Method of assessing the risk of death of a patient

Abstract

The invention concerns a method of assessing the risk of death of a patient, comprising the steps of: A1. Measuring a first value V1 reflecting the level of expression of CX3CR1 gene in a biological sample obtained from said patient, B1. Measuring a second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient.

Description

[0001] Method of assessing the risk of death of a patient

[0002] Technical Field

[0003] The present invention is in the technical field of health care. Particularly, the invention relates to methods for assessing the risk of death of a patient with sepsis and to kits systems comprising computers, computer programs and recording media allowing implementation of such method.

[0004] Background

[0005] Assessing the risk of death of a patient admitted in a health care facility, more specifically estimating the risk of death in a patient with sepsis or septic shock is essential in order to be able to provide personalized care and thus to attempt to reduce the risk of death.

[0006] The severity of the condition of a patient admitted into the intensive care unit may be estimated with the aid of a variety of clinical and physiological parameters. They can in particular be used to define scores that are predictive in terms of survival / mortality; those that may be cited include the following severity scores: SOFA (Sequential Organ Failure Assessment or Sepsis- related Organ Failure Assessment) (Vincent et al., 1996); and SAPSII (Simplified Acute Physiology Score II) (in French IGS II (Indice de Gravite Simplifie II) [Simplified Gravity Index], These composite scores, defined on the basis of substantial cohorts of intensive care patients, include a number of clinical- biological parameters such as the number of circulating platelets, bilirubinemia, diuresis, age, or body temperature. However, these scores are difficult to use in daily routine because they require the physician to carry out an active investigation into the clinical parameters of a patient's history.

[0007] Thus, there is a genuine need for the provision of other methods, in particular using measurable biomarkers, that can be used readily and rapidly to evaluate the risk of death of a patient. Biomarkers have already been proposed for assessing the risk of death.

[0008] Huckabee first suggested to use elevated blood lactate levels as a measure of oxygen debt in hospitalized patients in 1961 (Huckabee W.E., 1961). Since then, it has been widely accepted that lactate is a marker of anaerobic metabolism in patients that failed to ensure with insufficient oxygen delivery, with a subsequent lactic acidosis (Garcia- Alvarez M., 2014). However, several data failed to relate excess lactate to lack of oxygen and therefore suggest other non- dysoxic mechanisms. This multiplicity of underlying mechanisms may participate in explaining the low sensitivity of serum lactate level in predicting mortality in septic patients (Shankar- Hari M., 2016). Indeed, whether lactate is useful in identifying patients at high risk of mortality, its use as a biomarker able to guide personalized therapy in sepsis remains limited by poor other operating characteristics such as sensitivity and positive predictive value (Janse T.C., 2010). Thus, other methods that combine the level of lactate with other information have also been described in the state of the art. For instance, methods disclosed in EP 2615461 combine the level of lactate with the measurement of the level of Vasostatin- 1 in a biological sample obtained from a patient. WO 2019 / 006561 provides a prognostic and mortality risk assessment method for patients with sepsis that is very complex. This method involves measuring a combination of cell- free DNA (cfDNA), protein C, lactate, platelet count, creatinine level, and Glasgow Coma Score (GCS) and analysing the measured values using a complementary log- log model to determine the daily and 28- day probabilities of dying for septic patients and a binomial logit model to distinguish septic patients from non- septic patients.

[0009] In the literature, a decrease in the expression of CX3CR1 has already proved to be associated with an increase in mortality, in particular in patients in a septic state, and more particularly in a state of septic shock (Pachot A. 2006; Frigerri P. 2016). However, it is not possible to draw any conclusions from the work of Pachot A. et al. given the small size of the cohort used (n=36) and the use of a single sampling timepoint. Further, the work of Frigerri P. et al. implies a threshold that varies according to the sampling time, which is unreliable over time and does not allow for routine implementation.

[0010] In previous works (WO 2017 / 093672 and WO 2015 / 040328), the applicants have also proposed to use either the expression of sCD127 or at least one transcript of the IL7R gene for assessing the risk of complications, and in particular the risk of death, in patients with systemic inflammatory response syndrome (SIRS).

[0011] In addition, the successive failures of numerous interventional trials in sepsis have highlighted the need to develop stratification strategies to identify patients who would benefit most from the proposed therapies (Bodinier M., 2023). Thus, new methods of assessing the risk of death of a patient answer an ongoing need.

[0012] Object of the invention

[0013] The present invention overcomes one or more deficiencies of the prior art by proposing a method of assessing risk of death based on the identification of CX3CR1 gene and CDK1 gene, as highly relevant biomarkers when combined for the prognostic of the risk of death of a patient.

[0014] A first object of the invention relates to a first embodiment of a method of assessing the risk of death of a patient, comprising the steps of:

[0015] Al. measuring a first value VI reflecting the level of expression of CX3CR1 gene in a biological sample obtained from said patient,

[0016] Bl. measuring a second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient.

[0017] Particularly, CDK1 has been identified as an hub gene which is highly overexpressed (or upregulated) in biological samples of patients who are known to have died, in comparison with patients who are known to have survived. On the other hand, CX3CR1 gene is highly under expressed or downregulated in biological samples of patients who are known to have died in comparison with patients who are known to have survived. Without being bound by any theory, it is believed that the combination of these two genes allows to detect an high expression amplitude that overcomes patient's heterogeneity, especially those admitted in an intensive care unit (ICU), thus enabling improved assessment of the risk of death.

[0018] According to the first embodiment of the method of the invention, the further comprises a step of D assessing the risk of death based on at least on steps Al and / or Bl.

[0019] According to the first embodiment of the invention, the method comprises a step C of acquiring a third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient.

[0020] Advantageously, the additional use of the value of quantity of lactate allows further refining of the evaluation of the risk of death.

[0021] According to the first embodiment of the invention, step D comprises the sub steps of:

[0022] DI. Obtaining a data set of measured values of steps Al and Bl or steps A and B, and

[0023] D3. Correlating the data set to a level of risk of death.

[0024] According to the first embodiment of the invention, the data set of step DI can comprise acquired value of step C.

[0025] According to the first embodiment of the invention, the correlation of sub step D3 is a comparison of the data set to at least a threshold value TVI2, the result of the comparison being indicative of a level of risk of death.

[0026] The correlating step D3 may be performed by using a combination of at least the first value VI and at least the second value V2 and optionally a third value V3. The correlation step may use one or several comparison(s), a mathematical algorithm, the calculation of a processed data V4 of the first value VI and the second value V2 and its comparison with a relevant threshold value.

[0027] The invention relates also to a second embodiment of a method of assessing the risk of death of a patient, comprising the steps of:

[0028] A. Acquisition of a first value VI reflecting the level of expression of CX3CR1 gene in a biological sample obtained from said patient.

[0029] B. Acquisition of second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient.

[0030] D. Assessing the risk of death based on at least on steps A and / or B.

[0031] According to the second embodiment of the invention, the method of assessing the risk of death of the invention further comprises a step C of acquiring third value V3 reflecting the quantity of lactate in a biological sample. The third value V3 can be measured in a substep Cl.

[0032] According to the second embodiment of the method according to the invention, steps A, B and C of acquisition can comprise steps of measurements of values reflecting the level of expression of specific genes such as CX3CR1, CDK1 or quantity of lactate in a biological sample obtained from said patient. For example, steps Al, Bl and C from the first embodiment can be integrated respectively into steps A, B and C of the second embodiment.

[0033] According to the second embodiment of the method according to the invention, step D comprises the sub steps of:

[0034] DI. Obtaining a data set of measured values of steps A and B,

[0035] D2. Obtaining processed data V4 based on the combination of said measured values of the data set in step DI and

[0036] D3. Correlating the processed data V4 to a level of risk of death.

[0037] According to the second embodiment of the invention, assessing risk of death in step D can be based on at least on steps A and B and C.

[0038] According to the second embodiment of the invention, the processed data V4 corresponds a ratio of V2 / V1 or a ratio V1 / V2.

[0039] According to the second embodiment of the invention, the correlation of sub step D3 comprises: D31. a comparison of the processed data V4 to at least a threshold value TV4.

[0040] According to the second embodiment of the invention, sub step C. further comprises:

[0041] C2. a comparison of the value V3 to at least a threshold value TV3.

[0042] The steps A, B or Al, Bl, C, Cl and C2 can be performed simultaneously, sequentially, or in any order.

[0043] According to the second embodiment of the invention, wherein the risk of death is characterized in step D as following when V4 = V2 / V1:

[0044] • a high risk of death is attributed when V4 > TV4 and V3 > TV3,

[0045] • a moderate risk of death is attributed when either V4 < TV4 or V3 < TV3, and

[0046] • a low risk of death is attributed when V4 < TV4and V3 < TV3.

[0047] Alternately and according to the second embodiment of the invention, wherein the risk of death is characterized in step D as following when V4 = V1 / V2:

[0048] • a high risk of death is attributed to the patient when V4 < TV4 and V3 < TV3,

[0049] • a moderate risk of death is attributed to the patient when either V4 > TV4or V3 > TV3, and

[0050] • a low risk of death is attributed to the patient when V4 > TV4and V3 > TV3. According to the invention, the steps of the first and second embodiment of the method of the invention may be automated.

[0051] The whole specification hereinafter applies equally to the first embodiment and to the second embodiment of the invention that enable assessing the risk of death of a patient.

[0052] The method of the invention may further include determining one or more values corresponding to one of the biomarkers used in the method of assessment. In that case, the method does not include the sample taking. The methods of the invention are an in vitro or ex vivo method of assessment of the risk of death.

[0053] Typically, the patient is a patient admitted in a health care facility, in particular a patient admitted in an intensive care unit (ICU).

[0054] The methods of the invention are particularly useful, when the patient is a patient with sepsis, and more specifically a patient in a state of septic shock. In that case, the sepsis or the septic shock has already been diagnosed at the time of collection of the biological sample(s) used for measuring the first value VI, the second value V2 and the third value V3, when V3 is used.

[0055] In examples of implementation of the methods of the invention, the biological sample(s) has(have) been collected, at the same time, within six days as of the patient's admission, and in particular at day one, at day two, at day three, at day four, at day five or at day six by reference to patient's admission. A collection at the same time and on day one, on day two or on day three after the patient's admission is particularly preferred. In these definitions, patient's admission is in particular the admission of a patient in ICU.

[0056] Advantageously, the biological sample(s) are a blood sample. In particular, the biological sample(s) used for the first value VI and the second value V2 is(are) a whole blood sample, and, when a third value V3 reflecting the quantity of lactate in a biological sample obtained from the patient of interest is used, the biological sample used for the third value V3 is a serum sample.

[0057] Typical ways to carry out the methods of the invention use the levels of expression of CX3CR1 gene and of CDK1 gene, which are both measured at the RNA level, and in particular at the mRNA level. In other words, the first value VI is or reflects the mRNA quantity of CX3CR1 in the selected biological sample obtained from the patient of interest and the second value V2 is or reflects the mRNA quantity of CDK1 in the selected biological sample obtained from said patient. More specifically, the levels of expression of CX3CR1 gene and of CDK1 gene may both be measured by quantitative reverse transcriptase PCR (RT- PCR), and in particular by quantitative RT- PCR in real time. The invention also relates to a Kit for assessing the risk of death of a patient according to assessing method according to the preceding claims, the kit comprising reagent(s) required that allows to measure in a biological sample obtained from a patient, the level of expression of CX3CR1 gene and reagent(s) required that allows to measure in a biological sample obtained from a patient, the level of expression of CDK1 gene, and optionally reagent(s) required that allows to measure the quantity of lactate in a biological sample obtained from a patient.

[0058] The invention also relates to a computer system comprising a computer system for carrying out the method according to the invention:

[0059] - a data set unit configured to store or retrieve the data set comprising at least the first value VI and the second value V2;

[0060] - a processing unit configured to process data from the data set into processed data V4;

[0061] - a correlation unit comprising computer instructions for correlating the data set or the processed data V4 to a level of risk of death.

[0062] According to the invention, the instructions may relate to:

[0063] - storage and / or retrieval at least a threshold value; and / or

[0064] - comparison of the data set provided in step with a threshold value TVI2, wherein the comparison is indicative of a level of risk of death of the patient; and / or

[0065] - comparison of the processed data V4 with a threshold value TV4, wherein the comparison is indicative of a level of risk of death of the patient.

[0066] According to specific embodiments, the computer system further comprises a classification unit classifying said level of risk of death.

[0067] According to another aspect, the invention concerns a computer program comprising instructions for executing the steps of any one of the methods according to the invention, when said program is executed by the computer system.

[0068] The invention also relates to a computer- program comprising instructions for implementing the steps of the assessing method according to the invention when said computer- program is implemented in a computer system according to the invention.

[0069] The invention also relates to a non- transient recording medium readable by a computer on which a computer program is recorded when the computer- program is executed by a processor of the computer system. In another aspect, the invention relates to the use of a biomarker combination comprising:

[0070] (i) CX3CR1 gene and CDK1 gene and

[0071] (ii) optionally lactate, in the assessment of the risk of death of a patient.

[0072] Any of the embodiments may include an optional step E: a display or alert step.

[0073] This step E allows for the assessment of risk through a notification or the display of the risk after the system or computer has assessed the risk. The notification can be visual or auditory notification.

[0074] Whatever the embodiment of the method, the invention, provides a reliable method of assessing the risk of death that overcomes patients variability based on at least these two genes CX3CR1 and CDK1. In addition, the levels of expression of said two genes are relatively stable over time. Therefore, their use is not time- depending nevertheless, variability may exist in the collection of samples. As a result, their combination has a great value as a tool for assessing the risk of death. The risk of death is, in particular, the risk the patient dies within the 28 days after the collection of the biological sample(s).

[0075] Brief description of figures

[0076] Figure 1 shows the predictive performances of CDK1 combined with IL1B microarray genes expression on 100 patients with septic shock (32% ICU mortality) collected at (A) day 1 and at (B) day 2- 3. Performances are given with AUC (Area Under Curve) and 95 % Cl (Confidence Intervals).

[0077] Figure 2 shows the predictive performances of CDK1 combined with CX3CR1 microarray genes expression on 100 patients with septic shock (32% ICU mortality) collected at (A) day 1 and at (B) day 2- 3. Performances are given with AUROC (Area Under Curve) and 95 % Cl (Confidence Intervals).

[0078] Figure 3 shows the predictive performances of CDK1 combined with CX3CR1 microarray genes expression on 42 patients with septic shock (33% mortality) (Pachot A. 2006) collected within 4 days after ICU admission. Performances are given with AUC (Area Under Curve) and 95 % Cl (Confidence Intervals).

[0079] Figure 4 shows the predictive performances of CDK1 combined with CX3CR1 RT- qPCR genes expression (A) on the day 1 (n=32) and (B) on the day 2 or 3 (n=45). Performances are given with AUC (Area Under Curve) and 95 % Cl (Confidence Intervals).

[0080] Figure 5 shows the predictive performances assessed by computing ROC curve (A) on the day 1 and (B) on the day 3 validation data set, for CDK1- CX3CR1 RT- PCR combination and serum lactate. Figure 6 presents the decision tree for risk of death evaluation following ICU admission (Day 1) and 3 days after admission. Low- and High- risk of death groups are defined by using Youden index calculated with CDK1- CX3CR1 ROC curve from the qRT- PCR transfer cohort. The same cut- off (>0.47) was applied at both time points.

[0081] Figure 7 is a diagram representing the first embodiment of the method according to the invention.

[0082] Figure 8 is a diagram representing the second embodiment of the method according to the invention.

[0083] Figure 9 is a schematic representation of the computer system of the invention.

[0084] Definitions

[0085] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In case of conflict, the present document, comprising definitions, will prevail. Preferred methods, steps and reagents are described below, although methods, steps and reagents similar or equivalent to those described herein can be used in practice. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The methods, steps and reagents and examples disclosed herein are illustrative only and not intended to be limiting.

[0086] According to the invention, the terms risk of death and risk of mortality are considered synonymous. CX3CR1 gene (Gene ID: 1524, NCBI database) encodes for the fractalkine (or CX3CL1) receptor. Fractalkine is a transmembrane protein and chemokine involved in the adhesion and migration of leukocytes. The sequence of the human CX3CR1 gene is available under the accession number NG_016362.2 (NCBI Reference sequence, data available on November, 1st2023). More specifically, the first value VI reflects the level of expression of that human CX3CR1 gene.

[0087] CDK1 gene (Gene ID: 983, NCBI database) encodes for the Cyclin- dependent kinase 1 (CDK1) protein. The sequence of the human CDK1 gene is available under the accession number NG_029877.1 (NCBI Reference sequence, data available on November, 1st2023). More specifically, the second value V2 reflects the level of expression of that human CDK1 gene.

[0088] The term "lactate" refers to the conjugate base of lactic acid.

[0089] For simplification in the specification, CDK1 gene, CX3CR1 gene and lactate may be called biomarker.

[0090] For simplification in the specification, the first value VI reflecting the level of expression of CX3CR1 gene in a biological sample obtained from the patient assessed by the method will be simply referred to as first value VI or value VI, the second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from the patient assessed by the method will be simply referred to as second value V2 or value V2, the third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient will be simply referred to as third value V3 or value V3.

[0091] A method of assessing the risk of death of a patient is a method for determining if a patient is at risk of increased mortality. Furthermore, a method of assessing the risk of death of a patient assigns a probability that said patient will die in the near future. The information on the risk of death or of increased mortality may correspond to a risk classification, a risk identification, or a risk stratification.

[0092] The method according to the invention and whatever the embodiment, is aimed to assess a patient's risk of death, in the near future. In particular, the risk of death is the risk that the patient will die within the 28 days of the day of collection of the biological sample(s) providing the data used in the assessment method. More specifically, with the methods of the invention, the level of risk determined by the correlating step may be a binary result: high risk of death or low risk of death, or the result may correspond to a more elaborate assessment: stratification with a risk level, for instance low, moderate and high risk. By assessing the risk of death, the method of the invention enables making the treatment decisions regarding the patient on a more informed basis.

[0093] The term "patient" refers to an individual (human being) who has come into contact with a healthcare professional, such as a physician or doctor (for example, a general practitioner) or a medical structure or a health facility (for example, a hospital, and more particularly the emergency unit, the intensive care unit, the resuscitation unit, an on- going care unit, or a medical structure for the elderly, of the nursing home type). The invention is particularly useful for patients that have been admitted in a medical care unit, in particular in an emergency unit, an intensive care unit or a resuscitation unit. More precisely, the invention relates to a method of evaluating the risk of death in a patient who has been subjected to an insult such as surgery, burns, trauma, etc., generating sepsis, and more specifically a septic shock.

[0094] Definitions of sepsis and septic shock were last revised in 2016 for taking into account the considerable advances that have been made into the pathobiology (changes in organ function, morphology, cell biology, biochemistry, immunology, and circulation), management, and epidemiology of sepsis. Since 2016 and the publication of the Third International Consensus Definitions for Sepsis and Septic Shock (Spesis- 3)(Singer M. 2016), the sepsis is now defined as lifethreatening organ dysfunction caused by a dysregulated host response to infection. For clinical operationalization, organ dysfunction can be represented by an increase in the Sequential [Sepsis- related] Organ Failure Assessment (SOFA) score of 2 points or more, which is associated with an in- hospital mortality greater than 10%.

[0095] Septic shock is 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. This combination is associated with hospital mortality rates greater than 40%. In out- of- hospital, emergency department, or general hospital ward settings, adult patients with suspected infection can be rapidly identified as being more likely to have poor outcomes typical of sepsis if they have at least 2 of the following clinical criteria that together constitute a new bedside clinical score termed quickSOFA (qSOFA): respiratory rate of 22 / min or greater, altered mentation, or systolic blood pressure of 100 mm Hg or less.

[0096] Sepsis represents one of the primary causes of mortality of patients in intensive care units.

[0097] Estimating the risk of mortality in a sepsis and in particular in septic shock, is thus essential in order to be able to provide personalized care and thus to attempt to reduce the risk of death.

[0098] The expression "admission" in a medical care unit means the time the patient is considered for medical care in said medical care unit, typically in an emergency unit, an intensive care unit or a resuscitation unit. In the methods of the invention the biological samples used to generate de values VI, V2 and V3 may be taken within six days after the admission (therefore at any time during the 144 hours after the admission), within five days after the admission (therefore at any time during the 120 hours after the admission), within four days after the admission (therefore at any time during the 96 hours after the admission), within three days after the admission (therefore at any time during the 72 hours after the admission), within two days after the admission (therefore at any time during the 48 hours after the admission), or within one day after the admission (therefore at any time during the 24 hours after the admission). The expression "at day one" after the admission or by reference to the admission means within the first 24 hours (24h) following the admission, "at day 2" or "at day two" means within the second 24h following the admission (therefore after 24h and until 48h after the admission), "at day 3" or "at day three" means within the third 24h following the admission (therefore after 48h and until 72h after the admission), "at day 4" or "at day four" means within the fourth 24h following the admission (therefore after 72h and until 96h after the admission)... and so on.

[0099] The term "biological sample" describes any kind of fluid or tissue obtained from a patient. A biological sample collected from a patient may be of a different nature, such as blood or its derivatives. In particular, this sample may be a biological fluid, such as a blood sample or a sample derived from blood, which may in particular be chosen from whole blood, plasma, serum, as well as any type(s) of cells extracted from blood, such as peripheral blood mononuclear cells (or PBMCs, containing lymphocytes (B, T and NK cells), dendritic cells and monocytes), subpopulations of B cells, purified monocytes, or neutrophils. In particular, the sample may be any sample suitable for measuring the biomarkers used according to the present invention and may refer to a biological sample obtained for the purpose of evaluation in vitro. The sample may comprise material which can be specifically related to the individual and from which specific information about the selected biomarker can be determined, calculated or inferred. Preferably, the biological sample is a blood sample, more preferably selected from the group consisting of serum, plasma, and whole blood. As classically understood, whole blood is a blood sample containing the white and red cells, platelets and plasma. The biological sample may be obtained or collected from the patient by any method for obtaining a sample from the human body. The step of collection does not belong to the claimed method. For example, a needle may be used to draw blood from a vein in arm or hand from the patient. The blood sample can be transferred in a tube containing an anticoagulant, such as heparin, lithium heparinate or any other suitable anticoagulant, before the steps consisting in the relevant measurement, in particular the level of expression of the selected biomarkers. For example, a Vacutainer® tube (Becton- Dickinson) or a Greiner, Terumo, Sarstedt, tube etc., can be used.

[0100] In the description of the invention the first value VI, the second value V2 and the third value V3 can be obtained at the same time or at different times and whatever the order of obtention.

[0101] The term "data set" refers to a set of at least two values, and in particular at least two digital values.

[0102] The expression "value reflecting the level of expression of a gene refers to any value that is representative of the said level of expression in the biological sample. In particular, the first value VI and the second value V2 can be obtained by measuring the corresponding level of expression in a biological sample of said patient. The value reflecting the level of expression of a gene in a biological sample characterizes the level of expression of said gene. Typically, the value reflecting the level of expression of a gene may correspond to the quantity of transcripts of that gene, determined after an amplification step.

[0103] The term "quantity" describes a standard- defined quantity of a substance that measures the size of an ensemble of elementary entities, in particular number or mass of molecules, or other particles.

[0104] The "value V3 reflecting the quantity of lactate" refers to any value that is representative of the said quantity of lactate in the biological sample. The "value V3 reflecting the quantity of lactate" may be expressed as an amount or a concentration. The "concentration" of a lactate is the quantity of lactate divided by the total volume of the sample used for the measurement. Several types of concentrations can be used: mass concentration, molar concentration, number concentration, and volume concentration.

[0105] "Threshold value" as used herein refers to a cutoff value that is used to assess the risk of death. Examples of threshold value are given hereinafter. However, it is well- known that threshold values may vary depending on the nature of the assay used for the determination of the value reflecting the level of expression or the quantity of the biomarker (e.g., reactants employed, reaction conditions, nature of sample, etc.). In addition, it is well known within the ordinary skills of one in the art to adapt the specific disclosure herein for other types of assays. Whereas the precise value of the threshold value may vary between assays, the findings as described herein are generally applicable and a skilled person is capable to extrapolate the teachings of the present disclosure to other assays.

[0106] The term "processing" of data means the transformation of data, by any type of data treatment or calculation that does not alter the meaningful and valuable information of the original data. All the data of the data set may be processed, or only a part of the data set may be processed.

[0107] In the context of the invention, the term "processing" designates more specifically the calculation of a processed data V4 of the first value VI and the second value V2.

[0108] The term "processed data V4" of two values means a value calculated with the use of at least the two values or exclusively with the two values.

[0109] The "processed data" refers to the data obtained from the data set after processing. All the data of the data set may be processed, or only a part of the data set may be processed.

[0110] In the context of the kit of the present invention the term "reagent" describes a substance or compound added to a sample, and in particular a biological sample, that allows to measure the level of expression, the quantity, amount or concentration of the biomarker of interest. In particular, the reagents allow to measure the level of expression of the selected gene. The use of the reagents of the kit of the present invention leads to the values VI, V2 and V3 used in the methods of the invention.

[0111] The term "specifically measure" means to detect accurately the level of expression, the quantity, amount or concentration of the biomarker of interest. For a specific measurement, the selected sample will be incubated with the reagent(s) under conditions appropriate for formation of a complex of the reagent with the sought component. It is not necessary to specify such conditions because such appropriate incubation conditions are well- known to the skilled person.

[0112] A "kit" designates a set of reagent(s), tool(s) and / or instructions that have to be used together and that are useful to perform a method of assessment according to the invention. All components of the kit may be packaged separately in individual containers. However, it is also possible that two or more components of the kit may be packaged together in one or more containers. The kit may comprise a label, e.g. instructions on how to use the kit or describing the kit's contents. However, this information may also be provided in any other form, such as on a storage medium, for instance a ROM (e.g. a CD ROM or a microelectronic circuit ROM), a USB stick or magnetic storage means, for example a diskette (floppy disk) or a hard disk. The kit may also comprise further reagents that allows to measure other molecules or biomarkers, than those specified.

[0113] According to the invention, a computer program can use any programming language and take the form of source code, object code or a code intermediate between source code and object code, such as a partially compiled form, or any other desirable form.

[0114] A computer- readable information medium can be any entity or device capable of storing the program. For example, the medium can include storage means such as a ROM, for example a CD ROM or a microelectronic circuit ROM, a USB stick or magnetic storage means, for example a diskette (floppy disk) or a hard disk. Alternatively, the information medium can be an integrated circuit in which the program is incorporated, the circuit being adapted to execute the method in question or to be used in its execution.

[0115] Detailed description of the invention

[0116] The methods of assessing the risk of death of a patient according to the invention use a first value VI representing the level of expression of CX3CR1 gene in a biological sample obtained from said patient and a second value V2 representing the level of expression of CDK1 gene in a biological sample obtained from said patient. These values are provided as a data set in steps A, Al, B and Bl of specific method of the invention whatever the embodiment.

[0117] Whatever the embodiment of the method of the invention, the biological sample used for the measurement of the second value V2 may be the same biological sample as the biological sample used for the measurement of the first value VI or another biological sample coming from the same patient. Advantageously, when the biological sample used for the measurement of VI is different from the biological sample used for the measurement of the second value V2, those two biological samples are collected on the same day and are, preferentially, taken at the same time. At the same time means within a time of less than 1 hour, preferentially within a time of less than 30 minutes, of less than 20 minutes or of less than 10 minutes. In particular, the first value VI and the second value V2 are both obtained from one or several blood samples collected at the same time, in particular from whole blood sample(s). The collected blood sample may be divided into several collecting tubes and / or divided for the measurements resulting in the first value VI and the second value V2.

[0118] The first value VI and the second value V2 are part of a data set. The data set may comprise only the first value VI and the second value V2 or may comprise additional data, for instance a data representing the quantity or the level of expression of another biomarker. Advantageously, the data set comprises a third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient, V3 being, in particular, the molar concentration of lactate in said biological sample. More specifically, the data set consists of the first value VI reflecting the level of expression of CX3CR1 gene, the second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient and the third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient. In a similar way, the biological sample used for the measurement of the third value V3 can be the same sample as the sample used for the measurement of the first value VI and / or the second value V2 or another biological sample coming from the same patient. Advantageously, when the biological sample used for the measurement of V3 is different from the biological sample used for the measurement of VI and / or V2, all the biological samples are collected on the same day and are, preferentially, taken at the same time. In particular, the first value VI, the second value V2 and the third value V3 are all obtained from one or several blood samples collected at the same time. The collected blood sample may be divided into several collecting tubes and / or divided for the measurements resulting in the first value VI, the second value V2 and the third value V3.

[0119] When the data set also comprises a third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient, the method may further comprise the action of measuring a third value V3 reflecting the quantity of lactate in a biological sample obtained from said patient. The obtaining of the first value VI, the second value V2 and the third value V3 when it is present may be determined sequentially or simultaneously, using methods that are routine to the person skilled in the art, as indicated above.

[0120] The biological sample(s) used is(are) biological sample(s) originating from the patient for whom the risk of death is to be evaluated. In particular:

[0121] - for the measurement of the first value VI, such a biological sample is selected from those that are suspected of containing transcripts of the CX3CR1 gene, typically whole blood sample,

[0122] - for the measurement of the second value V2, such a biological sample is selected from those that are suspected of containing transcripts of the CDK1 gene, typically whole blood sample,

[0123] - for the measurement of the third value V3, such a biological sample is selected from those that are suspected of containing lactate, typically serum sample. As specific examples, the biological sample originates from a biological sample obtained within the 6 days or on day 6 (D6) following admission of the patient into the intensive care unit, preferably within the 5 days or on day 5 (D5) following admission to the medical care unit (i.e. the intensive care unit), more preferably within the 4 days or on day 4 (D4) following admission to the intensive care unit (i.e. the intensive care unit), yet more preferably within the 3 days or on day 3 (D3) following admission to the intensive care unit (i.e. the intensive care unit), or indeed within the 2 days or on day 2 (D2) following admission to the intensive care unit (i.e. the intensive care unit), or indeed within the 24 h or 24 h (DI) following admission to the intensive care unit (i.e. the intensive care unit).

[0124] In the context of the invention, the patient has, in particular, a sepsis at the time of collection of the biological sample(s). The methods of the invention are particularly suitable to the assessment of risk of death or risk of mortality in the case of patients in a state of septic shock at the time of collection of the sample(s).

[0125] The threshold values Tv3, Tv4 or Tvl2 and the values VI, V2 or V3 used in the method of assessing according to the invention may be determined by any assay having a certain specificity and sensitivity for the selected biomarker.

[0126] The level of expression of CX3CR1 gene and the level of expression of CDK1 gene can be measured by various methods or assays which are well known by the skilled person. These methods lead to a quantity reflecting the expression of the gene and said quantity may be processed by different ways. Any method of quantifying RNA that is well known to the person skilled in the art may be used to carry out the invention. The measurement of the expression level of a gene consists in quantifying at least one expression product of the gene. The expression product of a gene, in the context of the present invention, is any biological molecule resulting from the expression of said gene. Advantageously, the expression product of the gene is a transcript. By «transcript», it should be understood the RNAs, and in particular the messenger RNAs (mRNAs), resulting from the transcription of the gene. More specifically, the transcripts are RNAs produced by the transcription of the selected gene followed by the post- transcriptional modifications of the pre- RNA forms. Thus, preferably, in the method of the invention, in all embodiments thereof, the expression level of the genes CX3CR1 and CDK1 is measured at the RNA or mRNA transcript level. In the case of an mRNA transcript, the quantification may be carried out by a direct method, by any method known to those skilled in the art allowing quantifying the transcript in the sample, typically by hybridization with a bonding partner that is specific for the transcript to be detected. The quantification of mRNA transcripts may also be carried out by indirect method after transformation of the latter into DNA, or after amplification of said transcript or after amplification of the DNA obtained after transformation of said transcript into DNA. Many methods exist for the detection of nucleic acids (see for example Kricka, 1999 and Relier G. H. 1993).

[0127] The term "hybridization" means the process during which, under appropriate conditions, two nucleotide fragments bond together with stable and specific hydrogen bonds in order to form a double- stranded complex.

[0128] The "bonding partners" of a transcript to be quantified are any partner that could bond to said transcript, and in particular specific bonding partners. Examples of specific bonding partners that may be cited are hybridization probes and amplification primers, and any other molecule that is capable of binding to the transcript to be detected. It is possible to use specific bonding partners. The term "hybridization probe" means a nucleotide fragment comprising 5 to 100 nucleic motifs, in particular 10 to 35 nucleic motifs, having a hybridization specificity under predetermined conditions in order to form a hybridization complex with the transcript(s) of the selected gene. The hybridization probe may comprise a marker allowing it to be detected, also called "detection probe". Within the meaning of the present invention, the term "amplification primer" means a nucleotide fragment comprising 5 to 100 nucleic motifs, preferably 15 to 30 nucleic motifs, allowing initiation of an enzymatic polymerization, in particular such as an enzymatic amplification reaction. The term "enzymatic amplification reaction" means a process generating multiple copies of a nucleotide fragment by the action of at least one enzyme. Such amplification reactions are well known to the person skilled in the art and the following techniques may be cited in particular:

[0129] • PCR (Polymerase Chain Reaction), as described in patents US 4683 195, US 4683 202 and US 4800 159;

[0130] • LCR (Ligase Chain Reaction), disclosed, for example, in patent application EP 0 201 184;

[0131] • RCR (Repair Chain Reaction), described in patent application WO 90 / 01069;

[0132] • 3SR (Self- Sustained Sequence Replication) in patent application WO 90 / 06995;

[0133] • NASBA (Nucleic Acid Sequence- Based Amplification) in patent application WO 91 / 02818;

[0134] • TMA (Transcription Mediated Amplification) in patent US 5 399491; and

[0135] • LAMP (Loop- mediated Isothermal Amplification) in patent US 6410278.

[0136] The term "detection" means either a physical method or a chemical method with an intercalating dye such as SYBR® Green I or ethidium bromide, or a detection method using a marker. Many detection methods exist for the detection of nucleic acids (Kricka, 1999).

[0137] The term "marker" means a tracer that is capable of producing a signal that can be detected. A nonlimiting list of these tracers comprises enzymes that produce a detectable signal, for example by colorimetry, fluorescence, or luminescence, such as horseradish peroxidase, alkaline phosphatase, beta- galactosidase, glucose6- phosphate dehydrogenase; chromophores such as fluorescent, luminescent, or dye compounds; electron- dense groups detectable by electron microscopy or by their electrical properties such as conductivity, by amperometric, or voltametric methods, or by impedance measurements; groups that are detectable by optical methods such as diffraction, surface plasmon resonance, contact angle variation, or by physical methods such as atomic force spectroscopy, the tunnel effect, etc.; radioactive molecules such as32P,35S or125l.

[0138] In the context of the present invention, the hybridization probe may be a probe termed a detection probe. Under such circumstances, the "detection" probe is tagged with a marker as defined above. Because of the presence of this marker, the presence of a hybridization reaction between a given detection probe and the transcript to be detected can be detected.

[0139] Regarding real time quantitative PCR, for diagnostic applications, two types of tagging for a specific hybridization are generally used:

[0140] - Firstly, it is possible to use methods employing a probe between two primers. In particular, it is possible to use TaqMan®, probes, such as those described by Espy MJ., 2006 Holland P.M., 1991; molecular tags, also known as molecular beacons, such as those described by Espy, 2006; 2001; Sigma, 2008; adjacent hybridization probes, known as HybProbes (FRET); or indeed CPT (for "cycling probe technology"), as described by Duck P., 1990.

[0141] - It is also possible to use methods employing tagged primers. Primers of this type may be scorpion primers or Scorpion®, as described by Sigma, 2008; Plexor primers, as described by Buh Gasparic M., 2010; primers used in the AmpliFluor® technique, as described by Bio- Rad Laboratories, 2006; Nazarenko LA., 1997; LUX (light upon extension) primers, as described by Bio- Rad Laboratories, 2006; Buh Gasparic et al., 2010; Nazarenko LA., 2002; or indeed BD Qzyme™ primers, as described by Bio- Rad Laboratories, 2006; Clontech, 2003.

[0142] The hybridization probe may also be a probe termed a capture probe. Under such circumstances, the probe termed a capture probe is immobilized or can be immobilized on a solid support using any appropriate means, i.e. directly or indirectly, for example by covalence or adsorption. The solid support that may be used may be synthesized materials or natural materials, optionally chemically modified, in particular polysaccharides such as materials based on cellulose, for example paper, cellulose derivatives such as cellulose acetate and nitrocellulose or dextran, polymers, copolymers, in particular based on styrene type monomers, natural fibers such as cotton, and synthetic fibers such as nylon; mineral materials such as silica, quartz, glass, or ceramics; latexes; magnetic particles; metallic derivatives; gels, etc. The solid support may be in the form of a microtitration plate, or a membrane as described in the application WO- A-94 / 12670, or a particle.

[0143] It is also possible to immobilize a plurality of different capture probes on the support, each probe being specific for a target transcript. In particular, it is possible to use as the support a biochip on which a large number of probes may be immobilized. The term "biochip" means a solid support of small dimensions on which a multitude of capture probes are fixed at predetermined positions. The concept of a biochip or DNA chip dates from the beginning of the 1990s. It is based on a multidisciplinary technology that combines microelectronics, nucleic acid chemistry, image analysis, and data processing. The operating principle is based on a cornerstone of molecular biology: the hybridization phenomenon, i.e. pairing by the complementarity of bases of two DNA and / or RNA sequences. The biochip method is based on the use of capture probes fixed to a solid support on which a sample of target nucleotide fragments tagged directly or indirectly with fluorochromes is caused to act. The capture probes are positioned in a specific manner on the support or chip and each hybridization produces a particular piece of information pertaining to the target nucleotide fragment. The information obtained is cumulative and can, for example, be used to quantify the target transcript or plurality of target transcripts. After hybridization, the support or chip is washed and the transcript / capture probe complexes are revealed by a high affinity ligand bonded, for example, to a fluorochrome type marker. The fluorescence is read, for example, by a scanner and the fluorescence is processed digitally. By way of indication, DNA chips developed by Affymetrix ("Accessing Genetic Information with High- Density DNA arrays") (Chee M., 1996), may be cited for molecular diagnostics. In this technology, the capture probes are generally small, about 25 nucleotides. Other examples of biochips are given in the Patents US A 4 981 783, US A 5 700637, US A 5 445 934, US A 5 744 305, and US A 5 807 522. The principal characteristic of the solid support must be to preserve the hybridization characteristics of the capture probes on the target nucleotide fragments while generating minimal background noise for the detection method.

[0144] The techniques for immobilizing probes on a support are well known to the person skilled in the art; examples are depositing pre- synthesized probes by printing or microdeposition (patent applications WO- A00 / 71750, FR 00 / 14896, FR 00 / 14691), or indeed in situ synthesis (patent applications WO 89 / 10977 and WO 90 / 03382).

[0145] In order to detect the transcript of the biological sample, an extraction step might be necessary. The extraction is carried out using any of the protocols for extracting and purifying nucleic acids that are well known to the person skilled in the art. By way of indication, nucleic acids could be extracted by means of:

[0146] - a step for lysis of cells present in the biological sample in order to liberate the nucleic acids contained in the patient's cells. By way of example, lysis methods such as those described in the following patent applications could be used:

[0147] • WO 00 / 05338, regarding mixed magnetic and mechanical lysis;

[0148] • WO 99 / 53304, regarding electrical lysis;

[0149] • WO 99 / 15321, regarding mechanical lysis.

[0150] The person skilled in the art could use other well- known lysis methods, such as thermal shock or osmotic shock, or chemical lysis using chaotropic agents such as guanidinium salts (US 5 234809).

[0151] - a step for purification, in order to separate the nucleic acids from the other cellular constituents precipitated out in the lysis step. This step may be used in general to concentrate the nucleic acids, and could be adapted to the purification of RNA. By way of example, magnetic particles, optionally coated with oligonucleotides, by adsorption or covalence, could be used (see the patents US 4 672 040 and US 5 750 338 in this regard), then the nucleic acids that are fixed to these magnetic particles are purified by means of a washing step. This step for purifying the nucleic acids is of particular interest if said nucleic acids are to be amplified subsequently. One particularly advantageous implementation of these magnetic particles is described in patent applications WO- A97 / 45202 and WO- A99 / 35500. It is also possible to use silica, either in the form of a column, or in the form of inert particles or magnetic particles (Merck: MagPrep* Silica, Promega: MagneSil* paramagnetic particles). Other very popular methods are based on ion exchange resins in a column or in a particulate paramagnetic form (Whatman: DEAE- Magarose) (Levison P.R., 1998). Another method is that of adsorption onto a metallic oxide support (Xtrana: Xtra- Bind* matrix).

[0152] When the RNA is to be extracted specifically from a biological sample, extraction may in particular be carried out using phenol, chloroform, and alcohol in order to eliminate the proteins and precipitate the RNA with 100% ethanol. The RNA can then be pelletized by centrifuging, washing, and being taken up again into solution.

[0153] The level of expression of the genes may in particular be measured by Reverse Transcription- Polymerase Chain Reaction or RT- PCR, preferably by quantitative RT- PCR or RT- qPCR (for example using the FilmArray® technology), by RT- qPCR in real- time, by sequencing (preferably by high throughput sequencing) or by hybridization techniques (for example with hybridization microchips or by teclmiques of the NanoString® nCounter® type).

[0154] Even if it is not preferred, the expression product of the gene may also be a protein and / or a polypeptide which is the product of the translation of at least one of the transcripts of said gene. Thus, in the method as previously described, the expression of the gene(s) may also be measured at the protein level. As examples of techniques that can be used for a detection at the protein level, mention may be made of assays by immuno- assays, such as ELISA (Enzyme Linked Immumo Sorbent Assay), ELFA (Enzyme Linked Fluorescent Assay) and RIA (Radio Immuno Assay), and assays by mass spectrometry.

[0155] As regards the determination of the third value V3, a lot of methods to measure the quantity of lactate in a sample can be used. The quantity may be, for example, expressed as an amount or as a concentration. Lactate can be measured in various samples, comprising blood (in particular plasma, serum, or whole blood), CSF (cerebral spinal fluid) and other body fluids. To measure lactate in a sample, enzymatic assays, in particular lactate dehydrogenase or lactate oxidase assays are available. In particular, lactate may be measured in a plasma, serum, or whole blood sample using an enzymatic assay to generate a product that may be detected by colorimetry or by fluorometry by reaction with a selective probe. Lactate can also be measured using electrode methods, such as blood gas analyzers. Lactate assay kits are commercially available and routinely performed in medical facilities. For instance, Roche markets a device (Cobas®) to measure lactate level. Abeam and other companies provide a lactate assay fluorometric kit, where lactate is oxidized by lactate oxidase to generate a product, which interacts with a probe to produce colour and fluorescence.

[0156] The level of expression of CX3CR1 gene and level of expression of CDK1 gene may be any quantity, amount or concentration representing the quantity of transcript(s) of the corresponding gene. It could also be a value derived from said quantity, amount or quantity. By way of example, a derived value of the quantity may be the absolute concentration, calculated using a calibration curve obtained from successive dilutions of a solution of amplicon with a known concentration. But, in the context of the invention, advantageously, the levels of expression of CX3CR1 gene and of CDK1 gene are both measured by quantitative reverse transcriptase PCR (RT- PCR), and in particular by quantitative RT- PCR in real time. The simplest way of implementing the methods of the invention is to use the level of expression of CX3CR1 gene at the RNA level determined by an RT- PCR method as first value VI and the level of expression of CDK1 gene at the RNA level determined by an RT- PCR method as second value V2.

[0157] The first value VI, the second value V2 and the third value V3, when the third value V3 is present, can be used as such or combined to give a processed data V4 or only two of those three values can be combined to give a processed data V4. This processed data V4 is, for instance, the ratio of V1 / V2 or V2 / V1.

[0158] In particular, the first value VI is representative of the level of expression at the RNA level of CX3CR1 gene in a whole blood sample obtained from said patient, at day 1 or at day 2 or at day 3, following its admission in an ICU and the second value V2 is representative of the level of expression at the RNA level of CDK1 gene in a whole blood sample obtained from said patient, at day 1 or at day 2 or at day 3 (but advantageously, obtained on the same day as the whole blood sample used of the first value VI).

[0159] If processed data V4 is obtained by the ratio V2 / V1 and if processed data V4 is higher or equal to the threshold value TV4the patient will be classified as high risk of death.

[0160] If processed data V4 is obtained by the ratio V1 / V2 and if processed data V4 is lower or equal to the threshold value TV4, the patient will be classified as high risk of death.

[0161] According to the invention wherein the risk of death is characterized in step D as following when V4 = V2 / V1:

[0162] • a high risk of death is attributed when V4 > TV4 and V3 > TV3,

[0163] • a moderate risk of death is attributed when either V4 < TV4 or V3 < TV3, and

[0164] • a low risk of death is attributed when V4 < TV4 and V3 < TV3.

[0165] And when V4 = V1 / V2:

[0166] • a high risk of death is attributed to the patient when V4 < TV4 and V3 < TV3,

[0167] • a moderate risk of death is attributed to the patient when either V4 > TV4 or V3 > TV3, and a low risk of death is attributed to the patient when V4 > TV4 and V3 > TV3.

[0168] Whatever the embodiment of the method of the invention, the threshold value(s) can be determined or calculated using any suitable statistical method known in the art. In particular, the used threshold value(s) will be calculated by the Youden Index of a ROC curve. The Youden Index, also termed "J Statistic" in the literature, is a well- known indicator that represents a summary measurement of the receiver operating characteristic (ROC) curve for the accuracy of a diagnostic test (see, e.g., Youden WJ., 1950). The ROC curve is obtained with the measurement of the corresponding value for a reference population that comprises patients which are known to have survived or not to have survived. It can be defined as follows: Youden Index = Sensitivity + Specificity - 1, or Youden Index = [TP / (TP + FN)] + [TN / (FP + TN)] - 1 where TP = True Positives, TN = True Negatives, FP = False Positives, FN = False Negatives. Youden Index ranges between 0 and 1, with 0 values indicating that a diagnostic test gives the same proportion of positive results for groups with and without the outcome of interest (here death). A value of 1 indicates that there are no false positives or false negatives. The Youden Index can be used in conjunction with a receiver operating characteristic (ROC) analysis, where the index is defined for all points of the ROC curve. The maximal value of the index can then be used as a cut- off for numerical diagnostic tests. In particular, the used threshold value Tv4will be calculated by calculating the ratio between the threshold value Tvlof the first value VI and the threshold value Tv2of the second value V2. The threshold values TV1 andTv2will be determined by the Youden Index of a ROC curve and the selected ratio will be calculated and used as threshold value TV4. The determination of the threshold value, will, advantageously, be achieved by an assay or a method of the same type and under the same assay conditions as the assay that is to be applied to the biological sample from the patient, for the determination of the values VI, V2 or V3 used in the method of assessment according to the invention. The determination of the threshold value is also determined with the same kind of biological samples and collected as the same time as the biological sample(s) used for implementing the method of a patient of interest. But, it is well within the ordinary skill of one in the art to adapt the disclosure herein to obtain threshold values for other assays. In general, it is known that the results of analyte detection tests depend to a large extent on the characteristics of the binding partners used. Thus, when detecting RNA by hybridization with nucleotide probes, in particular, the results depend on the characteristics of size, composition, and percentage complementarity of the probes, and these characteristics influence the values measured with these probes. Thus, it can be understood that it is not possible to provide precise threshold values and that the threshold value adapted to each method or assays used may be determined in each case by simple and routine experiments.

[0169] The reference population can be a population of healthy subjects, or more preferably a population of patients that were admitted in a medical care unit, in particular in an emergency unit, an intensive care unit or a resuscitation unit and who are known to have survived, notably that are known to have survived more than 28 days after their admission. When the patient of interest is a patient with a sepsis, and, in particular, a patient in a state of septic shock, the reference population will be respectively a population of patients with sepsis or a population of patients in a state of septic shock. As way of examples, it has been found that a threshold value TV4for the processed data V4 to predict if a patient is at risk of increased mortality, between 0.4 and 0.5, and for instance around 0.47, could be suitable. Typically, this threshold value is of interest for values VI and V2, corresponding to the level of mRNA resulting from CX3R1 gene and CDK1 gene respectively, measured by RT- PCR in whole blood samples. The threshold value Tv3used for the lactate concentration in serum samples could be between 1 and 3 mmol / L, and for instance around 2 mmol / L. The threshold value Tv3was determined by Singer M., 2016, that gives the current definition of sepsis and septic shock.

[0170] The method of the invention (whatever the embodiment) allow the determination of a level of risk of death. This determination may correspond to a classification. The step D characterizes the levels of risk: a high risk of death, a moderate risk of death and a low risk of death and can be done by classifying or communicating a classification of the patient among these different levels of risk.

[0171] The method may directly include the classification of the level of risk of death, for instance with a classification. The method may communicate the information and / or the classification given in another location. At any step of the method of the invention, the information (processed data, threshold value, result of the comparison ...) may be communicated to another device, for instance to a device that is not a point- of- care device. "Communicate" or "communicated" as used herein refers to the conveying, transmitting and / or reporting of an item of information. The information obtained by performing an assay can be communicated by a computer, in a document, on a mobile device (e.g., a smart phone), on a website...

[0172] In some embodiments, in step D. the information (level of risk, classification ...) is classified on or from an instrument or device. In particular, the information is displayed on an instrument or device. The method of the invention is entirely suited to be performed with automated means corresponding to one or several automated devices. In particular, the method of the invention is a computer- implemented method. The method of the invention will be implemented on one or several devices or instruments. Automated analysis instruments or rapid tests may be used to obtain the value VI, V2 or V3.

[0173] Furthermore, instructions for performing the methods of the invention may be included in a computer program product configured for execution by one or more processors.

[0174] All the units form a computer system. The computer system can correspond to only one device or instrument or to a plurality of devices and / or instruments that are located in different places and that communicate with each other. The term "data set unit" describes an electronic device or part of an electronic device that collects data. The data set unit may be integrated in the processing unit and / or the correlation unit. The data set unit is formed by a processor and a storage with instructions that when executed by the processor cause the processor to store and / or retrieve the first value VI and the second value V2.

[0175] The term "processing unit" describes an electronic device or part of an electronic device that is configured to perform the method according to the invention, encoded by an executable code, in order to transform collected data into other data. Computer and mobile devices (for instance, smartphones) are examples of processing unit. The processing unit is formed by a processor and a storage with instructions that when executed by the processor cause the processor to process data from the data set provided in (A, B, Al or Bl), by combining values of the data set provided by the data set unit in processed data V4.

[0176] The term "correlation unit" describes an electronic device or part of an electronic device that is capable of performing a method encoded by an executable code, in order to correlate and / or compare information. The correlation unit is formed by a processor and a storage with instructions that when executed by the processor cause the processor to the data set provided by (Al, Bl) or the processed data V4 obtained with (A, B) when (A, B) is present to a level of risk of death.

[0177] Most of the time, the threshold value(s) used in the method of the invention is(are) retrieved from a database.

[0178] The term "classification unit" describes an electronic device or part of an electronic device displaying information, in particular the results of the operations of the correlation unit. Suitable classification unit are well- known to the person skilled in the art. For example, the indication unit may be any kind of visual display integrated in an electronic device, such as a computer or mobile device. Further, the classification unit may be any kind of visual display considered as a separate device that can be connected to a computer or a mobile device.

[0179] The invention also relates to kits for assessing the risk of death of a patient, the kit comprising reagent(s) required that allows to measure in a sample, and in particular in a biological sample obtained from a patient, the level of expression of CX3CR1 gene and reagent(s) required that allows to measure in a sample, and in particular in a biological sample obtained from a patient, the level of expression of CDK1 gene, and optionally reagent(s) required that allows to measure the quantity of lactate in a sample, and in particular in a biological sample obtained from a patient.

[0180] The reagents required that allow to measure the level of expression of CX3CR1 gene are, in particular, a pair of amplification primers. The reagents required that allow to measure the level of expression of CDK1 gene are, in particular, a pair of amplification primers. The reagents may further comprise a probe for the amplification product generated with the amplification primer pair. Generally, said probe is either tagged with a marker, or immobilized on a solid support. More details on the different kinds of probes (detection probes and capture probes) have been given previously. The methods, kits, computer systems, computer programs and recording media according to the invention are particularly useful to assess the risk of death of critically ill patients. Those patients whose lives are threatened and who may therefore die within a short period of time (hours or days), are, in particular, patients affected by sepsis, and in particular by septic shock. The invention is therefore extremely valuable in Intensive Care Units and emergency units, where patients at risk of increased mortality may receive a more intensive treatment and attention than other patients. The methods, kits, computer systems, computer programs and recording media according to the invention may thus help the physician to make a choice on a therapeutic treatment. The methods of the invention may further include a step of treatment of the patient, after having considered the conclusion of the method of assessing the risk of death for said patient. "Treatment" means reversing, alleviating, or inhibiting the progress of a disease and / or injury, or one or more symptoms of such disease, that the patient may have. Treatment is performed by administration of a suitable drug.

[0181] Figure 7 represents a diagram of the first embodiment of the invention. According to this first embodiment, step Al and Bl can be enabled simultaneously or in parallel whatever the order. The measures done in step Al and Bl lead to a step D of assessing risk. Step D, comprises at least a step DI of obtaining a data set of measured values of steps Al and Bl and a step D3 of correlating the data set to a level of risk of death (LR for Low Risk, HR for High Risk and MR for Moderate Risk).

[0182] Figure 8 represents a diagram of the second embodiment of the invention. According to this second embodiment, step Al and Bl are optional, and step A and step B include respectively optionally step Al and step Bl. Furthermore, a step C of acquiring a third value V3 is carried out in parallel or simultaneously of steps A and / or B and / or Al and / or Bl. Optionally a step Cl of measuring third value V3 is carried out during step C.

[0183] Step A and B lead to step D and substeps DI, D2 which are respectively: obtaining a data set of measured values of steps A and B (DI) and obtaining processed data V4 based on the combination of said measured values of the data set in step DI (D2). After D2, step D3 of correlating the processed data V4 to a level of risk of death is carried out. D3 comprises a sub step D31 which consists of a comparison of the processed data V4 to at least a threshold value TV4and Step C comprises a sub step of C2 which consists of a comparison of the value V3 to at least a threshold value Tv3. Step C2 and Step D31 lead to determination of level of risk LR, MR or HR.

[0184] Whatever the embodiment of the invention, an optional step E can be carried out to notify or alert the user of the determined level of risk of death. This can be a sound or an image or both. All optional steps are illustrated with discontinued line in Figures 7 and 8.

[0185] Figure 9 illustrates the computer system 100 of the invention. The computer system 100 comprises advantageously:

[0186] - a data set unit (101) configured to store or retrieve the data set comprising at least the first value VI and the second value V2 enabling carrying out at least DI, A, B, C;

[0187] - a processing unit (102) configured to process data enabling carrying out at least step D2;

[0188] - a correlation unit (103) comprising computer instructions for enabling carrying out at least steps C2, D3, D31;

[0189] - classification unit (104) enabling step E of the method.

[0190] Examples

[0191] METHODS

[0192] Discovery cohorts

[0193] Differentially expressed genes (DEG) that are consistently associated with mortality over time following ICU admission were identified. The obtained results have shown that the selection of hub genes (genes that is connected to many other genes in a gene network) of over- and underexpressed biomarkers helps incorporate multiphasic response heterogeneity while normalizing whole blood data without using complex and / or inappropriate methods. Gene expression (GE) data from septic patients enrolled in three prospective studies were retrospectively analysed, by using microarray whole- blood transcriptomic analysis performed within the first 72 hours after ICU admission (GSE95233, GSE57065 and a third unpublished microarray set). Two cohorts were previously published (GSE95233 and GSE57065) (Venet F., 2017; Cazalis M.- A., 2014). Briefly, all septic shock patients were identified according to the SEPSIS- 2 diagnostic criteria of the American College of Chest Physicians / Society of Critical Care Medicine (Bone R.C., 1992). Exclusion criteria were an age under 18 years and subjects with aplasia or immunosuppressive disease (e.g., HIV infection). The onset of septic shock was defined as the beginning of vasopressor therapy in combination with an identifiable site of infection, persisting hypotension - despite fluid resuscitation - and evidence of a systemic inflammatory response manifested by at least two of the following criteria: a) temperature >38 °C or <36 °C; b) heart rate >90 beats / min; c) respiratory rate >20 breaths / min; d) white blood cell count >12,000 / mm3 or <4000 / mm3. This definition of septic shock was the one existing before the new definition adopted since 2016 for sepsis and septic shock and given in Singer M., 2016. All patients had sepsis and were part of studies that have been approved by the Institutional Review Board for ethics, "Comite de Protection des Personnes Sud- Est II", which waived the need for informed consent (#IRB 11236). The third unpublished set of data consisted in 17 additional septic shock coming from the Immunosepsis cohort (Venet F., 2017). Validation Cohort

[0194] As a first validation step for the microarray approach, a previously published microarray study was used. This microarray study consisted in 42 samples from septic shock patients collected between day 1 and day 4 after ICU admission (Pachot A. 2006). Main patients' characteristics are summarized in Table 1 hereinafter. QI to Q3 are the three quartiles.

[0195] Table 1: Patient's clinical and demographic characteristics

[0196] As a validation cohort, a multicentric, non-interventional study conducted in 6 ICUs in Lyon from December 2009 to June 2011 was used. It has been approved by the ethical Institutional Review Board, "Comite d'Ethique des Centres d'investigation Clinique de I'lnter- Region Rhone- Alpes Auvergne" - IRB#5044. Inclusion and exclusion criteria as well as clinical description of the cohort have been published previously (Peronnet E., 2017). Briefly, the patients enrolled were every consecutive patient aged >18 years with an expected length of stay in the ICU of more than 2 days. SIRS (existing definition before 2016) was defined as the presence of at least two of the following clinical criteria: temperature >38 °C or <36 °C, heart rate >90 beats / minute, respiratory rate >20 breaths per minute or PaCO2 < 32 mmHg (4.3 kPa), and leucocyte count >12,000 / mm3 or <4000 / mm3. Sepsis was defined as the presence of a proven (visible either clinically / surgically, radiologically, or microbiologically) infection or a highly suspected infection at inclusion. Following the definitions proposed by Vincent et al., which partly rule out the former definitions of sepsis and severe sepsis described in the ACCP / SCCM 1992 consensus conference statement, sepsis was simply defined as an infection requiring ICU admission (Vincent J.- L., 2013). Septic shock was defined as persistent hypotension despite adequate fluid resuscitation requiring the use of epinephrine or norepinephrine at a dose >0.25 pg / kg / minute (Annane D., 2002).

[0197] Sample collection, processing, and microarray hybridization

[0198] Briefly, peripheral blood samples were collected in PAXgene™ Blood RNA tubes (QIAGEN®) to stabilize mRNA. Total RNA was isolated using the PAXgene™ blood RNA kit (according to the manufacturer's instructions). The residual genomic DNA was digested using the RNase- Free DNase set (Qiagen Valencia, CA, USA). The integrity of the total RNA was assessed using Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Gene expressions (GE) were then generated using GeneChip® Human Genome U133 Plus 2.0 arrays (Affymetrix, Sta. Clara, CA, USA) according to manufacturer's protocol. Raw GE data were normalized using the gcRMA method and technical variability across studies was corrected using the COMBAT algorithm (Johnson W.E., 2007).

[0199] Marker selection and evaluation

[0200] Differentially expressed genes (DEG) between survivors and non- survivors in ICU were identified (logFC > 0.6 and adjusted p- value [using the Benjamini- Hochberg correction] < 0.1) using two different time frames: during the first 24 hours (day 1) and during the following 48 hours (day 2- 3). The intersection of the two sets of genes results in a list of 41 DEG over time. To select the best candidate genes, focus was made on genes whose expression varied in opposite directions (over and under- expressed) and on Hub genes to avoid collinearity. The performance of those markers to predict ICU mortality was assessed for each marker individually, and by computing linear and nonlinear combinations of markers. As a performance metric, the area under the receiver operating characteristic (ROC) curve and confidence intervals (obtained with 2000 bootstrap replicates) were computed. Sensitivity and specificity values using an optimal threshold calculated by the Youden method (Youden W.J., 1950) were also computed.

[0201] Platform transfer and RT- qPCR methods

[0202] Primers and probes for the best candidate genes, selected from the discovery analysis, were designed to be evaluated in RT- qPCR using leftover of mRNA samples from the GSE95233 cohort. They were designed by routine methods for the skilled person with the use of the Primer3 program from Unipro Ugene (https: / / ugene.net / primer3- primer- design- tool / ). Based on MIQE guidelines (Bustin S.A., 2008) to limit the variability of the RT- qPCR methods, mRNA were treated using DNAse and quality was measured using Agilent Bioanalyzer 2100 (Bio- Rad). The cDNAs were synthesized from same concentration (200 ng) of tRNA by RT- VILO (Invitrogen) reaction following manufacturer's instructions. Polymerase chain reactions (PCRs) were performed in a LightCycler instrument (Roche Diagnostics) using the standard TaqMan Fast Advanced Master Mix PCR kit according to the manufacturer's instructions (Applied Biosystems, Foster City, CA, USA). Thermocycling was performed in a final volume of 20 pL containing 5 pM of required primers and 1 pM of required probe. PCR was performed with an initial denaturation step of 10 minutes at 95 °C, followed by 45 cycles of a touch- down PCR protocol (10 seconds at 95 °C, 29 seconds of annealing at 68 °C and a 1- second extension at 72 °C). The cDNA standards were prepared from purified PCR amplicons obtained with the corresponding primers. The second derivative maximum method was used with the LightCycler software to automatically determine the crossing point for individual samples, as previously described. Standard curves were generated by using quadruplicate cDNA standard. Relative standard curves describing the PCR efficiency of selected genes were created and used to perform efficiency corrected quantification. Relative fold gene expression was then calculated using the formula: 2-AACq (Livak KJ., 2001). Additionally, an inter- run calibrator (IRC) was included on each plate, so the different assays could be quantified relative to each other.

[0203] Statistical Methods

[0204] Categorical variables were reported as number and percentage, whereas quantitative variables were expressed as median with interquartile range (25th- 75th percentile). Significance levels for p- values were set at 0.05 and analyses were two- tailed. Statistical analyses were performed using R (v3.6.2) with packages from the BioConductor library and the tidyverse collection suite. The prognosis test characteristics were estimated using sensitivity, specificity, and predictive values. The net reclassification index (NRI) was used to compare ROC curves. Collinearity was taken into account using Hub genes. The selection of hub genes was done using three independent network building databases: Ingenuity Pathway Architect (radial layout representation from Qiagen) FunCoup Functional Association network (Persson E., 2021), and HumanNet integrated functional network (Kim C.Y., 2021) (data not shown).

[0205] RESULTS

[0206] Microarray discovery cohort

[0207] The discovery cohort consisted of 180 microarrays obtained from 100 patients in 3 different septic shock cohorts (GSE95233, GSE57065 and a third unpublished data set). Gathering all these cohorts, 80 patients had samples at the two timepoints (day 1 and day 2 or 3 as follow- up), 4 patients had only a sample at day 1 and 16 patients had a sample only at day 2 or 3. Main characteristics of the patients are summarized in previous Table 1.

[0208] After co- normalization between microarray cohorts, when comparing survivors to non- survivors, 101 differentially expressed genes (DEG) were identified at day 1 and 173 DEG were identified at day 2 / 3. Finally, 41 DEG were common between the two timepoints. Among them, only CX3CR1 and I Lib were downregulated in non- survivors whereas 39 genes were upregulated in non- survivors. To limit collinearity and to increase pathophysiological insight, a network analysis of the 39 remaining upregulated genes was performed and CDK1 was identified as the hub gene using three independent network building databases (Persson E., 2021 and Kim C.Y., 2021). CDK1 was then combined with either CX3CR1 or ILlb. The ratio of these up and downregulated genes was used to avoid normalization issues and to optimize signal. Performances of both individual genes and ratio to discriminate alive and deceased patients were then assessed. Figure 1 shows results when ILlb was used and Figure 2 shows results when CDK1 was used.

[0209] The best predictive performances were obtained using the CDK1 / CX3CR1 ratio (AUROC at day l(Dl)=0.78 [0.89- 0.67] and AUROC at day 2 / 3(D2- 3)=0.81 [0.91- 0.71]). These performances were better than the performances of each individual marker (CDK1: AUROC Dl=0.73 [0.86- 0.61]; D2- 3=0.72 [0.84- 0.61] and CX3CR1: AUROC Dl=0.73 [0.86- 0.61] D2- 3= 0.77 [0.86- 0.67]). Performances of the CDK1 / CX3CR1 ratio were better than the CDK1 / IL1B ratio at both time points, with an AUROC=0.76 [0.87- 0.65] and AUROC =0.73 [0.84- 0.62] respectively (Figure 2). The performances of the CDK1 / CX3CR1 ratio were assessed in an independent microarray cohort consisting of 42 patients with septic shock, with an overall AUROC value >0.90 (Figure 3).

[0210] RT- qPCR platform transfer

[0211] The performances of the CDK1 / CX3CR1 ratio were then assessed in RT- qPCR using 77 randomly selected mRNA samples from one of the microarray discovery cohort (GSE95233). This platform transfer was associated with good predictive performances of the CDK1 / CX3CR1 ratio at both day 1 and day 2 / 3 (AUROC= 0.83 [0.64- 1] and AUROC= 0.75 [0.59- 0.91], respectively) (Figure 4).

[0212] The Youden Index was used to calculate the optimal cut- off value of 0.47 for the CDK1 / CX3CR1 ratio based on this RT- qPCR data. Afterwards, this threshold value was applied to the validation cohort.

[0213] Validation cohort (RT- qPCR)

[0214] The validation cohort consisted in an independent cohort of 140 septic ICU patients (comprising 84 patients collected on both day 1 and day 3), whose main characteristics are summarized in Table 2 (Peronnet, E., 2017). Ta b I e 2. RT- qPCR Validation cohort n=140): Patient's clinical and demographic characteristics

[0215] Among them, 134 had a lactate measurement performed at admission on which we assessed the CDK1 / CX3CR1 ratio. The clinical values available for the cohort were used. Lactate had been dosed by blood gas analyzer. The performances of the CDK1 / CX3CR1 ratio were evaluated using RT- qPCR. At day 1, CDK1 / CX3CR1 ratio used to predict mortality had an AUROC value of 0.74 [0.64- 0.83- ] that was similar to lactate at day 1 (AUROC: 0.72 [0.61- 0.82- ]). At day 3, CDK1 / CX3CR1 ratio used to predict mortality had an AUROC value of 0.72 [0.59- 0.84- ] that was significantly higher (NRI p- value=0.008) than lactate (AUROC: 0.67 [0.54- 0.79- ]) (Figure 5).

[0216] In the SEPSIS- 3 cohort (cohort used for the new definition adopted since 2016 for sepsis and septic shock and given in Singer M. 2016), lactate value >2 mmol / L identified a group of patients with an approximately 40% overall mortality (Singer M., 2016). Similar results were retrieved in the present validation cohort, with a 38% mortality in the group of 84 septic patients with a first lactate value > 2 mmol / L. The mortality in patients with a lactate < 2 mmol / L was 14%. In this cohort, specificity, and sensitivity of the lactate on day 1 were 45% and 82%, respectively. On day 3, the specificity and sensitivity were 74% and 44%, respectively. Of note, using the threshold value obtained after platform transfer, the specificity and sensitivity of CDK1 / CX3CR1 ratio at day 1 were 83% and 54%, respectively. At day 3, specificity and sensitivity of the ratio were 91% and 44%, respectively.

[0217] Although lactate harbors a higher sensitivity to predict ICU mortality, the specificity of the CDK1 / CX3CR1 ratio enables the identification of a group of patients with a higher risk of mortality at both timepoints (57% ICU mortality when performed at day 1 and 65% ICU mortality when performed at day 3) (data presented in Table 3 hereinafter). Table 3. The contingency tables and predictive performances achieved for Lactate and CDK1 / CX3CR1 ratio on Day 1 and Day 3. Sensi = sensitivity, Speci=specificity, PPV=positive predictive value (true positive), NPV= negative predictive value (true negative). Prognostic and predictive enrichment in sepsis using lactate and CDK1 / CX3CR1 ratio

[0218] When combining CDK1 / CX3CR1 ratio to lactate, 3 groups with increasing ICU mortality were identified as shown on Figure 6. At day 1, the group of patients with a lactate >2 mmol / L and a CDK1 / CX3CR1 ratio > 0.47 had a 60% ICU mortality. On the opposite, the group of patients with a lactate < 2 mmol / L and a CDK1 / CX3CR1 ratio < 0.47 had a 9% ICU mortality. The patients in whom markers were found to be discordant (e.g., lactate >2 mM and CDK1 / CX3CR1 ratio <0.47 or lactate <

[0219] 2 mM and CDK1 / CX3CR1 ratio > 0.47) were pooled: this intermediate- risk group had a 28% ICU mortality. This enrichment was also found at day 3, identifying a group of patients with a 67% ICU mortality. Main clinical characteristics of patients classified as low, intermediate, or high- risk group using this enrichment strategy are summarized in Table 4. Table 4. Patients' characteristic according to Low- Inter or High- Risk classification at day 1 and day 3.

[0220] In this study, a robust and time independent combination of two genes (namely CDK1 and CX3CR1) associated with ICU mortality in septic patients was identified. After platform transfer and validation on an independent cohort of septic patients, the two genes, and as way of example, the CDK1 / CX3CR1 ratio can be associated with a higher risk of ICU mortality.

[0221] In addition, it is worthy to note the following:

[0222] First, the two selected genes exhibited significant differential expression over a period of 72 hours in microarrays cohorts of septic patients. This approach aimed at overcoming the effect of time on gene expression. This strategy had greatly limited the number of DEG commonly expressed at both timepoints.

[0223] Secondly, in these examples, the ratio of DEG was used for the risk assessment rather than using gene expression normalized by housekeeping genes. The rationale of this approach was to avoid potential biases related to the variability of expression of housekeeping genes, which are known to vary according to physiological or pathological conditions (Sturzenbaum S.R., 2001, Jin P., 2004). Moreover, the use of a ratio with genes of opposite expression (i.e. upregulated and downregulated) allows to increase the detectable difference and thus to improve marker performances. Thirdly, CDK1 and CX3CR1 genes expression were assessed using RT- qPCR, which is widely recognized as the most sensitive and specific method for quantifying mRNA (Wong M.L., 2005), and then validated with a new independent cohort of 140 septic patients measured at two time point.

[0224] With this strategy, the inventors built a robust combination of transcriptomic markers capable of identifying a group of septic patients at high risk of mortality throughout the first 72 hours of ICU stay. The combination of the CDK1 and CX3CR1 genes (especially as CDK1 / CX3CR1 ratio) with lactate further improves the stratification of patients at ICU admission. The association of lactate's sensitivity and the specificity of CDK1 / CX3CR1 ratio participates to build a refined stratification strategy of patients that could be useful in ICU management or as a stratification tool in interventional studies.

[0225] References

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[0264] EP 2615461

[0265] WO 2019 / 006561

[0266] WO 2017 / 093672

[0267] WO 2015 / 040328

Claims

CLAIMS1. A method of assessing the risk of death of a patient, comprising the steps of:Al. Measuring a first value VI reflecting the level of expression of CX3CR1 gene in a biological sample obtained from said patient,Bl. Measuring a second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient.

2. Method according to claim 1, comprising a step of :D. Assessing the risk of death based on at least on steps Al and / or Bl.

3. Method of assessing the risk of death of a patient, comprising the steps of:A. Acquisition of a first value VI reflecting the level of expression of CX3CR1 gene in a biological sample obtained from said patient,B. Acquisition of second value V2 reflecting the level of expression of CDK1 gene in a biological sample obtained from said patient.D. Assessing the risk of death based on at least on steps A and / or B4. Method of assessing according to claim 3, wherein step D comprises the sub steps of: DI. Obtaining a data set of measured values of steps A and B, andD3. Correlating the data set to a level of risk of death.

5. Method of assessing according to claim 4, wherein the correlation of sub step D3 is a comparison of the data set to at least a threshold value TVi2, the result of the comparison being indicative of a level of risk of death.

6. Method of assessing according to any one of the claims 3 to 5, wherein step D comprises the sub steps of:DI. Obtaining a data set of measured values of steps A and B,D2. Obtaining processed data V4 based on the combination of said measured values of the data set in step DI andD3. Correlating the processed data V4 to a level of risk of death.

7. Method of assessing according to claim 6, wherein the processed data V4 corresponds a ratio of V2 / V1 or a ratio V1 / V2.

8. Method of assessing according to any one of claims 6 or 7 , wherein the correlation of sub step D3 comprises:D31. a comparison of the processed data V4 to at least a threshold value TV4.

9. Method of assessing according to any one of the claims 3 to 8, comprising a step C. of acquiring third value V3 reflecting the quantity of lactate in a biological sample, wherein the data set further comprises the third value V3.

10. Method of assessing according to claim 9, wherein sub step C. further comprises: C2. a comparison of the value V3 to at least a threshold value TV3.

11. Method of assessing according to claim 10, wherein the risk of death is characterized in step D as following, when V4 = V2 / V1 :- a high risk of death is attributed when V4 > TV4 and V3 > TV3,- a moderate risk of death is attributed when either V4 < TV4 or V3 < TV3, and- a low risk of death is attributed when V4 < TV4 and V3 < TV3.

12. Method of assessing according to claim 10, wherein the risk of death is characterized in step D as following when V4 = V1 / V2 :- a high risk of death is attributed to the patient when V4 < TV4 and V3 < TV3,- a moderate risk of death is attributed to the patient when either V4 > TV4 or V3 > TV3, and- a low risk of death is attributed to the patient when V4 > TV4 and V3 > TV3.

13. Method of assessing according to any one of claims 3 to 12, wherein the steps of the assessing method are automated.

14. Kit for assessing the risk of death of a patient according to assessing method according to the preceding claims, the kit comprising reagent(s) required that allows to measure in a biological sample obtained from a patient, the level of expression of CX3CR1 gene andreagent(s) required that allows to measure in a biological sample obtained from a patient, the level of expression of CDK1 gene, and optionally reagent(s) required that allows to measure the quantity of lactate in a biological sample obtained from a patient.

15. Computer system (100) for carrying out the method according to any one of claims 3 to 13 comprising:- a data set unit (101) configured to store or retrieve the data set comprising at least the first value VI and the second value V2;- a processing unit (102) configured to process data from the data set into processed data V4;- a correlation unit (103) comprising computer instructions for correlating the data set or the processed data V4 to a level of risk of death.

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