpenicillin, Cefotaxim, Klaxacillin, Klindamycin, Aminoglycosides, Metronidazol, Piperacillin-Tazobactam, Meropenem, Imipinem, Erytromycin, Quinolone, Trimetoprim and Vancomycin.

[0187] Fungal treatments: Allyamines, Amphotericin B, Fluconazole and other Azoles, itraconazole, voriconazole, posaconazole, ravuconazole, echinocandins, Flucytosine, sordarins, chitin synthetase inhibitors, topoisomerase inhibitors, lipopeptides, pradimycins, Liposomal nystatin, Voriconazole, Echinocanidins, Imidazole, Triazole, Thiazole, Polyene.

[0188] Anti-viral treatments: Abacavir, Acyclovir (Aciclovir), activated caspase oligomerizer, Adefovir, Amantadine, Amprenavir(Agenerase), Ampligen, Arbidol, Atazanavir, Atripla, Balavir, Cidofovir, Combivir, Dolutegravir, Darunavir, Delavirdine, Didanosine, Double-stranded RNA, Docosanol, Edoxudine, Efavirenz, Emtricitabine, Enfuvirtide, Entecavir, Ecoliever, Famciclovir, Fixed dose combination (antiretroviral), Fomivirsen, Fosamprenavir, Foscarnet, Fosfonet, Fusion inhibitor, Ganciclovir, Ibacitabine, Imunovir, Idoxuridine, Imiquimod, Indinavir, Inosine, Integrase inhibitor, Interferon type III, Interferon type II, Interferon type I, Interferon, Lamivudine, Lopinavir, Loviride, Maraviroc, Moroxydine, Methisazone, Morpholinos, Nelfinavir, Nevirapine, Nexavir, Nitazoxanide, Nucleoside analogues, Novir, Oseltamivir (Tamiflu), Peginterferon alfa-2a, Penciclovir, Peramivir, Pleconaril, Podophyllotoxin, Protease inhibitor (pharmacology), Raltegravir, Reverse transcriptase inhibitor, Ribavirin, Ribozymes, Rifampicin, Rimantadine, Ritonavir, RNase H, protease inhibitors, Pyramidine, Saquinavir, Sofosbuvir, Stavudine, Synergistic enhancer (antiretroviral), Telaprevir, Tenofovir, Tenofovir disoproxil, Tipranavir, Trifluridine, Trizivir, Tromantadine, Truvada, Valaciclovir (Valtrex), Valganciclovir, Vicriviroc, Vidarabine, Viramidine, Zalcitabine, Zanamivir (Relenza), Zidovudine.

[0189] Furthermore, antibiotic agents comprise bacteriophages for treatment of bacterial infections, synthetic antimicrobial peptides or iron-antagonists/iron chelator can be used. Also, therapeutic antibodies or antagonist against pathogenic structures like anti-VAP-antibodies, anti-resistant clone vaccination, administration of immune cells, such as in vitro primed or modulated T-effector cells, are antibiotic agents that represent treatment options for critically ill patients, such as sepsis patients. Further antibiotic agents/treatments or therapeutic strategies against infection or for the prevention of new infections include the use of antiseptics, decontamination products, anti-virulence agents like liposomes, sanitation, wound care, surgery.

[0190] It is also possible to combine several of the aforementioned antibiotic agents or treatments strategies.

[0191] According to the present invention proADM and optionally PCT and/or other markers or clinical scores are employed as markers for therapy antibiotic therapy guidance, stratification and/or control in a patient suspected of having an infection.

[0192] A skilled person is capable of obtaining or developing means for the identification, measurement, determination and/or quantification of any one of the above proADM molecules, or fragments or variants thereof, as well as the other markers of the present invention according to standard molecular biological practice.

[0193] The level of proADM or fragments thereof as well as the levels of other markers of the present invention can be determined by any assay that reliably determines the concentration of the marker. Particularly, mass spectrometry (MS) and/or immunoassays can be employed as exemplified in the appended examples. As used herein, an immunoassay is a biochemical test that measures the presence or concentration of a macromolecule/polypeptide in a solution through the use of an antibody or antibody binding fragment or immunoglobulin.

[0194] Methods of determining proADM or other the markers such as PCT used in the context of the present invention are intended in the present invention. By way of example, a method may be employed selected from the group consisting of mass spectrometry (MS), luminescence immunoassay (LIA), radioimmunoassay (RIA), chemiluminescence- and fluorescence-immunoassays, enzyme immunoassay (EIA), Enzyme-linked immunoassays (ELISA), luminescence-based bead arrays, magnetic beads based arrays, protein microarray assays, rapid test formats such as for instance immunochromatographic strip tests, rare cryptate assay, and automated systems/analysers.

[0195] Determination of proADM and optionally other markers based on antibody recognition is a preferred embodiment of the invention. As used herein, the term, “antibody” refers to immunoglobulin molecules and immunologically active portions of immunoglobulin (Ig) molecules, i.e., molecules that contain an antigen binding site that specifically binds (immuno reacts with) an antigen. According to the invention, the antibodies may be monoclonal as well as polyclonal antibodies. Particularly, antibodies that are specifically binding to at least proADM or fragments thereof are used.

[0196] An antibody is considered to be specific, if its affinity towards the molecule of interest, e.g. proADM, or the fragment thereof is at least 50-fold higher, preferably 100-fold higher, most preferably at least 1000-fold higher than towards other molecules comprised in a sample containing the molecule of interest. It is well known in the art how to develop and to select antibodies with a given specificity. In the context of the invention, monoclonal antibodies are preferred. The antibody or the antibody binding fragment binds specifically to the herein defined markers or fragments thereof. In particular, the antibody or the antibody binding fragment binds to the herein defined peptides of proADM. Thus, the herein defined peptides can also be epitopes to which the antibodies specifically bind. Further, an antibody or an antibody binding fragment is used in the methods and kits of the invention that binds specifically to ADM or proADM, particularly to MR-proADM.

[0197] Further, an antibody or an antibody binding fragment is used in the methods and kits of the invention that binds specifically to proADM or fragments thereof and optionally to other markers of the present inventions such as PCT. Exemplary immunoassays can be luminescence immunoassay (LIA), radioimmunoassay (RIA), chemiluminescence- and fluorescence-immunoassays, enzyme immunoassay (EIA), Enzyme-linked immunoassays (ELISA), luminescence-based bead arrays, magnetic beads based arrays, protein microarray assays, rapid test formats, rare cryptate assay. Further, assays suitable for point-of-care testing and rapid test formats such as for instance immune-chromatographic strip tests can be employed. Automated immunoassays are also intended, such as the KRYPTOR assay.

[0198] Alternatively, instead of antibodies, other capture molecules or molecular scaffolds that specifically and/or selectively recognize proADM or fragments thereof may be encompassed by the scope of the present invention. Herein, the term “capture molecules” or “molecular scaffolds” comprises molecules which may be used to bind target molecules or molecules of interest, i.e. analytes (e.g. ADM, proADM, MR-proADM, and PCT), from a sample. Capture molecules must thus be shaped adequately, both spatially and in terms of surface features, such as surface charge, hydrophobicity, hydrophilicity, presence or absence of lewis donors and/or acceptors, to specifically bind the target molecules or molecules of interest. Hereby, the binding may, for instance, be mediated by ionic, van-der-Waals, pi-pi, sigma-pi, hydrophobic or hydrogen bond interactions or a combination of two or more of the aforementioned interactions or covalent interactions between the capture molecules or molecular scaffold and the target molecules or molecules of interest. In the context of the present invention, capture molecules or molecular scaffolds may for instance be selected from the group consisting of a nucleic acid molecule, a carbohydrate molecule, a PNA molecule, a protein, a peptide and a glycoprotein. Capture molecules or molecular scaffolds include, for example, aptamers, DARpins (Designed Ankyrin Repeat Proteins). Affimers and the like are included.

[0199] In certain aspects of the invention, the method is an immunoassay comprising the steps of:

[0200] a) contacting the sample with [0201] i. a first antibody or an antigen-binding fragment or derivative thereof specific for a first epitope of said proADM, and [0202] ii. a second antibody or an antigen-binding fragment or derivative thereof specific for a second epitope of said proADM; and

[0203] b) detecting the binding of the two antibodies or antigen-binding fragments or derivates thereof to said proADM.

[0204] Preferably, one of the antibodies can be labeled and the other antibody can be bound to a solid phase or can be bound selectively to a solid phase. In a particularly preferred aspect of the assay, one of the antibodies is labeled while the other is either bound to a solid phase or can be bound selectively to a solid phase. The first antibody and the second antibody can be present dispersed in a liquid reaction mixture, and wherein a first labeling component which is part of a labeling system based on fluorescence or chemiluminescence extinction or amplification is bound to the first antibody, and a second labeling component of said labeling system is bound to the second antibody so that, after binding of both antibodies to said proADM or fragments thereof to be detected, a measurable signal which permits detection of the resulting sandwich complexes in the measuring solution is generated. The labeling system can comprise a rare earth cryptate or chelate in combination with a fluorescent or chemiluminescent dye, in particular of the cyanine type.

[0205] In a preferred embodiment, the method is executed as heterogeneous sandwich immunoassay, wherein one of the antibodies is immobilized on an arbitrarily chosen solid phase, for example, the walls of coated test tubes (e.g. polystyrol test tubes; coated tubes; CT) or microtiter plates, for example composed of polystyrol, or to particles, such as for instance magnetic particles, whereby the other antibody has a group resembling a detectable label or enabling for selective attachment to a label, and which serves the detection of the formed sandwich structures. A temporarily delayed or subsequent immobilization using suitable solid phases is also possible.

[0206] The method according to the present invention can furthermore be embodied as a homogeneous method, wherein the sandwich complexes formed by the antibody/antibodies and the marker, proADM or a fragment thereof, which is to be detected remains suspended in the liquid phase. In this case it is preferred, that when two antibodies are used, both antibodies are labeled with parts of a detection system, which leads to generation of a signal or triggering of a signal if both antibodies are integrated into a single sandwich. Such techniques are to be embodied in particular as fluorescence enhancing or fluorescence quenching detection methods. A particularly preferred aspect relates to the use of detection reagents which are to be used pair-wise, such as for example the ones which are described in U.S. Pat. No. 4,882,733, EP0180492 or EP0539477 and the prior art cited therein. In this way, measurements in which only reaction products comprising both labeling components in a single immune-complex directly in the reaction mixture are detected, become possible. For example, such technologies are offered under the brand names TRACE® (Time Resolved Amplified Cryptate Emission) or KRYPTOR®, implementing the teachings of the above-cited applications. Therefore, in particular preferred aspects, a diagnostic device is used to carry out the herein provided method. For example, the level of proADM or fragments thereof and/or the level of any further marker of the herein provided method, such as PCT, is determined. In particular preferred aspects, the diagnostic device is KRYPTOR®.

[0207] The level of the marker of the present invention, e.g. the proADM or fragments thereof, PCT or fragments thereof, or other markers, can also be determined by a mass spectrometric (MS) based methods. Such a method may comprise detecting the presence, amount or concentration of one or more modified or unmodified fragment peptides of e.g. proADM or the PCT in said biological sample or a protein digest (e.g. tryptic digest) from said sample, and optionally separating the sample with chromatographic methods, and subjecting the prepared and optionally separated sample to MS analysis. For example, selected reaction monitoring (SRM), multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) mass spectrometry may be used in the MS analysis, particularly to determine the amounts of proADM or fragments thereof.

[0208] Herein, the term “mass spectrometry” or “MS” refers to an analytical technique to identify compounds by their mass. In order to enhance the mass resolving and mass determining capabilities of mass spectrometry, the samples can be processed prior to MS analysis. Accordingly, the invention relates to MS detection methods that can be combined with immuno-enrichment technologies, methods related to sample preparation and/or chromatographic methods, preferably with liquid chromatography (LC), more preferably with high performance liquid chromatography (HPLC) or ultra high performance liquid chromatography (UHPLC). Sample preparation methods comprise techniques for lysis, fractionation, digestion of the sample into peptides, depletion, enrichment, dialysis, desalting, alkylation and/or peptide reduction. However, these steps are optional. The selective detection of analyte ions may be conducted with tandem mass spectrometry (MS/MS). Tandem mass spectrometry is characterized by mass selection step (as used herein, the term “mass selection” denotes isolation of ions having a specified m/z or narrow range of m/z's), followed by fragmentation of the selected ions and mass analysis of the resultant product (fragment) ions.

[0209] The skilled person is aware how quantify the level of a marker in the sample by mass spectrometric methods. For example, relative quantification “rSRM” or absolute quantification can be employed as described above.

[0210] Moreover, the levels (including reference levels) can be determined by mass spectrometric based methods, such as methods determining the relative quantification or determining the absolute quantification of the protein or fragment thereof of interest.

[0211] Relative quantification “rSRM” may be achieved by:

[0212] 1. Determining increased or decreased presence of the target protein by comparing the SRM (Selected reaction monitoring) signature peak area from a given target fragment peptide detected in the sample to the same SRM signature peak area of the target fragment peptide in at least a second, third, fourth or more biological samples.

[0213] 2. Determining increased or decreased presence of target protein by comparing the SRM signature peak area from a given target peptide detected in the sample to SRM signature peak areas developed from fragment peptides from other proteins, in other samples derived from different and separate biological sources, where the SRM signature peak area comparison between the two samples for a peptide fragment are normalized for e.g to amount of protein analysed in each sample.

[0214] 3. Determining increased or decreased presence of the target protein by comparing the SRM signature peak area for a given target peptide to the SRM signature peak areas from other fragment peptides derived from different proteins within the same biological sample in order to normalize changing levels of histones protein to levels of other proteins that do not change their levels of expression under various cellular conditions.

[0215] 4. These assays can be applied to both unmodified fragment peptides and to modified fragment peptides of the target proteins, where the modifications include, but are not limited to phosphorylation and/or glycosylation, acetylation, methylation (mono, di, tri), citrullination, ubiquitinylation and where the relative levels of modified peptides are determined in the same manner as determining relative amounts of unmodified peptides.

[0216] Absolute quantification of a given peptide may be achieved by:

[0217] 1. Comparing the SRM/MRM signature peak area for a given fragment peptide from the target proteins in an individual biological sample to the SRM/MRM signature peak area of an internal fragment peptide standard spiked into the protein lysate from the biological sample. The internal standard may be a labelled synthetic version of the fragment peptide from the target protein that is being interrogated or the labelled recombinant protein. This standard is spiked into a sample in known amounts before (mandatory for the recombinant protein) or after digestion, and the SRM/MRM signature peak area can be determined for both the internal fragment peptide standard and the native fragment peptide in the biological sample separately, followed by comparison of both peak areas. This can be applied to unmodified fragment peptides and modified fragment peptides, where the modifications include but are not limited to phosphorylation and/or glycosylation, acetylation, methylation (e.g. mono-, di-, or tri-methylation), citrullination, ubiquitinylation, and where the absolute levels of modified peptides can be determined in the same manner as determining absolute levels of unmodified peptides.

[0218] 2. Peptides can also be quantified using external calibration curves. The normal curve approach uses a constant amount of a heavy peptide as an internal standard and a varying amount of light synthetic peptide spiked into the sample. A representative matrix similar to that of the test samples needs to be used to construct standard curves to account for a matrix effect. Besides, reverse curve method circumvents the issue of endogenous analyte in the matrix, where a constant amount of light peptide is spiked on top of the endogenous analyte to create an internal standard and varying amounts of heavy peptide are spiked to create a set of concentration standards. Test samples to be compared with either the normal or reverse curves are spiked with the same amount of standard peptide as the internal standard spiked into the matrix used to create the calibration curve.

[0219] The invention further relates to kits, the use of the kits and methods wherein such kits are used. The invention relates to kits for carrying out the herein above and below provided methods. The herein provided definitions, e.g. provided in relation to the methods, also apply to the kits of the invention. In particular, the invention relates to kits for therapy guidance, stratification and/or controlling a patient suspected of having an infection, wherein said kit comprises [0220] detection reagents for determining the level proADM or fragment(s) thereof, and optionally additionally for determining the level of PCT, lactate and/or C-reactive protein or fragment(s) thereof, in a sample from a subject, and [0221] reference data, such as a reference level, corresponding to a level of proADM or fragment(s) thereof in said sample equal to or above 1 nmol/L, preferably equal to or above 1.2 nmol/I, more preferably equal to or above 1.27 nmol/L, and optionally PCT, lactate and/or C-reactive protein levels, wherein said reference data is preferably stored on a computer readable medium and/or employed in the form of computer executable code configured for comparing the determined levels of proADM or fragment(s) thereof, and optionally additionally the determined levels of PCT, lactate and/or C-reactive protein or fragment(s) thereof, to said reference data.

[0222] As used herein, “reference data” comprise reference level(s) of proADM and optionally PCT, lactate and/or C-reactive protein. The levels of proADM and optionally PCT, lactate and/or C-reactive protein in the sample of the subject can be compared to the reference levels comprised in the reference data of the kit. The reference levels are herein described above and are exemplified also in the appended examples. The reference data can also include a reference sample to which the level of proADM and optionally PCT, lactate and/or C-reactive protein is compared. The reference data can also include an instruction manual how to use the kits of the invention.

[0223] The kit may additionally comprise items useful for obtaining a sample, such as a blood sample, for example the kit may comprise a container, wherein said container comprises a device for attachment of said container to a cannula or syringe, is a syringe suitable for blood isolation, exhibits an internal pressure less than atmospheric pressure, such as is suitable for drawing a pre-determined volume of sample into said container, and/or comprises additionally detergents, chaotropic salts, ribonuclease inhibitors, chelating agents, such as guanidinium isothiocyanate, guanidinium hydrochloride, sodium dodecylsulfate, polyoxyethylene sorbitan monolaurate, RNAse inhibitor proteins, and mixtures thereof, and/or A filter system containing nitro-cellulose, silica matrix, ferromagnetic spheres, a cup retrieve spill over, trehalose, fructose, lactose, mannose, poly-ethylen-glycol, glycerol, EDTA, TRIS, limonene, xylene, benzoyl, phenol, mineral oil, anilin, pyrol, citrate, and mixtures thereof.

[0224] As used herein, the “detection reagent” or the like are reagents that are suitable to determine the herein described marker(s), e.g. of proADM, PCT, lactate and/or C-reactive protein. Such exemplary detection reagents are, for example, ligands, e.g. antibodies or fragments thereof, which specifically bind to the peptide or epitopes of the herein described marker(s). Such ligands might be used in immunoassays as described above. Further reagents that are employed in the immunoassays to determine the level of the marker(s) may also be comprised in the kit and are herein considered as detection reagents. Detection reagents can also relate to reagents that are employed to detect the markers or fragments thereof by MS based methods. Such detection reagent can thus also be reagents, e.g. enzymes, chemicals, buffers, etc., that are used to prepare the sample for the MS analysis. A mass spectrometer can also be considered as a detection reagent. Detection reagents according to the invention can also be calibration solution(s), e.g. which can be employed to determine and compare the level of the marker(s).

[0225] The sensitivity and specificity of a diagnostic and/or prognostic test depends on more than just the analytical “quality” of the test, they also depend on the definition of what constitutes an abnormal result. In practice, Receiver Operating Characteristic curves (ROC curves), are typically calculated by plotting the value of a variable versus its relative frequency in “normal” (i.e. apparently healthy individuals not having an infection and “disease” populations, e.g. subjects having an infection. For any particular marker (like proADM), a distribution of marker levels for subjects with and without a disease/condition will likely overlap. Under such conditions, a test does not absolutely distinguish normal from disease with 100% accuracy, and the area of overlap might indicate where the test cannot distinguish normal from disease. A threshold is selected, below which the test is considered to be abnormal and above which the test is considered to be normal or below or above which the test indicates a specific condition, e.g. infection. The area under the ROC curve is a measure of the probability that the perceived measurement will allow correct identification of a condition. ROC curves can be used even when test results do not necessarily give an accurate number. As long as one can rank results, one can create a ROC curve. For example, results of a test on “disease” samples might be ranked according to degree (e.g. 1=low, 2=normal, and 3=high). This ranking can be correlated to results in the “normal” population, and a ROC curve created. These methods are well known in the art; see, e.g., Hanley et al. 1982. Radiology 143: 29-36. Preferably, a threshold is selected to provide a ROC curve area of greater than about 0.5, more preferably greater than about 0.7, still more preferably greater than about 0.8, even more preferably greater than about 0.85, and most preferably greater than about 0.9. The term “about” in this context refers to +/−5% of a given measurement.

[0226] The horizontal axis of the ROC curve represents (1-specificity), which increases with the rate of false positives. The vertical axis of the curve represents sensitivity, which increases with the rate of true positives. Thus, for a particular cut-off selected, the value of (1-specificity) may be determined, and a corresponding sensitivity may be obtained. The area under the ROC curve is a measure of the probability that the measured marker level will allow correct identification of a disease or condition. Thus, the area under the ROC curve can be used to determine the effectiveness of the test.

[0227] Accordingly, the invention comprises the administration of an antibiotic suitable for treatment on the basis of the information obtained by the method described herein.

[0228] The present invention encompasses administration of the pharmaceutical composition of the present invention to a subject. As used herein, “administration” or “administering” shall include, without limitation, introducing the composition by oral administration. Such administering can also be performed, for example, once, a plurality of times, and/or over one or more extended periods. A single administration is preferred, but repeated administrations over time (e.g., hourly, daily, weekly, monthly, quarterly, half-yearly or yearly) may be necessary in some instances. Such administering is also preferably performed using an admixture and a pharmaceutically acceptable carrier. Pharmaceutically acceptable carriers are well known to those skilled in the art.

[0229] Administration may also occur locally, for example by injection at the site where the antibiotic agent(s) should be active, for example by endoscopic or microinvasive means.

[0230] The composition described herein may comprise different types of carriers depending on whether it is to be administered in solid, liquid or aerosol form, and whether it need to be sterile for such routes of administration as injection. The composition of the present invention can be administered intravenously, intradermally, intraarterially, intraperitoneally, intralesionally, intracranially, intraarticularly, intraprostaticaly, intrapleurally, intratracheally, intranasally, intravitreally, intravaginally, intrarectally, topically, intratumorally, intramuscularly, intraperitoneally, subcutaneously, subconjunctival, intravesicularlly, mucosally, intrapericardially, intraumbilically, intraocularally, orally, topically, locally, inhalation (e.g., aerosol inhalation), injection, infusion, continuous infusion, localized perfusion bathing target cells directly, via a catheter, via a lavage, in cremes, in lipid compositions (e.g., liposomes), or by other method or any combination of the forgoing as would be known to one of ordinary skill in the art (see, for example, Remington's Pharmaceutical Sciences, 18th Ed. Mack Printing Company, 1990, incorporated herein by reference).

[0231] Additionally, such compositions can comprise pharmaceutically acceptable carriers that can be aqueous or non-aqueous solutions, suspensions, and emulsions, most preferably aqueous solutions or solid formulations of various types known in the art. Aqueous carriers include water, alcoholic/aqueous solutions, emulsions and suspensions, including saline and buffered media. Parenteral vehicles include sodium chloride solution, Ringer's dextrose, dextrose and sodium chloride, lactated Ringer's and fixed oils. Intravenous vehicles include fluid and nutrient replenishers, electrolyte replenishers such as Ringer's dextrose, those based on Ringer's dextrose, and the like. Fluids used commonly for i.v. administration are found, for example, in Remington: The Science and Practice of Pharmacy, 20th Ed., p. 808, Lippincott Williams S-Wilkins (2000). Preservatives and other additives may also be present, such as, for example, antimicrobials, antioxidants, chelating agents, inert gases, and the like.

[0232] As used herein, the terms “comprising” and “including” or grammatical variants thereof are to be taken as specifying the stated features, integers, steps or components but do not preclude the addition of one or more additional features, integers, steps, components or groups thereof. This term encompasses the terms “consisting of” and “consisting essentially of”.

[0233] Thus, the terms “comprising”/“including”/“having” mean that any further component (or likewise features, integers, steps and the like) can/may be present. The term “consisting of” means that no further component (or likewise features, integers, steps and the like) is present.

[0234] The term “consisting essentially of” or grammatical variants thereof when used herein are to be taken as specifying the stated features, integers, steps or components but do not preclude the addition of one or more additional features, integers, steps, components or groups thereof but only if the additional features, integers, steps, components or groups thereof do not materially alter the basic and novel characteristics of the claimed composition, device or method.

[0235] Thus, the term “consisting essentially of” means those specific further components (or likewise features, integers, steps and the like) can be present, namely those not materially affecting the essential characteristics of the composition, device or method. In other words, the term “consisting essentially of” (which can be interchangeably used herein with the term “comprising substantially”), allows the presence of other components in the composition, device or method in addition to the mandatory components (or likewise features, integers, steps and the like), provided that the essential characteristics of the device or method are not materially affected by the presence of other components.

[0236] 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, biological and biophysical arts.

[0237] The present invention is further described by reference to the following non-limiting examples.

EXAMPLES

[0238] The invention is further described by the following examples. These are not intended to limit the scope of the invention, but represent preferred embodiments of aspects of the invention provided for greater illustration of the invention described herein.

[0239] Methods of the Examples:

[0240] Study Design and Setting:

[0241] This study was conducted at the emergency department at Skåne University Hospital, Malmo, Sweden. Consecutive adult patients with a clinically suspected infection were prospectively enrolled between December 2013 and February 2015. The inclusion criteria were suspected infection as judged by the attending nurse and ≥2 SIRS criteria. SIRS was defined as the following; temperature >38° C. or <36° C. or self-reported fever/chills within the past 24 hours, respiration rate >20 breaths/min and a heart rate >90 beats/min. White blood cell count (WBC count) was not used as an inclusion criteria due to the lack of measurement at arrival. The study was approved by the Regional Ethical Review Board at Lund University, Sweden (2013/635) and was conducted in accordance with the Helsinki Declaration. Informed consent was obtained from all patients or their next of kin.

[0242] Data collection and Biomarker Measurements:

[0243] Patients were enrolled by the attending research nurse between 6 am and 6 pm, and medical records systematically reviewed for demographics, comorbidities and concomitant medications. Routine laboratory tests were performed by the certified laboratory of the Department of Clinical Chemistry at Skåne University Hospital, and microbiological tests and radiological examinations also noted. In addition, the time from emergency department presentation to the first dose of antibiotics and other treatments were registered, as was information on the requirement for supportive organ therapy such as supplemental oxygen, intravenous fluids, and the requirement for vasopressor, mechanical ventilation and renal placement therapy. Patient length of stay, admission to the ICU, 28 day and overall hospital mortality information was also registered. EDTA plasma samples were frozen within 2 hours after sample collection, stored at −80° C. and never thawed before analysis. PCT and MR-proADM were measured in all 213 samples using a commercially available double sandwich immunoassay on a KRYPTOR platform (Thermo Fisher Scientific, Germany).

[0244] Definition of Outcomes

[0245] The presence of organ dysfunction and infectious status for each patient was determined by the study physician. For patients not clearly meeting the criteria for organ dysfunction or infection, two infectious disease specialists reviewed the data and decided on the final classification. The primary outcomes were the requirement for intravenous antibiotics, time to treatment, the development of infection related organ dysfunction (severe sepsis) within a 48 hour period from enrolment, the presence of bacteremia, and all-cause 28 day mortality.

[0246] The criteria for organ dysfunction were adapted from the consensus criteria and the current SSC guidelines.sup.23, 24. Accordingly, severe sepsis was defined as an infectious disease with at least 2 SIRS criteria, and the presence or development of hypotension, hypoperfusion and/or organ failure within 48 h after admission. Septic shock was defined as sepsis plus hypotension (systolic blood pressure <90 mmHg, or mean arterial pressure <70 mmHg) requiring fluid resuscitation or the administration of vasopressors.

[0247] Statistical Analysis:

[0248] Differences in clinical characteristics with regards to 28 day mortality were assessed using the χ.sup.2 test for categorical variables, and depending on distribution normality, either Student's t-test or the Mann-Whitney U test for continuous variables. Normally and non-normally distributed variables were expressed in terms of mean (standard deviation) and median [first quartile—third quartile], respectively. The association between antibiotic requirement, prediction of bacteremia, development of severe sepsis and prediction of mortality within 28 days with each biomarker and clinical score was assessed using area under the receiver operating characteristic curves (AUROC), logistic and Cox regression analysis. Logistic regression models were created using either biomarkers or scores in isolation, or adjusted with sex and age variables, and expressed as Odds Ratios (OR) and 95% confidence intervals [95% CI]. A two sided p<0.05 was considered statistically significant. All data were analyzed using the statistics software R (version 3.1.2).

Example 1: Patient Characteristics

[0249] A total of 213 patients were enrolled in the study, with 113 (53.1%) developing severe sepsis within the first 48 hours after presentation, and 7 (6.9%) presenting with septic shock. The average age of the total population was 67.8 years, with no significant differences between genders (50.2% male). Patients exhibited a high degree of comorbidities, which included cases of hypertension (42.2%), anaemia (35.4%), coronary heart disease (22.3%), chronic obstructive pulmonary disease (18.4%) and diabetes (17.0%). An infectious origin could be established in 190 (89.2%) patients, with pulmonary (N=85; 39.9%), urinary tract (N=53; 24.9%) and soft tissue or skin (N=21; 9.9%) infections most prevalent. The overall 28 day mortality rate across the total population was 8.9%, with 203 (95.3%) patients having a SOFA score of 56 points. All biomarkers and clinical scores were significantly higher in non-surviving patients compared to survivors. Non-survivors were also more likely to develop severe sepsis (p<0.01), have a higher number of organ failures (p<0.001), or be admitted onto the intensive care unit (p<0.05).

[0250] Patient characteristics with respect to 28 day mortality are summarised in Table 1.

Example 2: The Use of Biomarkers as an Aid in Assessing Requirement for Antibiotics

[0251] Antibiotics were administered to a total of 187 (87.8%) patients within the study population. Of these patients, 164 (77.0%) were treated with intravenous antibiotics only, 6 (2.8%) were given a mix of intravenous and oral antibiotics, and 17 (8.0%) treated with oral antibiotics only. A comprehensive outline of the use of intravenous antibiotics can be found in Supplementary Table 2. The median time to initial intravenous antibiotic treatment was 93 [28-160] minutes, with 71 (43.8%) patients receiving initial antibiotic therapy within 60 minutes.

[0252] Logistic regression analysis indicated that MR-proADM had the strongest association with the requirement for intravenous antibiotics in both regression models (Table 3). Similar results were also found for PCT with the odds ratio for both markers greater than that of CRP or lactate. The addition of either PCT or MR-proADM to one another in a multivariate model significantly increased the prediction of antibiotic requirement (p<0.05).

[0253] Optimal cut-offs were subsequently calculated for all biomarkers based on AUROC analysis, resulting in PCT and MR-proADM cut-offs of 0.12 ng/ml and 1.27 nmol/L, respectively (Table 4). Subgroup analysis indicated significant differences between intravenous antibiotic requirement based on a combination of these marker cut-offs (Table 5). Interestingly, the median time to antibiotic administration in patients with MR-proADM values <1.27 nmol/L was 139 [81-209] minutes, which was significantly longer than in patients with values 21.27 nmol/L (43 [26-134] minutes; p<0.001). In contrast, there were no significant differences for PCT values.

[0254] Finally, 26 (12.6%) patients were found to have been prescribed antibiotics less than 48 hours prior to entering the ED. Whilst this had little effect on MR-proADM performance, the predictive value of PCT for antibiotic requirement was found to increase from OR [955 CI]: 4.22 [2.21-8.04] to 5.45 [2.49-11.93] when these patients were excluded from the analysis.

Example 3: Added Value of PCT and MR-proADM Combinations for Predicting the Requirement for Intravenous Antibiotics

[0255] In comparison to the logistic regression analysis for individual biomarkers alone and for a multivariate model including age and gender of the patients, the addition of PCT to the MR-proADM multivariate model (age+gender) (Table 6) and that addition of MR-proADM to the PCT multivariate model (age+gender) (Table 7) showed that MR-proADM adds more value to PCT for predicting the requirement for intravenous antibiotics (as evidenced by the higher added LR.sup.2 number, and the lower p-value for significance) than PCT does to MR-proADM. However, both combinations were significant.

[0256] Similarities can also be found when patients who were previously on antibiotic treatment (and therefore artificially decreasing the PCT concentration on arrival to the ED) were excluded from the analysis as shown in Table 8 for individual markers alone and in Table 9 for the multivariate model including age and gender. Addition of PCT to the MR-proADM multivariate model (age+gender) (Table 10) and addition of MR-proADM to the PCT multivariate model (age+gender) (Table 11) showed that both combinations were significant.

Example 4: Prediction of Bacteraemia and Development of Severe Sepsis

[0257] A positive blood culture could be obtained in 34 (16.1%) patients, with Escherichia coli (n=9), Staphylococcus aureus (n=4) and Klebsiella pneumonie (n=4) the most prevalent pathogens. The use of PCT had the strongest predictive value for bacteraemia (OR [95% CI]: 3.73 [2.14-6.51]), although within a multivariate model, the greatest predictive value could be found with MR-proADM (OR [95% CI]: 4.24 [2.31-7.76]); Table 12). Interestingly, the addition of MR-proADM to the multivariate model containing PCT could significantly increase predictive value (p<0.05), whereas PCT did not add to the corresponding model containing MR-proADM. Additional AUROC analysis is reported in Table 13.

[0258] Similar results could also be found for the development of severe sepsis within 48 hours of ED admission, with MR-proADM having the greatest predictive value (OR [95% CI]: 5.79 [3.30-10.16]) followed by PCT (OR [95% CI]: 4.33 [2.58-7.27]; Table 14 and Table 15). The use of lactate and CRP were relatively poor predictors of severe sepsis development (OR [95% CI]: 2.31 [1.48-3.61] and 1.94 [1.28-2.95], respectively).

Example 5: Prediction of all Cause 28 Day Mortality

[0259] AUROC and Cox regression analysis indicated that MR-proADM had the greatest performance in assessing disease severity, when measured in terms of overall 28 day mortality. Whilst there were no significant differences between the performance of MR-proADM and SOFA, values were consistently higher for MR-proADM in AUROC (AUROC [95% CI]: 0.86 [0.79-0.92] vs. 0.84 [0.77-0.91]; Table 16), univariate Cox regression (Hazard Ratio [95% CI]: 4.29 [2.54-7.26] vs. 3.29 [2.13-5.08]) and multivariate Cox regression (Hazard Ratio [95% CI]: 3.73 [2.12-5.58] vs. 2.77 [1.76-4.37]) analysis (Table 17).

[0260] In addition, AUROC analysis indicated an optimal sensitivity and specificity cut-off for MR-proADM of 1.73 nmol/L. When this cut-off was applied to the total patient population, 143 (67.1%) patients were found to have values of <1.73 nmol/L, with a resulting 28 day mortality rate of 1.4%, whereas 70 (32.9%) patients had values ≥1.73 nmol/L, with a corresponding 28 mortality rate of 24.3% (Hazard Ratio [95% CI] above cut-off vs. below cut-off: 15.0 [3.2-68.0]).

[0261] Finally, it could be observed that qSOFA had extremely high hazard ratios (HR IQR [95% CI]: 30.12 [5.56-163.24]; Table 16) in predicting 28 day mortality, however sensitivity at a cut-off of 2 points was relatively low (0.58 [0.36-0.77]). Indeed, of the 19 patients within this study that died within 28 days, 8 patients (42.1%) had a qSOFA score of <2 points. In each case, MR-proADM values were greater than 1.73 nmol/L.

[0262] Discussion of Examples

[0263] This study, for the first time, introduces the use of MR-proADM as a marker of sepsis disease severity in the emergency department, and uniquely highlights the importance of an early and accurate assessment of disease severity in terms of subsequent treatment decisions and likelihood of disease progression.

[0264] Such an assessment is essential in providing the appropriate level of treatment at the earliest opportunity. Indeed, it has been shown that for every hour of delay in administrating antibiotics, mortality can increase by almost 8% in the most severe cases.sup.25. However, relatively stable clinical signs and symptoms, in combination with low levels of diagnostic biomarkers, such as PCT and CRP, may lead to a delay in treatment whilst the severity of the patient's infectious condition is assessed. In these circumstances, biomarkers which are significantly increased earlier in the pathophysiological process may offer a rapid tool for assessing the need of immediate intravenous antibiotic treatment, and the requirement for specific sepsis therapies.

[0265] Accordingly, this study found that the use of mid-regional proadrenomedullin may fulfil this clinical requirement. Previous investigations have shown adrenomedullin to be increased in response to vascular permeability, endothelial and microcirculatory damage.sup.14, 17, 18, 26, 27, all of which are likely to precede any subsequent complications in organ function.sup.28, 29.

[0266] Our results show that MR-proADM performance at the earliest point of clinical contact is greater than that of all conventional biomarkers in assessing disease severity. Similar results were found in a previous intensive care sepsis study.sup.30, which grouped patients according to existing organ dysfunction, and found superior MR-proADM performance in the low (SOFA ≤6) and intermediate (SOFA between 8-13 points) severity groups. The low organ severity group is of particular interest, because not only does it “represent the earliest presentation in the clinical course of sepsis and/or the less severe form of the disease”.sup.30, but it also represents the largest infectious population entering clinical care. Furthermore, the similarities in cut-offs between the two study populations (1.73 vs. 1.79 nmol/L), as well as the high sensitivity values for predicting 28 day mortality (89% vs. 83%) strengthen the potential use of this biomarker in an ED setting, where the early stages of the disease are more prevalent. In addition, the use of a cut-off of 1.73 nmol/L found within this study can help identify a high risk infectious patient population, where potential therapies should be applied without delay.

[0267] Similarities with a previous study could also be found in the issues surrounding the use of qSOFA.sup.11. In both studies, extremely low sensitivities for predicting infectious related mortalities could be found (58% and 52%), with a significant proportion of non-surviving patients initially having a qSOFA score of 0 or 1 point. Interestingly, in each of these patients, MR-proADM values were 21.73 nmol/L, thus highlighting the use of the marker as an early tool for disease severity assessment—in this case being significantly increased earlier than established clinical signs and symptoms.

[0268] Whilst a limited number of studies using MR-proADM have focussed on overall mortality in patients presenting to the emergency department.sup.19-21, the use of MR-proADM concerning antibiotic administration and time to antibiotic treatment in sepsis patients has not been previously investigated. Whilst PCT is generally considered the optimal biomarker for antibiotic guidance in the ICU.sup.31-33, many studies have found conflicting results as to its use in the emergency department.sup.34, 35. Our results show that PCT was found to be a more accurate biomarker of antibiotic requirement and bacteraemia than CRP or lactate, however the use of MR-proADM was superior in comparison to all conventionally used biomarkers. Reasons for this may be, in part, due to the rapidly induced kinetics of the biomarker, which is increased significantly earlier than either PCT or CRP in response to lipopolysaccharide (LPS) stimulation.sup.36-38. This was also confirmed in a separate study investigating sepsis development in burns patients, with MR-proADM concentrations significantly increased one day before the diagnosis of sepsis, whereas PCT levels were significantly increased on the day of infection.sup.39.

[0269] For this study, detailed information on antibiotic administration, time to treatment, and disease progression were noted for each patient, as well as comparisons between the current gold standards of disease severity identification and the novel biomarker, MR-proADM. All patients were thoroughly reviewed by disease specialists to ensure correct diagnoses.

[0270] In conclusion, MR-proADM may offer a rapid diagnostic alternative to complex clinical scores in assessing disease severity, and can provide useful clinical information concerning the immediate requirement of antibiotics, the likelihood of disease progression, and the requirement for alternative treatment strategies in order to prevent an unfavourable outcome. Further studies are required to confirm and elaborate on these preliminary findings.

[0271] Tables

TABLE-US-00003 TABLE 1 Patient characteristics with regards to 28 day mortality Total (n = 213) Survivors (n = 194) Non-Survivors (n = 19) p-value* Age 67.8 (19.2) 66.4 (19.2) 82.2 (11.1) <0.0001 Male gender 107 (50.2%) 95 (88.8%) 12 (11.2%) 0.3367 Diagnosis Group Sepsis 100 (46.9%) 96 (96.0%) 4 (4.0%) 0.0116 Severe sepsis 113 (53.6%) 98 (50.5%) 15 (78.9%) 0.0040 ICU admission 7 (3.3%) 4 (2.1%) 3 (15.8%) 0.0171 Comorbidities Cardiovascular disease 47 (22.3%) 41 (91.1%) 6 (8.9%) 0.3838 Atrial fibrillation flutter 54 (25.6%) 44 (22.9%) 10 (52.6%) 0.0103 Congestive Heart Failure 33 (15.6%) 25 (13.0%) 8 (42.1%) 0.0034 COPD 39 (18.4%) 32 (16.6%) 7 (36.8%) 0.0552 Asthma 14 (6.6%) 12 (6.2%) 2 (10.5%) 0.3610 Fibrosis/Asbestos 4 (1.9%) 4 (2.1%) 0 (0.0%) 1.0000 Other Pulmonary Disease 3 (1.4%) 3 (1.6%) 0 (0.0%) 1.0000 Immunodeficiency 15 (7.1%) 14 (7.3%) 1 (5.6%) 1.0000 Diabetes 36 (17.0%) 31 (16.1%) 5 (26.3%) 0.3316 Renal disease 16 (7.6%) 14 (7.3%) 2 (10.5%) 0.6433 Hypertension 89 (42.2%) 77 (39.9%) 12 (66.7%) 0.0435 Stroke/TIA 34 (16.2%) 30 (15.6%) 4 (22.2%) 0.5020 Dementia 5 (2.4%) 5 (2.6%) 0 (0.0%) 1.0000 Anaemia 74 (35.4%) 64 (33.3%) 10 (58.8%) 0.0606 Thrombosis 24 (11.5%) 21 (11.0%) 3 (16.7%) 0.4421 Rheumatic Disease 14 (6.6%) 13 (6.8%) 1 (5.3%) 1.0000 Neuromuscular Disease 6 (2.8%) 6 (3.1%) 0 (0.0%) 1.0000 Malignancy 53 (25.1%) 46 (23.8%) 7 (38.9%) 0.1645 Organ dysfunction Number of organ dysfunctions 1 [0-2] 1 [0-1.25] 3 [1-3] <0.0001 Neurological 32 (15.0%) 23 (11.9%) 9 (47.4%) 0.0004 Cardiovascular 45 (21.1%) 36 (18.6%) 9 (47.4%) 0.0068 Respiratory 69 (32.4%) 56 (28.9%) 13 (68.4%) 0.0012 Renal 26 (12.2%) 21 (10.8%) 5 (26.3%) 0.0635 Hepatic 3 (1.4%) 3 (1.6%) 0 (0.0%) 1.0000 Haematological 10 (4.7%) 7 (3.6%) 3 (15.8%) 0.0485 Metabolic acidosis 25 (11.7%) 19 (9.8%) 6 (31.6%) 0.0135 Origin of infection Positive blood culture 34 (16.0%) 30 (15.5%) 4 (23.5%) 0.4873 Pulmonary 71 (33.3%) 65 (33.5%) 6 (31.6%) 1.0000 Upper airway 14 (6.6%) 14 (7.2%) 0 (0.0%) 0.6197 Urinary tract 53 (24.9%) 51 (26.3%) 2 (10.5%) 0.1688 Skeletal/Joint 1 (0.5%) 1 (0.5%) 0 (0.0%) 1.0000 Skin/Soft tissue 21 (9.9%) 16 (8.3%) 5 (26.3%) 0.0265 CNS 1 (0.5%) 1 (0.5%) 0 (0.0%) 1.0000 Abdomen 12 (5.6%) 11 (5.7%) 1 (5.3%) 1.0000 Foreign object 2 (0.9%) 1 (0.5%) 1 (5.3%) 0.1708 Unknown 2 (0.9%) 2 (1.0%) 0 (0.0%) 1.0000 Other 13 (6.1%) 13 (6.7%) 0 (0.0%) 0.6120 Treatment Corticosteroids 18 (8.5%) 15 (7.8%) 3 (15.8%) 0.2091 Mechanical ventilation 2 (0.9%) 1 (0.5%) 1 (5.3%) 0.0265 Non-invasive ventilation 5 (2.5%) 2 (1.1%) 3 (16.7%) 0.0010 Renal replacement 2 (1.0%) 2 (1.1%) 0 (0.0%) 1.0000 CPAP 1 (0.5%) 1 (0.5%) 0 (0.0%) 1.0000 Biomarker and clinical severity score values MR-proADM 1.36 [0.93-2.21] 1.30 [0.89-1.82] 2.65 [1.91-4.70] <0.0001 PCT 0.25 [0.10-1.40] 0.22 [0.09-1.09] 0.98 [0.21-6.41] 0.0032 CRP 76 [25-163] 71 [24-152.5] 134 [72.5-232] 0.0230 Lactate 1.7 [1.2-2.7] 1.7 [1.2-2.6] 2.4 [1.3-3.5] 0.0453 SOFA 2 [1-4] 2 [1-4] 5 [3-6] <0.0001 qSOFA 1 [1-1] 1 [1-1] 2 [1-2] 0.0007 Apart from age (medium and standard deviation), continuous data are given as median (interquartile range). Dichotomous variables are given as counts (%). *Refers to difference between 28-day survivors and non-survivors.

TABLE-US-00004 TABLE 2 Use of intravenous antibiotics during ED treatment No. of patients 28 day administered Time to mortality rate Antibiotic type (N) treatment (N, %) No intravenous antibiotics 43 (20.2%) n/a 2 (4.7%) Single i.v. antibiotic use 131 (79.9%) 137.9 mins 12 (8.6%) Bensylpenicillin 36  148.1 Cefotaxim 76  138.9 Klaxacillin 4 112.3 Klindamycin 0 n/a Aminoglycosides 0 n/a Metronidazol 0 n/a Piperacillin-Tazobactam 8 101.8 Meropenem 4 122.8 Imipinem 1 n/a Erytromycin 0 n/a Quinolone 0 n/a Trimetoprim 1 n/a Vancomycin 0 n/a Others 1 n/a Dual i.v. antibiotic use 27 (16.5%)  70.5 5 (18.5%) Cefotaxim-Aminoglycosides 10   65.4 Cefotaxim-Metronidazol 2 n/a Cefotaxim-Erytromycin 4  95.1 Klinamycin-Aminoglycosides 3 n/a Klinamycin-Bensylpenicillin 1 n/a Klinamycin-Meropenem 1 n/a Aminoglycosides-Piperacillin/Tazobactam 3 n/a Piperacillin/Tazobactam-Meropenem 1 n/a Iminipenem-Vancomycin 1 n/a Aminoglycosides-Bensylpenicillin 1 n/a Triple i.v. antibiotic use 3 (1.8%) n/a 0 (0.0%) Bensylpenicillin-Cefotaxim-Quinolone 1 n/a Cefotaxim-Aminoglycosides-Piperacillin/Tazobactam 1 n/a Metronidazol-Quinoline-Ciprofloxacin 1 n/a

TABLE-US-00005 TABLE 3 Logistic regression analysis for the requirement of intravenous antibiotics upon ED presentation N Events LR c.sup.2 DF p value C Index OR [95% CI] MR-proADM 213 164 31.72 1 0.0000 0.755 4.34 [2.40-7.87] PCT 213 164 25.62 1 0.0000 0.744 4.22 [2.21-8.04] Lactate 204 158 10.63 1 0.0011 0.660 2.37 [1.37-4.11] CRP 207 159 13.97 1 0.0002 0.683 2.30 [1.47-3.62] MR-proADM + Age + Gender 213 164 32.79 3 0.0000 0.755 5.09 [2.44-10.63] PCT + Age + Gender 213 164 28.76 3 0.0000 0.756 3.81 [2.00-7.27] Lactate + Age + Gender 204 158 14.74 3 0.0020 0.686 2.00 [1.13-3.54] CRP + Age + Gender 207 159 19.88 3 0.0002 0.723 2.24 [1.41-3.56]

TABLE-US-00006 TABLE 4 AUROC analysis for the requirement of intravenous antibiotics AUROC Cut-off Sensitivity Specificity PPV MR-proADM 1.27 0.66 [0.58-0.73] 0.80 [0.66-0.89] 0.92 [0.85-0.95] PCT 0.12 0.80 [0.74-0.86] 0.63 [0.49-0.75] 0.88 [0.82-0.92] Lactate 2.1 0.44 [0.36-0.51] 0.85 [0.72-0.92] 0.91 [0.82-0.95] CRP 40 0.66 [0.58-0.73] 0.69 [0.55-0.80] 0.88 [0.80-0.92] NPV LR+ LR− MR-proADM 0.41 [0.32-0.51] 3.23 [1.84-5.67] 0.43 [0.33-0.55] PCT 0.49 [0.37-0.61] 2.19 [1.51-3.19] 0.31 [0.21-0.45] Lactate 0.30 [0.23-0.39] 2.87 [1.42-5.81] 0.66 [0.55-0.80] CRP 0.38 [0.28-0.48] 2.11 [1.37-3.26] 0.49 [0.37-0.66]

TABLE-US-00007 TABLE 5 Subgroup analysis for antibiotic treatment based on PCT and MR-proADM cut-offs Intravenous PCT MR-proADM antibiotic Patient concentration Concentration Patients Mortality requirement Group (ng/ml) (nmol/L (N) (N, %) (N, %) OR [95% CI] 1 <0.12 <1.27 46 0 (0.0%) 19 (41.3%) 0.12 [0.09-0.51]* 2 <0.12 ≥1.27 18 2 (11.1%) 14 (77.8%) n.s.** 3 ≥0.12 <1.27 48 0 (0.0%) 37 (77.1%) 0.20 [0.06-0.71]*** 4 ≥0.12 ≥1.27 101 17 (16.8%) 94 (93.1%) 0.05 [0.02-0.13]**** Subgroup analysis: *Group 1 vs. Group 2; **Group 2 vs. Group 3; ***Group 1 vs. Group 3; ****Group 1 vs. Group 4. PCT: Procalcitonin; MR-proADM; Mid-regional proadrenomedullin; N: Number; OR: Odds ratio; CI: Confidence Interval

TABLE-US-00008 TABLE 6 Addition of PCT to the MR-proADM multivariate model (age + gender) p-value Added for new N Events LR c.sup.2 DF p-value C-index LR.sup.2 model PCT + MR-proADM 213 164 37.70778 4 1.29E−07 0.767795 4.92 0.026

TABLE-US-00009 TABLE 7 Addition of MR-proADM to the PCT multivariate model (age + gender) p-value Added for new N Events LR c.sup.2 DF p-value C-index LR.sup.2 model MR-proADM + PCT 213 164 37.71 4 1.29E−07 0.767795 8.9492 0.002776

TABLE-US-00010 TABLE 8 Individual biomarkers alone N Events LR c.sup.2 DF p-value C-index OR [95% CI] MR-proADM 187 147 27.71489 1 1.41E−07 0.761139 4.44 [2.32-8.49] PCT 187 147 24.8166 1 6.31E−07 0.751276 4.90 [2.35-10.23] Lactate 179 141 9.454986 1 0.002106 0.666013 2.42 [1.33-4.40] CRP 181 142 8.233092 1 0.004113 0.656013 2.00 [1.24-3.23]

TABLE-US-00011 TABLE 9 Multivariate model including age and gender N Events LR c.sup.2 DF p-value C-index OR [95% CI] MR-proADM + Age + Gender 187 147 27.88646 3 3.84E−06 0.759524 4.84 [2.20-10.65] PCT + Age + Gender 187 147 28.32618 3  3.1E−06 0.771173 4.44 [2.13-9.28] Lactate + Age + Gender 179 141 13.35143 3 0.003935 0.699048 2.04 [1.10-3.78] CRP + Age + Gender 181 142 14.22562 3 0.002614 0.713254 1.92 [1.17-3.14]

TABLE-US-00012 TABLE 10 Addition of PCT to the MR-proADM multivariate model (age + gender) p-value Added for new N Events LR c.sup.2 DF p-value C-index LR.sup.2 model PCT + MR-proADM 187 147 34.14024 4 6.97E−07 0.776531 6.253776 0.012393

TABLE-US-00013 TABLE 11 Addition of MR-proADM to the PCT multivariate model (age + gender) p-value Added for new N Events LR c.sup.2 DF p-value C-index LR.sup.2 model MR-proADM + PCT 187 147 34.14024 4 6.97E−07 0.776531 5.814053 0.015899

TABLE-US-00014 TABLE 12 Logistic regression analysis for the prediction of a positive bacterial culture N Events LR c.sup.2 DF p value C Index OR [95% CI] MR-proADM 211 34 24.07 1 0.0000 0.750 3.41 [2.01-5.78] PCT 211 34 24.29 1 0.0000 0.759 3.73 [2.14-6.51] Lactate 202 34 16.47 1 0.0000 0.712 3.14 [1.76-5.63] CRP 206 33 2.98 1 0.0845 0.583 1.65 [0.91-3.00] MR-proADM + Age + Gender 211 34 26.86 3 0.0000 0.748 4.24 [2.31-7.76] PCT + Age + Gender 211 34 24.37 3 0.0000 0.759 3.72 [2.12-6.54] Lactate + Age + Gender 202 34 16.60 3 0.0009 0.712 3.25 [1.76-6.01] CRP + Age + Gender 206 33 3.48 3 0.3231 0.589 1.62 [0.89-2.97] MR-proADM; Mid-regional proadrenomedullin; PCT: Procalcitonin; CRP: C-reactive protein; N: Number; DF: Degrees of Freedom; OR: Odds ratio; CI: Confidence Interval

TABLE-US-00015 TABLE 13 AUROC analysis for the prediction of a positive blood culture AUROC Cut-off Sensitivity Specificity PPV NPV LR+ LR− MR-proADM 0.75 1.78 0.65 0.77 0.35 0.92 2.79 0.46 [0.66-0.84] [0.48-0.79] [0.70-0.82] [0.24-0.47] [0.86-0.95] [1.94-4.03] [0.29-0.73] PCT 0.76 0.60 0.79 0.69 0.33 0.95 2.60 0.30 [0.67-0.84] [0.63-0.90] [0.62-0.76] [0.24-0.44] [0.89-0.97] [1.97-3.45] [0.15-0.58] Lactate 0.71 3 0.59 0.88 0.49 0.91 4.71 0.47 [0.61-0.81] [0.42-0.74] [0.82-0.92] [0.34-0.64] [0.86-0.95] [2.89-7.67] [0.31-0.71] CRP 0.58 50 0.79 0.41 0.20 0.91 1.34 0.52 [0.48-0.69] [0.62-0.89] [0.34-0.48] [0.14-0.28] [0.83-0.96] [1.08-1.66] [0.26-1.02]

TABLE-US-00016 TABLE 14 Logistic regression analysis for the prediction of severe sepsis development within 48 hours of ED arrival N Events LR c.sup.2 DF p value C Index OR [95% CI] MR-proADM 212 113 57.07 1 0.0000 0.782 5.79 [3.30-10.16] PCT 212 113 40.82 1 0.0000 0.753 4.33 [2.58-7.27] Lactate 203 108 14.90 1 0.0001 0.650 2.31 [1.48-3.61] CRP 206 109 10.73 1 0.0011 0.613 1.94 [1.28-2.95] MR-proADM + Age + Gender 212 113 58.57 3 0.0000 0.790 4.95 [2.68-9.13] PCT + Age + Gender 212 113 60.06 3 0.0000 0.801 4.47 [2.57-7.79] Lactate + Age + Gender 203 108 29.53 3 0.0000 0.718 1.97 [1.22-3.16] CRP + Age + Gender 206 109 32.85 3 0.0000 0.727 1.97 [1.26-3.07] MR-proADM; Mid-regional proadrenomedullin; PCT: Procalcitonin; CRP: C-reactive protein; N: Number; DF: Degrees of Freedom; OR: Odds ratio; CI: Confidence Interval

TABLE-US-00017 TABLE 15 AUROC analysis for the prediction of severe sepsis development within 48 hours of ED arrival AUROC Cut-off Sensitivity Specificity PPV NPV LR+ LR− MR-proADM 0.78 1.10 0.86 0.61 0.71 0.79 2.18 0.23 [0.72-0.84] [0.78-0.91] [0.51-0.70] [0.63-0.78] [0.69-0.87] [1.69-2.81] [0.14-0.38] PCT 0.75 0.17 0.78 0.62 0.70 0.71 2.03 0.36 [0.69-0.82] [0.69-0.85] [0.52-0.71] [0.61-0.77] [0.61-0.79] [1.55-2.65] [0.25-0.52] Lactate 0.65 2.2 0.49 0.82 0.76 0.59 2.74 0.62 [0.57-0.73] [0.40-0.58] [0.73-0.89] [0.65-0.84] [0.50-0.67] [1.71-4.40] [0.50-0.76] CRP 0.61 48 0.72 0.47 0.61 0.61 1.38 0.58 [0.63-0.76] [0.63-0.80] [0.38-0.57] [0.52-0.69] [0.49-0.71] [1.10-1.72] [0.40-0.84]

TABLE-US-00018 TABLE 16 AUROC analysis for the prediction of 28 day mortality AUROC Cut-off Sensitivity Specificity PPV NPV LR+ LR− MR-proADM 0.86 1.73 0.89 0.73 0.24 0.99 3.28 0.14 [0.79-0.92] [0.69-0.97] [0.66-0.78] [0.16-0.35] [0.95-1.00] [2.48-4.32] [0.04-0.54] PCT 0.71 0.41 0.74 0.61 0.16 0.96 1.88 0.43 [0.59-0.83] [0.51-0.88] [0.54-0.67] [0.09-0.24] [0.91-0.98] [1.36-2.59] [0.20-0.93] Lactate 0.64 2.2 0.63 0.69 0.17 0.95 2.01 0.54 [0.50-0.78] [0.41-0.81] [0.62-0.75] [0.10-0.28] [0.90-0.97] [1.34-3.02] [0.30-0.97] CRP 0.66 71 0.83 0.50 0.14 0.97 1.66 0.34 [0.54-0.71] [0.61-0.94] [0.43-0.57] [0.08-0.21] [0.91-0.99] [1.29-2.13] [0.12-0.95] SOFA 0.84 3 0.95 0.63 0.20 0.99 2.55 0.08 [0.77-0.91] [0.75-0.99] [0.56-0.69] [0.13-0.29] [0.96-1.00] [2.07-3.15] [0.01-0.57] qSOFA 0.71 2 0.58 0.81 0.23 0.95 3.12 0.52 [0.58-0.85] [0.36-0.77] [0.75-0.86] [0.14-0.37] [0.91-0.98] [1.92-5.06] [0.30-0.88]

TABLE-US-00019 TABLE 17 AUROC and logistic regression analysis for the prediction of 28 day mortality N Events LR c.sup.2 DF p value C Index HR IQR [95% CI] MR-proADM 213 19 28.11 1 0.0000 0.841 4.29 [2.54-7.26] PCT 213 19 10.05 1 0.0015 0.694 2.65 [1.46-4.82] Lactate 204 19 4.46 1 0.0346 0.640 1.99 [1.06-3.76] CRP 207 18 4.69 1 0.0303 0.653 2.37 [1.00-5.62] SOFA 213 19 22.92 1 0.0000 0.859 3.29 [2.13-5.08] qSOFA 213 19 14.63 1 0.0001 0.798 30.12 [5.56-163.24] MR-proADM + Age 213 19 35.76 2 0.0000 0.864 3.73 [2.12-6.58] PCT + Age 213 19 27.34 2 0.0000 0.824 2.87 [1.51-5.46] Lactate + Age 204 19 19.30 2 0.0001 0.767 1.70 [0.87-3.31] CRP + Age 207 18 20.25 2 0.0000 0.779 2.48 [1.01-6.09] SOFA 213 19 32.80 2 0.0000 0.856 2.77 [1.76-4.37] qSOFA 213 19 25.85 2 0.0000 0.811 15.55 [2.70-89.48]

REFERENCES

[0272] 1. Martin G S, Mannino D M, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. Apr. 17, 2003; 348(16):1546-1554. [0273] 2. Angus D C, Linde-Zwirble W T, Lidicker J, Clermont G, Carcillo J, Pinsky M R. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. July 2001; 29(7):1303-1310. [0274] 3. Kumar A, Roberts D, Wood K E, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. June 2006; 34(6):1589-1596. [0275] 4. Henriksen D P, Laursen C B, Jensen T G, Hallas J, Pedersen C, Lassen A T. Incidence rate of community-acquired sepsis among hospitalized acute medical patients-a population-based survey. Crit Care Med. January 2015; 43(1):13-21. [0276] 5. Yentis S M, Soni N, Sheldon J. C-reactive protein as an indicator of resolution of sepsis in the intensive care unit. Intensive Care Med. July 1995; 21(7):602-605. [0277] 6. Matson A, Soni N, Sheldon J. C-reactive protein as a diagnostic test of sepsis in the critically ill. Anaesth Intensive Care. May 1991; 19(2):182-186. [0278] 7. Assicot M, Gendrel D, Carsin H, Raymond J, Guilbaud J, Bohuon C. High serum procalcitonin concentrations in patients with sepsis and infection. Lancet. Feb. 27, 1993; 341(8844):515-518. [0279] 8. Al-Nawas B, Krammer I, Shah P M. Procalcitonin in diagnosis of severe infections. Eur J Med Res. Apr. 18, 1996; 1(7):331-333. [0280] 9. Bhat A, Asghar M, Raulia G, Mandal A K. Improving multidisciplinary severe sepsis management using the Sepsis Six. Clin Med (Lond). December 2016; 16(6):503-505. [0281] 10. Singer M, Deutschman C S, Seymour C W, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. Feb. 23, 2016; 315(8):801-810. [0282] 11. Williams J M, Greenslade J H, McKenzie J V, Chu K, Brown A F, Lipman J. Systemic Inflammatory Response Syndrome, Quick Sequential Organ Function Assessment, and Organ Dysfunction: Insights From a Prospective Database of E D Patients With Infection. Chest. March 2017; 151(3):586-596. [0283] 12. Bloos F, Ruddel H, Thomas-Ruddel D, et al. Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: a cluster randomized trial. Intensive Care Med. May 2, 2017. [0284] 13. Andriolo B N, Andriolo R B, Salomao R, Atallah A N. Effectiveness and safety of procalcitonin evaluation for reducing mortality in adults with sepsis, severe sepsis or septic shock. Cochrane Database Syst Rev. Jan. 18, 2017; 1:CD010959. [0285] 14. Temmesfeld-Wollbruck B, Brell B, David I, et al. Adrenomedullin reduces vascular hyperpermeability and improves survival in rat septic shock. Intensive Care Med. April 2007; 33(4):703-710. [0286] 15. Muller-Redetzky H C, Will D, Hellwig K, et al. Mechanical ventilation drives pneumococcal pneumonia into lung injury and sepsis in mice: protection by adrenomedullin. Crit Care. 2014; 18(2):R73. [0287] 16. Carrizo G J, Wu R, Cui X, Dwivedi A J, Simms H H, Wang P. Adrenomedullin and adrenomedullin-binding protein-1 downregulate inflammatory cytokines and attenuate tissue injury after gut ischemia-reperfusion. Surgery. February 2007; 141(2):245-253. [0288] 17. Brell B, Temmesfeld-Wollbruck B, Altzschner I, et al. Adrenomedullin reduces Staphylococcus aureus alpha-toxin-induced rat ileum microcirculatory damage. Crit Care Med. April 2005; 33(4):819-826. [0289] 18. Vigue B, Leblanc P E, Moati F, et al. Mid-regional pro-adrenomedullin (MR-proADM), a marker of positive fluid balance in critically ill patients: results of the ENVOL study. Crit Care. Nov. 9, 2016; 20(1):363. [0290] 19. Albrich W C, Dusemund F, Ruegger K, et al. Enhancement of CURB65 score with proadrenomedullin (CURB65-A) for outcome prediction in lower respiratory tract infections: derivation of a clinical algorithm. BMC Infect Dis. 2011; 11:112. [0291] 20. Albrich W C, Ruegger K, Dusemund F, et al. Optimised patient transfer using an innovative multidisciplinary assessment in Kanton Aargau (OPTIMA I): an observational survey in lower respiratory tract infections. Swiss Med Wkly. 2011; 141:w13237. [0292] 21. Albrich W C, Ruegger K, Dusemund F, et al. Biomarker-enhanced triage in respiratory infections: a proof-of-concept feasibility trial. Eur Respir J. October 2013; 42(4):1064-1075. [0293] 22. van der Starre W E, Zunder S M, Vollaard A M, et al. Prognostic value of pro-adrenomedullin, procalcitonin and C-reactive protein in predicting outcome of febrile urinary tract infection. Clin Microbiol Infect. October 2014; 20(10):1048-1054. [0294] 23. Dellinger R P, Levy M M, Carlet J M, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med. January 2008; 36(1):296-327. [0295] 24. Levy M M, Fink M P, Marshall J C, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med. April 2003; 31(4):1250-1256. [0296] 25. Christ M, Grossmann F, Winter D, Bingisser R, Platz E. Modern triage in the emergency department. Dtsch Arztebl Int. December 2010; 107(50):892-898. [0297] 26. Temmesfeld-Wollbruck B, Hocke A C, Suttorp N, Hippenstiel S. Adrenomedullin and endothelial barrier function. Thromb Haemost. November 2007; 98(5):944-951. [0298] 27. Gonzalez-Rey E, Chorny A, Varela N, Robledo G, Delgado M. Urocortin and adrenomedullin prevent lethal endotoxemia by down-regulating the inflammatory response. Am J Pathol. June 2006; 168(6):1921-1930. [0299] 28. Bustamante A, Garcia-Berrocoso T, Penalba A, et al. Sepsis biomarkers reprofiling to predict stroke-associated infections. J Neuroimmunol. Nov. 15, 2017; 312:19-23. [0300] 29. Valenzuela-Sanchez F, Valenzuela-Mendez B, Rodriguez-Gutierrez J F, Estella-Garcia A, Gonzalez-Garcia M A. New role of biomarkers: mid-regional pro-adrenomedullin, the biomarker of organ failure. Ann Transl Med. September 2016; 4(17):329. [0301] 30. Andaluz-Ojeda D, Nguyen H B, Meunier-Beillard N, et al. Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity. Ann Intensive Care. December 2017; 7(1):15. [0302] 31. Bloos F, Trips E, Nierhaus A, et al. Effect of Sodium Selenite Administration and Procalcitonin-Guided Therapy on Mortality in Patients With Severe Sepsis or Septic Shock: A Randomized Clinical Trial. JAMA Intern Med. Sep. 1, 2016; 176(9):1266-1276. [0303] 32. Kopterides P, Siempos, I I, Tsangaris I, Tsantes A, Armaganidis A. Procalcitonin-guided algorithms of antibiotic therapy in the intensive care unit: a systematic review and meta-analysis of randomized controlled trials. Crit Care Med. November 2010; 38(11):2229-2241. [0304] 33. Kip M M, Kusters R, M J I J, Steuten L M. A PCT algorithm for discontinuation of antibiotic therapy is a cost-effective way to reduce antibiotic exposure in adult intensive care patients with sepsis. J Med Econ. 2015; 18(11):944-953. [0305] 34. Chan Y L, Tseng C P, Tsay P K, Chang S S, Chiu T F, Chen J C. Procalcitonin as a marker of bacterial infection in the emergency department: an observational study. Crit Care. February 2004; 8(1):R12-20. [0306] 35. Gille-Johnson P, Hansson K E, Gardlund B. Clinical and laboratory variables identifying bacterial infection and bacteraemia in the emergency department. Scand J Infect Dis. October 2012; 44(10):745-752. [0307] 36. de Kruif M D, Lemaire L C, Giebelen I A, et al. The influence of corticosteroids on the release of novel biomarkers in human endotoxemia. Intensive Care Med. March 2008; 34(3):518-522. [0308] 37. Vila G, Resl M, Stelzeneder D, et al. Plasma NT-proBNP increases in response to LPS administration in healthy men. J Appl Physiol (1985). December 2008; 105(6):1741-1745. [0309] 38. Allaker R P, Kapas S. Adrenomedullin expression by gastric epithelial cells in response to infection. Clin Diagn Lab Immunol. July 2003; 10(4):546-551. [0310] 39. Gille J, Ostermann H, Dragu A, Sablotzki A. M R-proADM: A New Biomarker for Early Diagnosis of Sepsis in Burned Patients. J Burn Care Res. September/October 2017; 38(5):290-298. [0311] 40. Silvia Angeletti et al: “Diagnostic and prognostic role of procalcitonin (PCT) and MR-pro-Adrenomedullin (MR-proADM) in bacterial infections”, APMIS, vol. 123, no. 9, 8 Jun. 2015, pages 740-748. [0312] 41. J. M. Pereira et al: “Mid-regional proadrenomedullin: An early marker of response in critically ill patients with severe community-acquired pneumonia?”, Revista Portuguesa de Pneumologia (English Edition), vol. 22, no. 6, 1 Nov. 2016, pages 308-314. [0313] 42. Philipp Schuetz ET AL: “Blood biomarkers for personalized treatment and patient management decisions in community-acquired pneumonia:”, CURRENT OPINION ON INFECTIOUS DISEASES, vol. 26, no. 2, 1 Apr. 2013, pages 159-167. [0314] 43. M. Christ-Crain: “Procalcitonin Guidance of Antibiotic Therapy Community-acquired Pneumonia: A Randomized Trial”, American Journal of Respiratory and Critical Care Medicine, vol. 174, no. 1, 1 Jan. 2006, pages 84-93.