Program, information processing method, and information processing system

Abstract

To provide a program, an information processing method, and an information processing system capable of promptly detecting HFpEF.SOLUTION: A program is provided. The program is configured so as to allow a computer to execute an acquisition step, a calculation step, and an output step. In the acquisition step, first electrocardiogram data of a first specimen are acquired. In the calculation step, an index corresponding to HFpEF that is one of expression types of cardiac insufficiency grouped by a left ventricular ejection fraction on the basis of the first electrocardiogram data and reference information. The reference information shows a relationship between second electrocardiogram data of a second specimen and the index. In the output step, the calculated index is outputted.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] US Pat. No. 6,299,499 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. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2022-535513 Summary of the Invention [Problem to be solved by the invention]

[0005] Heart failure is classified into three phenotypes based on left ventricular ejection fraction. Among these phenotypes, HFpEF is a type of heart failure with 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. [Means for solving the problem]

[0007] According to one aspect of the present invention, there is provided a program. The program is configured to cause a computer to execute an acquiring step, a calculating step, and an outputting step. In the acquiring step, first electrocardiogram data of a first subject is acquired. In the calculating 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 and reference information. The reference information is information indicating the relationship between second electrocardiogram data of a second subject and the index. In the outputting step, the calculated index is output.

[0008] According to this embodiment, HFpEF can be detected early. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a configuration diagram illustrating an information processing system 100. [Figure 2] FIG. 2 is a block diagram showing the hardware configuration of an information processing device 200. [Figure 3] FIG. 2 is a block diagram showing the hardware configuration of the terminal 300. [Figure 4] FIG. 2 is a block diagram showing functions realized by an information processing device 200 (control unit 210). [Figure 5] 1 is an activity diagram showing the flow of an information processing method executed by information processing device 200. FIG. [Figure 6] FIG. 10 shows the contents displayed on a display unit 330 of a terminal 300. DETAILED DESCRIPTION OF THE INVENTION

[0010] 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.

[0011] Incidentally, the program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or may be provided so that it can be downloaded 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).

[0012] 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.

[0013] In one embodiment, a "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 and current, high and 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 a circuit in the broad sense.

[0014] 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. That is, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0015] 1. Hardware Configuration In Section 1, the hardware configuration of this embodiment will be described.

[0016] 1-1. Information Processing System 100 FIG. 1 is a configuration diagram showing 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.

[0017] 1-2. Information processing device 200 2 is a block diagram showing the hardware configuration of information processing device 200. 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 information processing device 200. Each component will be further described.

[0018] 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 further explained 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.

[0019] The storage unit 220 stores various information necessary for information processing by 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 information (arguments, arrays, etc.) temporarily required for program calculations. Alternatively, it may be implemented as a combination of these.

[0020] The communication unit 250 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as 5G / LTE / 3G, Bluetooth (registered trademark) communication, etc. as necessary. 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.

[0021] 1-3. Terminal 300 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. Explanations of the control unit 310, the storage unit 320, and the communication unit 350 are omitted because they are substantially the same as the explanations 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.

[0022] 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 screen of a graphical user interface (GUI) 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.

[0023] 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.

[0024] 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, a wearable terminal with an electrocardiograph function, or 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.

[0025] 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.

[0026] 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.

[0027] FIG. 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.

[0028] 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.

[0029] 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 according to HFpEF (hereinafter also referred to as "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.

[0030] Here, heart failure phenotypes based on left ventricular ejection fraction are classified into three: 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 greater. 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 mildly reduced ejection fraction, defined as a left ventricular ejection fraction of 40% or greater but less than 50%.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] The electrocardiograph 400 acquires first electrocardiogram data of a first subject, which is an arbitrary subject (activity A110).

[0035] The first electrocardiogram data may be composed of 1 to 50 beats. Specifically, the first electrocardiogram data may be composed 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 is composed 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.

[0036] The first electrocardiogram data may be composed of a waveform for 5 to 300 seconds. Specifically, for example, it 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 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 be data acquired from electrodes corresponding to any one of the 12 leads. Preferably, the one lead is lead I acquired from the right and left hands of the first subject. According to this aspect, lead I, which can be easily acquired, can be used. Therefore, it is possible to suppress an increase in the burden on the first subject due to acquisition of the first electrocardiogram data.

[0038] Next, the electrocardiograph 400 transmits the acquired first electrocardiogram data to the information processing device 200 via the network (activity A120).

[0039] 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 memory unit 220.

[0040] 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 these are performed in appropriate combinations. Preferably, the preprocessing is performed in the order of trend removal, motion artifact removal, noise removal, waveform data extraction for each heartbeat, and normalization. In activity A140, for example, the following three stages of information processing are performed: (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. According to activity A140, noise contained in the first electrocardiogram data can be removed, thereby improving the accuracy of the HFpEF index.

[0041] 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 the RR Interval), atrial fibrillation, and HRV (Heart Rate Variability). The same applies to second clinical data, which will be described later. In activity A150, for example, the following information processing is performed. The control unit 210 reads out 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.

[0042] 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 the HFpEF index. (3) The control unit 210 stores the calculated HFpEF index in the storage unit 220.

[0043] Here, the reference information is information indicating the 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.

[0044] 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 with NYHA classifications of "stage II" to "stage 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 "stage I" in the NYHA classification). That is, the trained model of this embodiment trains various electrocardiogram data related to HFpEF. Therefore, even in the case of early-stage HFpEF, which is difficult to diagnose even with ultrasound testing, 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 asymptomatic patients, such as patients with NYHA classification of "stage I" or those who are beginning to develop initial HFpEF.

[0045] Next, the control unit 210 in the information processing device 200 generates visual information related to the HFpEF index (hereinafter also simply referred to as "visual information") as information visible on the terminal 300 (activity A170). In activity A170, for example, the following three-stage information processing is executed: (1) The control unit 210 reads out 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.

[0046] 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.

[0047] 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.

[0048] Next, the control unit 310 in the terminal 300 causes the display unit 330 to display the HFpEF index (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 HFpEF index.

[0049] 4. Display example Section 4 explains examples of HFpEF index presentation.

[0050] 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 indicates 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.

[0051] 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.

[0052] In FIG. 6, the HFEF index is "50," indicating a moderate degree of left ventricular ejection fraction due to heart failure. Furthermore, since the HFpEF index is "55" and the HFrEF index is "20," 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 embodiment, the risk of each phenotype of heart failure can be presented.

[0053] According to this embodiment, 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.

[0054] 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.

[0055] 5. Variations In Section 5, a modification of this embodiment will be described.

[0056] 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.

[0057] The control unit 210 performs write processing (storage processing) and read processing of various data and information to the memory unit 220, but this is not limited to this, and for example, the information processing of each activity may be performed using a register or cache memory within the control unit 210.

[0058] 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 displayed on a display device of the information processing device 200, for example.

[0059] 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 can 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.

[0060] 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.

[0061] 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.

[0062] 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 sampling results of the first subject.

[0063] 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 this case, the reference information may be a trained model that has trained the relationship between the second electrocardiogram waveform and the index.

[0064] 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 the condition is HFpEF.

[0065] The first electrocardiogram data is not limited to data using lead I, and may use other leads. Furthermore, the first electrocardiogram data may use multiple leads. The more leads used, the more accurate the index. According to this embodiment, electrocardiogram data can be easily acquired, and the number of leads used can be adjusted depending on the purpose.

[0066] 6.Other It may be provided in the following manner.

[0067] (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, 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.

[0068] According to this embodiment, HFpEF can be detected early, and the simple configuration allows the saved resources to be used for other core functions.

[0069] (2) In the program described in (1) above, the reference information is a trained model that has trained the relationship between the second electrocardiogram data and the index.

[0070] According to this embodiment, it is possible to improve the accuracy of detecting HFpEF.

[0071] (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.

[0072] 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 "stage I" or patients who have just begun to develop their first episode of HFpEF.

[0073] (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.

[0074] According to this embodiment, electrocardiogram data can be easily acquired.

[0075] (5) In the program described in (4) above, the one lead is lead I obtained from the right hand and left hand of the first subject.

[0076] According to this embodiment, lead I, which can be easily obtained, can be used.

[0077] (6) A program according to any one of (1) to (5) above, 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.

[0078] According to this embodiment, the accuracy of detecting HFpEF can be further improved.

[0079] (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.

[0080] According to this embodiment, the accuracy of detecting HFpEF can be further improved.

[0081] (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.

[0082] According to this embodiment, the risk of each phenotype of heart failure can be presented.

[0083] (9) The program according to any one of (1) to (8) above, wherein the calculation step further calculates an index according to an expected value of the left ventricular ejection fraction.

[0084] According to this embodiment, it is possible to improve the visibility of the risk of heart failure.

[0085] (10) An information processing method comprising the steps of the program described in any one of (1) to (9) above.

[0086] According to this embodiment, HFpEF can be detected early, and the simple configuration allows the saved resources to be used for other core functions.

[0087] (11) 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 (9) above.

[0088] According to this embodiment, HFpEF can be detected early, and the simple configuration allows the saved resources to be used for other core functions. Of course, this is not the case. [Explanation of symbols]

[0089] 100: Information Processing Systems 200: Information processing device 210: Control unit 211: Acquisition Department 212: Calculation section 213: Output section 220: Storage section 250: Communications Department 260: Communication bus 300: Terminal 310: Control unit 320: Storage section 330: Display section 340: Input section 350: Communications Department 360: Communication bus 400: Electrocardiograph

Claims

1. A program, configured to cause a computer to perform an obtaining step, a calculating step, and an outputting step; In the acquiring 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 first electrocardiogram data and reference information; the reference information is information indicating a relationship between the second electrocardiogram data of the second subject and the index; In the output step, the calculated index is output. program.

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

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

4. 2. The program according to claim 1, the first electrocardiogram data is data acquired from an electrode corresponding to any one of 12 leads; program.

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

6. 2. The program according to claim 1, In the calculation step, the index is calculated based on the first electrocardiogram data, first clinical data of the first subject, and the reference information; the reference information is information indicating a relationship between the second electrocardiogram data, the second clinical data of the second subject, and the index. program.

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

8. 2. The program according to claim 1, In the calculation step, an index according to at least one of HFrEF and HFmrEF, which are the phenotypes other than HFpEF, is further calculated. program.

9. 2. The program according to claim 1, In the calculation step, an index according to an expected value of the left ventricular ejection fraction is further calculated. program.

10. An information processing method, comprising: The program comprises the steps of any one of claims 1 to 9. Information processing methods.

11. An information processing system, A control unit is provided, The control unit is configured to execute the steps of the program according to any one of claims 1 to 9. Information processing system.

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