Symptom determination program, information processing device, symptom determination method, and symptom determination system

Abstract

To provide a symptom determination program, an information processing device, a symptom determination method, and a symptom determination system which assist determination of a state of a preliminary step resulting in sarcopenia.SOLUTION: A body composition meter 1 comprises: body composition calculation means 100 which measures a patient's body electrically and calculates at least a muscle quantity and a bone quantity; and symptom determination means 102 which determines possibility of corresponding to pre-sarcopenia when the obtained muscle quantity and the bone quantity of the patient are less than respectively determined values, but determines possibility of corresponding to dynapenia when the muscle quantity is larger than a predetermined value and a ratio of an acquired grip to the muscle quantity of the patient is less than a predetermined value.SELECTED DRAWING: Figure 2

Description

Technical Field

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

Background Art

[0002] As a conventional technique, a symptom determination program for diagnosing sarcopenia early and simply has been proposed (see, for example, Patent Document 1).

[0003] The symptom determination program disclosed in Patent Document 1 includes an input unit that inputs information indicating the gender, weight, and lower leg circumference of an adult subject, and a determination unit that determines whether or not the subject has sarcopenia based on the information input to the input unit. The determination unit calculates a value of a substitute index used instead of the skeletal muscle index based on the information indicating the gender, weight, and lower leg circumference of the subject, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, although the above-described symptom determination program determines that the subject has sarcopenia, there is a problem that measurement of physical function (walking speed or five-time stand-up) is required to determine presarcopenia or dynapenia, which is a state as a stage prior to sarcopenia, and securing of personnel is required. Determining the symptoms at the previous stage is important from the viewpoint of preventing presarcopenia.

[0006] An object of the present invention is to provide a symptom determination program, an information processing apparatus, a symptom determination method, and a symptom determination system for assisting in determining a state in a stage prior to sarcopenia.

Means for Solving the Problems

[0007] One aspect of the present invention provides the following symptom determination program, information processing apparatus, symptom determination method, and symptom determination system in order to achieve the above object.

[0008] [1] A symptom determination program for causing a computer to function as a determination means for determining the possibility of presarcopenia when the muscle mass and bone mass of the acquired patient are smaller than predetermined values respectively. [2] The symptom determination program according to claim 1, wherein the determination means determines the possibility of dynapenia when the muscle mass is larger than a predetermined value and the ratio of the grip strength of the acquired patient to the muscle mass is smaller than a predetermined value. [3] The symptom determination program according to claim 1 or 2, wherein the determination means further determines the possibility of presarcopenia when the phase angle obtained by the bioelectrical impedance method is smaller than a predetermined value. [4] The symptom determination program according to claim 1 or 2, wherein the determination means determines sarcopenia when the muscle mass and bone mass of the acquired patient are smaller than predetermined values respectively. [5] The symptom determination program according to claim 1, wherein the determination means determines the possibility of presarcopenia based on the changes over time of the muscle mass and the bone mass. [6] The symptom determination program according to claim 2, wherein the determination means determines the possibility of dynapenia based on the changes over time of the muscle mass and the ratio of the grip strength to the muscle mass. [7] An information processing apparatus having a determination means for determining the possibility of presarcopenia when the muscle mass and bone mass of the acquired patient are smaller than predetermined values respectively. [8] A symptom determination method having a step of determining the possibility of presarcopenia when the muscle mass and bone mass of the acquired patient are smaller than predetermined values respectively. [9] A body composition analyzer that electrically measures a patient's body and calculates at least muscle mass and bone mass, An information processing device having a step of determining the possibility of presarcopenia when the muscle mass and bone mass of the patient obtained by the body composition analyzer are each smaller than a predetermined value, and a symptom determination system including the same. [Advantages of the Invention]

[0009] According to the inventions according to claims 1, 2, 7, 8, and 9, it is possible to assist in determining the state prior to sarcopenia. According to the invention according to claim 3, it is further possible to determine the possibility of presarcopenia when the phase angle obtained by the bioelectrical impedance method is smaller than a predetermined value. According to the invention according to claim 4, it is possible to determine sarcopenia when the muscle mass and bone mass of the patient obtained are each smaller than a predetermined value. According to the invention according to claim 5, it is possible to determine the possibility of presarcopenia based on the temporal changes in muscle mass and bone mass. According to the invention according to claim 6, it is possible to determine the possibility of dynapenia based on the temporal changes in muscle mass and the ratio of grip strength to muscle mass. [Brief Description of the Drawings]

[0010]

Figure 1

Figure 2

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Figure 5

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Figure 8

Figure 9

Mode for Carrying Out the Invention

[0011] [Embodiment] (Configuration of Symptom Determination System) Figure 1 is a schematic diagram showing an example of the configuration of the symptom determination system according to the embodiment.

[0012] This symptom determination system is configured by connecting a body composition meter 1 including an information processing device therein and a grip strength meter 2 to be communicable with each other. The body composition meter 1 and the grip strength meter 2 are each operated by a user 3 as a patient, and measure the body composition and the grip strength of the user 3.

[0013] The body composition meter 1 includes a measurement unit such as a plurality of electrodes for measurement and a sensor for body weight measurement, and includes an information processing device as a configuration for processing the numerical values measured by the measurement unit and the numerical values acquired from the grip strength meter 2, and operates in response to an operation request of the user 3 to the operation unit, and includes electronic components such as a CPU (Central Processing Unit) and a flash memory having a function for processing information in the main body. The body composition meter 1 can use, for example, MC-780A-N manufactured by Tanita Corporation, but the manufacturer and model are not limited as long as the numerical values described later can be measured.

[0014] The grip strength meter 2 is a device for measuring the grip strength of the user 3, and includes electronic components having a function for processing information inside the main body. Preferably, the grip strength value measured by the grip strength meter 2 is desirably shared with the body composition meter 1 by wireless communication, but it may be input by the user 3 to the body composition meter 1, or the grip strength meter 2 may be incorporated into the body composition meter 1. As the grip strength meter 2, for example, a muscle strength meter FR-100L manufactured by Tanita Corporation can be used, but the manufacturer and model are not limited as long as it can measure the grip strength.

[0015] As an example, the body composition meter 1 measures the body composition according to the request of the user 3, receives the measured grip strength value from the grip strength meter 2, and determines the symptoms when there is a possibility of pre-sarcopenia, dynapenia, sarcopenia from a plurality of measured values described later, and displays the determination result.

[0016] (Configuration of the information processing device) FIG. 2 is a block diagram showing a configuration example of the body composition meter 1 according to the embodiment.

[0017] The body composition meter 1 includes a control unit 10 composed of a CPU or the like, which controls each part and executes various programs, a storage unit 11 composed of a storage medium such as a flash memory for storing information, a display unit 12 composed of a display device such as an LCD (Liquid Crystal Display) for displaying the measured numerical values and determination results by characters and images, an operation unit 13 composed of a switch, a touch panel, etc. for receiving the operations of the user 3, a measurement unit 14 composed of electrodes, sensors, etc. for measuring the body composition of the user 3, and a communication unit 15 for communicating with the grip strength meter 2 and an external device via a network.

[0018] By executing the body composition calculation program 110 described later, the control unit 10 functions as a body composition calculation means 100 or the like, and by executing the symptom determination program 111, it functions as a grip strength information acquisition means 101, a symptom determination means 102, and a display control means 103.

[0019] The body composition calculation means 100 calculates each numerical value of the body composition information 112 described later from the electrical characteristic amounts of the user 3 obtained via the measurement unit 14, and stores them in the storage unit 11. The specific calculation method shall follow an existing method such as MC-780A-N manufactured by Tanita Corporation, for example.

[0020] The grip strength information acquisition means 101 acquires the grip strength information 113 from the grip strength meter 2 via the communication unit 15, or stores the information input from the user 3 in the storage unit 11 as the grip strength information 113.

[0021] The symptom determination means 102 determines whether the user 3 meets the symptoms of presarcopenia, dynapenia, or sarcopenia based on the body composition information 112 and the grip strength information 113, and stores the determination result information 114 in the storage unit 11.

[0022] The display control means 103 directly or indirectly displays the body composition information 112, the grip strength information 113, the determination result information 114, etc., together with other information according to the situation, on the display unit 12.

[0023] The storage unit 11 stores a body composition calculation program 110 that causes the control unit 10 to operate as the body composition calculation means 100 described above, a symptom determination program 111 that causes each of the means 101 - 103 to operate, the body composition information 112, the grip strength information 113, the determination result information 114, etc.

[0024] FIG. 3 is a schematic diagram showing a configuration example of the body composition information 112.

[0025] The body composition information 112 includes, as an example, weight, BMI, body fat percentage, body fat percentage determination, visceral fat level, muscle mass, muscle mass determination, body type determination based on body fat percentage and muscle mass, muscle quality score, left and right part-by-part measurements, basal metabolic rate, body age, body water percentage, estimated bone mass, MBA (My Body Analyzer) determination, activity level, leg beauty level, subcutaneous fat percentage, and pulse measurement. Note that the body fat percentage determination, visceral fat level, muscle mass determination, body type determination, muscle quality score, body age, MBA determination, activity level, leg beauty level, etc. are items shown as reference values for health and beauty calculated from the numerical values obtained by the body composition meter 1 using calculation formulas predetermined by the manufacturer of the body composition meter 1.

[0026] Figure 4 is a schematic diagram showing a configuration example of the grip strength information 113.

[0027] The grip strength information 113 has a right grip strength as the grip strength of the right hand and a left grip strength as the grip strength of the left hand.

[0028] (Operation of the information processing device) Next, the operation of this embodiment will be described by dividing it into (1) determination operation and (2) output operation.

[0029] (1) Determination operation First, the user 3 uses the body composition meter 1 or the grip strength meter 2 to prepare for the measurement of their own body composition information 112 or grip strength information 113. The order of measurement does not matter. The body composition meter 1 and the grip strength meter 2 execute the measurement of the body composition information 112 and the grip strength information 113 based on the following operation flow.

[0030] Figure 8 is a flowchart showing an operation example of the body composition meter 1.

[0031] First, the body composition calculation means 100 of the body composition meter 1 measures the user 3 via the measurement unit 14 and obtains the electrical characteristic quantity of the user 3 (S1).

[0032] Next, the body composition calculation means 100 calculates each numerical value of the body composition information 112 shown in FIG. 3 from the electrical characteristic quantity and stores it in the storage unit 11 (S2).

[0033] Next, the grip strength information acquisition means 101 acquires the grip strength information 113 shown in FIG. 3 from the grip strength meter 2 via the communication unit 15 and stores it in the storage unit 11 (S3).

[0034] Next, the symptom determination means 102 determines whether the user 3 meets the symptoms of presarcopenia or dynapenia (sarcopenia) based on the body composition information 112 and the grip strength information 113, and stores it in the storage unit 11 as the determination result information 114 (S4, S5). Hereinafter, the determination methods for sarcopenia, presarcopenia, and dynapenia will be specifically described. The symptom determination means 102 determines the applicability of each symptom based on the characteristics of each symptom described below.

[0035] FIG. 5 is a schematic diagram showing an example of the characteristics of each symptom.

[0036] As shown in the figure, compared with the normal state, in presarcopenia, the muscle mass decreases, the quality, muscle strength, and function remain unchanged, and the bone mass decreases.

[0037] Also, compared with the normal state, in dynapenia, although the muscle mass does not change, the quality, muscle strength, and function decrease. The correlation with bone mass is unclear.

[0038] Also, compared with the normal state, in sarcopenia, all of the muscle mass, quality, muscle strength, function, and bone mass decrease.

[0039] The symptom determination means 102 takes into account the characteristics of each symptom shown in FIG. 5, that is, the correlation between each symptom and the muscle mass, quality, muscle strength, function, and bone mass, and the muscle mass is a predetermined threshold value, for example, the skeletal muscle mass index (SMI) is 7.0 Kg / m for men 2 , 5.7 kg / m for women 2In the following cases, and when the bone mass is below a predetermined threshold, for example, 2.2 kg for men and 1.6 kg for women or less, there is a suspicion of presarcopenia (S4). Since bone mass has a high correlation with presarcopenia, the symptom determination means 102 may determine that there is a suspicion of presarcopenia based only on bone mass. In addition, muscle mass can be indicated by, for example, the Skeletal Muscle mass Index (SMI), which is the value obtained by dividing the total muscle mass of the limbs by the square of the height (m), or the Fat Free Mass Index (FFMI), which is the value obtained by dividing the fat-free mass (kg) by the square of the height (m).

[0040] In addition, the symptom determination means 102 may also use in combination a method of determining presarcopenia when the phase angle obtained by the bioelectrical impedance method is smaller than a predetermined threshold. This is because when the quality of the muscle is good, the proportion of muscle fibers contained in the muscle is large, and when the proportion of connective tissues such as fat and water is small, the reactance with respect to resistance becomes large, so the phase angle of impedance becomes large. On the contrary, when the quality of the muscle is poor, the proportion of muscle fibers contained in the muscle is small, and when the proportion of connective tissues such as fat and water is large, the reactance with respect to resistance becomes small, so the phase angle of impedance becomes small. This is utilized.

[0041] In addition, the symptom determination means 102 may also use in combination a sarcopenia determination method based on the Asian Working Group for Sarcopenia 2019 guidelines for determination.

[0042] In addition, for the symptom determination means 102, when the SMI, which is an index of muscle mass, is 7.0 kg / m for men 2 and 5.7 kg / m for women 2As described above, when the ratio of muscle mass to grip strength is equal to or lower than a predetermined threshold value, for example, 14.3 kg / kg for men and 14.0 kg / kg for women, it is determined that there is a suspicion of dynapenia (S5). Specifically, the ratio of muscle mass to grip strength is an average value of the ratio of muscle mass on the right side of the upper body of the patient to the grip strength of the right hand and the ratio of muscle mass on the left side of the upper body to the grip strength of the left hand. For example, the muscle mass may be indicated by the Skeletal Muscle mass Index (SMI), which is a value obtained by dividing the total muscle mass of the limbs by the square of the height (m), or the Fat Free Mass Index (FFMI), which is a value obtained by dividing the fat-free mass (kg) by the square of the height (m).

[0043] Note that the above correlation has been confirmed by the inventor using the AUC evaluation index as shown in FIGS. 6 and 7.

[0044] FIG. 6 is a table showing an example of the relationship between each feature quantity of sarcopenia and the AUC evaluation index.

[0045] The correlation between sarcopenia shown in FIG. 6 and each numerical value is the result of tabulating a group of 474 subjects in total, including 363 healthy subjects, 71 patients with presarcopenia symptoms, and 40 patients with sarcopenia symptoms. It can be seen that the AUC values for bone mass are 0.915 for men and 0.913 for women, and the discriminative ability is very high for both men and women.

[0046] FIG. 9 is a graph showing the relationship between each symptom and bone mass.

[0047] When tabulating the same group as above, as shown in FIG. 9, it was found that bone mass decreases in the process of the symptoms progressing from normal to presarcopenia and sarcopenia. Therefore, from the discriminative ability evaluation of bone mass for sarcopenia shown in FIG. 6 and the relationship between each symptom and bone mass reduction shown in FIG. 9, it is expected that the discriminative ability of bone mass for presarcopenia is also high. From this tendency, in the same method as the determination of presarcopenia described above, it may be determined that it is sarcopenia when the threshold value is 2.2 kg or less for men and 1.6 kg or less for women.

[0048] Note that the foot phase difference in Fig. 6 is a numerical value indicating muscle quality. The AUC values are 0.878 for men and 0.855 for women. Although the discriminative ability is high for both genders, it can be seen that bone mass shows a higher discriminative ability. In addition, the Fat Free Mass Index (FFMI) is a numerical value indicating the amount of muscle excluding the contribution of fat. The AUC values are 0.916 for men and 0.787 for women. It can be seen that the discriminative ability is high for men but low for women. Also, the Leg Muscle Score is a numerical value indicating the proportion of leg muscle mass in body weight. The AUC values are 0.795 for men and 0.830 for women. It can be seen that the discriminative ability is low for both genders, and bone mass shows a higher discriminative ability.

[0049] Fig. 7 is a table showing an example of the relationship between each feature quantity of dynapenia and the AUC evaluation index.

[0050] The correlation between dynapenia shown in Fig. 7 and each numerical value is the result of tabulating a group of 129 male subjects in total, including 117 healthy subjects and 12 patients with dynapenia symptoms. Also, for 304 female subjects in total, it is the result of tabulating a group of 249 healthy subjects and 55 patients with dynapenia symptoms. The AUC values for the quality of upper limb muscles (upper limb muscle mass / grip strength) are 0.806 for men and 0.849 for women. It can be seen that the discriminative ability is high for both genders.

[0051] Note that the arm phase difference is a numerical value indicating muscle quality. The AUC values are 0.615 for men and 0.583 for women. It can be seen that the discriminative ability is low for both genders, and the quality of upper limb muscles (weight power ratio) shows a higher discriminative ability. Also, the Leg Muscle Score is a numerical value indicating the proportion of leg muscle mass in body weight. The AUC values are 0.725 for men and 0.675 for women. It can be seen that the discriminative ability is low for both genders, and bone mass shows a higher discriminative ability. Also, the foot phase difference is a numerical value indicating muscle quality. The AUC values are 0.766 for men and 0.805 for women. It can be seen that the discriminative ability is low for men, and bone mass shows a higher discriminative ability for both genders.

[0052] (2) Output operation Next, the display control means 103 displays the determination result information 114 and the like on the display unit 12 together with the body composition information 112 and the grip strength information 113.

[0053] As an example of the display of the determination result information 114, the display control means 103 displays on the display unit 12 of the body composition meter 1 that there is a possibility of corresponding to presarcopenia, dynapenia, sarcopenia, or that it does not correspond to any of them. Note that this display may be made on the grip strength meter 2, or may be made on a terminal of the user 3 (not shown). Further, this display may be output to a terminal of a medical staff such as a doctor who diagnoses the user 3. The doctor or the like diagnoses the symptoms in consideration of the determination result displayed on the display unit 12.

[0054] (Effects of the embodiment) According to the above-described embodiment, by using the correlation between presarcopenia and bone mass and / or the correlation between dynapenia and the ratio of grip strength to muscle mass, the possibility of corresponding to presarcopenia and / or the possibility of corresponding to dynapenia are determined from the measured values measurable by the body composition meter 1. Therefore, it is possible to assist in determining the state before reaching sarcopenia without the need to measure walking speed or rising ability as in the prior art. As a result, the number of measurement assistants for the possibility of corresponding to presarcopenia and / or the possibility of corresponding to dynapenia can be reduced.

[0055] [Other embodiments] Note that the present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the spirit of the present invention.

[0056] For example, the symptom determination means 102 may determine the possibility of corresponding to presarcopenia or sarcopenia in the near future not only when the muscle mass and the estimated bone mass are below a predetermined threshold value, but also based on the temporal changes in the muscle mass and the estimated bone mass. Similarly, the symptom determination means 102 may determine the possibility of corresponding to dynapenia or sarcopenia in the near future based on the temporal changes in the correlation between the muscle mass and the ratio of grip strength to muscle mass.

[0057] In the above embodiment, the functions of the respective means 100 to 103 of the control unit 10 are realized by a program, but all or part of each means may be realized by hardware such as an ASIC. Also, the program used in the above embodiment can be stored and provided in a recording medium such as a CD-ROM. Further, the replacement, deletion, addition, etc. of the above steps described in the above embodiment are possible within a range that does not change the gist of the present invention.

Explanation of Signs

[0058] 1: Body composition meter 2: Grip strength meter 3: User 10: Control unit 11: Storage unit 12: Display unit 13: Operation unit 14: Measurement unit 15: Communication unit 100: Body composition calculation means 101: Grip strength information acquisition means 102: Symptom determination means 103: Display control means 110: Body composition calculation program 111: Symptom determination program 112: Body composition information 113: Grip strength information 114: Judgment result information

Claims

1. A symptom determination program for causing a computer to function as a determination means for determining the possibility of presarcopenia when the muscle mass and bone mass of an acquired patient are each smaller than a predetermined value.

2. The symptom determination program according to claim 1, wherein the determination means determines the possibility of dynapenia when the muscle mass is larger than a predetermined value and the ratio of the grip strength of the acquired patient to the muscle mass is smaller than a predetermined value.

3. The symptom determination program according to claim 1 or 2, wherein the determination means further determines the possibility of presarcopenia when the phase angle obtained by the bioelectrical impedance method is smaller than a predetermined value.

4. The symptom determination program according to claim 1 or 2, wherein the determination means determines sarcopenia when the muscle mass and bone mass of the acquired patient are each smaller than a predetermined value.

5. The symptom determination program according to claim 1, wherein the determination means determines the possibility of presarcopenia based on the temporal changes in the muscle mass and the bone mass.

6. The symptom determination program according to claim 2, wherein the determination means determines the possibility of dynapenia based on the temporal changes in the muscle mass and the ratio of the grip strength to the muscle mass.

7. An information processing apparatus having a determination means for determining the possibility of presarcopenia when the muscle mass and bone mass of an acquired patient are each smaller than a predetermined value.

8. A symptom determination method having a step of determining the possibility of presarcopenia when the muscle mass and bone mass of an acquired patient are each smaller than a predetermined value.

9. A body composition meter that electrically measures a patient's body and calculates at least muscle mass and bone mass, and An information processing apparatus having a step of determining the possibility of presarcopenia when the muscle mass and bone mass of the patient acquired by the body composition meter are each smaller than a predetermined value. ​

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