WO2021256960A1

WO2021256960A1 - Method and device for assisting in decision-making when providing cardiological aid

Info

Publication number: WO2021256960A1
Application number: PCT/RU2021/000104
Authority: WO
Inventors: Виталий Германович ПОЛОСИН
Original assignee: Виталий Германович ПОЛОСИН
Priority date: 2020-06-15
Filing date: 2021-03-15
Publication date: 2021-12-23
Also published as: RU2737860C1

Abstract

The invention relates to medicine, specifically to a method and a device for assisting in decision-making when selecting a method for providing emergency cardiological aid. On the basis of readings of an electrical cardiac signal (ECS), with a duration of at least three successive cardiac cycles, the following distribution features are determined: the standard deviation, the entropy rate K _э, the asymmetry coefficient As and the antikurtosis coefficient k for establishing the presence of a hemodynamically significant arrhythmia and issuing a recommendation for selecting a strategy for providing emergency cardiological aid when performing cardiovascular resuscitation: preparation of a patient for immediate revascularization – medical and surgical intervention aimed at eliminating a deficit in blood supply – or performance of defibrillation so as to shock the heart and restore normal cardiac rhythm for several minutes. In the absence of a hemodynamically significant arrhythmia, the method makes it possible to establish the presence of an independent symptom of a pathological cardiac state.

Description

METHOD AND DEVICE FOR SUPPORTING DECISION MAKING WHEN PROVIDING CARDIAC AID

The alleged invention relates to medicine, in particular to cardiology, and can be used to make decisions when choosing a method for providing emergency cardiac care, determining the presence of diseases from the category of sudden cardiac death (SCD) and obtaining an independent symptom of the presence of pathology.

Sudden cardiac arrest is one of the leading causes of death worldwide. Registration of an electrocardiogram during the first 4 minutes of sudden death in 95% of cases indicates the presence of arrhythmia of ventricular fibrillation [1]. With sudden cardiac arrest, a life-threatening cessation of normal heart rhythm and the development of arrhythmias - ventricular fibrillation or ventricular tachycardia - characteristic of severe ventricular disorders, in which there is no spontaneous circulation, occurs. In case of severe ventricular disturbances, detected by frequent, asynchronous contractions of the heart muscle, emergency defibrillation of the heart is performed.

There is a method for diagnosing the stages of ventricular fibrillation [2], which consists in registering an electrocardiogram and determining in segments of an electrocardiogram 1 with spectral power by the fast Fourier transform method, which allows to determine the spectral power of the theta rhythm with a frequency of 4-7 Hz, alpha rhythm - 8 -12 Hz, beta rhythm - 13-17 Hz and gamma rhythm - 18-40 Hz, if the gamma rhythm follows the 2nd ... 4th place in terms of power in 5 consecutive segments of the electrocardiogram, then determine stages of ventricular fibrillation by the specific gravity of theta, alpha, beta and gamma rhythms as a percentage of the sum of the power of these rhythms. Despite the fact that the method allows you to identify the stages of alpha, beta, theta fibrillations or diagnose the absence of ventricular fibrillation, the result of using the algorithm depends on the noise level of the signal. In the considered method, there is also no assessment of the reliability of the adoption of the statement "ventricular fibrillation" required for defibrillation, and there is no possibility of establishing the state of "severe ventricular disturbance", including various rhythms of ventricular tachycardia.

There is a known method and device for assessing the reliability of the recommendation regarding the discharge during cardiopulmonary resuscitation [3], which includes a defibrillator with the ability to supply a high-voltage pulse to the heart to restore a normal rhythm, the circuit of the main unit of which is made with the possibility of segment analysis ECG and reliability analysis scheme, designed with the ability to analyze the pacemaker segment and the previous segment to determine the reliability of the discharge decision.

According to the author of the present invention, the disadvantages of the known methods for diagnosing severe ventricular disorders - a method for diagnosing the stages of ventricular fibrillation and a method for assessing the reliability of recommendations regarding a discharge in cardiopulmonary resuscitation - are:

- in the absence of an assessment of the likelihood of accepting a statement about the state of severe ventricular disorders, which determines the reliability of recommendations for defibrillation;

- in the absence of recommendations for myocardial revascularization;

- in the absence of the possibility of establishing an independent symptom about the presence of a pathological condition of the heart;

- in the absence of an analysis of the chaotic properties of the pacemaker when determining the shock states of the cardiovascular system;

- in reducing the reliability of the decision taken (in particular, recommendations for defibrillation) in the provision of emergency cardiac care, caused by distortion of the pacemaker during preliminary processing due to the overlap of the continuous spectrum of chaotic components of the pacemaker and the frequency range of noise and artifact filtering devices.

The closest in terms of the achieved result is the method of providing emergency cardiac care [4], which consists in the fact that the pacemaker is recorded, the pacemaker is analyzed, the standard deviation of the mean values of the cardiac cycle (SDANN), the ratio of low and high frequency waves (LF / HF ) variability of QT intervals, ejection fraction (EF) during the day and the distance between adjacent R waves on the ECG to assess hemodynamically significant arrhythmia, to determine the presence of ventricular tachycardia and to calculate the prognosis of the severity of arrhythmic syndrome. In the presence of prolongation of the QT interval, determined by the true result of the inequality assessment

-QT> 0, where the coefficient k is taken equal to 0.37, 0.39 and 0.38 for men, women and children, respectively, and the values of the EF assessment are given recommendations for defibrillation or cardiac revascularization. In the absence of an extended QT interval, the coefficient for predicting the severity of arrhythmic syndrome is determined by the expression:

K = -4.518 + 0.02-Ф5 + 0.03T-SDANN + 0.049- LF / HF -Q, 0 \ 9varQT If the K coefficient is> 0.25, a severe arrhythmic syndrome is predicted and a recommendation for revascularization is made.

The disadvantages of this method should be noted:

- the inability to determine hemodynamically significant arrhythmias without preliminary processing of the pacemaker in order to assess the ejection fraction by detecting, isolating and analyzing the pacemaker teeth, carried out to determine the time intervals of the pacemaker, on the accuracy of which the diagnostic result depends;

- inability to determine the state of severe ventricular disorders, in which arrhythmias of ventricular fibrillation, ventricular flutter and, in particular, ventricular tachycardia are observed;

- the lack of the possibility of obtaining recommendations for the provision of emergency cardiac care by assessing the difference in time intervals determined on the basis of individual taken parameters of the QRS complex;

- the absence of an algorithm for determining the likelihood of an unlawful determination of a symptom of heart pathology and an unlawful determination of the presence of severe ventricular disorders directly from the characteristics of the distributions of the pacemaker counts.

Brief Description of Drawings

Figure 1 shows a diagram of a process that implements a known method of providing emergency cardiac care.

Figure 2 shows examples of electrocardiographic recordings of signals for heart rhythms in severe ventricular disturbances,

Figure 3 shows diagrams of the entropy-parametric space, illustrating the detection of the presence of a disease in the space of the coefficient of entropy, asymmetry and counter-excess.

Figure 4 shows a diagram of the process that implements the proposed method of decision support in the provision of emergency cardiac care. Figure 5 shows a diagram of the formation of the coordinate space of the entropy-parametric signs of the distribution of ECS counts for a real state. Figure 6 shows a scheme for determining the reliability of establishing the pacemaker for the state with "TZHN".

Figure 7 shows a diagram of a process for predicting a pathological condition.

Figure 8 shows a diagram for determining the reliability of an independent symptom of a pathological condition.

Figure 9 shows the graphs of the pacemaker with ventricular flutter, where it is indicated Figure 10 shows the graphs of the pacemaker with ventricular tachycardia,

Figure 11 shows a feature table for base-constrained distributions.

The figure 12 shows the graphs of the pacemaker with ventricular fibrillation.

Figure 13 shows the display of the area of states of the cardiovascular system and the area of the state with "TZHN" in the space of the coefficient of entropy and counterexcess to establish the parameter of the reliability of the pacemaker.

Figure 14 shows a block diagram of a mobile decision support device in the provision of emergency cardiac care

Detailed description of the invention

The material of the detailed description explains the embodiments of the invention with reference to the drawings, where like reference numbers represent the same or similar elements.

Cardiopulmonary resuscitation is used as a treatment protocol for VOS, according to which blood circulation in the cardiovascular system and ventilation of the lungs are ensured by compensating for the chest. VF treatment is provided by defibrillation with an electrical impulse. The likelihood of restoring spontaneous circulation during defibrillation increases with a decrease in the time between the last cardiopulmonary compensation and the delivery of a defibrillating shock.

Figure 1 is an illustration of a flow diagram of an implementation process for a prior art method of providing emergency cardiac care. As illustrated in Figure 1, information processing begins with a step 105 of registering an electrocardiosignal (ECS), including pre-amplification, digitization and recording of the ECS into a database. Next, there is a preliminary analysis of the electrocardiosignal at step 110, including filtering from interference and determining the distance between adjacent R waves to determine the duration of the ECS cycle, determining the standard deviation of the mean values of the cardiac cycle. If a hemodynamically significant arrhythmia (VTA) is detected at step 115, ventricular tachycardia (VT) is determined at step 120. If VT is detected, a recommendation for defibrillation is given at step 125. If VT or HCA is not found, then severe arrhythmia is predicted at step 130, followed by a recommendation for cardiac revascularization at step 135. Next, the standard stages of the emergency cardiac care process are performed: stage 140 of making a preliminary diagnosis and stage 145 of generating a report on the patient's condition. Defibrillation to restore the normal rhythm and contractile function of the heart is carried out in case of circulatory disorders as a result of the establishment of a rhythm, such as ventricular fibrillation (VF), ventricular flutter (VF) or ventricular tachycardia (VT), which are established in severe ventricular disturbances [ 7]. Defibrillation is not performed in the presence of sinus rhythm or in cases of a number of arrhythmias, such as supraventricular tachycardia, premature ventricular contraction, atrial fibrillation, etc., in which spontaneous circulation is possible [8].

The rhythms of the heart in severe ventricular disturbances include the rhythms illustrated in figure 2.

1) Ventricular fibrillation (VF) (flickering) - the rhythm of the heart in the presence of pathology, as a result of which the ventricles of the heart begin to contract with a huge frequency of 200-300 beats per minute in a chaotic manner. The accelerated rhythm of contractions does not allow them to fill with blood, which is why a critical circulatory disturbance occurs corresponding to cardiogenic shock. An example of a rhythm in ventricular fibrillation is given in figure 2. a.

2) Ventricular tachycardia (VT) - the rhythm of the heart in ventricular disorders as a result of serious damage to the heart muscle. The violation can provoke an attack of a rapid heartbeat, which is most likely to develop into ventricular fibrillation. An example of the development of a paroxysm of polymorphic ventricular tachycardia of the Torsade de Pointes type is given in figure 2, b.

3) Ventricular flutter (VF) is a rhythm disturbance similar to fibrillation, in which contractions occur rhythmically and in an orderly manner without an ejection fraction. An example of the rhythm during ventricular flutter is given in figure 2, c.

Cardiac arrest can be canceled if cardiopulmonary resuscitation (CPR) is performed or a defibrillator is used to shock the heart and restore a normal heart rate within a few minutes. To quickly and correctly determine shock rhythms in automatic defibrillators, algorithms are used to detect such severe cardiac arrhythmias as VF and VT, for the construction of which the most widespread methods of detecting ventricular fibrillation in the time domain.

The VF detection method in the time domain provides real-time VF detection based on a complex QRS search by the slope, amplitude and width of the electrocardiosignal (ECS). Such methods are based on the Tompkins algorithm, the autocorrelation function algorithm, and the threshold intervals algorithm [9]. Lack of way The way to assess the reliability of the recommendation regarding the discharge during cardiopulmonary animation in the time domain is that the recommendation is given on the basis of the analysis of the properties of a separate temporal area of the pacemaker. To apply the methods for detecting ventricular fibrillation in the time domain, it is necessary to reliably detect, isolate and analyze individual teeth and pacemaker complexes.

Known methods for detecting ventricular fibrillation (VF) in the frequency domain detect signals with a VF rhythm in their close to sinusoidal form. Normal ECS is a broadband signal with fundamental harmonics up to 25 Hz. With the development of the rhythm of ventricular fibrillation, the pacemaker is concentrated in a narrow frequency band from 3 to 10 Hz. The basic principle of algorithms for detecting ventricular fibrillation (VF) in the frequency domain is to analyze the Fourier spectrum normalized to the first spectral component. To detect VF, Fourier spectrum analysis methods use the sum of amplitudes in different frequency bands [10]. Despite the fact that spectrum analysis methods can reveal the stages of fibrillation [2], the reliability of the result depends on the noise level of the pacemaker and the methods of preliminary filtration. According to [11], for known methods of detecting and diagnosing VF, such as notch filtration, spectral analysis, linear analysis of the autocorrelation function, algorithm of suprathreshold integrals, the sensitivity does not exceed 79% with a specificity of 95%.

According to the author of the alleged invention, the disadvantages of the known algorithms for detecting VF and VT in the frequency and time domain are that the ECS has chaotic properties and a continuous spectrum, which does not allow filtering the signal without losing information due to signal distortion in the frequency and time domain. ... Among the disadvantages of the known methods for detecting severe ventricular disorders, it should also be noted that there is no assessment of the reliability of decision-making, obtained directly from the readings of the studied pacemaker.

Most modern devices for automatic external defibrillation are limited only to recording the signal from surface electrocardiography and diagnostics of the baseline heart rate [3]. The presence of a chaotic component of heart contraction imposes a limitation on filtration and subsequent diagnosis of the basic pacemaker rhythm. Since no known method of filtering the electrocardiogram is perfect, the analyzed signal contains residual artifacts that can potentially lead to incorrect determination of the baseline rhythm by the algorithm used to recommend a shock for an automatic external defibrillator. If the heart rate is unstable during asystole, imperfect filtering may cause the algorithm to erroneously recommend pacing. discharge, since the residual filtration will be analyzed as ventricular fibrillation [3]. On the other hand, the filtering technique may mistakenly filter out some of the ventricular fibrillation information and make the rhythm for the shock recommendation algorithm as a rhythm at which shock stimulation will not induce a recovery effect, or as a rhythm in which shock stimulation is not recommended. Thus, the existing methods for analyzing the pacemaker do not allow to obtain an acceptable pacemaker, on the basis of which it is possible to make a fairly reliable decision on the conduction of cardiac stimulation with an electric discharge. [9]

Despite the fact that recently new methods have been developed based on the analysis of the complexity of the signal dynamics, for example, the plexity measure algorithm [9], it is urgent to develop new methods for detecting severe ventricular disorders based on the analysis of chaotic properties. ECS in determining shock conditions of the cardiovascular system. Qualitatively new opportunities for determining the state of the heart and identifying pathologies directly from the ECS readings contains an entropy-parametric approach based on combining the methods of probabilistic and informational analysis due to the synergetic combination of Euclid's measure and Shannon's measure [12].

The aim of the proposed invention is to expand the functional capabilities of assessing the state of the heart based on the entropy-parametric analysis of the pacemaker for making a decision on taking measures for defibrillation of the heart or preparing the patient for immediate myocardial revascularization when shock rhythms are detected. In the absence of hemodynamically significant arrhythmias, the method of decision support based on the analysis of the entropy-parametric criterion formed in the space of the entropy coefficient, counterexcess and asymmetry, makes it possible to establish the presence of an independent symptom of a pathological heart condition.

To do this, in a way to support decision-making in the provision of emergency cardiological care, including registration, analysis of the electrocardiosignal (ECS), determination of the standard deviation parameter of mean values of cardiac cycles, determination of ventricular tachycardia and extrasystole for at least three consecutive cardiac cycles, defibrillation in the case of hemodynamically significant arrhythmias, predicting severe arrhythmic syndrome and performing revascularization in the absence of ventricular tachycardia; making a preliminary diagnosis and generating a report on the patient's heart condition; characterized in that the space of coordinates of entropy-parametric signs of the distribution of ECS readings for a real state is additionally formed by

- determination of the central moments of the distribution of samples of the ECS time interval, calculated by the formula:

where / V is the number of counts of the ECS time interval; t is the number of grouping intervals; ri _j is the number of samples in the; -th grouping interval; y, is the average value of the ECS counts in the j-th grouping interval; s - order of distribution moment, s = 2, 3, 4, ...; M is the mathematical expectation of the pacemaker for the investigated time interval

- determination of the informational sign of the distribution of samples of the ECS time interval

where Ау is the width of the intervals for grouping ECS samples;

- determination of the coefficient of entropy K asymmetry As and counter-excess k for the distribution of the time interval of the electrocardiosignal (ECS) with a duration equal to at least three consecutive cardiocycles, according to the formulas:

where s is the standard deviation of the ECS time interval counts (a parametric sign of the ECS counting uncertainty);

- determination of the scatter of the signs of the distribution of the pacemaker counts for the real state of the patient H _\ ,

where S _\ , Si, Si - spreads of the coefficient of entropy, counter-acceleration and asymmetry, respectively; determination of a parametric criterion for the occurrence of hemodynamically significant arrhythmia (HAA) by assessing the truth of the inequality of the difference in the asymmetry modulus As of the distribution of readings of the time interval of the electrocardiosignal and its minimum critical value -y _kRit

| L $ | - L £ _CRIT <0, (6) and if expression (6) is true, determining the reliability of the statement about the establishment of the rhythm of the electrocardiosignal for a state with severe ventricular disorders by

- the formation of the boundaries of the area of the state "severe ventricular disorders (VVD)", specified using the matrix of expressions:

where k _etax , As _max , k _max , ^ _min , ^ _{тт Kmin} , are the maximum and minimum values of the coefficient of entropy, asymmetry and counterexcess for the pacemaker counts with severe ventricular disorders;

- determination of the probability Rtzhn of the appearance of an error as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiac signal of a pathological state with severe ventricular disturbances according to the formula:

where Фо (х) is the Laplace function; determining the reliability criterion of the statement “the rhythm of the electrocardiosignal corresponds to a pathological state with severe ventricular disturbances” on the basis of comparing the probability of Rtzh of the appearance of an error as a result of the adoption of an incorrect statement “the rhythm of the pacemaker corresponds to a pathological state with severe ventricular disturbances and critical probability b _krHT

Rtzhn <b _MT ; (9) and the implementation of measures for the provision of emergency cardiac care in the event that the probability of Rtzh of the appearance of an error as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiosignal of a pathological state with severe ventricular disorders is less than a critical value equal to 20%, which corresponds to a reliable determination of the rhythm EKS in the presence of severe ventricular disorders, heart defibrillation is performed; if the probability bt> k _{H of the} appearance of an error in as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiosignal of a pathological condition with severe ventricular disturbances of a more critical value equal to 20%, which corresponds to an unreliable determination of the pacemaker rhythm with severe ventricular disturbances, arrhythmic heart syndrome and revascularization are predicted if expression (6) is false, the possibility of a pathological condition is predicted by

- determination of the entropy-parametric criterion for the rhythm of the electrocardiogram signal of the optimal state of the patient's heart according to the expression:

where K _e0 , Aso, co-coefficient of entropy, asymmetry and counter-excess for the rhythm of the electrocardiosignal of the optimal state of the heart; a, b and c - parameters of the border of the zone of optimal heart conditions;

- comparison of the criterion r and its critical value at the level of significance a using the expression: r <r _a , (11) where a is the level of significance of the decision to reject the statement “the rhythm of the electrocardiosignal of the optimal state” a (r) = 1 + 2 [g-cf (g) -F ₀ (g)]; (12)

- if expressions (11) (r <r _a ) are true, informing the “heart rhythm of the optimal state”, and if expression (11) (r <r _a ) is false, the prediction of the pathological state for this purpose is additionally determined the reliability of an independent symptom of a pathological condition by

- determination of the parameters of the boundary of the decision-making area “rhythm of the electrocardiosignal of the optimal state” in the space of signs of the distribution of readings for the rhythm of the electrocardiosignal of the real state:

- determination of the coordinates of the rhythm of the electrocardiosignal of the optimal state in the space of indications of the distributions of readings for the rhythm of the electrocardiosignal of the patient's real state: hoi 02

- the formation of the boundaries of the decision-making area "the rhythm of the electrocardiosignal of the optimal state" in the space of signs of the distributions of readings for the rhythm of the electrocardiosignal of the real state

Arnax3 ⁼ A03 ⁺ ^ 3 ^r a 'Amt3 ^~ LOZ ^{_ A} 3 ^r <x>

- determination of the probability bo of committing an error as a result of accepting an incorrect statement “the rhythm of the electrocardiosignal of the optimal state” by calculating the expression:

- comparison of the probability bo of the appearance of an error as a result of the adoption of an incorrect statement "the state is optimal" and its critical value b _krHT (equal to 20%), bq> b crit _? (17)

- if expression (17) is true, which characterizes the pacemaker in the presence of pathological deviations, establishing the presence of a symptom of cardiac pathology,

- if expression (17) is false, which characterizes the pacemaker in the absence of pathological deviations, informing about the possible development of a pathological state.

2. Decision support device in the provision of emergency cardiac care, containing:

- the unit for registration and preliminary analysis of the ECS (block 1405), made with the possibility of amplifying the signals of the ECS leads, monitoring the separation of wires, analog digital transformation of signals, filtering of interference, independent recording of digitized information into the database, preliminary analysis of ex, determination of the standard deviation of the mean value of the cardiocycle;

- a block for the formation of entropy-parametric signs of a sampling of an electrocardiosignal of a real state (block 1410), made with the possibility of selecting ^ a sample of data from cardiocycles, determining the central moments of the pacemaker, determining the informational sign of the pacemaker, determining the entropy-parametric signs - the coefficient entropy, asymmetry and counter-excess - for the distribution of counts of the time interval of the pacemaker, determination of the scatter of signs of distribution of counts of the pacemaker for the real state;

- a block for determining the criterion of hemodynamically significant arrhythmia (block 1415), configured to assess the truth of the inequality of the difference in the modulus of the asymmetry feature of the distribution of the ECS time interval counts and its minimum critical value, and the ability to switch the sequence of information processing in the event of hemodynamically significant arrhythmia;

- a unit for determining the reliability of establishing the rhythm of the pacemaker of a state with severe ventricular disturbances (VVD) (block 1420), made with the possibility of forming the boundaries of the region of the state of VVD, calculating the probability of an error as a result of making an incorrect statement about establishing the rhythm of a pathological state with severe ventricular disturbances; determining the reliability criterion of the statement about the pathological state of “TZHN” by comparing it with its critical value, and the possibility of connecting the means of informing about the need for defibrillation or revascularization (during revascularization, information is limited to the formation of a preliminary diagnosis and report);

- a unit for informing about the need for defibrillation (block 1425), with the possibility of presenting audio and visual information about the need for defibrillation and the ability to connect defibrillator controls;

- a block for predicting a pathological state (block 1430), configured to determine the entropy-parametric criterion for the pacemaker optimal state; comparison of the entropy-parametric criterion and its critical value at a given level of significance a; informing about the optimal heart rhythm if the entropy-parametric criterion is less than its critical value, and predicting the possibility of a pathological state if the entropy-parametric criterion is equal to or greater than its critical values by determining the parameters of the boundary of the decision-making area “pacemaker of the optimal state” and the coordinates of the rhythm of the optimal state in the space of signs of distribution of the pacemaker counts of the real state, forming the boundaries of the decision-making area of the rhythm of the electrocardiosignal of the real state; determining the probability of error as a result of making an incorrect statement “ECG rhythm of the optimal state”; comparing the probability of an error as a result of accepting an incorrect statement “pacemaker optimal state” and its critical value for establishing the presence of an independent symptom of a pathological condition of the heart;

- block for the formation of a preliminary diagnosis (block 1435);

- block for generating a report (block 1440).

The introduced actions with their connections show new properties, expand the functional capabilities of the known method and make it possible to obtain an independent symptom of the presence of cardiac pathology. Expansion of functionality in the way of decision-making in the provision of emergency cardiac care is provided by:

- displaying the state of the heart in the entropy-parametric space of the signs of the distribution of the electrocardiosignal: the coefficient of entropy, counterexcess and asymmetry;

- establishment of hemodynamically significant arrhythmia (HAA) based on the comparison of asymmetry As of the distribution of readings of the ECS time interval with the minimum critical value of asymmetry As _Kpm ;

- making a decision on defibrillation on the basis of assessing the reliability of the analysis of the distribution shape in the entropy-parametric space by comparing the probability of RTP of the appearance of an error as a result of making an incorrect statement about the pathological state “severe ventricular disturbances” with its critical value;

- establishing an independent symptom of a pathological state based on an assessment of the reliability of a symptom in the entropy-parametric space by comparing the probability bo of making an error as a result of accepting an incorrect statement “the state is optimal” and its critical value.

The essence of the invention is to make judgments about the state of the cardiovascular system based on the assessment of the shape of the distribution of the pacemaker counts of the time interval characteristic of three consecutive cycles of heart contraction.

It is known that the display of the electrocardiosignal in the entropy-parametric space of distribution signs: the entropy coefficient, counterexcess and asymmetry is an effective tool for analyzing the state of the heart system by the form of the distribution of counts [12, 13]. Figure 3 shows a diagram of the distribution of the entropy-parametric space for detecting the presence of a disease in the space of the coefficient of entropy, asymmetry and counterexcess, where 305 is the point of optimal state with a normal sinus rhythm; 310 - the area of the optimal state of the heart (and the cardiovascular system as a whole); 315 - area of possible pathological state of the heart; 320 - area of conditions with severe ventricular disorders; 325 - position of arcsine distributions; 330 - position of signs of distribution of ECG readings for a real state; 335 - surface of critical values of asymmetry. There, 340, 345, and 350 are also designated curves for families of statistical distributions: families of Weibull-Gnedenko distributions; families of bounded gamma distributions (with a shape factor of 0.6) and families of exponential distributions, respectively, from which one can see that the distributions are poorly distinguishable in the space of parametric features of distributions - asymmetry and counter-excess. Histogram 355 illustrates the typical distribution of counts from one cardiocycle. The use of the entropy coefficient makes it possible to unambiguously distinguish between these distributions. Obviously, the three-dimensional space given by the parametric distribution characteristics - counterexcess, asymmetry, and entropy coefficient - can be advantageously used to analyze heart conditions by the form of distribution of ECS counts. In the three-dimensional space of distribution signs, the area of the optimal state 310 and the area of states with rhythms of the pacemaker 320 corresponding to severe ventricular disturbances are spatially separated, which makes it possible to unambiguously identify the rhythms in which defibrillation is required to restore the normal heart rate.

The author of the present invention is convinced that the mapping of distributions in the entropy-parametric space of the signs of the ECS distributions allows one to obtain the most important diagnostic indicators of the state of the heart and the cardiovascular system as a whole, which allow making a decision during emergency cardiac care. To illustrate the features and new possibilities of the decision-making method in the provision of emergency cardiac care, let us consider the characteristic pacemaker rhythms for conditions with severe ventricular disturbances.

Flutter of the ventricles. As an example, let us analyze the violation of the pacemaker rhythm due to ventricular flutter (VF), which is a common case of ventricular tachycardia with a frequency of 200-300 heart beats per minute. Ventricular flutter occurs due to the steady circular motion of autowaves along the perimeter of the myocardial zone with a frequency of 180 to 250 pulses per minute. With ventricular flutter QRS complexes and T waves merge into a single wave of large amplitude. Since these waves arrive regularly, a picture of regular sinusoidal oscillations arises, in which, unlike VT, it is not possible to single out individual elements. In 75% of cases, ventricular demand passes into VF. [7]. An example of an ECG with ventricular flutter is given in figure 2, c, which shows the spontaneous development of ventricular flutter with evolution into a sinusoidal curve and subsequent transition to ventricular fibrillation on the pacemaker recording during Holter monitoring, which recorded the moment of sudden arrhythmic death. Typical examples of pacemakers with ventricular flutter are shown in figure 9. With ventricular flutter, pacemakers have a shape close to harmonic signals. The distribution of counts during ventricular flutter tends to a symmetric shape.

The counts for sinusoidal (harmonic) oscillations are distributed arcsinusoidally with known values of the features: the coefficient of entropy and counter-excess are equal to 1.11 and 0.816, respectively [14]. Since the readings are distributed symmetrically with correct harmonic oscillations, the asymmetry coefficient is zero. The position of states with violation of the pacemaker due to "ventricular flutter" due to the spread of oscillations in amplitude and frequency in the entropy-parametric space of distribution signs corresponds to a certain small area in the vicinity of the point of arcsinusoidal distributions 325 in figure 3, located in the plane specified equal to zero asymmetry. Obviously, the state from the coordinates of point 325 in Figure 3 is diagnosed as a violation of the pacemaker due to severe ventricular disturbances, in which, according to the recommendations [15, 16], defibrillation is required to restore the normal heart rhythm.

A more general example of violation of the pacemaker rhythm is observed in various types of ventricular tachycardia, which are characterized by an accelerated rhythm with a heart rate of more than 100 beats / min. The source of the accelerated rhythm of ventricular tachycardia is located in the legs or branches of the His bundle, in the Purkinje fibers or the working myocardium of the ventricles. Tachycardia is considered stable, in which the duration of paraoxism is equal to or exceeds 30 s [15]. Depending on the number and location of sources of accelerated rhythm, paraxial and polyform ventricular tachycardias are distinguished.

Paroxysmal ventricular tachycardia is a type of arrhythmia characterized by heart attacks (paroxysms) with a heart rate of 140 to 220 or more beats per minute, arising under the influence of ectopic impulses that lead to the replacement of the normal sinus rhythm. The term "ventricular parasystole "refers to a condition in which the heart rate is controlled by two independent drivers. One of them is the main one (most often - the sinus node), the other is parasystolic, located in the ventricles [17, 18, 19]. Examples of pacemaker plots at different rhythms of ventricular tachycardia are given in figure 10. With the development of paraxial tachycardia, the pacemaker is well approximated by superimposing a harmonic signal in figure 10, or by superimposing triangular signals in figure 10.6. The distribution of samples of such a signal has a bimodal symmetric distribution. If the signal is approximated using triangular signals, then the samples of the approximation correspond to a uniform distribution with the known entropy coefficient and counterexcess equal to 1.73 and 0.745, respectively. Since with a uniform distribution the samples are distributed symmetrically with respect to the mathematical expectation, the asymmetry coefficient for the distribution of approximation samples is equal to zero. The deviation from the triangular approximation is approximately 5 ... 10 times less than the amplitude, which causes the deviation of the asymmetry coefficient from zero. The coefficient of asymmetry of the distribution of samples of such signals does not exceed 0.3 ... 0.5, which can be used to limit the area of possible forms of signal asymmetry in ventricular tachycardia. For the distribution of ECS counts of paraxial tachycardia in Figure 10, c is characterized by a bimodular distribution with an asymmetry of less than 0.5, which is determined on the basis of the distribution of counts of the triangular impulse model.

Polymorphic ventricular tachycardia is characterized by progressive (from shock to shock) changes in QRS complexes in configuration, amplitude and direction of the prevailing electrical deviations. The most common polymorphic ventricular tachycardia of the pirouette type - Torsade de Pointes (TdP) - is another name for "bi-directional fusiform" VT, which is one of the most dangerous forms of VT due to severe clinical manifestations (hemodynamic instability) and a high risk of transformation into VF. Figure 2, b gives an example of the development of a paroxysm of polymorphic ventricular tachycardia of the Torsade de Pointes type against the background of physical activity in a patient with Romano-Ward syndrome (a fragment of continuous recording of daily ECG monitoring according to Holter) [16].

Figure 10, d shows typical examples of the pacemaker for the rhythm of polymorphic ventricular tachycardia of the Torsade de Pointes type. The frequency of the rhythm of polymorphic ventricular tachycardia is 150 - 250 oscillations per second with fluctuations in RR intervals within 0.2 ... 0.3 s. A characteristic feature of VT of the Torsade de Pointes type is a change in the amplitude and polarity of wide irregular QRS complexes during a short period of time. short time intervals 1 ... 3 s. Outside an attack of VT of the Torsade de Pointes type, a significant lengthening of the QT interval is recorded on the ECG.

Despite the fact that for such rhythms, when moving a sliding window with a duration of 2 ... 3 s, sections of the pacemaker with different amplitude and direction of QRS complexes are distinguished, the signs of the distribution of counts fluctuate near the signs of a two-module, uniform and triangular distribution with a zero value asymmetry. The distribution of ECS counts between two points of change in the polarity of the QRS complex is formed by summing the counts of bimodal distributions. For the pacemaker rhythm in Figure 10, a separate oscillation corresponds to a limited arcsinusoidal distribution. As shown in [14], the composition of arcsine distributions with different ranges, limited by the amplitude of the ECS oscillations, allows one to obtain a family of two-module peaked distributions bounded at the base. The composition of the distributions of arcsinusoidal distributions is characterized by the limitation in the range and the absence of peakedness. Figure 11 shows a table with the main features of base-limited distributions, such as arcsine, peaked two-module, uniform and triangular distributions, a distribution in the form of an “Old Russian helmet”, Shapo distribution, etc. [14]. A characteristic property of distributions limited at the base consists in a low kurtosis value - a sign of a peaked distribution. The kurtosis e of distributions is bounded from above by a value of 2.5, which corresponds to the lower bound of the counter-kurtosis (k = e ^0.5 ), equal to 0.63. When passing the QRS flip point, the distribution of the ECS sample tends to a symmetric shape and is on a plane with a zero asymmetry value. Thus, in spite of the variety of forms of counting distribution at different rhythms of ventricular tachycardia, the point reflecting the state of the heart in the entropy-parametric space will be located near the surface with zero asymmetry value.

Ventricular fibrillation is the third example of a pacemaker rhythm seen in severe ventricular disturbances. In the state of ventricular fibrillation, continuous uncoordinated excitation occurs, which is supported by random intermittent excitations of individual elements and irregular activation of the myocardium with the appearance of multiple small waves [7]. In this condition, the heart ceases to perform its pumping functions, and the blood supply to the entire body is cut off. On the ECG, ventricular fibrillation is recognized by continuous chaotic sharply deformed oscillations of various heights, widths and shapes, following with a frequency of 400

... 600 vibrations per minute (6 ... 10 Hz) [7]. Frequency of basic fibrillar oscillations in the first 30 - 40 s, more than 300 oscillations. As the duration of ventricular fibrillation increases, the frequency of oscillations decreases. Depending on the amplitude of the oscillations, the following are distinguished: large-wave, medium-wave and small-wave fibrillations with amplitudes of more than 0.7-1, 2 mV, 0.4 ... 0.7 mV and less than 0.3 mV, respectively. Ventricular fibrillation is usually irreversible and requires cardiopulmonary resuscitation and defibrillation. [twenty]

To identify the features of the distribution of the pacemaker counts at different rhythms of ventricular fibrillation, Figure 12 shows examples of typical pacemakers corresponding to large-wave, medium-wave and small-wave fibrillations.

For large-wave fibrillations, illustrated in figure 12, a, a superposition of the distributions of samples from a plurality of chaotic waves, commensurate in amplitude, is characteristic. For individual waves, the sample distribution is well approximated by arcsinusoidal, bimodal and uniform distributions. The composition of such distributions with close distribution centers has a peakedness limitation [14]: the kurtosis of the distributions does not exceed 2.5, the counter-kurtosis is limited in the range from 0.63 to 1.

A feature of medium-wave fibrillations, examples of which are shown in figure 12, b, is that its values fall into a limited number of grouping intervals. When choosing the width of the grouping interval equal to 0, 1 mV, all values are grouped in 4 ... 7 intervals with a close to uniform distribution. For the distribution of samples formed by periodic harmonic and triangular waveforms, the counterexcess is in the range of 0.7 ... 0.8. A decrease in the amplitude during the period of small-wave fibrillation to values less than 0.3 mV determines the distribution of the signal in 1 ... 2 intervals. Such signals are characterized by a low value of the entropy coefficient, at which there are no signs of the object's vital activity. Despite the fact that with a decrease in the width of the grouping interval to 0.01 mm, the distribution concurrency is in the range from 0.6 to 1, the value of the entropy coefficient is more than 1 and the asymmetry does not exceed 0.5, at this level of analysis signal has low reliability due to the presence of noise. The condition of a lethal outcome with a signal amplitude of less than 0.1 mV is established by a medical specialist. Examples of periods of small-wave fibrillation are illustrated in figure 12, c.

Thus, from the considered analysis, it is possible to establish boundaries in the entropy-parametric space to limit the area of states with severe ventricular disorders: entropy coefficient from 0.8 to 2.2; counterexcess from 0.6 to 1; asymmetry modulus from 0 to 0.6. In the presence of a condition with a severe ventricular rhythm, The key element of resuscitation (ie, it is unambiguously recommended) is emergency electrical defibrillation using a discharge energy of 150–360 J [15, 16].

To illustrate the features of the distributions of the pacemaker counts at the heart rate with "TZHN" in figure 13 shows the display of the area of optimal states of the cardiovascular system and the area of the state of the heart with TZHN in the form of a projection of states on the plane of the entropy coefficient and counterexcess. There are also given curves of the location of known distributions in the space of attributes, constructed according to the well-known topographic diagram of Novitsky P.V. [14], where the following notation is used: 350 is the curve of the positions of the family of distributions of the exponential class with exponents a from 0 to oo; 1305 - area of scatter of positions of signs of distribution of ECG readings for a real state; 1310 - curve of positions of the family of bimodal distributions; 1315 — area of possible projections onto the mapping plane of symmetric distributions; 1320, 1325 - curves of the position of compositions of exponential and discrete two-valued distributions; 1330, 1335 and 1340 - points of the position of the Laplace distribution, normal and uniform distributions, respectively; 1345 - curve position of the family of compositions of discrete and exponential distributions with parameters of the form 1/3; 1350, 1355 - points of limitation for the position of the class of arc cosine distributions; 1360 - point of the position of the discrete two-digit distribution; 1365 - dashed curve, limiting part of the space of signs of the coefficient of entropy and counter-process for the most probable position of the representing point for the distributions of the pacemaker counts of the real state: including both the region of the optimal state 310 and the state with severe ventricular disorders (border of TZHN 320).

It can be seen from the diagram that the area of optimal state and the area of states with severe ventricular disorders are separated in space and, therefore, can be unambiguously established. For an optimal state with a cycle time of 0.8 s and an R-wave height of 1 mV, the collapse corresponds to 0.26. The area of severe ventricular disorders is characterized by a flattened distribution and counterexcess values of more than 0.6.

The author of the alleged invention believes that in order to ensure the reliability of decision-making in the provision of emergency cardiac care, it is advisable to use the display of the real state of the patient's cardiovascular system in the form of a representative point of the distribution of ECS readings in the space of signs of the entropy coefficient, counterexcess and asymmetry. The position of the representative point in the state area 305 corresponds to the normal sinus rhythm of the heart. When the imaging point 330 goes beyond the region of the optimal state 310, it can be stated about the change in the distributions of readings in individual ECS cycles, which is possible with changes in the shapes, amplitudes, durations of the teeth and time intervals of the ECS. Such changes occur with the development of pathologies of the cardiovascular system. Obviously, the position of the representative point outside the area of the optimal state should be considered as an independent symptom of the manifestation of the pathological state of the cardiovascular system. To reliably establish a pathological state, it is necessary to assess the probability of making an error as a result of making an incorrect statement about the optimal state of the system.

The state of the heart with severe ventricular disturbances corresponds to the pacemaker, the distribution of readings of which is characterized by the symmetry of the signal and a low value of peakedness. Distributions of ECS counts at heart rhythms with severe ventricular disturbances are limited to a relatively small area in the entropy-parametric space of distribution signs. With the position of the depicting point of the distribution of the pacemaker counts of the real state in the space of the signs of the distributions of the pacemaker counts of the heart rhythms with TZhN, in accordance with the clinical recommendations of the Ministry of Health of the Russian Federation from 2017, emergency electrical defibrillation is unambiguously recommended in order to restore the normal heart rhythm [15, 16]. To make a decision on defibrillation, it is necessary to reliably determine the heart rate with severe ventricular disturbances. Comparison of the assessment of the likelihood of an error as a result of the adoption of an incorrect statement "state with TZHN" with its critical value increases the reliability of decision-making aimed at choosing measures to provide emergency cardiac care.

To implement new possibilities in the proposed invention, the following actions are carried out, illustrated in the form of steps 405, 410, 415, 420, 425 in figure 4 of the diagram of the decision support process in the provision of emergency cardiac care.

Formation of the coordinate space of entropy-parametric signs of the distribution of ECS counts for a real state

The main purpose of this action, illustrated by block 405 of the diagram in FIG. 4, is to obtain the coordinates of the representative sample distribution point ECS for a real state in the entropy-parametric space of distribution signs and an assessment of the state uncertainty in the form of a scatter of the coordinates of the representing point to determine the boundaries of the regions of the optimal state 310 and the boundaries of the state region with TZhN 320 in the real state space with the given coordinates h ,.

The scheme of the formation of the coordinate space of the entropy-parametric signs of the distribution of ECS counts for the real state is given in figure 5 in the form of steps 505, 510, 515, 520. From figure 5 it follows that the first distinctive effect of the proposed decision-making method in the provision of emergency cardiac care contains

- determination at step 505 of the central moments of the second, third and fourth orders of the distribution of samples of the ECS time interval according to the formula (1);

- determination at step 510 of the informational sign of the uncertainty of the counts of the ECS time interval according to the formula (3);

- determining at step 515 the coefficient of entropy K _e , asymmetry As and counter-excess k according to formulas (4) for the distribution of counts of the time interval of the electrocardiosignal (ECS) of a real state with a duration equal to three cardiocycles, and displaying the result in the entropy-parametric space of signs of distributions of counts THE EX;

- determination at step 520 of the scatter of the signs of the distribution of the sample counts of the pacemaker for the real state of the patient 330.

Scatter of signs of the coefficient of entropy, counter-acceleration and asymmetry of the distribution of ECS readings for the real state of the patient 330, designated, respectively, as elements S _\ , S2 S3 of the scatter vector. The spreads of features are found by formulas (5), given in the form of a matrix vector of spreads.

The spreads of the distribution signs allow to form the boundaries of the area of the optimal state and the state with TOL in the space of samples of the current sample of ECS counts.

Determination of the entropy-parametric criterion for the occurrence of GZA.

Step 115 of the decision support scheme illustrated in figure 4 corresponds to the action of determining the entropy-parametric criterion for the occurrence of HCA. It is known that with normal heart function, the optimal state corresponds to the value signs of asymmetry in the distribution of counts of an individual cardiocycle of the order of 2.4. With the development of severe ventricular disturbances, the heart rhythm corresponds to a symmetrical sample of distributions with a sign of asymmetry close to zero. With the development of a heart attack, the ST section rises, which corresponds to a shift in the displacement of values from the interval of the position of the readings of the TP section to the intervals where the values of only the R wave are located, which leads to an increase in the symmetry of the distribution of the samples. The area of possible pathological condition of the heart 315 includes, with a high probability, conditions in the presence of pathology. When a symptom of a pathological state develops, the signal shifts outside the region 315, where the probability of a normal state is less than 1 ... 5%. The surface of the critical values of the asymmetry 335 divides the space into two parts. The displacement of the imaging currents in the area with a sign of asymmetry less than its critical value UP _{CRIT is} taken as a condition for the development of hemodynamically significant arrhythmias (HAA), which requires the provision of emergency cardiac care. The entropy-parametric criterion for the occurrence of GZA is the true value of inequality (6): \ As \ <As _Kpm .

Determination of the reliability of the pacemaker setting for the condition "severe ventricular disturbances".

The introduction of the third additional action, illustrated by step 415 in figure 4 of the decision support diagram, consists in the need to assess the reliability of decision making for carrying out measures for cardiac defibrillation. If the circulation is impaired as a result of arrhythmias, such as ventricular fibrillation (VF) or ventricular tachycardia (VT), defibrillation is performed to restore normal heart rhythm and contractile function. With the development of HZA and the absence of heart rhythms corresponding to "TZHN", medical measures are taken to provide emergency emergency cardiac care associated with cardiac revascularization. The decrease in the ejection fraction is compensated by the implementation of a set of measures for cardiopulmonary resuscitation (CPR). To make a decision on defibrillation, it is necessary to assess the reliability of the statement about the establishment of the pacemaker for a condition with “severe ventricular disturbances”.

The scheme of action "Determination of the reliability of establishing the pacemaker for the state with TZHN" is shown in figure 6 and contains steps 605, 610 and 615. From the flowchart of figure 6 it follows that the third distinctive action of the proposed method of support decision making in the provision of emergency cardiac care, illustrated by step 605, consists in the formation of the border of the area of the state of TOL.

In the feature space, the distributions h ,, centered relative to the real position of the patient's state and reduced to from the scatter S „, the boundaries of the TOL state depend on the signs of the entropy coefficient & _e , asymmetry As and counter-excess to the distribution of ECS counts and spreads Si, S ₂ S ₃ signs distribution of ECS counts. The boundaries of the "TZhN" state in the real state space can be determined using the matrix of expressions (7):

The area of the TZhN state in the space of signs of the coefficient of entropy, asymmetry and counterexcess, is limited by six planes: three planes of limitation of the

X are given by the minimal criteria for the distributions [£ _{3 mjn} E.? _t ; _n to _t u], and three other flat faces are given by the maximum features [ _etax As _max k _max ] t.

To set the boundaries, the following estimates are recommended, written in the form of vectors of minimum and maximum feature boundaries:

Step 610 of the decision support circuit of FIG. 6 is to determine the likelihood bc _{\ of} an error occurring as a result of an incorrect statement of the severe ventricular disorder pathological condition.

In the coordinate space of the features of the distributions of ECS counts, the position of the representing point of the real state is specified using the entropy coefficient, asymmetry and counter-excess. The scatter of signs characterizes the uncertainty of the position of the representing point of the real state. Possible positions of the image point for the real state are distributed according to the normal law [21, 22]. Since linear transformations of displacement and scaling are performed during the transition to the real state space, then during the transition to the real state space, the position of the representing point of the real state is also distributed according to the normal laws. The probability dP (h of the hypothetical realization due to the scatter of the real state H _\ into the elementary volume άn = (άt _[\ άt \ 2άn \,) with coordinates hi is determined by an expression of the form:

The probability bhiai of the appearance of an error as a result of accepting an incorrect statement about the absence of a pathological state of TOL is obtained by summing the probabilities over the entire area of acceptance of the statement about a pathological state of TOL. Then, for the probability Rtzhn of the appearance of an error as a result of the adoption of an incorrect statement about the pathological state of the TZhN, an integral expression of the form

where r | - signs of distributions centered relative to the real position of the patient's state and reduced to their scatter S ,.

Since in the space of signs of the coefficient of entropy, asymmetry and counter-excess, the position of the state region with TOL is limited by flat boundaries drawn through the minimum and maximum values of the distribution signs, the expression ( eight).

The table determines the values of the Laplace function for six estimates of the maximum and minimum boundaries of features. After substituting the values of the Laplace function, determined from the table for six estimates of the maximum and minimum boundaries of features, into expression (8), the probability of occurrence of an error bt> k is calculated: _H ·

Step 615 of the decision support scheme in figure 6 consists in determining the reliability criterion of the statement “the pacemaker rhythm corresponds to a pathological state with severe ventricular disturbances (VVD)”

To select the need for medical measures for defibrillation or revascularization, it is necessary to establish a criterion for the reliability of the statement "Pace rhythm of a pathological state with severe ventricular disturbances (VVD)" based on an assessment of the truth of the expression: the likelihood of an error occurring as a result of an incorrect statement "PAC rhythm pathological condition with TZhN "less than the critical probability b _krii bPKH <b Crete?

Decision making in the choice of defibrillation or revascularization interventions in a cardiac emergency is illustrated at 420 in the flowchart of FIG. 4. If the probability of b-gzhn of the appearance of an error as a result of making an incorrect statement about the pathological condition "severe ventricular disturbances" is less than a critical value equal to 20%, which corresponds to a reliable determination of the pacemaker rhythm in the presence of severe ventricular disturbances, in accordance with the recommendations [15, 16], the key the element of resuscitation (ie, definitely recommended) is emergency electrical defibrillation using a discharge energy of 150-360 J. Carrying out medical measures for cardiac defibrillation is illustrated at step 125 of the diagram in Figure 4.

If the probability of Rtjn of the appearance of an error as a result of the adoption of an incorrect statement about the pathological condition "severe ventricular disturbances" is more than a critical value equal to 20%, then measures are taken to predict severe arrhythmic syndrome at stage 130 and emergency revascularization at stage 135. In accordance with the recommendations for revascularization of the myocardium, patients with cardiogenic shock are recommended to complete revascularization - performing through skin intervention on all critically stenotic large epicardial coronary arteries [23, 24, 25].

Revascularization in cardiogenic shock

Significant hemodynamic arrhythmia causes cardiological shock, in which a state of pronounced hypoxia of organs and tissues is observed due to clinically pronounced disorders of systemic or regional circulation, caused by a sharp decrease in cardiac output of blood. Significant hemodynamic arrhythmias should be treated immediately.

Cardiogenic shock is an acute pathological condition in which the cardiovascular system is unable to provide adequate blood flow. Cardiogenic shock is the leading cause of death in acute myocardial infarction. In the absence of highly qualified medical care, the probability of a fatal outcome among patients with cardiogenic shock is 70-90%. Death can be prevented through rapid diagnosis, surgical use of revascularization methods and the use of modern medical treatment methods in conjunction with supportive therapy. Rapid revascularization of the affected coronary arteries in patients with ischemic heart disease or infarction reduces the risk of death during emergency cardiac care. Since revascularization in cardiogenic shock is the main method of treatment, emergency coronary angiography is necessary. To eliminate the deficiency of blood supply (ischemia) in case of impaired patency of the coronary arteries supplying the heart, revascularization of the myocardium is performed - a medical surgical intervention aimed at eliminating the deficiency of blood supply to the damaged area of the heart muscle. Myocardial revascularization is a broad concept that includes both coronary artery bypass grafting (CABG) and various types of percutaneous coronary intervention (PCI) on the coronary arteries. In case of unstable hemodynamics, including “cardiological shock” (blood circulation interruption), revascularization is performed - ad hoc percutaneous coronary intervention (PCI ad hoc), which is considered as a medical interventional procedure performed immediately after diagnostic coronary angiography, without removing the patient from the operating table. Immediate revascularization is indicated in patients with cardiac shock and ST-elevation myocardial infarction.

When carrying out myocardial revascularization, the most famous and widespread balloon angioplasty, which is combined with other effects on atherosclerotic changes in the coronary artery: the installation of a metal frame - an endoprosthesis (stent), plaque burning with a laser, plaque destruction with a rapidly rotating drill and plaque cutting with a special catheter athero- tomomy. Revascularization, like pharmacotherapy, has 2 goals: improving prognosis (prevention of MI and VS), reduction or complete elimination of symptoms. The main factors that determine the choice of treatment method are individual cardiovascular risk and severity of symptoms [23, 24, 25]. In the absence of HCA, a symptom of the pathological condition is predicted, illustrated by step 425 in FIG. 4.

Predicting a symptom of a pathological condition

The next fourth distinguishing feature of the proposed invention consists in predicting a symptom of a pathological condition at step 425 of Figure 4. The action to be introduced is necessary to identify the possible development of a pathological condition or to establish a symptom of the presence of a pathology.

A diagram of a detailed algorithm for predicting a symptom of a pathological condition is shown in figure 7. The fourth distinctive effect of the proposed decision-making method in the provision of emergency cardiac care contains steps 705, 710, 715, 720 and 725.

Step 705 consists in determining an entropy-parametric criterion for the region of optimal state.

In the absence of hemodynamically significant arrhythmias, the heart provides the blood circulation necessary for life. In this state, it is important to find out about the state of the ser- the vascular system and the presence of pathology. For this reason, the first action that the algorithm performs is to assess the optimal state of the heart. For these purposes, we used the estimate of the position of the sample of readings of the real state relative to the position of the sample of samples of the optimal state in the coordinate space of the distribution signs, where for the optimal state the entropy coefficient K _e , the asymmetry Aso and the counterexcess ko are set equal to 1.3, 0.26 and 2.4, respectively. The values of the signs were obtained on the basis of the average assessment of the analysis of the pacemaker records of 75 patients in the absence of pathological abnormalities. The range of assessments regarding the optimal state depends on the functional state of the body's systems and the variety of external factors such as conditions of existence, stimuli, goals, exposure to physical fields, and others. The normal distribution law was used to describe the spread of the signs of the distribution of ECS counts of the completed cycle of the coefficient of entropy, asymmetry and counter-excess near the optimal state 305. The scatter is set using the parameters a, b, c from the condition of the normal distribution of ECS counts according to the corresponding features. In this case, the confidence intervals for each characteristic intercepts boundaries _e of (1 ± a), 4 ^ o (± 1 s), to (1 ± k) falls 68.2% [27] izob- reflects points for optimal state ... The parallelepiped, limited by the boundaries of the features, contains 32% of the representing points of the optimal state. When the confidence intervals for each individual feature are doubled, 95% falls into the confidence intervals for each feature cut off by the boundaries 2K, o (1 ± a), 2ASQ (1 ± c), 2ko (1 ± b) , the area of the parallelepiped contains 73% of the representing points of the optimal state.

To assess the deviation of the real state from its optimal value, the entropy-parametric criterion r was used, specified in the space of features of the coefficient of entropy, asymmetry and counter-excess [12, 13]. The formula for calculating the criterion is:

Signs of the distribution of ECS counts of a completed cardiocycle, centered relative to the optimal state and reduced to scatter, can be conveniently written in the form of a matrix vector:

Criterion r in the space of centered features x „reduced to the scatter of features of the optimal state, limits the area in the form of a sphere of radius r. Step 710 of the diagram in figure 7 consists in comparing the entropy-parametric criterion for the region of the optimal state and its critical value at the level of significance o.

Elementary probability άR ([x "x, + d2,]) hit distributions centered features x, in the interval [x" x, + 6x] , limited elementary increments άί, _ί centric features, is the product of the probabilities of observing / ith the symptoms with in the interval [x „x, + dx] of elementary increment:

- the density of the probability distribution of the centered feature x ,:

The elementary probability of the event "criterion r in the interval of its elementary increment [r, r + dr]" is equal to the product of the volume of the sphere, radius r and its thickness dr by the product of the probability density of the centered feature x,:

Expression (24) is the Maxwell distribution density for a random criterion value specified as a radius vector in the space of centered features x, with scale parameters equal to 1. Maxwell distribution for a random criterion value has the form:

where Ф ₀ (г) is the Laplace function; <p (z) is the probability density of the normal distribution.

Maxwell's distribution (25) is written for the probability F _r (r) of an event for which the representative point of the features of the ECS count distribution at the optimal state is in the region bounded by the criterion r.

The level of significance a of making a decision about deviations from the optimal state is associated with the probability distribution F _{r (} r) of the criterion using the expression: = 1 - F _r () (26)

Thus, the level of significance o (z) of making a decision about deviation from the optimal state is uniquely related to the criterion r. The formula for calculating the level of significance with known values of the criterion has the form: a (r) = l + 2 [r - p (r) - Φ0 (r)]. (27)

For the most used significance levels of 5%, 10%, 20% and 80%, the value of the criterion r _{a is} taken to be 2.8, 2.5, 2.2, 1, respectively. From the assessment of the significance criterion, it follows that outside the region r = 1, there are 80% of the readings corresponding to the optimal state. If the representative point is in the region r <1, then the sample of ECS counts corresponds to the optimal state. In the regions at r <2.5 and at r <2.8, there is 90% and 95% of the representative point of the optimal state. Going beyond these zones during normal functioning of the body is unlikely. If the criterion r of the real state is greater than the critical values r _\ o and r, then the statement "the state is optimal" should be considered as erroneous. The indicated limits should be used in cases where the disease has not been previously detected.

Thus, if, when comparing, the criterion r, calculated from the sample of the pacemaker counts of the completed cardiac cycle, is less than or equal to its critical value r _a , set using the significance level a, then the sample of the pacemaker counts of the cardiac cycle corresponds to the optimal state. Then, if the inequality (r <r _a ) is true, then the state is assumed to be optimal. Step 715 of the decision support circuit in Figure 7 illustrates the output of information about the optimal state of the heart rhythm, which does not require the provision of cardiac care.

If the inequality (r <r _a ) is false, then for the obtained value of the representing point, it is necessary to establish the possible development of a pathological state. To establish the possibility of a pathological condition, the reliability of an independent symptom of a pathological condition is additionally determined, illustrated by step 720 of the pathological condition prediction scheme in FIG. 7.

Determination of the reliability of an independent symptom of a pathological condition.

The reliability of pathology detection is estimated based on the probability bo of making an error as a result of making an incorrect statement about the optimality of the state. For this, according to the scheme of the algorithm for determining the reliability of an independent symptom of a pathological condition, shown in figure 8, the following four actions are carried out, illustrated by steps 805, 810, 815, 820, 825, 830 and 835. The first action (step 805): determination of the parameters of the boundary of the decision-making area “the rhythm of the electrocardiosignal of the optimal state” in the space of signs of the distribution of samples of the real state.

In the coordinate space, the signs of the entropy coefficient, asymmetry and counter-excesses of the ECS count distributions for the possible positions of the representing point of the real state are distributed according to the normal law [21, 22]. Densities of distribution of probabilities / i (hi),

s (Az) for each individual feature have a symmetric form in the space of features c, centered relative to the position of the real state and reduced to the scatter of features S When passing into the space of centered features of the real state h, the boundaries of the region of the optimal state undergo a change due to linear transformations of scaling and displacement. Correspondence formulas for Maritz vectors for determining the parameters of the boundary of the decision-making region "state is optimal" in the real state space has the form (13).

Since the scaling operations are carried out in the direction of the coordinate axes of the distribution signs - the entropy coefficient, asymmetry and counter-excess - in the space of the centered signs of the real state, the boundaries of the optimal state region take the form of an ellipsoid with the dimensions of the semiaxes equal to the ratio of the spread of the signs of the optimal state to the spread of the signs of the real state. states.

The second action (step 810): determining the coordinates of the optimal state in the space of signs of the distribution of samples for the pacemaker rhythm of the real state of the patient.

Since the density of the probability distribution

have a symmetric form in the space of signs h „centered relative to the position of the real state and normalized to the spread of signs S, then in order to determine the reliability of an independent symptom of a pathological state, it is necessary to determine the coordinates of the position of the hypothesis of the optimal state in the space of the real state. The transfer and normalization of coordinates, the real state area is specified using the matrix expression (14).

In the space of the real state, the center of coordinates is aligned with the position of the real state. The coordinates of the position of the optimal state and the parameters of the boundaries of the decision-making area "the state of the optimal" are necessary to determine the reliability of an independent symptom of a pathological state. The third action (step 815): the formation of the boundaries of the decision-making area "rhythm of the electrocardiosignal of the optimal state" in the space of signs of the distribution of samples for the rhythm of the real state.

Due to the scatter of the position of the representing point of the real state, the position of the representing point inside the region of the optimal state is possible. To estimate the possible position of the representing point with coordinates h, = [hi, t _| 2, Лз] in the region of the optimal state, the boundaries of the decision-making region “the state is optimal” are formed in the space of the real state. The matrix of the limiting values of the characteristics of distributions has the form

Expressions for specifying the boundaries of the region of the optimal state have the form (15).

In the coordinate space of the features of the distributions of the ECS counts, the position of the representing point of the real state is specified using the scatter of features, which characterizes the uncertainty of the position of the representing point of the real state. The possible position of the real state realization are distributed in the real state coordinate space with the probability density / i (hi) 72 Ί2) UC zX equal to the product of the distribution densities of the normalized features.

Fourth action (step 820): determining the probability bo of committing an error as a result of making an incorrect statement "the rhythm of the electrocardiosignal of the optimal state"

Due to the scatter of the real state H _\, there is a nonzero elementary probability d P of the hypothetical realization falling into the elementary volume (c1r | c1c2c1g | h) with coordinates h, has the form:

The summation of the elementary probabilities over three independent coordinates within the boundaries of the ellipsoid makes it possible to determine the probability of making an error as a result of accepting the statement "the state is optimal", calculated by formula (16). Integration of expression (16) is carried out by numerical methods.

The establishment of a symptom of pathology or the possibility of developing a pathological state is established on the basis of comparison with the help of expression (17) the probability of occurrence of an error as a result of accepting an incorrect statement “the rhythm of the electrocardiogram diosignal of the optimal state "and its critical value, illustrates step 825 of the scheme for determining the reliability of an independent symptom in figure 8. If expression (17) is true, which characterizes the pacemaker in the presence of pathological deviations, the decision support method in the provision of emergency cardiac care allows to establish the presence pathological condition of the heart. This result should be considered as an independent symptom of pathology, established with a reliability of more than 80%, in which additional measures are required to identify the diagnosis of the disease. Block 830 of the diagram in Figure 8 illustrates establishing the presence of a symptom of pathology.

If expression (17) is false, which characterizes the pacemaker in the absence of pathological abnormalities, the decision-making algorithm for the provision of emergency cardiological care provides for informing about the possible development of a pathological condition with insufficient reliability of establishing the symptom of pathology, illustrated by step 835 in figure 8. The results of the prediction of the pathological condition obtained in step 425 of the decision support circuit in FIG. 4 are transmitted in step 140 of FIG. 4 for a preliminary diagnosis. At step 145, a patient condition report is generated.

Thus, the actions carried out make it possible to formalize the decision-making in the provision of emergency cardiac care and to obtain an independent symptom of the development of pathology.

Block diagram of a decision support device in the provision of emergency cardiac care.

The considered method of decision support in the provision of emergency cardiac care can be implemented with the software of mobile andradites, or hardware in the form of separate decision blocks, or by combining software and hardware using the universal capabilities of modern computing technology.

A block diagram of information conversion of a mobile decision support device in the provision of emergency cardiac care is shown in figure 14. The technological conveyor of information conversion of a decision support device includes: block 1405 for registration and preliminary analysis of the pacemaker, made with the possibility of amplifying the pacemaker lead signals , wire breakage control, analog-to-digital conversion of signals, filtering of interference, independent recording of digitized information into the database, preliminary analysis of ex, estimation of the distance RR, determining the standard deviation of the mean value of the cardiac cycle, implements steps 105, 110, 115 of the decision support scheme in figure 4; block 1410 for the formation of entropy-parametric features of a sampling of an electrocardiosignal of a real state, which implements the scheme of the algorithm of Fig. 5, and is executed with the ability to select a sample of cardiac cycles data, determine the central moments of the pacemaker, determine the informational sign of the pacemaker, determine the entropy-parametric signs - coefficient of entropy, asymmetry and counterexcess - for the distribution of counts of the time interval of the pacemaker, determination of the scatter of signs of distribution of counts of the pacemaker for the real state; block 1415 for determining the criterion of hemodynamically significant arrhythmia, which implements steps 410 and 120 of the decision support circuit of Figure 4, made with the possibility of assessing the validity of the inequality difference in the modulus of the asymmetry feature of the distribution of the ECS time interval counts and its minimum criterion value, and the ability to switch the sequence of information processing in the event of hemodynamically significant arrhythmias; block 1420 for determining the reliability of establishing the rhythm of the pacemaker of a state with severe ventricular disturbances (VVD), which implements the scheme of the algorithm of Figure 6 and is made with the possibility of forming the boundaries of the region of the state of VVD, calculating the probability of an error as a result of making an incorrect statement about the establishment the rhythm of a pathological condition with severe ventricular disturbances; determination of the reliability criterion of the statement about the pathological state of “TZHN” by comparing it with its critical value, and the possibility of connecting means of informing about the need for defibrillation or revascularization (during revascularization, information is limited to the formation of a preliminary diagnosis and report); block 1425 informing about the need for defibrillation, with the ability to provide audible and visual information about the need for defibrillation and the ability to connect defibrillator controls, implements step 125 of the decision support circuit in figure 4; block 1430 for predicting a pathological state, which implements the schemes of algorithms of Figures 7 - Figures 8 and is configured to determine the entropy-parametric criterion for the pacemaker rhythm of the optimal state; comparison of the entropy-parametric criterion and its critical value at a given level of significance a; informing about the optimal heart rate if the entropy-parametric criterion is less than its critical value, and predicting the possibility of a pathological state in the event that the entropy-parametric criterion is equal to or greater than its critical value by determining the parameters of the boundary of the decision-making area “pacemaker optimal state” and coordinates of the optimal state rhythm in the space of signs of the distribution of pacemaker counts of the real state, formation the boundaries of the decision-making area of the rhythm of the electrocardiosignal of the real state; determining the probability of error as a result of making an incorrect statement “ECG rhythm of the optimal state”; comparing the likelihood of an error as a result of the adoption of an incorrect statement “pacemaker optimal state” and its critical value for establishing the presence of an independent symptom of a pathological condition of the heart; block 1435 generating a preliminary diagnosis, implements step 140 of the decision support circuit in figure 4; block 1440 for generating a report; implements step 145.

Blocks can be made as a stand-alone mobile device or as an add-on module integrated into healthcare information products. The characteristics and ideas disclosed in the description, claims, drawings and illustrations of the invention provide those skilled in the art with important information intended for the implementation of a single technical device or any combination as part of modern medical information systems, devices and devices. Literature

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Claims

Method and device for decision support in the provision of emergency cardiac care

1. A method of supporting decision-making in the provision of emergency cardiac care, including registration, analysis of the electrocardiosignal (ECS), determination of the standard deviation parameter of mean values of cardiac cycles, determination of ventricular tachycardia and extrasystole for at least three consecutive cardiac cycles, defibrillation in case of hemodynamically significant arrhythmias, predicting severe arrhythmic syndrome and performing revascularization in the absence of ventricular tachycardia; making a preliminary diagnosis and generating a report on the patient's heart condition; characterized in that the space of coordinates of entropy-parametric signs of the distribution of ECS readings for a real state is additionally formed by

where N is the number of counts of the ECS time interval; t is the number of grouping intervals; n, is the number of samples in the i-th grouping interval; y _{} is the} average value of the ECS counts in the i-th grouping interval; s is the order of the distribution moment, s = 2, 3, 4, ...; M is the mathematical expectation of the pacemaker for the investigated time interval

(2)

determination of the informational sign of the distribution of counts of the time interval of the ECS

where Ay is the width of the intervals for grouping ECS counts; determining the coefficient of entropy K asymmetry As and counter-excess k for the distribution of the time interval of the electrocardiosignal (ECS) with a duration equal to at least three consecutive cardiocycles, according to the formulas:

37

SUBSTITUTE SHEET (RULE 26) , (4)

where S _I , S2, Xs - spreads of the coefficient of entropy, counter-process and asymmetry, respectively; determination of the parametric criterion for the occurrence of hemodynamically significant arrhythmia (HAA) by assessing the truth of the inequality of the difference in the asymmetry modulus As of the distribution of counts of the time interval of the electrocardiosignal and its minimum critical value Л ^ _rit

IM E5 _CRIT <o, (6) and if expression (6) is true, determining the reliability of the statement about the establishment of the rhythm of the electrocardiosignal for a state with severe ventricular disorders by

- the formation of the boundaries of the area of the state of "severe ventricular disorders (VVD)", specified using the matrix of expressions:

where _{_{_{C max, As max, K max}}} , C min, Ll _Tm to _Tm - maximum and minimum values coeffi- cient entropy asymmetry and kontrekstsessa sampling rate for the pacemaker with heavy zhelu- dochkovymi impairment;

- determination of the likelihood of the occurrence of an error as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiac signal of a pathological state with severe ventricular disturbances according to the formula:

where Ф ₀ (х) is the Laplace function;

38

SUBSTITUTE SHEET (RULE 26) - determination of the reliability criterion of the statement “the rhythm of the electrocardiosignal corresponds to a pathological state with severe ventricular disturbances” on the basis of comparing the likelihood of RTI of the appearance of an error as a result of the adoption of an incorrect statement “the pacemaker corresponds to a pathological state with severe ventricular disturbances and critical probability b _kr „ _t rtzhn <bkrip; and the implementation of measures for the provision of emergency cardiac care in the event that the probability of Rtzh of the appearance of an error as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiosignal of a pathological condition with severe ventricular disturbances is less than a critical value equal to 20%, which corresponds to a reliable determination of the pacemaker rhythm in the presence of severe ventricular disturbances, heart defibrillation is performed; if the probability of an error occurs as a result of the adoption of an incorrect statement about the establishment of the rhythm of the electrocardiosignal of a pathological condition with severe ventricular disturbances of a more critical value equal to 20%, which corresponds to an unreliable determination of the pacemaker rhythm with severe ventricular disturbances, arrhythmia is predicted heart syndrome and revascularization; if expression (6) is false, the possibility of a pathological condition is predicted by

where Km, ASQ, co-coefficient of entropy, asymmetry and counterexcess for the rhythm of the electrocardiosignal of the optimal state of the heart; a, b and c - parameters of the border of the zone of optimal heart conditions;

- comparison of the criterion r and its critical value at the level of significance a using the expression:

Г </ · «, (10) where a - the level of significance of decision-making on rejection of the statement“ rhythm of the electrocardiosignal of the optimal state ”a (r) = 1 + 2 [r · sr (r) - Ф ₀ (r)]; (eleven)

39

SUBSTITUTE SHEET (RULE 26) - if expressions (10) (r <r _a ) are true, informing the "heart rhythm of the optimal state", and if expression (10) (r <r _a ) is false, predicting a pathological state for which in addition the reliability of an independent symptom of a pathological condition is determined by

- determination of the parameters of the boundary of the decision-making area “rhythm of the electrocardiosignal of the optimal state” in the space of signs of the distribution of counts for the rhythm of the electrocardiosignal of the real state:

- determination of the coordinates of the rhythm of the electrocardiosignal of the optimal state in the space of signs of the distributions of readings for the rhythm of the electrocardiosignal of the patient's real state:

40

SUBSTITUTE SHEET (RULE 26) - comparison of the probability bo of the appearance of an error as a result of the adoption of an incorrect statement “the rhythm of the electrocardiosignal of the optimal state” and its critical value b _krM t (equal to 20%),

- if expression (16) is true, which characterizes the pacemaker in the presence of pathological deviations, establishing the presence of a symptom of cardiac pathology,

- if expression (16) is false, which characterizes the pacemaker in the absence of pathological deviations, informing about the possible development of a pathological state.

- block for registration and preliminary analysis of the pacemaker, made with the ability to amplify the signals of the pacemaker. control of wire breakage, analog-to-digital conversion of signals, filtering of interference, independent recording of digitized information into the database, preliminary analysis of ex, determination of the standard deviation of the mean value of the cardiocycle;

- a block for the formation of entropy-parametric signs of a sampling of an electrocardiosignal of a real state, made with the ability to select a sample of data from cardiocycles, determine the central moments of the pacemaker, and determine the informational sign of the pacemaker. determination of the entropy-parametric features - the coefficient of entropy, asymmetry and counter-excess - for the distribution of counts of the time interval of the pacemaker, determination of the scatter of signs of the distribution of counts of the pacemaker for the real state;

- a unit for determining the criterion of hemodynamically significant arrhythmia, made with the ability to assess the truth of the inequality of the difference in the modulus of the asymmetry feature of the distribution of the ECS time interval counts and its minimum criterion value, and the ability to switch the sequence of information processing in the event of hemodynamically significant arrhythmia;

- a unit for determining the reliability of establishing the pacemaker rhythm of a state with severe ventricular disturbances (VVD), made with the possibility of forming the boundaries of the region of the VVD state, calculating the probability of an error occurring as a result of an incorrect statement about the establishment of the rhythm of a pathological state with severe ventricular dysfunctions; determining the reliability criterion of the statement about the pathological state of “TZHN” by comparing it with its critical value.

41

SUBSTITUTE SHEET (RULE 26) and the possibility of connecting means of informing about the need for defibrillation or revascularization (during revascularization, information is limited to the formation of a preliminary diagnosis and report);

- a block for informing about the need for defibrillation, with the ability to present audio and visual information about the need for defibrillation and the ability to connect defibrillator controls;

- a block for predicting a pathological state, made with the ability to determine the entropy-parametric criterion for the pacemaker optimal state; comparison of the entropy-parametric criterion and its critical value at a given level of significance a; informing the optimal state of the heart rate if the entropy-parametric criterion is less than its critical value, and predicting the possibility of a pathological state if the entropy-parametric criterion is equal to or greater than its critical value by determining the parameters of the boundary of the decision-making area " the rhythm of the pacemaker of the optimal state ”and the coordinates of the rhythm of the optimal state in the space of signs of the distribution of the counts of the pacemaker of the real state, the formation of the boundaries of the decision-making area of the rhythm of the electrocardiosignal of the real state; determining the probability of an error as a result of making an incorrect statement “ECG rhythm of the optimal state”; comparing the likelihood of an error as a result of accepting an incorrect statement "the pacemaker of the optimal state" and its critical value to establish the presence of an independent symptom of a pathological condition of the heart;

- block for the formation of a preliminary diagnosis;

- block for generating a report.

42

SUBSTITUTE SHEET (RULE 26)