Method and apparatus for monitoring parameters of patient during extracorporeal circulation surgery

Abstract

A method for monitoring a parameter of a patient during an extracorporeal circulation procedure is used to estimate an AKI risk presence and includes calculating a dynamic global index of AKI risk as a logistic regression derived from a static AKI risk index and a dynamic index of AKI risk. Values and / or temporal trends of a global index of such AKI risk may advantageously be displayed on a monitor during surgery. The dynamic AKI risk index is calculated based on at least an extracorporeal circulation time, a minimum oxygen supply level, and a time of exposure to an oxygen supply below a critical threshold that are repeatedly measured or determined during the procedure. Preferably, the dynamic AKI risk index is also calculated based on a minimum mean arterial pressure during the procedure and / or a maximum concentration of lactic acid in the blood during the procedure and / or a minimum hematocrit during the procedure and / or a fact that the patient has undergone transfusion during extracorporeal circulation.

Description

[0001] describe Field of the Invention

[0002] The present invention relates to a method for monitoring parameters of a patient during extracorporeal circulation surgery and calculating a risk index derived from these parameters. This method can be implemented by a monitoring device adapted to display in particular one or more risk indexes. Background of the Invention

[0003] Extracorporeal circulation or cardiopulmonary bypass (=CPB) is an intraoperative technique used in cardiac surgery, i.e. a technique performed during surgery with the aim of temporarily replacing the natural function of the patient's heart and lungs with artificial function achieved through the use of a heart-lung machine. This technique is often used to perform so-called "open-heart" surgeries.

[0004] Given the nonphysiological nature of extracorporeal circulation, it can produce many possible postoperative complications, such as those related to inflammatory responses, the need for complete anticoagulation, hemodilution, non-pulsatile flow, etc.

[0005] In general, it is not uncommon for organ damage to occur after complex surgery and prolonged extracorporeal circulation. In particular, in addition to cardiac complications, conditions of hepatic insufficiency, impaired pulmonary function, gastrointestinal hypoperfusion, focal or diffuse brain damage and, in particular, renal insufficiency are frequently reported. In fact, of all organs, the kidney is one of the most susceptible to the consequences of cardiac surgery and extracorporeal circulation and is also the organ that can provide quantitative indications, such as the ability to assess the presence and possible extent of damage. In this sense, it can be considered a “spy organ” for the multi-organ consequence of cardiac surgery and extracorporeal circulation.

[0006] In fact, it is known that after surgery, in particular cardiac surgery, or more generally during critical situations to which the patient is subjected, one can witness the onset of acute kidney injury (AKI), a clinical syndrome characterized by a rapid decrease in renal function, which can be demonstrated by measurement of creatinine.

[0007] Currently, there are several predictive “static” AKI risk models, i.e., based on patient and surgical characteristics that can be defined and quantified before the surgery itself; in other words, the risk is preoperative AKI risk.

[0008] However, other parameters may influence AKI during CPB surgery; therefore, these parameters, which are related to the execution of CPB and are therefore of essentially dynamic type, are not taken into account by predictive "static" risk models. Furthermore, these models do not allow the possibility of real-time monitoring of risk trends, which would be useful for the user, in particular for the cardiac anesthesiologist and / or the person responsible for the use and management of the heart-lung machine during CPB (i.e., the perfusion technician), in order to be able to modify with appropriate strategies during the CPB itself. Overview

[0009] A general object of the present invention is to provide a monitoring system that improves upon known solutions.

[0010] This general object as well as these and other more specific objects are achieved as expressed in the appended claims forming an integral part of the present description. List of Figures

[0011] The present invention will become more apparent from the following detailed description considered in conjunction with the accompanying drawings, in which: Figure 1 A block diagram showing an embodiment of a method according to the present invention; Figure 2 Example of a graph showing the relationship between the risk of AKI and the patient's minimum oxygen supply level (DO2); Figure 3 The risk of AKI is shown as a function of the time of exposure to oxygen supply below a critical threshold (T DO2 ) is an example of a graph showing the relationship between Figure 4 The risk of AKI is shown to be related to the extracorporeal circulation time (T CPB ) is an example of a graph showing the relationship between FIG5 shows three examples of graphs showing the relationship between the risk of AKI and the minimum value of hematocrit (HCT), the minimum value of mean arterial pressure (MAP), and the maximum value of lactate (LAC); Figure 6 An example of a graph showing ROC (Receiver Operating Characteristic) curves of a first static index (SR), a third dynamic index (PRR), and a fourth global dynamic index (MDPI); and Figure 7 An example of displaying time trends and numerical values ​​on a screen according to the present invention is shown.

[0012] As can be easily understood, there are many ways of implementing the invention in practice, the invention is defined in its primary advantageous aspects in the appended claims and is not limited to the following detailed description or the appended claims. Detailed Description

[0013] The idea behind the present invention is to provide a method for monitoring parameters of a patient during an extracorporeal circulation operation, in particular in the context of a cardiac operation, and calculating an AKI risk index derived from these parameters. In particular, the present invention proposes both a dynamic AKI risk index and a global AKI risk index, the global AKI risk index depending on the dynamic AKI risk index and a static AKI risk index (i.e., the static AKI risk index before the start of the operation, in particular before the start of the extracorporeal circulation), the static AKI risk index already being known before the present invention. Such a dynamic AKI risk index and / or such a global AKI risk index is displayed on the screen of the device in real time (as a numerical value and / or as a time trend) during the operation in such a way that a user, in particular a perfusion technician or a surgeon or a cardiac anesthesiologist, can advantageously understand the trend of such an index and / or display the trend of such an index. Advantageously, the parameters on which such an index depends are also displayed, so that it can be further understood and / or displayed which parameters modify the index the most.

[0014] In this way, advantageously, such a parameter or parameters can also be manipulated rapidly in order to, for example, minimize a dynamic AKI risk value. Furthermore, it is important to highlight that the calculated global AKI risk provides an indicator of the perfusion quality during surgery.

[0015] The global index is not a simple sum of the static index and the dynamic index; rather, it is provided by a logistic regression derived from the static index and the dynamic index.

[0016] The dynamic AKI risk index is calculated based on at least the CPB duration, the lowest oxygen supply level, and the time of exposure to oxygen supply below a critical threshold; these parameters are measured or received repeatedly during CPB.

[0017] Preferably, the dynamic AKI risk index is also calculated based on the minimum mean arterial pressure during extracorporeal circulation and / or the maximum concentration of lactate in the blood during extracorporeal circulation and / or the minimum hematocrit during extracorporeal circulation and / or the fact that the patient has undergone a blood transfusion during extracorporeal circulation.

[0018] The method according to the invention originates from a retrospective study of 830 patients who underwent surgery at the Department of Cardiac Surgery of the IRCCS Policlinico San Donato and has been validated by statistical analysis, in particular by ROC (Receiver Operating Characteristic) analysis, and also compared with currently known methods, as will be better explained below. In general, cardiac surgery with extracorporeal circulation involves the use of a heart-lung machine that temporarily replaces the natural functions of the heart and lungs and helps maintain the patient's blood supply (perfusion) and provides the oxygen supply required for the patient's survival. However, prolonged exposure of the patient to poor quality perfusion can lead to undesirable postoperative complications, in particular the risk of renal failure. As is known and as mentioned above, the risk of renal failure is assessed using the AKI (Acute Kidney Injury) risk, and when it occurs as a postoperative complication after cardiac surgery, it is particularly referred to as CSA-AKI (Cardiac Surgery Associated Acute Kidney Injury). Therefore, it is desirable to estimate the AKI risk of patients undergoing extracorporeal circulation surgery as accurately as possible during the surgery itself, so that the AKI risk can be monitored and modified (in particular by modifying one or more parameters on which the AKI risk depends) using appropriate strategies.

[0019] As already mentioned, the method according to the invention is used to monitor the patient's parameters during extracorporeal circulation surgery to estimate the presence of AKI risk. More specifically, the method according to the invention is used to display on a screen the numerical value and / or time trend of at least one index of the presence of AKI risk in a patient during extracorporeal circulation, the index being a global dynamic index of the presence of AKI risk. For example, the method can be performed by a monitoring device comprising a screen, an electronic computer and an electronic computer program, wherein the electronic computer can be connected to one or more sensors for receiving the patient's parameters, and wherein the electronic computer program is suitable for performing the method according to the invention when executed by the electronic computer.

[0020] Non-restrictive reference Figure 1 , the method generally comprises the following steps: A. Before starting extracorporeal circulation, receiving 100 first parameters related to the patient from a device and / or apparatus; B. calculating 200 a first index SR derived from the first parameter received in step A, the first index SR being a static index of the presence of AKI risk; C. Receiving 300 at least three second parameters T related to the patient from the device and / or apparatus during extracorporeal circulation CPB ,DO2,T DO2 , wherein the at least three second parameters are extracorporeal circulation time T CPB , the minimum oxygen supply level DO2 and the time T of exposure to oxygen supply below the critical threshold (less than the critical threshold) DO2, and wherein the at least three second parameters are received and updated during extracorporeal circulation; D. Calculate at least three secondary indices of AKI risk T during CPB CPB , AKIriskDO2 and AKIriskT DO2 , at least three secondary indexes AKIriskT CPB , AKIriskDO2 and AKIriskT DO2 Each of the at least three second parameters T received in step C is respectively CPB ,DO2,T DO2 At least one of the three secondary indices derived from AKIriskT CPB , AKIriskDO2 and AKIriskT DO2 Each of them is referred to three second parameters T CPB ,DO2,T DO2 A dynamic index of AKI risk. E. calculating 500 a third index PRR during extracorporeal circulation by means of logistic regression derived from at least three second indices calculated in step D, wherein the third index PRR is a dynamic index of the presence of AKI risk involving all second indices calculated in step D; F. calculating 600 a fourth index MDPI during extracorporeal circulation by means of logistic regression derived from the first index SR and the third index PRR, wherein the fourth index MDPI is a global dynamic index of the presence of AKI risk; G. The numerical value 710 and / or the time trend 720 of the fourth index MDPI during extracorporeal circulation are displayed 700 on the screen.

[0021] It should be noted that, in step G, the time trend displayed on the screen is advantageously a graphical display (for example by means of a line graph) of the variation of the fourth index MDPI over time.

[0022] As described in Figure 7As will be better understood when, according to this example, the received second parameters and the calculated second indices are advantageously greater than three in number; more precisely, they are seven parameters and seven indices, respectively, from which the calculation of a third dynamic index PRR of the presence of AKI risk involving all seven calculated second indices is derived. However, the method according to the invention can be implemented by receiving at least three second parameters and therefore at least three second indices, each second index being derived from at least one of the three previously received second parameters. Reference will be made below to two non-limiting examples of implementation of the method: a first example in which only three second parameters are received and a second example in which, in particular more advantageously, seven second parameters (with greater sensitivity) are received.

[0023] The minimum three second parameters that must be received are: Extracorporeal circulation time T CPB , which is the time the patient is on extracorporeal circulation; minimum oxygen supply level DO2, or in particular the oxygen level supplied to a patient with the aid of a heart-lung machine, which is the lowest level; Time T of exposure to oxygen supply below the critical threshold DO2 , ie the time during which a patient, in particular with the aid of a heart-lung machine, is subjected to a critical level of oxygen supply (wherein, in particular, critical is due to a low oxygen supply, ie an oxygen supply below a critical threshold).

[0024] As mentioned, the calculation of the fourth index (MDPI = Multifactorial Dynamic Perfusion Index) is derived from the first index (SR = Static Risk) and the third index (PRR = Perfusion-Related Risk), which are the static and dynamic indices of the presence of AKI risk, respectively.

[0025] Before starting the extracorporeal circulation, a first static index SR is calculated from a first parameter related to the patient. In fact, it is known that for a patient who has to undergo cardiac surgery, a static predictive risk index for renal failure can be calculated based on some parameters of the patient and some parameters of the surgery itself. A previous study determined the so-called Cleveland Clinic Score (=CCS), a clinical score for predicting acute kidney injury (AKI risk) after cardiac surgery, including the influence of its main risk factors, such as the patient's gender, the type of surgery, the possible emergency of the surgery, the baseline creatinine value, the patient's ejection fraction, the presence of chronic obstructive pulmonary disease, the presence of diabetes, the performance of previous cardiac surgery and the use of an aortic counterpulsor. These parameters are usually collected and set by the user (for example with the help of a keyboard or a touch screen) before performing the cardiac surgery, in particular before starting the extracorporeal circulation. The static risk index SR according to the invention is developed starting from the known Cleveland Clinic Score. However, unlike the Cleveland Clinic Score, it does not include the baseline creatinine value in the first parameter, because there is a mathematical connection between the baseline creatinine value and the creatinine value defining the AKI risk. In addition, the static risk index SR calculated according to the present invention also includes the parameter "age" and the parameter "HCT", i.e., the preoperative hematocrit value of the blood (i.e., the percentage of blood volume occupied by red blood cells). Typically, these parameters are also set or received before starting cardiac surgery, in particular, before starting extracorporeal circulation. It should be noted that one or more of the first parameters from which the first index SR is derived can be manually received and / or set by the user, or they can be automatically received and / or set. Typically, these first parameters are received by a device and / or means, in particular a device and / or means of an electronic computer. For example, the device can be a keyboard and / or a mouse and / or a microphone and / or a touch screen (i.e., a component of an electronic computer), and the device can be a storage disk and / or a communication card (i.e., a component of an electronic computer). Advantageously, the screen on which the numerical value and / or time trend of the fourth index MDPI (and possibly also the numerical value and / or time trend of the first index SR and / or the third index PRR, which will be better described below) is displayed is also a component of the electronic computer.

[0026] Advantageously, the first static index SR of the presence of risk of AKI calculated in step B of the method is calculated by the following equation, in particular according to a logistic equation:

[0027] in: CCS is the Cleveland Clinic score. E is the patient's age measured in years [years], HCT is the percentage of blood volume occupied by red blood cells (hematocrit) measured in percent [%). A1 is a value comprised between -0.2 and 0.7, preferably a value comprised between 0 and 0.27, more preferably a value equal to 0.078, A2 is a value comprised between 0.011 and 0.06, preferably a value comprised between 0.015 and 0.055, more preferably a value equal to 0.035, and A3 is a value comprised between -0.17 and 0.015, preferably comprised between -0.14 and -0.05, more preferably equal to -0.095.

[0028] In particular, a first static index SR of the presence of AKI risk can be assumed to have a value between 0 (corresponding to the absence of risk) and 1 (corresponding to a 100% risk). Note that this first index SR does not vary with time, since it does not depend on a quantity that varies with time. Thus, the calculated index SR becomes a constant value. Advantageously, for example, Figure 7 As shown, the method further comprises a step B0 of displaying a numerical value 210 of the index SR and / or a constant stroke 220 (dashed line) on the screen.

[0029] As already mentioned, step C of the method comprises a step D of receiving 300 at least three second parameters and calculating 400 at least three second indices, each second index being derived from at least one of the three second parameters and relating to one of the three second parameters. Figures 2 to 4 According to the first embodiment example, the three second parameters received in step C are the extracorporeal circulation time T CPB , the minimum oxygen supply level DO2 and the time T of exposure to oxygen supply below the critical threshold DO2 For example, these parameters can be automatically calculated with the aid of sensors and / or timers connected to the monitoring device. For each of the second parameters received in step C, a second dynamic risk of the presence of an AKI risk is then calculated in step D. In other words, for each of the second parameters received, the association of the parameter with the AKI risk is studied and verified, and in particular an equation is calculated that determines the relationship between the parameter and the AKI risk. Reference Figure 2 , shows a graphical relationship between the minimum oxygen supply level DO2 and the AKI risk associated therewith, that is, a second oxygen supply related index AKIriskDO2 is graphically shown. Advantageously, the second index AKIriskDO2 is calculated by the following equation:

[0030] - minimum oxygen supply level DO2 within a first predetermined value range (particularly between 0 and 300 [ ], preferably between 0 and 289 [ ]) is:

[0031] in: B3 is a value comprised between 0.25 and 1.09, preferably comprised between 0.35 and 0.98, more preferably equal to 0.67, B4 is a value comprised between -0.005 and -0.0006, preferably comprised between -0.003 and -0.001, more preferably equal to -0.002; - In the second value range (particularly between 289 and 800 [ ]) is a constant, where, in particular, the constant is equal to 0.053 (i.e., the percentage of constant AKI risk present is equal to 5.3%); Among them, DO2 is [ ]Measured quantity.

[0032] Note that in 262 [ ] and 300 [ ] is considered to contain the critical DO2 threshold; preferably, the critical DO2 threshold is 289 [ ].

[0033] It is important to emphasize that DO2 is the lowest oxygen supply level achieved and maintained for at least 5 minutes. In other words, a subsequent decrease in DO2 that lasts less than 5 minutes does not modify the DO2 variable in the formula, and a subsequent increase in DO2 does not modify the DO2 variable in the formula (remember that DO2 is the minimum value).

[0034] refer to Figure 3 , shows the time T of exposure to oxygen supply below the critical threshold DO2 The graphical relationship between the AKI risk and the AKI risk associated therewith, i.e., the second index AKIriskT is graphically shown in relation to the time of exposure to oxygen supply below a critical threshold. DO2 In particular, the critical threshold of oxygen supply is included in 262 [ ] and 300[ ], preferably, the critical threshold is 289 [ ].

[0035] Advantageously, the second index AKIriskT DO2 Calculated by the following equation: - Time T of exposure to oxygen supply below the critical threshold DO2Cubic regression within a first predetermined range of values ​​(specifically between 2 and 360 [minutes]):

[0036] in: B5 is a value comprised between 0.036 and 0.10, preferably comprised between 0.044 and 0.092, more preferably equal to 0.068, B6 is a value comprised between 0.002 and 0.03, preferably comprised between 0.0052 and 0.0261, more preferably equal to 0.016, B7 is a value comprised between -0.0014 and 0.00027, preferably comprised between -0.0012 and 0.000066, more preferably equal to -0.000557, B8 is a value comprised between -0.00000691 and 0.0000153, preferably comprised between -0.00000388 and 0.0000153, more preferably equal to 0.00000183; - is constant within a second predetermined range of values, in particular is constant between 0 and 2 [minutes], in particular the constant value is equal to 0.05 (ie the percentage of constant AKI risk being present is equal to 5%); Among them, T DO2 It is a quantity measured in [minutes].

[0037] refer to Figure 4 , shows the extracorporeal circulation time T CPB The graphical relationship between the AKI risk associated with the extracorporeal circulation time is shown in FIG. CPB .

[0038] Advantageously, the second index AKIriskT CPB The extracorporeal circulation time T is calculated by the following equation: CPB Extracorporeal circulation time T CPB Linear regression over a predetermined range of values ​​(specifically between 30 and 360 [minutes]):

[0039] in: B1 is a value comprised between -0.18 and 0.027, preferably a value comprised between -0.074 and 0.015, more preferably a value equal to -0.029, B2 is a value comprised between 0.0008 and 0.0048, preferably comprised between 0.00092 and 0.00172, more preferably equal to 0.0013; Among them, T CPB It is a quantity measured in [minutes].

[0040] It should be noted that according to T CPB For some values ​​of the second parameter AKIriskT CPB The value of may be less than zero: in this case, or if , zero risk is assumed (i.e., ).

[0041] Advantageously, the method further comprises displaying on the screen at least three second indices AKIriskT calculated in step D CPB 、AKIriskDO2、AKIriskT DO2 The numerical value and / or time trend of one or more of Figure 7 In particular, the time trend refers to the extracorporeal circulation time T CPB , that is, graphically displaying at least three second indices AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 One or more of the CPB Changes of changes.

[0042] The method further provides in step E that a third index PRR is calculated during extracorporeal circulation by means of logistic regression derived from at least three second indices calculated in step D, wherein the third index PRR is a dynamic index of the presence of AKI risk involving all second indices calculated in step D. Advantageously, in this embodiment, in step D the three indices AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 The third index PRR which has been calculated and calculated in step E is calculated by the following equation:

[0043]

[0044] in: C1 is a value comprised between -6.4 and -1.82, preferably comprised between -5.83 and -2.39, more preferably equal to -4.11, C2 is a value comprised between -0.01 and 9.2, preferably comprised between 1.03 and 8.07, more preferably equal to 4.55, C4 is a value comprised between -3.7 and 11.3, preferably a value comprised between -1.88 and 9.48, more preferably a value equal to 3.8, and C6 is a value comprised between -9.3 and 9.8, preferably comprised between -6.94 and 7.5, more preferably equal to 0.28.

[0045] However, as already mentioned and as will be better explained later, in step C several second parameters (in particular 7 second parameters) may advantageously be received and in step D several second indices (in particular 7 second indices) may be calculated.

[0046] Advantageously, e.g. Figure 7 As shown, the method further comprises a step E0 of displaying on the screen the value 510 and / or the time trend 520 (dashed line) of the third index PRR calculated in step E. In particular, the time trend 520 refers to the extracorporeal circulation time T CPB , that is, to graphically display the third index PRR versus extracorporeal circulation time T CPB Changes of changes.

[0047] Finally, the method provides a step F of calculating a fourth index MDPI during extracorporeal circulation by means of a logistic regression derived from the first index SR and the third index PRR, wherein the fourth index MDPI is a global dynamic index of the presence of AKI risk, and a step G of displaying a numerical value 710 and / or a time trend 720 of the fourth index MDPI calculated in step F on a screen during extracorporeal circulation.

[0048] In particular, the fourth index calculated in step F is calculated by the following equation:

[0049] in: D1 is a value comprised between -3.95 and -2.74, preferably comprised between -3.8 and -2.9, more preferably equal to -3.35, D2 is a value comprised between 0.33 and 8.4, preferably comprised between 1.25 and 7.09, more preferably equal to 4.17, D3 is a value comprised between 2.58 and 10.15, preferably comprised between 3.31 and 7.41, more preferably equal to 5.37.

[0050] Finally, without limitation, reference is made to Figure 7 , showing an example of displaying the value 710 and the time trend 720 of the fourth index MDPI on the screen, wherein the time trend refers to the extracorporeal circulation time TCPB , that is, to graphically display the fourth index MDPI as a function of extracorporeal circulation time T CPB Changes of changes.

[0051] Advantageously, the method further comprises a step G0 of comparing a fourth index MDPI with the first index SR and activating signalling means according to the difference between the fourth index MDPI and the first index SR; in particular, the signalling means may be a graphic signalling (e.g. display of an alarm message) and / or an auditory signalling, e.g. reproduction of an alarm sound; in particular, one or more such signallings may occur (e.g. a signalling may occur if MDPI is 50% greater than SR) if the difference between MDPI and SR is greater than a predetermined value (e.g. a configurable predetermined value) or depends on a variable value such as the value SR; in particular, one or more such signallings may occur only if certain conditions persist for at least a predetermined time; in particular, different signallings may be envisaged depending on the severity of the situation.

[0052] As already mentioned, a second non-limiting embodiment example will be described below, in which seven second parameters are received in step C, and seven second indices are calculated in step D, respectively relating to each of the parameters received in step C. Note that steps A, B, F and G of the method do not differ between these embodiment examples. In other words, only steps C, D and E differ between the first embodiment example and the second embodiment example.

[0053] In particular, in addition to the above three parameters (i.e., extracorporeal circulation time T CPB , the minimum oxygen supply level DO2 and the time T of exposure to oxygen supply below the critical threshold DO2 ), in step C, further and advantageously receiving the following items: The minimum value of mean arterial pressure (MAP) measured in [mmHg], where MAP is equal to the extracorporeal circulation time T CPB a minimum value of mean arterial pressure detected during the period, and wherein the detection is automatic; Extracorporeal circulation time T CPB the maximum value of the blood lactate concentration LAC in the blood measured in [mMol / L] during the period, wherein the detection is a manual detection; Extracorporeal circulation time T CPB the minimum hematocrit value HCT detected during the period and measured in [%], wherein the detection is an automatic detection; and Extracorporeal circulation time T CPB Blood transfusion information TRANSF detected during the period, wherein the detection is manual detection.

[0054] Therefore, step D of the method according to this second embodiment also includes calculating the following terms: - A second index, AKIriskMAP, was derived from the mean minimum blood pressure MAP values ​​and calculated by the following equation: In particular, the quadratic regression

[0055] in: B9 is a value comprised between -0.43 and 1.71, preferably a value comprised between -0.17 and 1.45, more preferably a value equal to 0.64, B10 is a value comprised between -0.05 and 0.0188, preferably comprised between -0.042 and 0.0098, more preferably equal to -0.0162, B11 is a value comprised between -0.000152 and 0.00039, preferably comprised between -0.0000871 and 0.000323, more preferably equal to 0.00012; - The second index AKIriskLAC, which is derived from the maximum value of lactate LAC and calculated by the following equation: In particular, linear regression

[0056] in: B12 is a value comprised between -0.1 and 0.32, preferably a value comprised between -0.06 and 0.20, more preferably a value equal to -0.02, B13 is a value comprised between 0.069 and 0.155, preferably a value comprised between 0.08 and 0.145, more preferably a value equal to 0.11; - The second index AKIriskHCT is derived from the minimum hematocrit value HCT and calculated by the following equation: Linear regression of the minimum hematocrit (HCT) within a first predetermined value range (particularly between 10 and 26 [%])

[0057] in: B14 is a value comprised between -0.16 and 1.9, preferably comprised between 0.144 and 1.15, more preferably equal to 0.65, B15 is a value comprised between -0.082 and 0.014, preferably comprised between -0.042 and 0.001, more preferably equal to -0.02; is substantially a constant within a second predetermined range of values ​​(particularly between 26 and 100 [%]), wherein, in particular, the constant is equal to 0.064 (ie the percentage of the risk of AKI being present is equal to 6.4%); - A second index AKIriskTRANSF is derived from the information of the transfusion TRANSF and calculated by the following equation: If the patient did not receive a blood transfusion, it is a constant, specifically, it is equal to 0.082 (i.e. the percentage of AKI risk present is equal to 8.2%); If the patient undergoes a blood transfusion, then it is a constant, specifically, the constant is equal to 0.293 (or the percentage of AKI risk present is equal to 29.3%).

[0058] It is important to note that MAP is the lowest mean blood pressure achieved and maintained for at least 5 minutes. In other words, subsequent decreases in MAP that last less than 5 minutes do not change the MAP variable in the equation, and subsequent increases in MAP do not change the MAP variable in the equation (remember that MAP is the minimum value). Similarly, HCT is the lowest hematocrit value achieved and maintained for at least 5 minutes. In other words, subsequent decreases in HCT that last less than 5 minutes do not change the HCT variable in the equation, and subsequent increases in HTC do not change the HCT variable in the equation (remember that HTC is the minimum value).

[0059] According to this second embodiment, the third index PRR calculated in step E during extracorporeal circulation is further derived from the second indices AKIriskMAP, AKIriskLAC, AKIriskHCT, AKIriskTRANSF and is advantageously calculated by the following equation:

[0060] in: C1 is a value comprised between -6.4 and -1.8, preferably comprised between -5.83 and -2.39, more preferably equal to -4.11, C2 is a value comprised between -0.01 and 9.2, preferably comprised between 1.03 and 8.07, more preferably equal to 4.55, C3 is a value comprised between 0.07 and 8.33, preferably a value comprised between 1.07 and 7.33, more preferably a value equal to 4.2, C4 is a value comprised between -3.7 and 11.3, preferably a value comprised between -1.88 and 9.48, more preferably a value equal to 3.8, C5 is a value comprised between -7.3 and 8.5, preferably a value comprised between -5.3 and 6.46, more preferably a value equal to 0.58, C6 is a value comprised between -9.3 and 9.8, preferably a value comprised between -6.94 and 7.5, more preferably a value equal to 0.28, C7 is a value comprised between -1.15 and 8.44, preferably a value comprised between 0.01 and 7.29, more preferably a value equal to 3.65, C8 is a value comprised between -19.8 and 20.8, preferably comprised between -0.48 and 1.48, more preferably equal to 0.5.

[0061] Note that the equation for calculating the third index PRR reported in the first embodiment is substantially identical to the equation just reported in the second embodiment, wherein the values ​​of AKIriskLAC, AKIriskHCT, AKIriskTRANS and AKIriskMAP are empty, since in step C of the first embodiment example, there are only three parameters T CPB , DO2 and T DO2 is accepted, and therefore there are only three indices AKIriskT CPB , AKIriskDO2 and AKIriskT DO2 is calculated.

[0062] As already mentioned, the method according to the invention has been validated by statistical analyses, in particular by ROC (=Receiver Operating Characteristic) analysis of the fourth index MDPI and advantageously also of the first index SR and of the third index PRR (see e.g. Figure 6 ). In the first embodiment described, that is, only three second parameters T CPB , DO2 and T DO2 In the case where in step C only three second indices are received (and therefore in step D only three second indices are calculated, respectively relating to the three second parameters received), the ROC analysis of the fourth index MDPI yields an Area Under the Curve (=AUC) equal to 0.75. In the second embodiment described, i.e. in the case where in step C seven second parameters are received (and therefore in step D seven second indices are calculated, respectively relating to the seven second parameters received), the ROC analysis of the fourth index MDPI (in Figure 6 ) yielded an area under the curve (=AUC) equal to 0.767.

[0063] As experts in the field know, the closer the AUC is to 1, the better the performance of the model (so the AUC is an indicator of the discriminative ability of the model). Therefore, although the AUC of the first embodiment is already considered a good indicator, the AUC of the second embodiment indicates that the performance of the model is better. It should also be noted that Figure 6 The graph shown also reports the ROC curves for only the first index SR and only the third index PRR; the areas under the curves for both were calculated to be, respectively, 0.696 for the first index SR and 0.723 for the third index PRR. In summary, it can therefore be concluded that the fourth index MDPI integrating the first index SR and the third index PRR has a greater discriminatory power than the individual indices SR and PRR.

[0064] According to another aspect, the subject matter disclosed in this document relates to a monitoring device comprising an electronic computer and an electronic computer program, wherein the electronic computer is adapted to receive as input a parameter value related to a patient, for example at least one extracorporeal circulation time T experienced by the patient. CPB The relevant parameter values, the lowest oxygen supply level DO2 experienced by the patient and the time T that the patient is exposed to an oxygen supply below the critical threshold DO2 , and the electronic computer is suitable for displaying the numerical values ​​and / or time trends of the parameters and / or indices, for example via a computer screen or an equivalent data output device, and wherein the electronic computer program is suitable for performing the described method when executed by the electronic computer using components of the electronic computer (such as a screen and / or keyboard and / or a storage disk).

[0065] Advantageously, the electronic computer may also be adapted to receive the following parameters as input from one or more sensors: The minimum value of mean blood pressure MAP; The maximum value of lactate LAC; Minimum hematocrit value HCT; and Blood transfusion information TRANSF.

[0066] Advantageously, the one or more sensors are electrically connected to the electronic computer so that the electronic computer can receive as input the automatically detected value of the patient's parameter; in other words, the electronic computer receives as input data from the one or more sensors, for example by means of a cable.

[0067] Advantageously, the electronic computer may also be adapted to receive and / or set parameter values ​​manually in the input, for example by means of a keyboard or equivalent data input device.

[0068] The processor may be adapted to be connected to an external memory device for reading and / or writing data, for example for reading and / or writing parameter and / or index values.

[0069] The processor may be adapted to be connected to other electronic computers and / or electronic devices for reading and / or writing data, for example for reading and / or writing parameter values ​​and / or indices.

Claims

1. A method for monitoring parameters of a patient during an extracorporeal circulation surgery to estimate the risk of AKI, the method comprising the following steps: A. before starting extracorporeal circulation, receiving (100) first parameters related to the patient from a device and / or apparatus; B. calculating (200) a first index (SR) derived from the first parameter received in step A, the first index (SR) being a static index of the presence of the AKI risk; C. receiving (300) at least three second parameters (T) related to the patient during extracorporeal circulation from a device and / or apparatus CPB ,DO2,T DO2 ), the at least three second parameters are extracorporeal circulation time (T CPB ), minimum oxygen supply level (DO2), and exposure time to oxygen supply below the critical threshold (T DO2 ), wherein the at least three second parameters are received and updated during extracorporeal circulation; D. Calculate (400) at least three secondary indices (AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 ), the at least three second indices (AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 ) are each respectively selected from the at least three second parameters (T CPB ,DO2,T DO2 ), the at least three second indices (AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 ) are each related to the at least three second parameters (T CPB ,DO2,T DO2 ) is a dynamic index of AKI risk; E. calculating (500) a third index (PRR) during extracorporeal circulation by means of logistic regression derived from the at least three second indices calculated in step D, the third index (PRR) being a dynamic index of the presence of AKI risk involving all second indices calculated in step D; F. calculating (600) a fourth index (MDPI) during extracorporeal circulation by means of logistic regression derived from the first index (SR) and the third index (PRR), the fourth index (MDPI) being a global dynamic index of the presence of the AKI risk; G. Displaying (700) on the screen the value (710) and / or the time trend (720) of the fourth index (MDPI) during extracorporeal circulation.

2. The method according to claim 1, wherein: The first parameters received in step A include the patient's age, the percentage of blood volume occupied by red blood cells (hematocrit), and the Cleveland Clinic score, Wherein, the first index (SR) calculated in step B is calculated by the following equation: ， in: CCS is the Cleveland Clinic score. E is the patient's age, HCT is the percentage of blood volume occupied by red blood cells (hematocrit). A1 is a value comprised between -0.2 and 0.7, preferably a value comprised between 0 and 0.27, more preferably a value equal to 0.078, A2 is a value comprised between 0.011 and 0.06, preferably a value comprised between 0.015 and 0.055, more preferably a value equal to 0.035, A3 is a value comprised between -0.17 and 0.015, preferably a value comprised between -0.14 and -0.05, more preferably a value equal to -0.095; Where E and HCT are quantities measured in [years] and [%] respectively.

3. The method according to claim 1 or 2, wherein: One of the at least three second indices is an index related to the extracorporeal circulation time (AKIriskT CPB ) and is calculated by the following equation: The extracorporeal circulation time (T CPB ) Extracorporeal circulation time (T CPB ) within a predetermined range of values, in particular between 30 and 360 [minutes]: ， in: B1 is a value comprised between -0.18 and 0.027, preferably comprised between -0.074 and 0.015, more preferably equal to -0.029, B2 is a value comprised between 0.0008 and 0.0048, preferably comprised between 0.00092 and 0.00172, more preferably equal to 0.0013; Among them, T CPB is a quantity measured in [minutes]; And among them, if ,So .

4. The method according to claim 1, 2 or 3, wherein: One of the at least three second indices is an index related to the minimum oxygen supply level (AKIriskDO2) and is calculated by the following equation: - oxygen supply (DO2) is within a first predetermined value range, in particular between 0 and 289 [mL / min / m 2 ]: ， in: B3 is a value comprised between 0.25 and 1.09, preferably comprised between 0.35 and 0.98, more preferably equal to 0.67, B4 is a value comprised between -0.005 and -0.0006, preferably comprised between -0.003 and -0.001, more preferably equal to -0.002; - is constant in the second range of values, in particular in the range of 289 to 800 [mL / min / m 2 ] is a constant, in particular, the constant is equal to 0.053; Where DO2 is expressed in [mL / min / m 2 ]Measured quantity.

5. The method according to claim 1 or 2 or 3 or 4, wherein: One of the at least three second indices is an index related to the time of exposure to an oxygen supply below a critical threshold (AKIriskT DO2 ) and is calculated by the following equation: - Time of exposure to oxygen supply below the critical threshold (T DO2 ) is a cubic regression within a first predetermined range of values, in particular between 2 and 360 [minutes]: ， in: B5 is a value comprised between 0.0036 and 0.1, preferably comprised between 0.044 and 0.092, more preferably equal to 0.068, B6 is a value comprised between 0.0002 and 0.03, preferably comprised between 0.0052 and 0.0261, more preferably equal to 0.016, B7 is a value comprised between -0.0014 and 0.00027, preferably a value comprised between -0.0012 and 0.000066, more preferably a value equal to -0.000557, B8 is a value comprised between -0.00000691 and 0.0000183, preferably comprised between -0.00000388 and 0.0000153, more preferably equal to 0.00000573; - is constant within a second predetermined range of values, in particular is constant between 0 and 2 [minutes], in particular said constant is equal to 0.05; Among them, T DO2 is a quantity measured in [minutes], Wherein, the critical threshold is included in 262 to 300 [mL / min / m 2 ], in particular, the critical threshold is equal to 289 [mL / min / m 2 ].

6. A method according to any one of the preceding claims, wherein: Step C also includes receiving a minimum value of mean arterial pressure (MAP), the value being equal to the minimum value of mean arterial pressure (MAP) during the extracorporeal circulation time (T CPB ), wherein the detection of mean arterial pressure is automatic, And wherein the calculation step D further comprises calculating a second index (AKIriskMAP) derived from the minimum value of mean arterial pressure, the second index being calculated by the following equation: Especially the quadratic regression ， in: B9 is a value comprised between -0.43 and 1.471, preferably a value comprised between -0.17 and 1.45, more preferably a value equal to 0.64, B10 is a value comprised between -0.05 and 0.018, preferably comprised between -0.042 and 0.0098, more preferably equal to -0.0162, B11 is a value comprised between -0.000152 and 0.00039, preferably comprised between -0.0000871 and 0.000323, more preferably equal to 0.00012; Where MAP is the quantity measured in [mmHg]; Therein, in step E, the third index (PRR) is calculated during extracorporeal circulation by means of logistic regression also derived from the second index.

7. A method according to any one of the preceding claims, wherein: Step C also includes receiving the extracorporeal circulation time (T CPB ) during the period of time when the blood lactate concentration (LAC) is detected manually, And wherein the calculation step D further comprises calculating a second index (AKIriskLAC) derived from the maximum value of lactate concentration, the second index being calculated by the following equation: Especially linear regression ， in: B12 is a value comprised between -0.1 and 0.032, preferably comprised between -0.06 and 0.20, more preferably equal to -0.02, B13 is a value comprised between 0.069 and 0.155, preferably a value comprised between 0.08 and 0.145, more preferably a value equal to 0.11; Wherein, LAC is the amount measured in [mMol / L]; Therein, in step E, the third index (PRR) is calculated during extracorporeal circulation by means of logistic regression also derived from the second index.

8. A method according to any one of the preceding claims, wherein: Step C also includes receiving the extracorporeal circulation time (T CPB ) during the test, the test is an automatic test, And wherein the calculation step D further comprises calculating a second index (AKIriskHCT) derived from the minimum value of the hematocrit, the second index being calculated by the following equation: - Linear regression within a first predetermined value range of hematocrit (HCT), in particular between 10 and 26 [%] ， in: B14 is a value comprised between 0.16 and 1.9, preferably a value comprised between 0.144 and 1.15, more preferably a value equal to 0.65, B15 is a value comprised between -0.082 and 0.014, preferably comprised between -0.042 and 0.001, more preferably equal to -0.02; - is substantially constant within a second predetermined range of values, in particular is constant between 26 and 100 [%], in particular said constant is equal to 0.064; Wherein, HCT is the amount measured in [%]; Therein, in step E, the third index (PRR) is calculated during extracorporeal circulation by means of logistic regression also derived from the second index.

9. A method according to any one of the preceding claims, wherein: Step C also includes receiving the extracorporeal circulation time (T CPB ) during which the transfusion was detected (TRANSF), the detection being manual, And wherein the calculation step D further comprises calculating a second index (AKIriskTRANSF) derived from the transfusion information, wherein the second index is calculated by the following scheme: if the patient has not received a blood transfusion, a constant, in particular the constant is equal to 0.082; if the patient has undergone a blood transfusion, a constant, in particular said constant is equal to 0.293; Therein, in step E, the third index (PRR) is calculated during extracorporeal circulation by means of logistic regression also derived from the second index.

10. The method according to claims 6, 7, 8 and 9, wherein: The third index PRR calculated in step E is calculated by the following equation: ， in: C1 is a value comprised between -6.4 and -1.8, preferably comprised between -5.83 and -2.39, more preferably equal to -4.11, C2 is a value comprised between -0.01 and 9.2, preferably comprised between 1.03 and 8.07, more preferably equal to 4.55, C3 is a value comprised between 0.07 and 8.32, preferably comprised between 1.07 and 7.33, more preferably equal to 4.2, C4 is a value comprised between -3.7 and 11.3, preferably a value comprised between -1.88 and 9.48, more preferably a value equal to 3.8, C5 is a value comprised between -7.3 and 8.5, preferably a value comprised between -5.3 and 6.46, more preferably a value equal to 0.58, C6 is a value comprised between -9.3 and 9.8, preferably a value comprised between -6.94 and 7.5, more preferably a value equal to 0.28, C7 is a value comprised between -1.15 and 8.44, preferably a value comprised between 0.01 and 7.29, more preferably a value equal to 3.65, C8 is a value comprised between -19.8 and 20.8, preferably comprised between -0.48 and 1.48, more preferably equal to 0.

5.

11. A method according to any one of the preceding claims, wherein: The fourth index (MDPI) calculated in step F is calculated by the following equation: ， in: D1 is a value comprised between -3.95 and -2.74, preferably comprised between -3.8 and -2.9, more preferably equal to -3.35, D2 is a value comprised between 0.33 and 8.4, preferably comprised between 1.25 and 7.09, more preferably equal to 4.17, D3 is a value comprised between 2.58 and 10.15, preferably comprised between 3.31 and 7.41, more preferably equal to 5.

37.

12. The method according to any one of the preceding claims, further comprising the steps of: B0. Displaying the first index (SR) on a screen numerically (210) and / or graphically (220).

13. The method according to any one of the preceding claims, further comprising the steps of: D0. Displaying the at least three second indexes (AKIriskT CPB 、AKIriskDO2、AKIriskT DO2 ) in terms of the numerical value and / or time trend of one or more of the following.

14. The method according to any one of the preceding claims, further comprising the steps of: E0. Displaying the value (510) and / or the time trend (520) of the third index (PRR) on the screen.

15. The method according to any one of the preceding claims, further comprising the steps of: G0. Comparing the fourth index (MDPI) with the first index (SR), and activating the signal transmission means according to the difference between the fourth index (MDPI) and the first index (SR); Wherein, the signal transmission means is suitable for providing graphic signals and / or sound signals.

16. A monitoring device comprising an electronic computer and an electronic computer program, wherein: The electronic computer is adapted to receive as input the values ​​of patient-related parameters, including at least one extracorporeal circulation time (T CPB ), minimum oxygen supply level (DO2), and exposure time to oxygen supply below the critical threshold (T DO2 ), and the electronic computer is suitable for displaying the numerical value and / or time trend of the parameter and / or index, And wherein the electronic computer program is adapted to implement the method according to any one of the preceding claims when executed by the electronic computer using components of the computer.

17. The monitoring device according to claim 16, wherein: The electronic computer can be connected to one or more sensors to receive as input automatically detected values ​​of parameters of the patient.

18. The monitoring device according to claim 16 or 17, wherein: The electronic computer is also adapted to receive manually set or detected parameter values ​​as input.

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