Program, information processing method, and information processing system

Abstract

[Problem] To provide a program, an information processing method, an information processing system, and the like with which it is possible to detect HFpEF early. [Solution] According to one aspect of the present invention, there is provided a program configured to cause a computer to execute an acquisition step, a calculation step, and an output step. In the acquisition step, first electrocardiogram data for a first subject is acquired. In the calculation step, an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by the left ventricular ejection fraction, and an index corresponding to the expected value of the left ventricular ejection fraction are calculated on the basis of the first electrocardiogram data and reference information. The reference information indicates the relationship between second electrocardiogram data for a second subject and the indexes. In the output step, the calculated indexes are outputted. The index corresponding to HFpEF is at least one from among the probability that HFpEF has developed, an expected value calculated from the probability, and information obtained by scaling the expected value to a prescribed range.

Description

Program, information processing method and information processing system

[0001] The present invention relates to a program, an information processing method, and an information processing system.

[0002] US Patent No. 6,299,949 discloses an assay for assessing heart failure.

[0003] The assay is described as an immunoassay method for detecting and / or monitoring cardiovascular disease in a patient and / or assessing the likelihood or severity of cardiovascular disease in a patient, comprising contacting a biological fluid sample from the patient with a monoclonal antibody that specifically binds to a C-terminal epitope in the C5 domain of the α3 chain of type VI collagen and / or contacting a biological fluid sample from the patient with a monoclonal antibody that specifically binds to a C-terminal neo-epitope in the N-terminal propeptide of type III collagen.

[0004] Special Publication No. 2022-535513

[0005] Heart failure is classified into three phenotypes based on the left ventricular ejection fraction. Among these classified phenotypes, HFpEF is heart failure with a preserved left ventricular ejection fraction, making early detection difficult.

[0006] In view of the above circumstances, the present invention provides a program, an information processing method, an information processing system, and the like that are capable of detecting HFpEF at an early stage.

[0007] According to one aspect of the present invention, there is provided a program configured to cause a computer to execute an acquisition step, a calculation step, and an output step, wherein the acquisition step acquires first electrocardiogram data of a first subject, the calculation step calculates an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, and an index corresponding to an expected value of the left ventricular ejection fraction based on the first electrocardiogram data and reference information, the reference information being information indicating the relationship between the second electrocardiogram data of a second subject and the index, and the output step outputs the calculated index, and the index corresponding to HFpEF is at least one of the probability of developing HFpEF, an expected value calculated from the probability, and information obtained by scaling the expected value within a predetermined range.

[0008] The above aspect provides an improvement in the control function of a computer in the technical field related to heart failure, in that it is possible to detect HFpEF early, which is particularly difficult to detect early. That is, according to this aspect, the function of a computer can be improved to achieve at least one of the following (1) to (4): (1) The processing speed of the computer can be increased. (2) Power consumption of the computer can be reduced. (3) The communication speed of the computer can be increased. (4) The resources saved in the computer can be used for other core functions.

[0009] According to this embodiment, HFpEF can be detected early.

[0010] 1 is a configuration diagram showing an information processing system 100. FIG. 2 is a block diagram showing the hardware configuration of an information processing device 200. FIG. 3 is a block diagram showing the hardware configuration of a terminal 300. FIG. 4 is a block diagram showing functions realized by the information processing device 200 (control unit 210). FIG. 5 is an activity diagram showing the flow of an information processing method executed by the information processing device 200. FIG. 6 is a diagram showing the contents displayed on a display unit 330 of the terminal 300.

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to the accompanying drawings. Various features shown in the following embodiments can be combined with each other.

[0012] Incidentally, a program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0013] Furthermore, various information processing according to an embodiment may realize input and output corresponding to the input. Here, the form of information referenced in such information processing (hereinafter referred to as reference information) is not limited as long as an output is obtained as a result of the input. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a decision formula such as a regression formula constructed using a statistical method), a trained model that has previously trained the correlation between input and output, or a large-scale language model that can output a desired result by inputting a prompt.

[0014] In one embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In one embodiment, various information is handled, and this information is represented, for example, by physical values ​​of signal values ​​representing voltage or current, high or low signal values ​​as a binary bit set consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculations can be performed on the circuit in the broad sense.

[0015] Furthermore, a circuit in a broad sense is a circuit realized by at least an appropriate combination of a circuit, circuitry, a processor, a memory, etc. The processor may be a general-purpose processor or a dedicated circuit. That is, it includes application specific integrated circuits (ASICs), programmable logic devices (e.g., simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)), etc.

[0016] 1. Hardware Configuration In Section 1, the hardware configuration of this embodiment will be described.

[0017] 1-1. Information Processing System 100 FIG. 1 is a configuration diagram illustrating an information processing system 100. The information processing system 100 includes an information processing device 200, a terminal 300, and an electrocardiograph 400, which are connected via a network. These components will be further described. Here, a system exemplified as the information processing system 100 is composed of one or more devices or components. Therefore, for example, even the information processing device 200 alone can become a system exemplified as the information processing system 100.

[0018] 2 is a block diagram showing the hardware configuration of the information processing device 200. The information processing device 200 has a control unit 210, a storage unit 220, and a communication unit 250, and these components are electrically connected via a communication bus 260 inside the information processing device 200. Each component will be further described below.

[0019] The control unit 210 processes and controls the overall operations related to the information processing device 200. The control unit 210 is, for example, a central processing unit (CPU) (not shown). The control unit 210 realizes various functions related to the information processing device 200 by reading out predetermined programs stored in the storage unit 220. In other words, information processing by software stored in the storage unit 220 is specifically realized by the control unit 210, which is an example of hardware, and can be executed as each functional unit included in the control unit 210. This will be described further in Section 2. Note that the control unit 210 is not limited to being a single unit, and multiple control units 210 may be provided for each function. A combination of these may also be used.

[0020] The storage unit 220 stores various information necessary for information processing of the information processing device 200. This may be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs related to the information processing device 200 executed by the control unit 210, or as a memory such as a random access memory (RAM) that stores temporarily required information related to program calculations (arguments, arrays, etc.), or may be a combination of these.

[0021] The communication unit 250 is preferably a wired communication means such as USB, IEEE 1394, Thunderbolt (registered trademark), or wired LAN network communication, but may also include wireless LAN network communication, mobile communication such as 5G / LTE / 3G, Bluetooth (registered trademark) communication, etc. as needed. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, the information processing device 200 communicates various information with the terminal 300 via the communication unit 250 over a network.

[0022] 3 is a block diagram showing the hardware configuration of the terminal 300. The terminal 300 has a control unit 310, a storage unit 320, a display unit 330, an input unit 340, and a communication unit 350, and these components are electrically connected inside the terminal 300 via a communication bus 360. Descriptions of the control unit 310, the storage unit 320, and the communication unit 350 are omitted here because they are substantially the same as the descriptions of the control unit 210, the storage unit 220, and the communication unit 250 in the information processing device 200. Note that the terminal 300 may be, for example, a desktop personal computer, a laptop computer, a smartphone, a tablet terminal, or the like.

[0023] The display unit 330 may be included in the housing of the terminal 300 or may be externally attached. The display unit 330 displays a graphical user interface (GUI) screen that can be operated by the user. This is preferably implemented by selectively using display devices such as a CRT display, a liquid crystal display, an organic EL display, and a plasma display depending on the type of terminal 300. In the following description, the display unit 330 is assumed to be included in the housing of the terminal 300.

[0024] The input unit 340 may be included in the housing of the terminal 300 or may be externally attached. For example, the input unit 340 may be implemented as a touch panel integrated with the display unit 330. A touch panel allows a user to input tapping, swiping, and the like. Of course, a switch button, a mouse, a QWERT keyboard, or the like may be used instead of a touch panel. That is, the input unit 340 accepts an operation input made by the user. The input is transferred as a command signal to the control unit 310 via the communication bus 360. The control unit 310 can then execute predetermined control and calculation as necessary.

[0025] 1.4 Electrocardiograph 400 The electrocardiograph 400 is configured to acquire data relating to temporal fluctuations in the action potential of myocardial cells accompanying the beating of the heart as electrocardiogram data. The electrocardiograph 400 may be, for example, a 12-lead electrocardiograph or a wearable device with an electrocardiograph function, or may be a vector electrocardiograph, a long-term recording electrocardiograph, a body surface potential meter, an automatic electrocardiograph, or the like, as appropriate depending on the application.

[0026] The electrocardiograph 400 is connected to the communication unit 250 in the information processing device 200 via a network and is configured to be able to transfer acquired electrocardiogram data to the information processing device 200. Note that the electrocardiograph 400 does not necessarily have to have a communication unit. In this case, the acquired electrocardiogram data may be recorded on a recording medium such as a memory card, transferred from the recording medium to the terminal 300, and transferred from the terminal 300 to the information processing device 200.

[0027] 2. Functional Configuration The functional configuration of this embodiment will be described in Section 2. As described above, information processing by software stored in the storage unit 220 is specifically realized by the control unit 210, which is an example of hardware, and can be executed as each functional unit included in the control unit 210.

[0028] 4 is a block diagram showing functions realized by the information processing device 200 (control unit 210). As described above, the information processing device 200 (information processing system) includes the control unit 210. Specifically, the information processing device 200 (control unit 210) is configured to execute each step of the program of this embodiment. The information processing device 200 (control unit 210) includes an acquisition unit 211, a calculation unit 212, and an output unit 213, corresponding to each step of the program of this embodiment. Here, the program of this embodiment is configured to cause a computer such as the information processing device 200 to execute an acquisition step, a calculation step, and an output step.

[0029] The acquiring unit 211 is configured to acquire various information. The acquiring unit 211 is configured to execute an acquiring step. For example, the acquiring unit 211 acquires first electrocardiogram data of a first subject from the electrocardiograph 400.

[0030] The calculation unit 212 is configured to calculate various information. The calculation unit 212 is configured to execute a calculation step. For example, the calculation unit 212 calculates an index corresponding to HFpEF (hereinafter also referred to as an "HFpEF index"), which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, based on the acquired first electrocardiogram data and reference information. The reference information is information indicating the relationship between the index and second electrocardiogram data of a second subject different from the first subject.

[0031] Here, heart failure phenotypes based on left ventricular ejection fraction are classified into three types: HFpEF, HFrEF, and HFmrEF. HFpEF (heart failure with preserved ejection fraction) is defined as heart failure with preserved ejection fraction, defined as a left ventricular ejection fraction of 50% or more. HFrEF (heart failure with reduced ejection fraction) is defined as heart failure with reduced ejection fraction, defined as a left ventricular ejection fraction of less than 40%. HFmrEF (heart failure with mid-range ejection fraction) is defined as heart failure with a mildly reduced left ventricular ejection fraction, and is defined as a left ventricular ejection fraction of 40% or more but less than 50%.

[0032] The output unit 213 is configured to output various information. The output unit 213 is configured to execute an output step. For example, the output unit 213 outputs the calculated index to the terminal 300.

[0033] 3. Information Processing Method In Section 3, the flow of the information processing method executed by the information processing device 200 described above will be described. This information processing method includes each step of the program of this embodiment. This information processing method includes an acquisition step, a calculation step, and an output step. In the acquisition step, first electrocardiogram data of a first subject is acquired. In the calculation step, an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, is calculated based on the acquired first electrocardiogram data and reference information. The reference information is information indicating the relationship between second electrocardiogram data of a second subject and the index. In the output step, the calculated index is output.

[0034] 5 is an activity diagram showing the flow of an information processing method executed by information processing device 200. Below, an explanation will be given along with each activity in this activity diagram.

[0035] The electrocardiograph 400 acquires first electrocardiogram data of a first subject, which is an arbitrary subject (activity A110).

[0036] The first electrocardiogram data may consist of 1 to 50 beats. Specifically, the first electrocardiogram data may consist of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 beats, or may be within a range between any two of the values ​​exemplified here. Preferably, the first electrocardiogram data consists of 1 to 2 beats. In this way, the information processing device 200 can calculate and output an HFpEF index even with a small amount of data. Therefore, the time required to acquire the first electrocardiogram data can be shortened.

[0037] The first electrocardiogram data may consist of waveforms for a period of 5 to 300 seconds. Specifically, for example, the waveform may be composed of waveforms over 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, or 300 seconds, and may be within a range between any two of the numerical values ​​exemplified here. Preferably, the first electrocardiogram data is composed of waveforms for 5 to 10 seconds. In this way, the information processing device 200 can calculate and output the HFpEF index even with a small amount of data. Therefore, the time required to acquire the first electrocardiogram data can be shortened.

[0038] The first electrocardiogram data may be data acquired from electrodes corresponding to any one of the 12 leads. Preferably, the one lead is Lead I acquired from the right arm and left arm of the first subject. Here, the right arm refers to the range from the right hand to the base of the right arm. Similarly, the left arm refers to the range from the left hand to the base of the left arm. Therefore, the electrodes for acquiring Lead I may be attached at any position between the hand and the base of the arm. According to this aspect, Lead I, which can be easily acquired, can be used. Therefore, an increase in the burden on the first subject due to acquisition of the first electrocardiogram data can be suppressed.

[0039] Next, the electrocardiograph 400 transmits the acquired first electrocardiogram data to the information processing device 200 via the network (activity A120).

[0040] Next, the control unit 210 in the information processing device 200 receives the first electrocardiogram data transmitted from the electrocardiograph 400 (activity A130). In other words, in the acquisition step, the first electrocardiogram data of the first subject is acquired. In activity A130, for example, the following two-stage information processing is executed: (1) The communication unit 250 receives the first electrocardiogram data transmitted from the electrocardiograph 400. (2) The control unit 210 stores the received first electrocardiogram data in the storage unit 220.

[0041] Next, the control unit 210 in the information processing device 200 preprocesses the first electrocardiogram data (activity A140). Here, preprocessing includes, for example, trend removal, motion artifact removal, noise removal, waveform data extraction for each heartbeat, normalization, etc., and is performed in an appropriate combination. Preferably, the preprocessing is performed in the order of trend removal, motion artifact removal, noise removal, waveform data extraction for each heartbeat, and normalization. Activity A140 performs, for example, the following three stages of information processing: (1) The control unit 210 reads the first electrocardiogram data and predetermined parameters from the storage unit 220. (2) The control unit 210 applies predetermined parameters to the raw data of the first electrocardiogram data to preprocess the first electrocardiogram data. (3) The control unit 210 stores the preprocessed first electrocardiogram data in the storage unit 220. Activity A140 removes noise contained in the first electrocardiogram data, thereby improving the accuracy of the HFpEF index.

[0042] Next, the control unit 210 in the information processing device 200 reads out first clinical data of the first subject (activity A150). Here, the first clinical data may include at least one of age, sex, BMI (Body Mass Index), PWTT (Pulse Wave Transit Time), blood pressure, heart rate, SDNN (Standard Deviation of the NN Interval), CVRR (Coefficient of Variation of RR Interval), atrial fibrillation, and HRV (Heart Rate Variability). The same applies to second clinical data described later. In activity A150, for example, the following information processing is executed: The control unit 210 reads the first clinical data from the storage unit 220. According to activity A150, by using the first clinical data in addition to the first electrocardiogram data, the accuracy of the HFpEF index can be improved.

[0043] Next, the control unit 210 in the information processing device 200 calculates an HFpEF index based on the first electrocardiogram data of the first subject, the first clinical data of the first subject, and the reference information (activity A160). In other words, in the calculation step, an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, is calculated based on the first electrocardiogram data, the first clinical data of the first subject, and the reference information. The HFpEF index may be presented as information useful for detecting HFpEF, such as the probability of developing HFpEF, an expected value calculated from the probability, or information obtained by scaling the expected value within a predetermined range. In activity A160, for example, the following three stages of information processing are performed: (1) The control unit 210 further reads out the preprocessed first electrocardiogram data and the reference information from the storage unit 220. (2) The control unit 210 inputs the preprocessed first electrocardiogram data and the first clinical data into the reference information and calculates an HFpEF index. (3) The control unit 210 stores the calculated HFpEF index in the storage unit 220.

[0044] Here, the reference information is information indicating a relationship between the second electrocardiogram data of the second subject, the second clinical data of the second subject, and the HFpEF index. Preferably, the reference information is a trained model that has trained the relationship between the second electrocardiogram data, the second clinical data, and the HFpEF index. Use of such a trained model can further improve the accuracy of HFpEF detection.

[0045] Here, the second subject includes a subject who has developed HFpEF but has no subjective symptoms of heart failure. That is, the trained model of this embodiment trains not only electrocardiogram data of subjects who have subjective symptoms of heart failure due to the onset of HFpEF (subjects classified as "NYHA Grade II" to "NYHA Grade IV"), but also electrocardiogram data of subjects who previously developed HFpEF and had subjective symptoms of heart failure but currently have no subjective symptoms of heart failure (subjects currently classified as "NYHA Grade I"). That is, the trained model of this embodiment trains a variety of electrocardiogram data related to HFpEF. Therefore, even in the case of early-stage HFpEF, which is difficult to diagnose even with ultrasound examination, an HFpEF index is output, which can be presented as useful information for HFpEF screening. According to this aspect, HFpEF can be detected more accurately even in patients who have no subjective symptoms, such as patients classified as "NYHA Grade I" or patients who are beginning to develop HFpEF for the first time.

[0046] Next, the control unit 210 in the information processing device 200 generates visual information (hereinafter simply referred to as "visual information") related to the HFpEF index as information visible on the terminal 300 (activity A170). In activity A170, for example, the following three stages of information processing are executed: (1) The control unit 210 reads the HFpEF index from the storage unit 220. (2) The control unit 210 executes a generation process to generate the visual information. (3) The control unit 210 stores the visual information in the storage unit 220.

[0047] Next, the control unit 210 in the information processing device 200 transmits visual information related to the HFpEF index to the terminal 300 (activity A180). In other words, in the output step, the calculated index is output. In activity A180, for example, the following two-stage information processing is executed: (1) The control unit 210 reads the visual information from the storage unit 220. (2) The control unit 210 transmits the visual information to the terminal 300 via the communication unit 250.

[0048] Next, the control unit 310 in the terminal 300 receives the visual information transmitted from the information processing device 200 (activity A190). In activity A190, for example, the following two-stage information processing is executed: (1) The communication unit 350 receives the visual information transmitted from the information processing device 200. (2) The control unit 310 stores the received visual information in the memory unit 320.

[0049] Next, the control unit 310 in the terminal 300 causes the display unit 330 to display the index of the HFpEF (activity A200). In activity A200, for example, the following two-stage information processing is executed: (1) The control unit 310 reads the received visual information from the storage unit 320. (2) The control unit 310 inputs the visual information to the display unit 330 via the communication bus 360. (3) The display unit 330 displays the index of the HFpEF.

[0050] 4. Display Examples Section 4 describes display examples of HFpEF indexes.

[0051] FIG. 6 is a diagram showing the content displayed on the display unit 330 of the terminal 300. In addition to the HFpEF index, the display unit 330 displays an HFrEF index and further displays an HFEF index. Here, the HFEF index represents an index corresponding to the expected value of the left ventricular ejection fraction as a concept that collectively represents each phenotype of heart failure. In FIG. 6, the HFEF index is calculated using the respective probabilities of HFpEF and HFrEF, and may also be calculated using the probability of HFmrEF. That is, in FIG. 6, in the calculation step of activity A160, an index corresponding to at least one of HFrEF and HFmrEF, which are phenotypes other than HFpEF, and an index corresponding to the expected value of the left ventricular ejection fraction are further calculated.

[0052] Each index displayed on the display unit 330 is set in the range from 0 to 100. The closer the HFpEF index is to 0, the lower the risk of HFpEF, and the closer it is to 100, the higher the risk of HFpEF. Similarly, the closer the HFrEF index is to 0, the lower the risk of HFrEF, and the closer it is to 100, the higher the risk of HFrEF. The HFEF index estimates the degree of left ventricular ejection fraction in heart failure, and the closer it is to 0, the higher the left ventricular ejection fraction in heart failure, and the closer it is to 100, the lower the left ventricular ejection fraction in heart failure. In other words, the HFEF index is an index that is calculated and displayed when the first subject is a patient who has developed heart failure.

[0053] In FIG. 6 , the HFEF index is "50," indicating that the degree of left ventricular ejection fraction of heart failure is moderate. Furthermore, the HFpEF index is "55" while the HFrEF index is "20," indicating that the HFpEF index is higher, indicating a stronger tendency toward HFpEF than toward HFrEF. Therefore, the display unit 330 in FIG. 6 displays "There appears to be a tendency toward HFpEF" as the measurement result of the electrocardiogram data. According to this aspect, the risk of each phenotype of heart failure can be presented.

[0054] According to this aspect, HFpEF, which is particularly difficult to diagnose, can be detected early. Furthermore, due to the simple configuration, the saved resources can be used for other core functions.

[0055] Although the embodiment of the present invention has been described above, the present invention is not limited to this and can be modified as appropriate within the scope of the technical idea of ​​the invention.

[0056] 5. Modifications Modifications of this embodiment will be described in Section 5. The following modifications can be combined as appropriate.

[0057] An aspect of the present embodiment may be a recording medium. The recording medium is a non-transitory computer-readable recording medium. The recording medium records the program of the present embodiment.

[0058] The control unit 210 performs writing (storing) and reading processes for various data and information in the memory unit 220, but this is not limited to this, and for example, the information processing for each activity may be performed using a register or cache memory within the control unit 210.

[0059] The output by the output unit 213 is not limited to transmitting the visual information related to the index to the terminal 300, but may be, for example, displayed on a display device of the information processing device 200.

[0060] The range of the index is not limited to the range of 0 to 100, and may be, for example, the range of 0 to 1 or the range of 0 to 10, and may be set as appropriate. Furthermore, the degree of weighting for each index may be set as appropriate, and the values ​​may be reversed. For example, in the HFEF index, the closer to 0, the lower the left ventricular ejection fraction during heart failure, and the closer to 100, the higher the left ventricular ejection fraction during heart failure.

[0061] The reference information is not limited to a trained model, but may also be a database that stores lookup tables, a function that represents the correspondence of values ​​that depend on certain variables, a mathematical model that mathematically relates multiple pieces of information, etc.

[0062] The electrocardiograph 400 may be configured to be able to communicate with the information processing device 200 via the terminal 300. In this case, the electrocardiograph 400 may be connected to the communication unit 350 in the terminal 300 via a network, or may be directly connected to the terminal 300.

[0063] The output unit 213 may be configured to output other items in addition to the HFpEF index. For example, the output unit 213 may further output the blood collection results of the first subject.

[0064] The reference information may be information indicating a relationship between the second electrocardiogram data of the second subject and the HFpEF index, regardless of the clinical data of the second subject, in which case the reference information may be a trained model that has trained the relationship between the second electrocardiogram waveform and the index.

[0065] The output unit 213 may display only the HFpEF index as the index of the heart failure phenotype. That is, as shown in activity A160, only the HFpEF index may be calculated. This aspect improves visibility when checking whether or not a patient has HFpEF.

[0066] The first electrocardiogram data is not limited to data using lead I, and may be data using other leads. Furthermore, the first electrocardiogram data may be data using multiple leads. The more leads used, the more accurate the index. According to this aspect, electrocardiogram data can be easily acquired, and the number of leads used can be adjusted depending on the purpose.

[0067] 6. Others The present invention may be provided in the following forms.

[0068] (1) A program configured to cause a computer to execute an acquisition step, a calculation step, and an output step, wherein the acquisition step acquires first electrocardiogram data of a first subject, the calculation step calculates an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, and an index corresponding to an expected value of the left ventricular ejection fraction based on the first electrocardiogram data and reference information, the reference information being information indicating the relationship between second electrocardiogram data of a second subject and the index, and the output step outputs the calculated index, and the index corresponding to HFpEF is at least one of the probability of developing HFpEF, an expected value calculated from the probability, and information obtained by scaling the expected value within a predetermined range.

[0069] According to this aspect, HFpEF can be detected early, and because of the simple configuration, the saved resources can be used for other core functions.

[0070] (2) In the program described in (1) above, the reference information is a trained model that has learned the relationship between the second electrocardiogram data and the index.

[0071] According to this aspect, it is possible to improve the accuracy of detecting HFpEF.

[0072] (3) In the program according to (1) or (2) above, the second subject includes a subject who has developed HFpEF but has no subjective symptoms of heart failure.

[0073] According to this embodiment, HFpEF can be detected more accurately even in patients who have no subjective symptoms, such as patients in the NYHA classification of "grade I" or patients who have just begun to develop their first episode of HFpEF.

[0074] (4) In the program described in any one of (1) to (3) above, the first electrocardiogram data is data obtained from an electrode corresponding to any one of 12 leads.

[0075] According to this embodiment, electrocardiogram data can be easily acquired.

[0076] (5) In the program described in (4) above, the one lead is lead I obtained from the right arm and left arm of the first subject.

[0077] According to this embodiment, it is possible to use lead I, which can be easily obtained.

[0078] (6) In the program described in any one of (1) to (5) above, in the calculation step, the index is calculated based on the first electrocardiogram data, the first clinical data of the first subject, and the reference information, and the reference information is information indicating the relationship between the second electrocardiogram data, the second clinical data of the second subject, and the index.

[0079] According to this aspect, the accuracy of detecting HFpEF can be further improved.

[0080] (7) In the program described in (6) above, the reference information is a trained model that has learned the relationship between the second electrocardiogram data, the second clinical data, and the index.

[0081] According to this aspect, the accuracy of detecting HFpEF can be further improved.

[0082] (8) A program according to any one of (1) to (7) above, wherein the calculation step further calculates an index corresponding to at least one of the phenotypes other than HFpEF, HFrEF and HFmrEF.

[0083] According to this embodiment, the risk of each phenotype of heart failure can be presented.

[0084] (9) An information processing method comprising the steps of the program described in any one of (1) to (8) above.

[0085] According to this aspect, HFpEF can be detected early, and because of the simple configuration, the saved resources can be used for other core functions.

[0086] (10) An information processing system comprising a control unit, the control unit being configured to execute each step of the program described in any one of (1) to (8) above.

[0087] According to this aspect, HFpEF can be detected early. In addition, because of the simple configuration, the saved resources can be used for other core functions. Of course, this is not limited to the above.

[0088] 100: Information processing system, 200: Information processing device, 210: Control unit, 211: Acquisition unit, 212: Calculation unit, 213: Output unit, 220: Storage unit, 250: Communication unit, 260: Communication bus, 300: Terminal, 310: Control unit, 320: Storage unit, 330: Display unit, 340: Input unit, 350: Communication unit, 360: Communication bus, 400: Electrocardiograph

Claims

1. A program configured to cause a computer to execute an acquisition step, a calculation step, and an output step, wherein the acquisition step acquires first electrocardiogram data of a first subject, the calculation step calculates an index corresponding to HFpEF, which is one of the phenotypes of heart failure classified by left ventricular ejection fraction, and an index corresponding to an expected value of the left ventricular ejection fraction, based on the first electrocardiogram data and reference information, the reference information being information indicating the relationship between second electrocardiogram data of a second subject and the index, and the output step outputs the calculated index, and the index corresponding to HFpEF is at least one of the probability of developing HFpEF, an expected value calculated from the probability, and information obtained by scaling the expected value within a predetermined range.

2. A program according to claim 1, wherein the reference information is a trained model that has trained the relationship between the second electrocardiogram data and the index.

3. The program according to claim 1 or 2, wherein the second subject includes a subject who has developed HFpEF but has no subjective symptoms of heart failure.

4. The program according to any one of claims 1 to 3, wherein the first electrocardiogram data is data acquired from an electrode corresponding to any one of 12 leads.

5. The program according to claim 4, wherein the one lead is lead I obtained from the right arm and the left arm of the first subject.

6. A program according to any one of claims 1 to 5, wherein in the calculation step, the index is calculated based on the first electrocardiogram data, the first clinical data of the first subject, and the reference information, and the reference information is information indicating the relationship between the second electrocardiogram data, the second clinical data of the second subject, and the index.

7. A program according to claim 6, wherein the reference information is a trained model that has trained the relationship between the second electrocardiogram data, the second clinical data, and the index.

8. A program according to any one of claims 1 to 7, wherein the calculation step further calculates an index according to at least one of the phenotypes other than HFpEF, HFrEF and HFmrEF.

9. An information processing method comprising the steps of the program according to any one of claims 1 to 8.

10. An information processing system comprising: a control unit configured to execute each step of the program according to any one of claims 1 to 8.

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