JP2020202946A - Cardiac function stratification system - Google Patents

Abstract

To provide a system capable of easily grasping a cardiac event risk.SOLUTION: A stratification system comprises: a data acquisition unit which acquires biological marker data related to the cardiac functions of a subject at plural time points; a multi-dimensional vector constitution unit which constitutes multi-dimensional vectors from the biological marker data at the time points; an intervector distance calculation unit which selects at least two time points of at least a first point and a second point from the time points and calculates an intervector distance between multidimensional vectors at the two time points; and a stratification unit which compares the intervector distance with a predetermined threshold to stratify the subject on the basis of a result of the comparison.SELECTED DRAWING: Figure 2

Description

The present disclosure relates to a cardiac function stratification system.

Heart failure is a syndrome in which the left ventricular function of the heart is impaired due to various primary diseases, and the blood pump function of the heart is impaired so that the tissues in the body cannot receive the necessary blood. Examples of the primary disease include heart diseases such as hypertension, ischemic heart disease (myocardial infarction), arrhythmia (atrial fibrillation, etc.), valvular disease, cardiomyopathy, and congenital heart disease. Patients with heart failure often have severe cardiac function that continues to decline during repeated hospitalizations and discharges. Therefore, patients at risk of acute exacerbation of heart failure need to receive appropriate treatment at the right time.

Therefore, a technique for detecting a cardiac event in a heart failure patient based on a biological marker of the heart failure patient is disclosed (Patent Documents 1 to 3). These techniques focus on, for example, the intensity of a specific biological marker in a predetermined period, and predict the parent event according to the intensity of the biological marker or the like.

Special Table No. 2017-500934 Japanese Patent No. 6283670 Japanese Patent No. 6190033

Patients with the underlying disease of heart failure may be diagnosed with acute heart failure even if they do not have heart failure syndrome.
Patients diagnosed with acute heart failure have a high risk of cardiac events 2-3 months after discharge, even if they recover from treatment after hospitalization for acute heart failure. Patients with acute heart failure may be re-hospitalized due to acute exacerbation of chronic heart failure over time, even if the risk of cardiac events decreases due to medication after discharge and shifts to chronic heart failure.

On the other hand, patients with chronic heart failure have a high risk of cardiac events 2-3 months before readmission. However, conventionally, a method that can easily grasp the risk of cardiac events during the period of acute exacerbation of chronic heart failure has not been proposed. For this reason, patients at high risk of cardiac events may not be treated appropriately, and chronic heart failure may be acutely exacerbated and forced to be readmitted to the hospital.
Heart failure can be classified into acute decompensated heart failure, acute heart failure, and chronic heart failure, but it has been difficult to properly grasp the risk of cardiac events in any heart failure patient.

In view of these issues, the present disclosure aims to provide a cardiac function stratification system that can easily grasp the risk of cardiac events.

In order to solve the above-mentioned problems, the stratification system according to one aspect of the present disclosure includes a data acquisition unit that acquires biological marker data related to the cardiac function of a subject at a plurality of time points, and a data acquisition unit at a plurality of time points. A multidimensional vector component that composes a multidimensional vector from biological marker data, and at least two or more time points, the first point and the second point, are selected from multiple time points, and between the multidimensional vectors at the two time points. It is characterized by having an inter-vector distance calculation unit for calculating the inter-vector distance and a stratification unit for comparing the inter-vector distance with a predetermined threshold value and stratifying the subject based on the result of the comparison. And.

In order to solve the above-mentioned problems, the stratification system according to another aspect of the present disclosure includes a data acquisition unit that acquires biological marker data related to the cardiac function of a subject at a plurality of time points, and a plurality of time points. A multidimensional vector component that constitutes a multidimensional vector from the biological marker data in, and a multidimensional vector at at least three time points selected from a plurality of time points, that is, a first point, a second point, and a third point. It is a movement vector between the first multidimensional movement vector and the multidimensional vector at the second point and the third point, which is a movement vector between the multidimensional vectors at the first point and the second point. The first angle, which is the angle with the second multidimensional movement vector, the third multidimensional movement, which is the movement vector between the first multidimensional movement vector and the multidimensional vectors at the first and third points. An inter-vector angle calculation unit that calculates the second angle, which is the angle with the vector, and the third angle, which is the angle between the second multidimensional movement vector and the third multidimensional movement vector, and the first angle. The first angle comparison result comparing with the predetermined first angle threshold, the second angle comparison result comparing the second angle with the predetermined second angle threshold, and the third. It is characterized by comprising a stratification unit for stratifying a subject based on any one or more of a third angle comparison results comparing an angle and a predetermined third angle threshold. ..

According to the present disclosure, it is possible to provide a cardiac function stratification system that can easily grasp the risk of cardiac events.

It is a figure which shows the relationship between the time course of a heart failure patient immediately after admission, the time of ward treatment (between admission and discharge), the time immediately before discharge, and the time of outpatient, and the risk of cardiac events. It is a block diagram which shows one configuration example of the cardiac function stratification system which concerns on 1st Embodiment. It is the schematic explaining the electrocardiographic data and the heart sound data used in the cardiac function stratification system which concerns on 1st Embodiment. It is a figure which shows the relationship of the timing of performing the CABs examination which calculates CABs used in the cardiac function stratification system which concerns on 1st Embodiment. It is an example of a scatter plot created by using different kinds of inter-vector distances between CABs multidimensional vectors used in the cardiac function stratification system according to the first embodiment. It is a figure which assists one explanation of the example in the clinical practice of the CABs examination. It is a figure which assists one explanation of the example in the clinical practice of the CABs examination. It is a block diagram which shows one configuration example of the cardiac function stratification system which concerns on 2nd Embodiment. This is an example of a scatter plot created using the distances between CABs multidimensional vectors. It is a concrete example of the figure which drew the locus of the cardiac function state point of the patient group without a cardiac event. This is a specific example of a diagram depicting the locus of cardiac function state points of a group of patients with a cardiac event. This is an example of displaying the risk level area where the risk of cardiac events is high. This is an example of displaying the risk level area where the risk of cardiac events is low. This is an example in which a risk level region having a high risk of cardiac events is superimposed on the scatter plot of FIG. It is a block diagram which shows one configuration example of the cardiac function stratification system which concerns on 3rd Embodiment. This is an example of a boxplot of the Euclidean distance of the movement vector from the CABs vector immediately after admission to the CABs vector immediately before discharge of the patient group without cardiac event and the patient group with cardiac event. This is an example of a boxplot of the Euclidean distance of the movement vector from the CABs vector immediately after admission to the CABs vector at the time of the first outpatient in the patient group without cardiac event and the patient group with cardiac event. Movement of patients without cardiac event and patients with cardiac event from CABs vector immediately after admission to CABs vector immediately before discharge and from CABs vector immediately before discharge to CABs vector at first outpatient This is an example of a box whiskers diagram of the angles formed by vectors. It is a block diagram which shows one configuration example of the cardiac function stratification system which concerns on 4th Embodiment.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. However, the embodiments described below are merely examples, and there is no intention of excluding the application of various modifications and techniques not specified below. The present disclosure can be implemented in various modifications (for example, by combining each embodiment) without departing from the spirit of the present disclosure. Further, in the description of the following drawings, the same or similar parts are designated by the same or similar reference numerals.

1. 1. Heart Failure and Risk of Heart Event First, with reference to FIG. 1, the general relationship between heart failure and the risk of heart event, which indicates the risk of heart failure such as readmission or death, will be described.
As shown in FIG. 1, patients with the primary disease of heart failure are hospitalized after being initially hospitalized for acute decompensated heart failure (ADHF) or after being readmitted with ADHF due to acute exacerbation of chronic heart failure. He recovered from the treatment for acute heart failure and was discharged from the hospital. However, the risk of cardiac events remains high in all patients until 2-3 months after discharge. How long after discharge the patient is at high risk of cardiac events depends on the patient's cardiac function, medication, and lifestyle.

Patients with acute heart failure are treated with acute heart failure to reduce their risk of cardiac events and transition from acute heart failure to chronic heart failure. Patients with chronic heart failure manage chronic heart failure by taking medication. However, over time, chronic heart failure worsens acutely and is readmitted to the hospital. The risk of cardiac events gradually increases from 2-3 months before readmission.
Through repeated hospitalizations and discharges, the cardiac function of patients with heart failure continues to decline, often leading to severe illness. Therefore, patients at risk of acute exacerbation of heart failure need to receive appropriate treatment at the right time. On the other hand, medical professionals such as doctors need to quantitatively and accurately grasp the deterioration of the cardiac function state of such patients over time.

Patients with heart failure have various pathological conditions depending on the underlying disease, its complications, lifestyle, age, and the like. Therefore, it is important for the medical staff to grasp the individual condition of the heart failure patient over time, stratify the heart failure patient, and provide individual medical care (individualized medical care) for each patient.
In addition, heart failure is a disease that progresses with repeated remission and exacerbation and is not completely cured. Therefore, patients with heart failure have great anxiety and are often depressed. Prevention of readmission by managing patients with heart failure requires collaboration with patients, their families, and healthcare professionals (doctors, etc.). As a means for facilitating this, a common linguistic quantification method and a charting method for the state of heart failure are required.
Hereinafter, a cardiac function stratification system that can easily grasp the cardiac function state of a heart failure patient, quantitatively grasp the progression of heart failure, and stratify the heart failure patient based on the progress will be described.

2. 2. First Embodiment <Structure of Cardiac Function Stratification System>
Hereinafter, the cardiac function stratification system 1 according to the first embodiment will be described with reference to FIGS. 2 to 7.
FIG. 2 is a block diagram showing a configuration example of the cardiac function stratification system 1. As shown in FIG. 2, the cardiac function stratification system 1 includes a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, a stratification unit 40, and a display unit 50. The cardiac function stratification system 1 determines whether or not an individual patient belongs to a group of patients who are prone to cardiac events, based on a plurality of biological marker data related to the cardiac function of the living body, and stratifies. It has a function to separate.

The cardiac function stratification system 1 is realized as, for example, a small device. Such devices include, for example, stick-on (patch-type), cable-type (holter-type), wear-type (belt-type, vest-type) non-invasive (wearable) medical devices, or implantable medical devices. It will be realized.
Even if only a part of the cardiac function stratification system 1 (for example, a function of acquiring the subject's electrocardiographic data and Shinon data) is realized as a small device, and the other part is realized on a host computer or the cloud. good.
Hereinafter, each part of the cardiac function stratification system 1 will be described in detail.

(Data acquisition department)
The data acquisition unit 10 acquires biological marker data related to the subject's cardiac function at a plurality of time points from the subject's electrocardiographic data and cardiac sound data measured at the same time. The subject to be stratified in the cardiac function stratification system 1 is a person or an animal having heart failure symptoms.
The data acquisition unit 10 may have a function as a medical device capable of simultaneously measuring the electrocardiographic data and the heartbeat data of the subject, for example. The data acquisition unit 10 measures electrocardiographic data and cardiac sound data of a patient suffering from acute decompensated heart failure regardless of whether they are in the hospital (immediately after admission, during ward treatment, immediately before discharge), outpatient, or at home. Further, the data acquisition unit 10 is a biological marker calculated based on the electrocardiographic data and the electrocardiographic data, or the electrocardiographic data and the cardiac sound data from an external medical device capable of simultaneously measuring the electrocardiographic data and the electrocardiographic data of the subject. It may be configured to acquire data.
The data acquisition unit 10 outputs the acquired biological marker to the multidimensional vector configuration unit 20.

As the biological marker indicating the cardiac function state acquired by the data acquisition unit 10, for example, a parameter indicating the length of a section such as heart rate, systole or diastole of the heart (hereinafter referred to as a cardiac section length parameter). ), It may be a parameter indicating the intensity of the heartbeat (hereinafter referred to as a heartbeat intensity parameter).

Biological markers representing cardiac function states that can be calculated from electrocardiographic data and cardiac sound data measured at the same timing are collectively called "CABs (Cardiac Acoustic Biomarkers)". The CABs are, for example, the above-mentioned heart section length parameter or the heart sound intensity parameter. Further, a test in which ECG data and Shinon data are measured at the same timing and CABs are calculated from the ECG data and Shinon data is called a "CABs test".
As shown in FIG. 4, the CABs examination is performed, for example, during hospitalization (immediately after admission, ward treatment, immediately before discharge), outpatient (first outpatient, nth outpatient), and at home.

(Heart rate)
The heart rate (hereinafter, may be referred to as HR (Heart Rate)) is the number of heartbeats per minute. As shown in FIG. 3A, the heart rate can be measured by counting the number of heartbeats per minute, with the interval from the R point of the electrocardiographic data to the next R point as one heart rate. .. Further, as shown in FIG. 3B, the heart rate can be measured by counting the number of heartbeats per minute, with the interval from the normal heartbeat S1 of the heart sound data to the next S1 as one heartbeat. it can.

(Heart rate)
The heartbeat length is the interval from the R point of the electrocardiographic data to the next R point, and is the length of one heartbeat. Hereinafter, for convenience, the heart rate may be referred to as RR.

(CABs)
Specific examples of CABs include, for example, electromechanical activity time (EMAT), left ventricular contraction time (LVST), left ventricular diastolic perfusion time (LDPT), left ventricular dilatation time (LVDT), and the sum of EMAT and LVST. Time (QoS2), QR width (QRI: QR Interval), which is the time interval from the Q point to the R point of the electrocardiographic data, and QRS, which is the time interval from the Q point to the S point of the electrocardiographic data via the R point. Width (QRSD: QRS Duration) can be mentioned.
Further, as specific examples of CABs, for example, S1 intensity (S1 Integrity) which is the maximum value of the peak peak amplitude (peak-to-peak amplitude) in the section of the normal heart sound S1 of the heart sound data, and the normal heart sound S2 of the heart sound data. S2 intensity (S2 Intensity) which is the maximum value of the peak peak amplitude of the section, S3 intensity (S3 Integrity) which is the maximum value of the peak peak amplitude of the section of the abnormal heart sound S3 of the heart sound data, and the abnormal heart sound S4 of the heart sound data. The S4 intensity (S4 Integrity), which is the maximum value of the peak peak amplitude, can be mentioned.

Further, as a specific example of CABs, for example, EMATc, LVSTc, LDPTc, LVDTc, QoS2c, which are values obtained by dividing the above-mentioned EMAT, LVST, LDPT, LVDT, QoS2, CID, and QRSD by the heart rate (RR), respectively. , QRIc, QRSDc and the like.
Further, specific examples of CABs include, for example, S1 probability (S1 Strength) and S2 probability (S2 Strength), which are the certainty (or likelihood) of the normal heart sounds S1 and S2 and the abnormal heart sounds S3 and S4 of the heart sound data. S3 accuracy (S3 Strength) and S4 accuracy (S4 Strength), as well as the above-mentioned S1 intensity, S2 intensity, S3 intensity, and S4 intensity, which are the natural logarithmic values of log (S1 Integrity), log (S2 Integrity), and log (S3 Integrity). ) And log (S4 Integrity).

The electromechanical activation time (EMAT) is the interval from the Q point of the electrocardiographic data to the point where the S1 intensity of the normal heart sound S1 of the heart sound data is the strongest. EMAT represents the interval from the electrical firing of electrocardiographic data for the contraction of the myocardium of the left ventricle to the onset of contraction of the left ventricle. It is said that when EMAT exceeds 120 ms, it suggests that the contractility of the heart is reduced.
The left ventricular systolic time (LVST: Left Ventricular Systolic Time) is the interval from the point where the normal heart sound S1 has the strongest S1 intensity to the point where the normal heart sound S2 has the strongest S2 intensity. LVST represents the contraction time interval of the heart.
The left ventricular diastolic perfusion time (LDPT) is the interval from the point where the S2 intensity of the normal heart sound S2 is the strongest to the point Q of the electrocardiographic data. LDPT represents the time interval obtained by subtracting the electromechanical activity time (EMAT) from the expansion time of the left heart.

The left ventricular diastolic time (LVDT) is the interval from the point where the S2 intensity of the normal heart sound S2 is the strongest to the point where the S1 intensity of the subsequent normal heart sound S1 is the strongest. LVDT represents the expansion time interval of the heart. LVDT is indicated by the sum of LDPT and EMAT.

The total time (QoS2) of EMAT and LVST is the interval from the Q point of the electrocardiographic data to the point where the S2 intensity of the normal heart sound S2 is the strongest. QoS2 represents the interval from the electrical firing of electrocardiographic data for contraction of the myocardium of the left ventricle to the end of contraction of the left heart.
The QR width (QRI: QR Interval) is the time interval from the Q point to the R point of the electrocardiographic data.
The QRS width (QRSD: QRS Duration) is the time interval from the Q point of the electrocardiographic data to the S point via the R point. A wide QRS complex means that the excitatory conduction of the electrocardiogram in the left heart takes time, and the contraction start timing of the myocardium is shifted between the location of the fast excited myocardium and the location of the last excited myocardium.

Each index (marker) described above is a specific example of CABs that can be calculated from the simultaneously measured electrocardiographic data and the heartbeat data, but any index that can be calculated from the simultaneously measured electrocardiographic data and the heartbeat data. For example, the present invention is not limited to the above.

(Multidimensional vector component)
The multidimensional vector component 20 constructs a multidimensional vector from biological marker data at a plurality of time points. The multidimensional vector configuration unit 20 constitutes a CABs vector which is a multidimensional vector composed of various CABs. The multidimensional vector configuration unit 20 outputs the configured CABs vector to the inter-vector distance calculation unit 30.

In the multidimensional vector configuration unit 20, for example, nine CABs of HR, EMAT, LVST, LDPT, QRSD, log (S1 Integrity), log (S2 Integrity), log (S3 Integrity), and log (S4 Integrity) are added. Dimensional vectorization. EMAT, LVST, LDPT, and QRSD are CABs (hereinafter referred to as cardiac section length CABs) relating to the contraction of the heart as a blood pump and the time length of diastolic exercise. The log (S1 Intensity), log (S2 Intensity), log (S3 Intensity), and log (S4 Intensity) are CABs related to the intensity of heart sounds related to hemodynamics inside the heart as a blood pump (hereinafter referred to as heart sound intensity CABs). ).

When constructing a multidimensional vector, these CABs have different dynamic ranges. Therefore, the multidimensional vector configuration unit 20 converts each CABs into [0.0, 1.0] interval normalization values by a method such as linear normalization. When there is a missing data of CABs, a method of filling in the missing data by a method such as linear interpolation or polynomial approximation using the values of CABs before and after, or a method of filling in the median value of each CABs may be used.

The multidimensional vector component 20 is, for example, HR, EMAT, LVST, LDPT, QRSD, log from the electrocardiographic data and the heartbeat data simultaneously measured for 5 minutes at the time of admission, immediately before discharge, and the first outpatient for each heart failure patient. The average value of nine CABs of (S1 Intensity), log (S2 Intensity), log (S3 Intensity), and log (S4 Intensity) was calculated, and the average value was further normalized to [0.0, 1.0] intervals. Convert to values and integrate them to form a 9-dimensional CABs vector. This 9-dimensional CABs vector is considered to be a phenotype of the cardiac function state of a heart failure patient.

(Distance calculation unit between vectors)
The inter-vector distance calculation unit 30 selects two points, a first point and a second point, from a plurality of time points, and determines the inter-vector distance between the multidimensional vectors between the first point and the second point. calculate. The two points (first point and second point) to be selected are preferably either immediately after admission, immediately before discharge, or at the first outpatient clinic after discharge.
The inter-vector distance calculation unit 30 may calculate the daily average distance of the inter-vector distance from the inter-vector distance and the time interval between two points.

Further, the inter-vector distance calculation unit 30 may select three points including the first point and the third point different from the second point from a plurality of time points. In this case, the inter-vector distance calculation unit 30 uses the first distance, which is the distance between the multidimensional vectors at the first point and the second point, and the multidimensional vector between the first point and the third point. The second distance, which is the distance, and the third distance, which is the distance between the multidimensional vectors at the second and third points, are calculated. The three points (first point, second point, and third point) to be selected are preferably immediately after admission, immediately before discharge, and at the first or second outpatient visit after discharge. ..

The inter-vector distance calculation unit 30 calculates the first daily average distance by dividing the above-mentioned first distance by the time of the first point and the time interval of the second point, and calculates the above-mentioned second. Divide the distance by the time of the first point and the time interval of the third point to calculate the second daily average distance, and the third distance mentioned above is the time of the second point and the third. The third day average distance may be calculated by dividing by the time interval of the points.
The inter-vector distance calculation unit 30 outputs the calculated distance or the daily average distance to the stratification unit 40.

The inter-vector distance calculation unit 30 calculates, for example, the distance between the CABs vectors between the 9-dimensional vectors at the time of admission, immediately before discharge, and the first outpatient for each patient with heart failure. The inter-vector distance calculation unit 30 can calculate existing distances such as the Euclidean distance, the Mahalanobis distance, the Manhattan distance, and the inner product as the inter-vector distance.

FIG. 5 is a scatter diagram of the Euclidean distance of the above-mentioned 9-dimensional CABs vector calculated by the inter-vector distance calculation unit 30. In FIG. 5, the Euclidean distance between the 9-dimensional CABs vector immediately after admission of a heart failure patient and the 9-dimensional CABs vector immediately before discharge is taken on the horizontal axis. Further, in FIG. 5, the Euclidean distance between the 9-dimensional CABs vector immediately after admission of the heart failure patient and the 9-dimensional CABs vector at the time of the first outpatient is taken on the vertical axis.
In FIG. 5, the group of patients who had a cardiac event of readmission or death within one year from the first outpatient (patient group with cardiac event) is indicated by a circle (○), and the group of patients who were readmitted or died within one year after the first outpatient. The patient group in which no cardiac event occurred (patient group without cardiac event) is indicated by a triangle (Δ).

In FIG. 5, the distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge is short, and the distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient is Shorter times indicate a higher risk of cardiac events.
Further, FIG. 5 shows that even if the distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge is short, the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient are Longer distances suggest a lower risk of cardiac events.

Further, in FIG. 5, when the distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge is long, the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient are The distance is also long, suggesting a low risk of cardiac events.
Further, FIG. 5 shows the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient, although the distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge is long. It suggests that no patient has a short distance to.

(Stratization Department)
The stratification unit 40 compares the calculated inter-vector distance with a predetermined threshold value, and stratifies the subject based on the result of the comparison. The stratification unit 40 displays the comparison result or the stratification result on the display unit 50.
When two time points (first point and second point) are selected in the inter-vector distance calculation unit 30, the stratification unit 40 compares the first inter-vector distance with the first distance threshold. The first distance comparison result is obtained, and the second distance comparison result is obtained by comparing the second distance with the second distance threshold value. The stratification unit 40 stratifies the subjects based on any one or more of the first distance comparison result and the second distance comparison result.
Further, when three time points (first point, second point and third point) are selected in the inter-vector distance calculation unit 30, the stratification unit 40 determines the first distance comparison result and the third point. In addition to the second distance comparison result, a third distance comparison result comparing the third distance and the third distance threshold value is obtained. The stratification unit 40 stratifies the subjects based on any one or more of the first distance comparison result, the second distance comparison result, and the third distance comparison result.

FIG. 6 is an example of a CABs test in a clinical setting. FIG. 6 schematically shows how the stratification unit 40 stratifies the subject based on the inter-vector distance between the multidimensional vectors calculated by the inter-vector distance calculation unit 30. FIG. 6 shows the Euclidean distances of the two 9-dimensional CABs vectors calculated by the inter-vector distance calculation unit 30. The two 9-dimensional CABs vectors were obtained by performing a CABs test immediately after admission due to acute decompensated heart failure and by performing a CABs test immediately before discharge to determine whether or not to be discharged. It is a dimensional CABs vector.

The stratification unit 40 acquires the Euclidean distances of these two 9-dimensional CABs vectors calculated by the inter-vector distance calculation unit 30. As shown in FIG. 6, the stratification unit 40 compares the acquired Euclidean distance with a distance threshold value (for example, 0.6) which is a threshold value for a predetermined distance. The distance threshold value is an example of the threshold value, and is stored in a memory (not shown) included in the stratification unit 40 or the cardiac function stratification system 1. The threshold value stored in the memory may be stored in advance or may be rewritten by the control of a processor (not shown). The stratification unit 40 stratifies the subjects based on the result of the distance comparison.

That is, the stratification unit 40 has a high risk of cardiac events when the Euclidean distance at the time of discharge of the subject is equal to or less than the distance threshold value (for example, 0.6) (the left region of the straight line shown in FIG. 6). Judge as a patient. Further, when the Euclidean distance at the time of discharge of the subject exceeds the distance threshold value (for example, 0.6) (the region on the right side of the straight line shown in FIG. 6), the stratification unit 40 is at risk of a cardiac event. Judge as a low patient. In this way, the stratification unit 40 stratifies the subjects.

(Display part)
The display unit 50 is, for example, a liquid crystal display, and displays the result of comparison in the stratification unit 40 (the magnitude relationship between the Euclidean distance and the distance threshold value) or the stratification result (high or low risk of cardiac events). The comparison result or the stratification result is presented to the display unit 50 as information assisting the diagnosis of the standard treatment by the medical staff. Further, the display unit 50 may display a plurality of objects such as characters, numbers, tables, and figures as operation buttons on the screen according to the control of the control unit (not shown).
Further, the display unit 50 may be in a form in which the comparison result (large / small relationship) in the stratification unit 40 or the stratification result is printed on paper or the like and displayed.

(About the use of the cardiac function stratification system)
When the comparison result displayed on the display unit 50 is less than the preset threshold value or the stratification result indicates that the risk of cardiac event is high, the medical staff such as a doctor informs the patient of the initial outpatient department. It can be determined that there is a high risk of a cardiac event occurring later.
Healthcare professionals instruct patients to continue to perform CABs tests at a high frequency (eg, once a day) after discharge if they determine that they are at high risk of developing cardiac events after discharge. The patient takes a medical device capable of CABs examination to his / her home by an appropriate method, and performs the CABs examination at home or the like according to an appropriate procedure instructed by a doctor. In addition, the patient may perform a CABs test in the hospital at each outpatient time after discharge.

It should be noted that the biological marker data of the subjects measured at the same time is always acquired regardless of whether the subject is hospitalized or discharged, and the biological marker data is transmitted to the cardiac function stratification system 1 via the network. Is also good. In this case, the doctor may instruct the patient on the CABs test and medication by referring to the result of stratification in the cardiac function stratification system 1 by telephone call, voice or video communication via the Internet, or the like. good. In this case, the patient can receive guidance from a doctor while staying at home, which is preferable because the burden on the patient can be reduced.

The cardiac function stratification system 1 described above includes at least one processor, and the processors function as a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, and a stratification unit 40. To do.
That is, the cardiac function stratification system 1 includes at least one processor that executes an instruction and a storage unit that stores a program. The program gets the processor to obtain biological marker data related to the subject's cardiac function at multiple time points, constructs a multidimensional vector from the biological marker data at multiple time points, and at least first from multiple time points. Select two or more time points of the point and the second point, calculate the inter-vector distance between the multidimensional vectors at the two time points, compare the inter-vector distance with the predetermined distance threshold, and use the comparison result. Execute commands to stratify subjects based on.

<Modification example>
In the present embodiment, an example of the cardiac function stratification system 1 that stratifies immediately before discharge to determine whether or not the patient may be discharged due to heart failure treatment during hospitalization is shown, but the configuration is limited to such a configuration. I can't. For example, the cardiac function stratification system 1 may perform a CABs test at an arbitrary timing during ward treatment or at an outpatient clinic after discharge to perform stratification instead of the timing immediately before discharge.

For example, FIG. 7 is another example of a CABs test in the clinical setting. FIG. 7 schematically shows how the stratification unit 40 stratifies the subject based on the inter-vector distance between the multidimensional vectors calculated by the inter-vector distance calculation unit 30. FIG. 7 shows the Euclidean distances of the two 9-dimensional CABs vectors calculated by the inter-vector distance calculation unit 30.

The data acquisition unit 10 acquires the test results of the CABs test performed immediately after admission due to acute decompensated heart failure as biological marker data. In addition, the data acquisition unit 10 acquires the test results of the CABs test performed at the first outpatient clinic after the patient is discharged as biological marker data.
The multidimensional vector configuration unit 20 constructs two 9-dimensional CABs vectors from the biological marker data immediately after admission and at the time of the first outpatient acquisition acquired by the data acquisition unit 10.

The inter-vector distance calculation unit 30 calculates the inter-vector distance (for example, Euclidean distance) of two 9-dimensional CABs vectors composed of the multi-dimensional vector configuration unit 20, and outputs the inter-vector distance to the stratification unit 40.
The stratification unit 40 compares the inter-vector distance input from the inter-vector distance calculation unit 30 with a preset threshold value (for example, 0.6), and stratifies the subjects based on the comparison result. To do. The stratification unit 40 outputs a comparison result or a stratification result to the display unit 50.
The display unit 50 displays the comparison result or the stratification result. This makes it possible to present the results of comparison or stratification to medical professionals such as doctors.

Medical professionals such as doctors can predict the risk of future cardiac events based on the comparison results or stratification results displayed on the display unit 50. Healthcare professionals can instruct patients to perform in-hospital CABs tests at home or outpatiently based on the predicted risk of cardiac events.

<Effect of the first embodiment>
The cardiac function stratification system 1 according to the first embodiment has the following effects.
(1) In the cardiac function stratification system 1, the patient stratification result (risk of cardiac event) is based on the electrocardiographic data continuously obtained from the subject and the biological marker data obtained from the heartbeat data. The result of comparison (the relationship between the distance between vectors and the threshold value), which is the standard for stratification, can be presented to medical personnel such as doctors. Therefore, for example, a doctor can more appropriately grasp and judge the state of a patient with heart failure and provide appropriate medical care for each heart failure patient, and can support the medical field.

(2) In the cardiac function stratification system 1, the above-mentioned stratification results and comparison results that serve as criteria for stratification can be presented to medical personnel such as doctors. Therefore, it is possible to individualize and optimize heart failure treatment such as medication therapy by medical personnel such as doctors and cardiac rehabilitation exercise therapy for each patient to prevent readmission of heart failure patients, and the QOL (Quality) of patients. Of Life) can be improved and medical economic benefits can be created.

3. 3. Second Embodiment Hereinafter, the cardiac function stratification system 2 according to the second embodiment will be described with reference to FIGS. 2 to 7 and FIGS. 8 to 14.
The cardiac function stratification system 2 according to the second embodiment has a cardiac function state point display unit 70 that draws and displays a locus of the cardiac function state of a heart failure patient, and thus has a cardiac function layer according to the first embodiment. It is different from the separation system 1.

FIG. 8 is a block diagram showing a configuration example of the cardiac function stratification system 2. As shown in FIG. 8, the cardiac function stratification system 2 includes a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, a stratification unit 40, and a display unit 50. Further, the cardiac function stratification system 2 includes a two-dimensional coordinate calculation unit 60, a cardiac function state point display unit 70, and an alert notification unit 80. The cardiac function stratification system 2 does not necessarily require the display unit 50.

Hereinafter, the two-dimensional coordinate calculation unit 60, the cardiac function state point display unit 70, and the alert notification unit 80 of the cardiac function stratification system 2 will be described in detail. Since the data acquisition unit 10, the multidimensional vector configuration unit 20, the inter-vector distance calculation unit 30, the stratification unit 40, and the display unit 50 have the same configurations as the corresponding units of the cardiac function stratification system 1. , The description is omitted.

<Structure of cardiac function stratification system>
(Two-dimensional coordinate calculation unit)
The two-dimensional coordinate calculation unit 60 calculates the coordinates on the two-dimensional plane corresponding to the plurality of multidimensional vectors configured by the multidimensional vector configuration unit 20 by using a mathematical method.
As a mathematical method used in the two-dimensional coordinate calculation unit 60, for example, the document "JW Sammon," A nonlinear mapping for data structure analysis ", IEEE Trans. Computers, vol.C-18, no.5, pp.401" -409, May 1969. ”, the Sammon method, the projection tracking method, the self-organizing map method, and other multi-dimensional scale construction methods (MDS: Multi-Dimensional Scaling), and the two-dimensional system using the principal components of the principal component analysis method. Examples include algorithms such as visualization.

(Cardiac function state point display)
The cardiac function state point display unit 70 displays points corresponding to a plurality of multidimensional vectors on the two-dimensional plane based on the coordinates on the two-dimensional plane calculated by the two-dimensional coordinate calculation unit 60, and a plurality of cardiac functions. Draw by connecting the state points with a line segment. Points corresponding to a plurality of multidimensional vectors are displayed as cardiac function state points representing a plurality of cardiac function states. The cardiac function state point display unit 70 presents the trajectory of the cardiac function state of a heart failure patient to medical professionals such as doctors and patients by visualizing the CABs vector group composed of the multidimensional vector constituent unit 20 in two dimensions. can do.
Information including medication, doctor's findings, diagnosis, medical history, etc. is linked to the cardiac function status point displayed on the cardiac function status point display unit 70. In addition, a corresponding multidimensional vector is associated with the cardiac function state point.

The cardiac function state point display unit 70 displays a risk level region corresponding to the cardiac event risk on a two-dimensional plane. The risk level area is, for example, an area with a high cardiac event risk or an area with a low cardiac event risk. The risk level area is displayed as a circle, a semicircle, a polygon, or a shape surrounded by a curve.
The cardiac function state point display unit 70 may be integrally configured with the display unit 50.

(Alert notification section)
The alert notification unit 80 notifies a medical person such as a doctor of an alert when the patient's cardiac function state falls within a predetermined risk level range or falls outside the predetermined risk level range. For example, in the alert notification unit 80, a line segment connecting a plurality of cardiac function state points displayed on the cardiac function state point display unit 70 intersects the boundary of the risk level area displayed on the cardiac function state point display unit 70. At that time, an alert is notified to medical personnel such as doctors.

The alert notification unit 80 is, for example, a speaker that outputs voice as an alert. Further, the alert notification unit 80 may be a display unit such as a liquid crystal display or a touch panel on which characters, figures, photographs and the like are displayed as alerts. When the alert notification unit 80 is a display unit, the display unit 50 may function as the alert notification unit 80.

Alerts are used, for example, by doctors to encourage patients to come to the hospital or to notify them to rest. Alerts can also be used to suggest changing the dosage regimen of current medications prescribed to patients, to administer different therapeutics, to administer different combinations of therapeutics, to change exercise intensity, and more. can do. Alerts are not only when the patient's condition transitions from a "low cardiac event risk" state to a "high cardiac event risk" state, but also from a "high cardiac event risk" state to a "low cardiac event risk" state. Medical personnel will be notified even if there is a transition.

Information associated with the cardiac function state point (information such as medical history and corresponding multidimensional vector) and the alert notified by the alert notification unit 80 are shared by the presentation target person of the cardiac event prediction information presentation unit, which will be described later. You can do and receive.

<Specific example of drawing cardiac function state points>
Hereinafter, drawing of the cardiac function state point on the cardiac function state point display unit 70 will be described with reference to a specific example.

(Trajectory of cardiac function state points in a group of patients hospitalized for acute decompensated heart failure)
FIG. 9 shows the cardiac function state points corresponding to the 9-dimensional CABs vector of the deemed healthy subjects immediately after admission, immediately before discharge, and at the first outpatient department of the group of patients admitted with acute decompensated heart failure (ADHF). , Is a specific example of a scatter plot drawn on a two-dimensional mapping plane using the Sammon method.

In the scatter plot of FIG. 9, the cardiac function state points corresponding to the 9-dimensional CABs vector immediately after admission, which are indicated by triangles (Δ), are distributed around the lower right region. The cardiac function state points corresponding to the 9-dimensional CABs vector immediately before discharge, which are indicated by squares (□), are distributed around the central region. The cardiac function state points that correspond one-to-one to the 9-dimensional CABs vector at the time of the first outpatient, which is indicated by a circle (◯), are distributed around the upper left region. Further, from FIG. 9, the cardiac function state points corresponding to the 9-dimensional CABs vector (indicated by a diamond (◇)) of the deemed healthy subject group are distributed mainly in the vicinity of the upper left region.
In the ADHF inpatients, the heart failure treatment as a whole restores the cardiac function with the passage of time immediately after admission → immediately before discharge → at the time of the first outpatient. Therefore, in the scatter plot of FIG. 9, the cardiac function state points corresponding to the 9-dimensional CABs vectors are moved from the lower right to the upper left region. Therefore, it can be observed that the cardiac function state point of the ADHF inpatient is close to the cardiac function state point of the deemed healthy subject group.

(Trajectory of cardiac function state points in ADHF patients without cardiac events)
FIG. 10 is a diagram in which the locus of cardiac function state points is drawn on a two-dimensional mapping plane using the Sammon method, limited to the group of ADHF patients who have not been readmitted or died in one year after the first outpatient visit. This is a specific example. FIG. 10 shows a one-to-one correspondence between 9-dimensional CABs vectors between three time points from the time immediately after admission to the time immediately before discharge to the time of the first outpatient in a group of ADHF patients who have no cardiac event in one year after the first outpatient. It shows the locus of points.

From FIG. 10, in the ADHF patient group without cardiac events, there are ADHF patients having a long length (the length of a line segment connecting a plurality of cardiac functional state points) on the two-dimensional mapping plane of the locus of the cardiac functional state points. Many are observed. In particular, in the ADHF patient group without cardiac events, the length of the two-dimensional mapping plane of the locus of cardiac function state points from immediately after admission indicated by a triangle (△) to immediately before discharge indicated by a square (□). Can be observed to be long.

From these observations, it can be inferred that ADHF patients with a long locus of cardiac function state points corresponding to the 9-dimensional CABs vector from immediately after admission to the first outpatient are less likely to have a post-first outpatient cardiac event. In addition, it is presumed that ADHF patients who do not have cardiac events have recovered significantly by medical treatment during hospitalization.

(Travels of cardiac function state points in ADHF patients with cardiac events)
FIG. 11 is a diagram in which the locus of cardiac function state points is drawn on a two-dimensional mapping plane using the Sammon method, limited to the group of ADHF patients who had a cardiac event of readmission or death in one year after the first outpatient. This is a specific example. FIG. 11 shows one-to-one to the 9-dimensional CABs vector between the three time points from immediately after admission to immediately before discharge to the time of the first outpatient in the group of ADHF patients who had a cardiac event of readmission or death in one year after the first outpatient. The trajectory of the cardiac function state point corresponding to is shown. In FIG. 11, patients with 1 or 2 cardiac function status points show that the CABs test at the time of the first outpatient visit could not be performed for some reason immediately before discharge.

From FIG. 11, in the group of ADHF patients who had a cardiac event, the length of the locus of the cardiac functional state points on the two-dimensional mapping plane (the length of the line segment connecting the plurality of cardiac functional state points) was short. Many are observed. From these observations, it can be inferred that many of the ADHF patients with cardiac events had little change in the state of heart failure and did not obtain sufficient recovery of cardiac function during hospitalization and after discharge.

<Specific example of drawing cardiac function state points>
Hereinafter, a risk level region indicating a risk level corresponding to the risk of a cardiac event, which is displayed on the cardiac function state point display unit 70, will be described with reference to a specific example.

FIG. 12 is an example of a scatter plot of FIG. 9 overlaid with a semicircle showing a risk level region where the risk of cardiac events is high. In FIG. 12, when the two-dimensional mapping plane coordinates of the locus of the cardiac function state point are located within this semicircle, it is suggested that the patient's cardiac event risk corresponding to the cardiac function state point is high. There is.

FIG. 13 is an example of a scatter plot of FIG. 9 overlaid with a semicircle showing a risk level region where the risk of cardiac events is low. In FIG. 13, when the two-dimensional mapping plane coordinates of the locus of the cardiac function state point are located within this semicircle, it is suggested that the patient's cardiac event risk corresponding to the cardiac function state point is low. There is.

FIG. 14 is an example of a diagram in which a locus of cardiac function state points of the ADHF patient group having a cardiac event in FIG. 11 is drawn and a semicircle indicating a risk level region with a high risk of cardiac event is superimposed and displayed. .. In FIG. 14, it is observed that the entire or part of the locus of the cardiac function state point of the patient in which the cardiac event is occurring (the tip of the locus) is included in this semicircle.

In the display of the risk level areas showing the risk of these heart events, clinical scenario (CS) classification, acute heart failure pathology classification, heart failure hospitalization history classification, Killip classification, NoHRia-Stephenson classification, Forester classification, etc. for individual cases of heart failure, It goes without saying that the NYHA classification, identified exacerbating factors for heart failure, ejection fraction, physician findings, etc. should be considered.

The cardiac function stratification system 2 described above includes at least one processor, which includes a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, a stratification unit 40, and two. It functions as a dimensional coordinate calculation unit 60. Further, the processor may function as a part of the display unit 50, the cardiac function state point display unit 70, and the alert notification unit 80.
That is, the cardiac function stratification system 1 includes at least one processor that executes an instruction and a storage unit that stores a program. The program gets the processor to obtain biological marker data related to the subject's cardiac function at multiple time points, constructs a multidimensional vector from the biological marker data at multiple time points, and at least first from multiple time points. Select two or more time points of the point and the second point, calculate the inter-vector distance between the multidimensional vectors at the two time points, compare the inter-vector distance with a predetermined threshold, and based on the result of the comparison. The subjects are stratified and the commands for calculating the coordinates on the two-dimensional plane corresponding to a plurality of multidimensional vectors are executed by using a mathematical method.

<Effect of the second embodiment>
The cardiac function stratification system 2 according to the second embodiment has the following effects in addition to the effects (1) and (2) described in the first embodiment.
(3) The cardiac function stratification system 2 provides the patient with the locus of the patient's cardiac function state points (FIGS. 10 and 11) and the risk level region (FIG. 12 and 13) under the appropriate judgment of the doctor. Can be shown. Therefore, the progress of the patient's heart failure treatment can be shared among the patient, his / her family, and the medical staff.

(4) The cardiac function stratification system 2 can quantitatively indicate the state of heart failure based on the locus of the cardiac function state points corresponding to the 9-dimensional CABs vector of the ADHF patient on a one-to-one basis. For example, if the locus of cardiac function state points that correspond one-to-one to the 9-dimensional CABs vector of an ADHF patient changes from the lower right region to the upper left region, the doctor heads for the treatment of heart failure for the patient and family. Can be shown to be. As a result, the patient can be convinced that the medication treatment is being performed well, and the anxiety may be eliminated, leading to the avoidance of a decrease in the psychological state (for example, depression).

(5) The cardiac function stratification system 2 can quantitatively indicate the state of heart failure based on the locus of the cardiac function state points corresponding to the 9-dimensional CABs vector of the ADHF patient on a one-to-one basis. Therefore, the doctor can infer the medication status of the ADHF patient based on the locus of the cardiac function state points corresponding to the 9-dimensional CABs vector of the ADHF patient on a one-to-one basis. For example, if the movement of the ADHF patient's cardiac function state point trajectory to the upper left region is stagnant, the doctor can guess that the ADHF patient may be neglecting to take the drug and give appropriate guidance. There is a possibility of becoming.
As described above, by sharing the method of quantifying and charting the state of heart failure in the cardiac function stratification system 2 with patients, their families, and medical professionals (doctors, etc.), the three parties Collaborative work becomes easier.

4. Third Embodiment Hereinafter, the cardiac function stratification system 3 according to the third embodiment will be described with reference to FIGS. 2 to 14 with reference to FIG. 15.
The cardiac function stratification system 3 according to the third embodiment has a cardiac event prediction information presentation unit 90 that presents cardiac event prediction information based on the stratification result stratified by the stratification unit 40. Therefore, it is different from the cardiac function stratification system 1 and the cardiac function stratification system 2.

FIG. 15 is a block diagram showing a configuration example of the cardiac function stratification system 3. As shown in FIG. 15, the cardiac function stratification system 3 includes a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, a stratification unit 40, and a display unit 50. Further, the cardiac function stratification system 2 includes a two-dimensional coordinate calculation unit 60, a cardiac function state point display unit 70, and an alert notification unit 80. Further, the cardiac function stratification system 2 includes a cardiac event prediction information presentation unit 90. The cardiac function stratification system 2 does not necessarily require the display unit 50, the two-dimensional coordinate calculation unit 60, the cardiac function state point display unit 70, and the alert notification unit 80.

Hereinafter, the cardiac event prediction information presentation unit 90 of the cardiac function stratification system 3 will be described in detail. The data acquisition unit 10, the multidimensional vector configuration unit 20, the inter-vector distance calculation unit 30, the stratification unit 40, the display unit 50, the two-dimensional coordinate calculation unit 60, the cardiac function state point display unit 70, and the alert notification unit 80. Has the same configuration as each corresponding part of the cardiac function stratification system 2, and thus the description thereof will be omitted.

<Structure of cardiac function stratification system>
(Mental event prediction information presentation department)
The cardiac event prediction information presentation unit 90 predicts a cardiac event based on the stratification result stratified by the stratification unit 40, and presents the cardiac event prediction information. The cardiac event prediction information is, for example, a result of predicting whether or not a heart failure patient will undergo a readmission or death cardiac event within one year after discharge from the hospital or the first outpatient clinic.

The cardiac event prediction information presentation unit 90 extracts a group of patients in which a cardiac event occurs one year after discharge or the first outpatient clinic based on the stratification result in the stratification unit 40, and presents it as cardiac event prediction information. To do. The cardiac event prediction information presentation unit 90 presents cardiac event prediction information, for example, at the first outpatient clinic of an ADHF patient. The presentation target of the cardiac event prediction information presentation unit 90 is, for example, a patient, a family member, a doctor, a nurse, a pharmacist, a caregiver, a medical device company, a pharmaceutical company, or the like.

Hereinafter, the cardiac event prediction information presented by the cardiac event prediction information presentation unit 90 will be considered.
(Welch t-test A)
(A) Welch's t-test was performed between the group of ADHF patients with cardiac events and the group of patients without cardiac events regarding the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge.
(B) Welch's t-test was performed between the group of ADHF patients with cardiac events and the group of patients without cardiac events regarding the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient visit.
(C) Welch's t-test was performed between the group of ADHF patients with cardiac events and the group of patients without cardiac events regarding the Euclidean distance between the 9-dimensional CABs vector immediately before discharge and the 9-dimensional CABs vector at the time of the first outpatient visit.

(D) The Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge divided by the number of days between the time intervals immediately after admission and immediately before discharge. A Welch t test was performed between a group of patients with events and a group of patients without cardiac events.
(E) The heart of an ADHF patient regarding the daily average Euclidean distance obtained by dividing the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the first outpatient department by the number of days between the time intervals immediately after admission and at the time of the first outpatient department. A Welch t test was performed between a group of patients with events and a group of patients without cardiac events.
(F) The heart of an ADHF patient with respect to the daily average Euclidean distance obtained by dividing the Euclidean distance between the 9-dimensional CABs vector immediately before discharge and the 9-dimensional CABs vector at the first outpatient department by the number of days between the time intervals immediately before discharge and at the time of the first outpatient visit. Welch's t-test was performed between the group of patients with events and the group of patients without cardiac events.

(Welch t-test C)
(G) 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector immediately before discharge and the 9-dimensional movement vector from the 9-dimensional CABs vector immediately before discharge to the 9-dimensional CABs vector at the time of the first outpatient A Welch t test was performed between a group of ADHF patients with cardiac events and a group of patients without cardiac events.
(H) 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector immediately before discharge and the 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector at the time of the first outpatient visit. A Welch t test was performed between a group of ADHF patients with cardiac events and a group of patients without cardiac events.
(I) 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector at the first outpatient department and the 9-dimensional movement vector from the 9-dimensional CABs vector immediately before discharge to the 9-dimensional CABs vector at the time of the first outpatient department. A Welch t test was performed between a group of ADHF patients with cardiac events and a group of patients without cardiac events.

In the above, the angle formed by the two 9-dimensional movement vectors is calculated by dividing the inner product of the two 9-dimensional movement vectors by the lengths of the two 9-dimensional movement vectors, as in the case of 2D. be able to.

When the p-value in the Welch's t test is p <0.05, the distribution of the Euclidean distance and angle of the movement vector is statistically significantly different between the group of patients with cardiac events and the group of patients without cardiac events. Is judged. The results (p-values) of Welch's t-test A to Welch's test C are shown in Tables 1 to 3 below.

In addition, FIG. 16 shows a box-and-whisker plot of the Euclidean distances of the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge for each of the ADHF patient group with cardiac event and the patient group without cardiac event. ..

From Table 1 and FIG. 16, the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector immediately before discharge is statistically significantly shorter in the group of patients with cardiac events than in the group of patients without cardiac events. Can be estimated.

In addition, FIG. 17 shows a box-and-whisker plot of the Euclidean distances of the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient treatment for each of the patient group with cardiac event and the patient group without cardiac event of ADHF patients. ..

From Table 2 and FIG. 17, the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the first outpatient is statistically significantly shorter in the group of patients with cardiac events than in the group of patients without cardiac events. Can be estimated.

Further, FIG. 18 shows a 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector immediately before discharge and immediately before discharge for each of the patient group with cardiac event and the patient group without cardiac event of ADHF patients. The box whiskers of the angle formed by the 9-dimensional movement vector from the 9-dimensional CABs vector of time to the 9-dimensional CABs vector of the first outpatient are shown.

From Table 1 and FIG. 18, the group of patients with cardiac events had a 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector immediately before discharge and the time immediately before discharge as compared with the group of patients without cardiac events. It can be estimated that the angle of the 9-dimensional movement vector from the 9-dimensional CABs vector to the 9-dimensional CABs vector at the time of the first outpatient is statistically significantly smaller.

From these estimates obtained from Tables 1, 2 and 3 and the scatter plot of the Euclidean distance shown in FIG. 5, as a threshold value for the Euclidean distance of the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the first outpatient clinic. For example, set 0.6.
Table 4 shows the performance evaluation results of the method of predicting whether readmission or death cardiac events occur in the first year after the first outpatient visit, with the threshold set to 0.6.

In Table 4, the prediction "true" indicates the number of subjects whose Euclidean distance was 0.6 or less. Predicted "true" means that the risk of readmission or death cardiac events was predicted to be high in the first year after the first outpatient visit. Further, in Table 2, the prediction "false" indicates the number of subjects whose Euclidean distance was more than 0.6 as described above. Predicted "false" means that the risk of readmission or death cardiac events was predicted to be low one year after the first outpatient visit.
In Table 4, the cardiac event “true” indicates the number of subjects who actually experienced a cardiac event of readmission or death in one year after the first outpatient visit. In Table 2, the cardiac event “false” indicates the number of subjects who did not actually experience a cardiac event of readmission or death within one year after the first outpatient visit.

In Table 4, "sensitivity" indicates that there is a high risk of readmission or death cardiac events occurring in the first year after the first outpatient, compared to the number of subjects who actually experienced readmission or death cardiac events in the first year. The ratio of the number of subjects predicted to be (predicted "true" / cardiac event "true").
In Table 4, "specificity" refers to the risk of re-hospitalization or death cardiac events occurring in the first year after the first outpatient, as opposed to the number of subjects who did not experience readmission or death cardiac events in the first year. Percentage of subjects predicted to be low (predicted "false" / cardiac event "false").
In Table 4, the "positive predictive value" refers to the number of subjects who were predicted to be at high risk of readmission or death cardiac events in the first year after the first outpatient, and the hearts of readmission or death in the first outpatient year. The ratio of the number of subjects in which the event actually occurred (heart event "true" / predicted "true").
In Table 4, the "negative predictive value" refers to the number of subjects who were predicted to have a low risk of re-hospitalization or death in the first year after the first outpatient, and the number of subjects who were readmitted or died in the first year after the first visit. The percentage of subjects whose cardiac events did not actually occur (cardiac event "false" / predicted "false").

As shown in Table 4, the prediction of the cardiac event by the cardiac event prediction information presentation unit 90 gives a sensitivity of about 90% and a negative predictive value.
That is, according to the method for predicting cardiac events in the present embodiment, it means that a doctor can extract about 90% of the patient group in which cardiac events occur in one year after the first outpatient of ADHF patients at the first outpatient. This can help physicians provide selectively appropriate medical care to patients with heart failure who are at high risk of cardiac events.
The cardiac event prediction information presentation unit 90 predicts and displays the risk of cardiac events of the ADHF patient based on the test results obtained by performing the CAB test at the first outpatient clinic after the first outpatient clinic of the ADHF patient, for example.

In the above-mentioned prediction of cardiac events, the readmission rate within 1 year after the first outpatient treatment of the ADHF patient group predicted to have a high risk of cardiac events for the ADHF patient group predicted to have a low risk of developing cardiac events. Was about 5.5 times, the relative risk was about 5.5 times, and the odds ratio was about 11 times.
The cardiac event prediction information presentation unit 90 displays a score representing the readmission rate, the relative risk, the odds ratio, or the cardiac event occurrence risk calculated from these.

As shown in FIGS. 7 and 4, an example in which, for example, 0.6 is set as a threshold value for the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient visit has been described. Similarly, the ADHF patient group predicted to have a high risk of cardiac events and the ADHF patient group predicted to have a low risk of cardiac events based on the prediction of cardiac events by the cardiac event prediction information presentation unit 90. An example of calculating the positive predictive value, the negative predictive value, the readmission rate within one year after the first outpatient visit, etc. was explained by dividing into the two groups.
However, for example, 0.4 may be set in addition to 0.6 as the threshold value for the Euclidean distance between the 9-dimensional CABs vector immediately after admission and the 9-dimensional CABs vector at the time of the first outpatient visit. In addition, the ADHF patient group may be stratified into three groups, and the readmission rate within one year after the first outpatient visit and the associated risk of cardiac events may be calculated and displayed for each stratum.

Furthermore, the cardiac event prediction information presentation unit 90 uses not only the Euclidean distance of the 9-dimensional CABs vector immediately after admission and the first outpatient, but also the Euclidean distance of the 9-dimensional CABs vector immediately after admission and immediately before discharge. Event prediction information may be displayed.
In addition, the cardiac event prediction information presentation unit 90 replaces the Euclidean distance or, together with the Euclidean distance, with a 9-dimensional movement vector from the 9-dimensional CABs vector immediately after admission to the 9-dimensional CABs vector immediately before discharge, and discharge. Cardiac event prediction information may be displayed using the angle formed by the 9-dimensional CABs vector at the time immediately before and the 9-dimensional movement vector from the 9-dimensional CABs vector at the time of the first outpatient visit.
The cardiac event prediction information presentation unit 90 stratifies the ADHF patient group using one or more threshold values for the Euclidean distance and the angle formed by the nine-dimensional movement vectors, and divides the ADHF patient group into a plurality of layers after discharge or after the first outpatient. A score expressing the risk of cardiac event occurrence, which is calculated in association with the readmission rate and readmission rate of the patient, may be displayed.

The cardiac function stratification system 3 described above includes at least one processor, which includes a data acquisition unit 10, a multidimensional vector configuration unit 20, an inter-vector distance calculation unit 30, a stratification unit 40, and two. It functions as a dimensional coordinate calculation unit 60. Further, the processor may function as a part of the display unit 50, the cardiac function state point display unit 70, the alert notification unit 80, and the cardiac event prediction information presentation unit 90.
That is, the cardiac function stratification system 3 includes at least one processor that executes an instruction and a storage unit that stores a program. The program gets the processor to obtain biological marker data related to the subject's cardiac function at multiple time points, constructs a multidimensional vector from the biological marker data at multiple time points, and at least first from multiple time points. Select two or more time points of the point and the second point, calculate the inter-vector distance between the multidimensional vectors at the two time points, compare the inter-vector distance with a predetermined threshold, and based on the result of the comparison. The subjects are stratified and the commands for calculating the coordinates on the two-dimensional plane corresponding to a plurality of multidimensional vectors are executed by using a mathematical method.

<Effect of the third embodiment>
The cardiac function stratification system 3 according to the third embodiment has the following effects in addition to the effects (1) to (4) described in the first or second embodiment.
(5) The cardiac function stratification system 3 is a cardiac event prediction information presentation unit that predicts the cardiac event of the ADHF patient and displays the cardiac event prediction information based on the test result obtained by performing the CAB test on the ADHF patient. Has 90. Therefore, the doctor can refer to the cardiac event prediction information and extract about 90% of the patient group in which the cardiac event is unlikely to occur in one year after the first outpatient, for example, at the first outpatient. This prevents physicians from providing excessive medical care to patients with heart failure who have a low risk of cardiac events.

(6) The cardiac function stratification system 3 can also perform a CABs test on an ADHF patient at the start of medication treatment after hospitalization and several days after the start of medication treatment, and present cardiac event prediction information. In this case, the doctor can grasp the therapeutic effect of the drug based on the cardiac event prediction information. In addition, the doctor can easily grasp the effect of changing the combination of drugs and the usage / dose at the time of ward treatment based on the cardiac event prediction information.

(7) The cardiac function stratification system 3 can confirm the therapeutic effect of cardiac rehabilitation for a heart failure patient by presenting cardiac event prediction information. For example, when exercise therapy, which is one of cardiac rehabilitation, is started, a 9-dimensional CABs vector at each time point is constructed from the results of CABs tests performed weeks or months after the start of exercise therapy. Compare the distance with a preset threshold. As a result, the doctor can easily grasp the effect of the exercise therapy based on the cardiac event prediction information. In addition, when the prescription of the exercise therapy is changed, the doctor can easily grasp the effect of the exercise therapy based on the cardiac event prediction information.

5. Fourth Embodiment <Structure of Cardiac Function Stratification System>
Hereinafter, the cardiac function stratification system 4 according to the second embodiment will be described with reference to FIGS. 2 to 15 with reference to FIG. 19.

FIG. 19 is a block diagram showing a configuration example of the cardiac function stratification system 4. As shown in FIG. 19, the cardiac function stratification system 4 includes a data acquisition unit 10, a multidimensional vector configuration unit 20, a multidimensional movement vector configuration unit 25, an inter-vector angle calculation unit 30A, a stratification unit 40A, and a display. The part 50 is provided. That is, the cardiac function stratification system 4 newly includes the multidimensional movement vector configuration unit 25, and replaces the inter-vector distance calculation unit 30 and the stratification unit 40 with the inter-vector angle calculation unit 30A and the stratification unit 40A. It is different from the cardiac function stratification system 1 according to the first embodiment in that it is provided with.
Hereinafter, the multidimensional movement vector configuration unit 25, the inter-vector angle calculation unit 30A, and the stratification unit 40A will be described in detail. The data acquisition unit 10, the multidimensional vector configuration unit 20, and the display unit 50 are the same as those in the first embodiment, and thus the description thereof will be omitted.

(Multidimensional movement vector component)
The multidimensional movement vector constituent unit 25 constitutes a movement vector between the multidimensional vectors at two selected time points among the multidimensional vectors composed of the multidimensional vector constituent unit 20. For example, the multidimensional movement vector component 25 selects at least three time points of the first point, the second point, and the third point from the plurality of time points from which the biological marker data is acquired, and at each time point. Construct a movement vector between multidimensional vectors. That is, the multidimensional movement vector component 25 includes a first multidimensional movement vector, which is a movement vector between the multidimensional vectors at the first point and the second point, and multiple points at the second and third points. It constitutes a second multidimensional movement vector, which is a movement vector between dimensional vectors, and a third multidimensional movement vector, which is a movement vector between the multidimensional vectors at the first point and the third point.

(Angle between vectors calculation unit)
The inter-vector angle calculation unit 30A calculates the angle formed by the multidimensional movement vectors obtained by the multidimensional movement vector configuration unit 25. Specifically, the inter-vector angle calculation unit 30A calculates the first angle, which is the angle between the first multidimensional movement vector and the second multidimensional movement vector configured by the multidimensional movement vector configuration unit 25. .. Similarly, the inter-vector angle calculation unit 30A calculates a second angle, which is an angle between the first multidimensional movement vector and the third multidimensional movement vector configured by the multidimensional movement vector configuration unit 25. Similarly, the inter-vector angle calculation unit 30A calculates a third angle which is an angle between the second multidimensional movement vector and the third multidimensional movement vector configured by the multidimensional movement vector constituent unit 25. To do.

The three points (first point, second point, and third point) to be selected are preferably immediately after admission, immediately before discharge, and at the first or second outpatient visit after discharge. ..
The inter-vector angle calculation unit 30A outputs the calculated inter-vector angle to the stratification unit 40A.
The inter-vector angle calculation unit 30A calculates, for example, the angle between the CABs vectors between the 9-dimensional vectors at the time of admission, immediately before discharge, and the first outpatient for each patient with heart failure.

(Stratization Department)
The stratification unit 40A compares the inter-vector angle calculated by the inter-vector angle calculation unit 30A with a predetermined threshold value, and stratifies the subject based on the result of the comparison. The stratification unit 40 displays the comparison result or the stratification result on the display unit 50.

The stratification unit 40A acquires the inter-vector angles (first to third angles) between the three 9-dimensional CABs vectors calculated by the inter-vector angle calculation unit 30A. The stratification unit 40A compares the acquired inter-vector angle with an angle threshold value which is a threshold value for a predetermined angle. The angle threshold value is an example of the threshold value, and is stored in a memory (not shown) included in the stratification unit 40A or the cardiac function stratification system 1. The threshold value stored in the memory may be stored in advance or may be rewritten by the control of a processor (not shown).

The stratification unit 40A compares the first angle, the second angle, and the third angle with the predetermined first angle threshold value, second angle threshold value, and third angle threshold value. The first angle comparison result, the second angle comparison result, and the third angle comparison result are obtained. The stratification unit 40A stratifies the subjects based on any one or more of the results of these comparisons.

<Effect of Fourth Embodiment>
The cardiac function stratification system 1 according to the fourth embodiment has the same effect as that of the first embodiment.

Although the specific configuration of the present disclosure has been described above with respect to each embodiment, the scope of the present disclosure is not limited to the illustrated and described exemplary embodiments, and the present disclosure is intended. It also includes all embodiments that provide equal effect. Furthermore, the scope of the present disclosure is not limited to the combination of technical features defined by the claims, but may be defined by any desired combination of specific features among all disclosed features.

For example, the scope of the present disclosure is not limited to heart failure, but the primary diseases of heart failure are hypertension, ischemic heart disease (myocardial infarction), arrhythmia (atrial fibrillation, etc.), valvular disease, cardiomyopathy. Also includes application to heart diseases such as congenital heart disease.
Further, the inter-vector angle calculation 30A described in the cardiac function stratification system 4 may be combined with the cardiac function stratification systems 1 to 3. In this case, the stratification unit stratifies the subjects based on one or more of the comparison result of the Euclidean distance and the comparison result of the inter-vector angle. For example, when three time points, a first time point, a second time point, and a third time point, are selected, the stratification unit determines the first distance comparison result, the second distance comparison result, and the third distance. Subjects are stratified based on any one or more of the comparison result, the first angle comparison result, the second angle comparison result, and the third angle comparison result.

1, 2, 3 Coordinate function stratification system 10 Data acquisition unit 20 Multidimensional vector configuration unit 25 Multidimensional movement vector configuration unit 30 Inter-vector distance calculation unit 30A Inter-vector angle calculation unit 40, 40A Stratification unit 50 Display unit 60 Two-dimensional coordinate calculation unit 70 Cardiac function state point display unit 80 Alert notification unit 90 Cardiac event prediction information presentation unit

Claims (16)

A data acquisition unit that acquires biological marker data related to the subject's cardiac function at multiple time points,
A multidimensional vector component that constitutes a multidimensional vector from the biological marker data at the plurality of time points,
An inter-vector distance calculation unit that selects at least two time points, the first point and the second point, from the plurality of time points and calculates the inter-vector distance between the multidimensional vectors at the two time points.
A stratification unit that compares the inter-vector distance with a predetermined threshold value and stratifies the subject based on the result of the comparison.
Cardiac functional stratification system with. The inter-vector distance calculation unit calculates the daily average distance of the inter-vector distance from the inter-vector distance and the time at the two time points.
The cardiac function stratification system according to claim 1, wherein the stratification unit compares the daily average distance with the threshold value and stratifies the subject based on the result of the comparison. The inter-vector distance calculation unit selects three time points including the first point and a third point different from the second point from the plurality of time points, and the first point and the second point. The first distance, which is the distance between the multidimensional vectors at the points, the second distance, which is the distance between the multidimensional vectors at the second point and the third point, the first point, and the third point. Calculate the third distance, which is the distance between the multidimensional vectors at the point of
The stratifying unit determines the first distance comparison result of comparing the first distance with the predetermined first distance threshold, and the second distance and the predetermined second distance threshold. The subjects are stratified based on any one or more of the second distance comparison result compared and the third distance comparison result comparing the third distance with a predetermined third distance threshold. The cardiac function stratification system according to claim 1. A data acquisition unit that acquires biological marker data related to the subject's cardiac function at multiple time points,
A multidimensional vector component that constitutes a multidimensional vector from the biological marker data at the plurality of time points,
Multidimensional vector at the first point and the second point based on the multidimensional vector at at least the first point, the second point and the third point selected from the plurality of time points. The first multidimensional movement vector that is the angle between the first multidimensional movement vector that is the movement vector between and the second multidimensional movement vector that is the movement vector between the multidimensional vectors at the second point and the third point. An angle, a second angle that is the angle between the first multidimensional movement vector and a third multidimensional movement vector that is a movement vector between the first point and the multidimensional vector at the third point, and An inter-vector angle calculation unit that calculates a third angle, which is an angle between the second multidimensional movement vector and the third multidimensional movement vector,
The result of the first angle comparison comparing the first angle with the predetermined first angle threshold value, and the second angle comparison comparing the second angle with the predetermined second angle threshold value. With the stratification unit that stratifies the subject based on the result and any one or more of the third angle comparison results comparing the third angle with the predetermined third angle threshold value. ,
Cardiac functional stratification system with. A first point and a second point composed of the multidimensional vector component by selecting at least three or more time points of the first point, the second point, and the third point from the plurality of time points. And extract the multidimensional vector at the third point,
The first multidimensional movement vector, which is a movement vector between the multidimensional vector at the first point and the multidimensional vector at the second point, and the multidimensional vector at the second point and the third point. A multidimensional movement vector constituting a second multidimensional movement vector which is a movement vector between the two, and a third multidimensional movement vector which is a movement vector between the multidimensional movement vectors at the first point and the third point. The cardiac function stratification system according to claim 4, further comprising a movement vector component. A third, which is the distance between the multidimensional vector at the first point and the second point by selecting three time points including at least the first point, the second point, and the third point from the plurality of time points. One distance, the second distance which is the distance between the multidimensional vectors at the second point and the third point, and the distance between the multidimensional vectors at the first point and the third point. Equipped with an inter-vector distance calculation unit that calculates the third distance
The stratifying unit determines the first distance comparison result of comparing the first distance with the predetermined first distance threshold, and the second distance and the predetermined second distance threshold. Second distance comparison result compared, third distance comparison result comparing the third distance with a predetermined third distance threshold, the first angle comparison result, the second angle comparison result , And the cardiac function stratification system according to claim 4, wherein the subject is stratified based on any one or more of the third angle comparison results. Claims 1 to 6 further include a cardiac event prediction information presentation unit that predicts the subject's cardiac event based on the stratification result of the subject in the stratification unit and presents the cardiac event prediction information. The cardiac function stratification system according to any one item. The cardiac function stratification system according to claim 1 or 2, wherein the two time points are either immediately after admission, immediately before discharge, or at the first outpatient clinic after discharge. The cardiac function stratification system according to any one of claims 3 to 6, wherein the three time points are immediately after admission, immediately before discharge, and at the first or second outpatient time after discharge. .. The cardiac function according to any one of claims 1 to 9, wherein the data acquisition unit acquires the biological marker data based on the electrocardiographic data and the heart sound data simultaneously measured from the subject. Stratification system. A two-dimensional coordinate calculation unit that calculates coordinates on a two-dimensional plane corresponding to the plurality of multidimensional vectors composed of the multidimensional vector configuration unit by using a mathematical method.
Based on the coordinates on the two-dimensional plane, the points corresponding to the plurality of multidimensional vectors are displayed on the two-dimensional plane as the cardiac function state points representing the plurality of cardiac function states, and the plurality of cardiac function state points are displayed. And the cardiac function state point display part that draws by connecting with a line segment,
The cardiac function stratification system according to any one of claims 1 to 10. The cardiac function stratification system according to claim 11, wherein the mathematical method is a multidimensional scaling method or an algorithm capable of two-dimensional visualization. Information including medication, doctor's findings, diagnosis, and medical history is associated with the cardiac function state point.
The cardiac function stratification system according to claim 11 or 12. The corresponding multidimensional vector is associated with the cardiac function state point.
The cardiac function stratification system according to any one of claims 11 to 13. The cardiac function stratification system according to any one of claims 11 to 14, which displays a risk level region indicating a risk level according to the risk of a cardiac event on the two-dimensional plane. The cardiac function stratification system according to claim 15, further comprising an alert notification unit that notifies an alert when the line segment intersects the boundary of the risk level region.

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