Sarcopenia diagnostic device and program

Abstract

To provide a sarcopenia diagnostic device and program capable of diagnosing sarcopenia at an early stage with ease.SOLUTION: A sarcopenia diagnostic device 1 comprises an input unit 10 and a determination unit 11. The input unit 10 inputs information indicating the sexuality, the weight, and the lower leg circumference of a subject being an adult. The determination unit 11 determines whether the subject exhibits sarcopenia, on the basis of the information inputted to the input unit 10. This makes it possible to determine whether the subject exhibits sarcopenia, without obtaining a skeletal muscle index which needs a special device.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a sarcopenia diagnostic device and program. [Background technology]

[0002] In an aging society, measures to extend healthy lifespan are desirable. Healthy lifespan is the period during which one can live a healthy, active, and independent daily life. Sarcopenia is one of the causes of locomotive syndrome that shortens healthy lifespan. Sarcopenia is a condition in which skeletal muscle mass and muscle function are reduced due to aging or disease.

[0003] When diagnosing sarcopenia using global diagnostic criteria, it is essential to measure skeletal muscle mass in the limbs and calculate the skeletal muscle index. Skeletal muscle mass is measured using body composition measurement methods such as dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) (see, for example, Non-Patent Documents 1 and 2).

[0004] Measurement using the DXA method requires the installation of large, dedicated equipment in an X-ray examination room, and although the amount of radiation exposure during measurement is relatively small, it is unavoidable. Measurement using the BIA method can be performed using portable dedicated equipment, making it possible to perform measurements at the bedside. However, such dedicated equipment is expensive. Furthermore, due to the measurement principle, it is not possible to measure patients with implanted devices such as pacemakers.

[0005] Sarcopenia increases overall and cardiovascular mortality, so early diagnosis and prevention are desirable, but the rate of diagnostic testing in clinical practice remains low. One reason for this is the difficulty of measuring appendicular skeletal muscle mass and calculating skeletal muscle index, which are essential for diagnosis, namely, DXA and BIA methods. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] Ken Yamauchi, "Basics and Applications of Body Composition Analysis: Principles of BIA and Body Composition Assessment," Surgery and Metabolism / Nutrition, Vol. 53, No. 4, August 2019 [Non-patent document 2] Yuki Yanagimachi, Hirofumi Nakayama, Masahiko Yamaichi, Tomoyuki Fujita, and Makoto Daimon, "Basics and Applications of Body Composition Analysis: Principles of Dual Energy X-ray Absorptiometry (DXA) and Body Composition Assessment," Journal of Surgery, Metabolism, and Nutrition, Vol. 53, No. 4, August 2019 Summary of the Invention [Problem to be solved by the invention]

[0007] As described above, measuring the skeletal muscle mass required for diagnosing sarcopenia requires large or expensive special equipment, which makes it difficult to diagnose early and simply.

[0008] The present invention has been made in light of the above-mentioned circumstances, and aims to provide a sarcopenia diagnostic device and program that can diagnose sarcopenia early and easily. [Means for solving the problem]

[0009] In order to achieve the above object, a sarcopenia diagnostic device according to a first aspect of the present invention comprises: an input unit for inputting information indicating the sex, weight, and lower leg circumference of an adult subject; The input to the input section Calculate a value of a substitute index to be used instead of a skeletal muscle index based on information indicating the sex, weight, and lower leg circumference of the subject, and if the value of the substitute index is less than a reference value, The subject has sarcopenia and a determination unit for determining Equipped with 、 The value of the substitute index is expressed as follows, where the term for sex is a real number a1 or a2, the coefficient for the term for weight is a real number b1, and the coefficient for the term for lower leg circumference is a real number c1: When the subject is male, the value is calculated by the formula (1), Substitute index = a1 + b1 × weight + c1 × lower leg circumference (1) When the subject is a woman, the calculation formula (2) is used: Substitute index = a2 + b1 × weight + c1 × lower leg circumference (2) When the unit of the weight is kg and the unit of the lower leg circumference is cm, a1 is 2.01 and a2 is 1.25, b1 is 0.06 and c1 is 0.05, The reference value is 5.78 .

[0013] The sarcopenia diagnostic device according to the second aspect of the present invention comprises: an input unit for inputting information indicating the sex, weight, lower leg circumference, and thigh circumference of an adult subject; A determination unit that calculates a value of a substitute index to be used in place of a skeletal muscle index based on information indicating the sex, weight, lower leg circumference, and thigh circumference of the subject inputted to the input unit, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value; Equipped with The value of the substitute index is expressed as follows: the sex term is a real number a3 or a real number a4, the weight term coefficient is a real number b2, the lower leg circumference term coefficient is a real number c2, and the thigh circumference term coefficient is a real number d2. When the subject is male, the calculation formula (3) is used: Substitute index = a3 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (3) When the subject is a woman, the calculation formula (4) is used: Substitute index = a4 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (4) If the unit of weight is kg and the unit of lower leg circumference is cm, a3 is 0.67 and a4 is -0.08, b2 is 0.04, c2 is 0.04, and d2 is 0.08; The reference value is 6.02.

[0017] The determination unit When the walking speed of the subject is equal to or less than a reference value or the grip strength of the subject is less than a reference value, Using the calculation formula (1) or (2), determine whether the subject has sarcopenia. This may also be the case.

[0018] The determination unit If the subject's grip strength is less than the reference value, if the subject's result in a five-time chair stand test is equal to or greater than the reference time, or if the subject's walking speed is equal to or less than the reference value, Using the calculation formula (3) or (4), determine whether the subject has sarcopenia. This may also be the case.

[0019] The determination unit If the grip strength of the subject is less than the reference value and the result of the five-time chair stand test of the subject is equal to or greater than the reference time, if the grip strength of the subject is less than the reference value and the walking speed of the subject is equal to or less than the reference value, Using the calculation formula (3) or (4), determine whether the subject has severe sarcopenia. This may also be the case.

[0020] The calculation formulas (1) and (2) or the calculation formulas (3) and (4) are: a regression line equation generated by performing multivariate analysis on data of a plurality of subjects who are equal to or greater than a first age and equal to or less than a second age; The determination unit When the age of the subject is equal to or greater than the first age and equal to or less than the second age, Determine whether the subject has sarcopenia using the calculation formula (1) or (2) or the calculation formula (3) or (4). This may also be the case.

[0021] The first age is 40 years old and the second age is 89 years old. This may also be the case.

[0022] A program according to a third aspect of the present invention comprises: Computer, an input unit for inputting information indicating the sex, weight, and lower leg circumference of an adult subject; The input to the input section , indicating the subject's sex, weight, and lower leg circumference Based on the information, A substitute index value used in place of the skeletal muscle index is calculated, and if the value of the substitute index is less than the reference value, The subject has sarcopenia and a determination unit for determining It functions as The value of the substitute index is expressed as follows, where the term for sex is a real number a1 or a2, the coefficient for the term for weight is a real number b1, and the coefficient for the term for lower leg circumference is a real number c1: When the subject is male, the value is calculated by the formula (1), Substitute index = a1 + b1 × weight + c1 × lower leg circumference (1) When the subject is a woman, the calculation formula (2) is used: Substitute index = a2 + b1 × weight + c1 × lower leg circumference (2) When the unit of the weight is kg and the unit of the lower leg circumference is cm, a1 is 2.01 and a2 is 1.25, b1 is 0.06 and c1 is 0.05, The reference value is 5.78.

[0023] A program according to a fourth aspect of the present invention comprises: Computer, an input unit for inputting information indicating the sex, weight, lower leg circumference, and thigh circumference of an adult subject; The input to the input section , indicating the subject's sex, weight, lower leg circumference, and thigh circumference Based on the information, A substitute index value used in place of the skeletal muscle index is calculated, and if the value of the substitute index is less than the reference value, The subject has sarcopenia and a determination unit for determining It functions as The value of the substitute index is expressed as follows: the sex term is a real number a3 or a real number a4, the weight term coefficient is a real number b2, the lower leg circumference term coefficient is a real number c2, and the thigh circumference term coefficient is a real number d2. When the subject is male, the calculation formula (3) is used: Substitute index = a3 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (3) When the subject is a woman, the calculation formula (4) is used: Substitute index = a4 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (4) If the unit of weight is kg and the unit of lower leg circumference is cm, a3 is 0.67 and a4 is -0.08, b2 is 0.04, c2 is 0.04, and d2 is 0.08; The reference value is 6.02. [Effects of the Invention]

[0024] According to the present invention, whether or not an adult subject has sarcopenia is determined based on information indicating the subject's gender, weight, and lower leg circumference. This makes it possible to determine whether or not a subject has sarcopenia using only easily measurable items, without the need for a special device to determine a skeletal muscle index. As a result, sarcopenia can be diagnosed early and simply. [Brief explanation of the drawings]

[0025] [Figure 1] Figure 1 shows a sarcopenia diagnostic chart based on the 2014 Asian criteria diagnostic criteria. [Figure 2] FIG. 1 is a block diagram showing the functional configuration of a sarcopenia diagnostic device according to a first embodiment of the present invention. [Figure 3] FIG. 3 is a block diagram showing the configuration of a determination unit of the sarcopenia diagnostic device of FIG. 2. [Figure 4] FIG. 3 is a block diagram showing the hardware configuration of the sarcopenia diagnostic device of FIG. 2. [Figure 5] 3 is a flowchart showing the operation of the sarcopenia diagnostic device of FIG. 2. [Figure 6] FIG. 10 is a diagram illustrating an example of an information input screen. [Figure 7] 10A and 10B are diagrams showing an example of a display screen for the determination result. [Figure 8] (A) is a graph showing the correlation between skeletal muscle index and surrogate index in general health examinees, and (B) is a graph showing the correlation between skeletal muscle index and surrogate index in cardiovascular disease patients. [Figure 9] Figure 1 shows a sarcopenia diagnostic chart based on the 2019 Asian criteria diagnostic criteria. [Figure 10] This figure shows a chart for diagnosing sarcopenia or severe sarcopenia using data other than the SPPB (Short Physical Performance Battery), based on the 2019 Asian Standard Sarcopenia Diagnostic Chart. [Figure 11] FIG. 10 is a block diagram showing the functional configuration of a sarcopenia diagnostic device according to a second embodiment of the present invention. [Figure 12] 12 is a flowchart showing the operation of the sarcopenia diagnostic device of FIG. 11. [Figure 13] FIG. 10 is a diagram illustrating an example of an information input screen. [Figure 14] 10A, 10B, and 10C are diagrams showing examples of display screens for determining results. DETAILED DESCRIPTION OF THE INVENTION

[0026] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the drawings, the same or equivalent parts are designated by the same reference numerals.

[0027] [Asian Standard Sarcopenia Diagnostic Chart] First, we will explain the conventional method for diagnosing sarcopenia. This diagnostic method is based on the Asian sarcopenia diagnostic chart shown in Figure 1. This chart was created based on the sarcopenia diagnostic criteria published in 2014. As shown in Figure 1, this diagnostic chart classifies elderly people as those whose walking speed is 0.8 m / sec or less, or whose grip strength is less than 26 kg for men and less than 18 kg for women (Step S1; Yes), and whose muscle mass (skeletal muscle index, SMI) is 7.0 kg / m for men and 8.0 kg / m for women (Step S2; Yes), respectively. 2 less than 5.4 kg / m for women 2 If the level is less than 100%, sarcopenia is diagnosed.

[0028] The skeletal muscle index (SMI) is the sum of the muscle mass of the four limbs divided by the square of the height (m). Muscle mass can be obtained by measuring body composition using DXA or BIA, as described above.

[0029] Embodiment 1 [Sarcopenia diagnostic device] The sarcopenia diagnostic device 1 according to this embodiment diagnoses whether or not a Japanese adult male or female who is 40 years or older as a first age and 89 years or younger as a second age, at which skeletal muscle mass is thought to naturally decline, has sarcopenia, using a method different from that used in the chart shown in Fig. 1. This diagnosis does not use the skeletal muscle index SMI, but uses its substitute index AI (Alternative Index).

[0030] [Overall configuration] As shown in FIG. 2, the sarcopenia diagnostic device 1 is an information processing device including an input unit 10, a determination unit 11, and an output unit 12.

[0031] The input unit 10 inputs information indicating the subject's grip strength, walking speed, sex, weight, and lower leg circumference. The information indicating the subject's grip strength, walking speed, weight, and lower leg circumference uses values ​​measured in advance. Here, the lower leg circumference is the circumference at the midpoint between the upper edge of the patella and the calcaneus.

[0032] The determination unit 11 determines whether or not the subject has sarcopenia based on the information input to the input unit 10. Specifically, the determination unit 11 substitutes the information input to the input unit 10 into an arithmetic formula described below to obtain a value of a substitute index AI, and determines that the subject has sarcopenia if the value of the substitute index AI is less than a reference value. In this embodiment, the reference value is set to 5.78.

[0033] The output unit 12 outputs the determination result as to whether or not the subject has sarcopenia. The output by the output unit 12 may be a display output or an audio output.

[0034] [Determination process] A more detailed description will be given of the sarcopenia determination process performed by the determination unit 11. As shown in FIG. 3, the determination unit 11 includes a determination procedure execution unit 20, a personal data storage unit 22, and a determination condition data storage unit 23.

[0035] The determination procedure execution unit 20 determines whether or not the subject has sarcopenia according to a predetermined determination procedure based on information indicating the subject's walking speed, grip strength, sex, weight, and lower leg circumference. The determination procedure execution unit 20 calculates the value of a surrogate index AI when, for example, the subject's walking speed is equal to or less than a reference value (0.8 m / sec) or the subject's grip strength is less than a reference value (26 kg for men and 18 kg for women). The determination procedure execution unit 20 determines that the subject has sarcopenia if the value of the surrogate index AI calculated by the surrogate index calculation unit 21 is less than a threshold value (5.78). The determination procedure execution unit 20 outputs a determination result indicating whether or not the subject has sarcopenia to the output unit 12.

[0036] More specifically, the determination procedure execution unit 20 calculates the value of the substitute index AI. The substitute index AI is a linear combination formula having a term for gender, a term for weight, and a term for lower leg circumference. In this formula, the gender term is a real number a1 or a2, the coefficient of the weight term is a real number b1, and the coefficient of the lower leg circumference term is a real number c1. When the gender of the subject is male, the value of the substitute index AI is calculated using the following calculation formula (1). AI = a1 + b1 × weight + c1 × lower leg circumference (1) Furthermore, when the subject is female, the proxy index value AI is calculated using the following formula (2). AI = a2 + b1 × weight + c1 × lower leg circumference (2) When the unit of body weight is kg and the unit of lower leg circumference is cm, a1 is 2.01, a2 is 1.25, b1 is 0.06, and c1 is 0.05.

[0037] The personal data storage unit 22 stores information indicating the walking speed, grip strength, sex, weight, and lower leg circumference of the subject input to the input unit 10. The determination procedure execution unit 20 executes a determination procedure to determine whether or not the subject has sarcopenia based on the information stored in the personal data storage unit 22.

[0038] The judgment condition data storage unit 23 stores the judgment condition data input to the input unit 10. The judgment condition data includes, for example, walking speed, grip strength, reference values ​​of the substitute index AI, and real numbers a1, a2, b1, and c1 used for judgment in the judgment procedure. The judgment procedure execution unit 20 makes a judgment based on the reference values ​​of walking speed and grip strength stored in the judgment condition data storage unit 23, and calculates the substitute index AI to which the real numbers a1, a2, b1, and c1 are set. Furthermore, the judgment procedure execution unit 20 judges that the subject has sarcopenia if the value of the substitute index AI is less than the reference value (5.78).

[0039] As described above, the judgment unit 11 judges that the subject has sarcopenia if the walking speed of the subject is below the standard value or if the grip strength of the subject is less than the standard value, and if the value of calculation formula (1) or (2) is less than the standard value.

[0040] [Hardware configuration] Fig. 4 shows the hardware configuration of the sarcopenia diagnostic device 1. As shown in Fig. 4, the sarcopenia diagnostic device 1 includes a CPU (Central Processing Unit) 30, a memory 31, an auxiliary storage device 32, a man-machine interface 33, a communication interface 34, and an input / output interface 35. The components of the sarcopenia diagnostic device 1 are connected via an internal bus 40.

[0041] The CPU 30 is a processor (arithmetic device) that executes a software program (hereinafter simply referred to as a "program"). A determination program 41 is loaded into the memory 31 from the auxiliary storage device 32. The CPU 30 executes the determination program 41 stored in the memory 31, thereby realizing the function of the determination procedure execution unit 20 provided in the determination unit 11.

[0042] The memory 31 is, for example, a RAM (Random Access Memory). As described above, the memory 31 reads the determination program 41 and determination condition data 42 executed by the CPU 30, and also stores the determination result resulting from execution of the determination program 41 by the CPU 30. The sarcopenia diagnostic device 1 also includes a ROM (Read Only Memory). A startup program for the sarcopenia diagnostic device 1 is implemented in the ROM, and the sarcopenia diagnostic device 1 is started up when the CPU 30 executes the startup program in the ROM.

[0043] The auxiliary storage device 32 is, for example, a hard disk. The auxiliary storage device 32 stores a judgment program 41 and judgment condition data 42 to be executed by the CPU 30. The judgment program 41 is stored in a recording medium (a recording medium that performs non-temporary recording) 50 such as a portable USB (Universal Serial Bus) memory. The judgment program 41 transferred from the recording medium 50 is stored in the auxiliary storage device 32. The judgment condition data 42 is data used when the judgment program 41 is executed, and corresponds to the judgment condition data stored in the judgment condition data storage unit 23 of FIG. 3. In this embodiment, the memory 31 corresponds to the personal data storage unit 22, and the memory 31 and the auxiliary storage device 32 correspond to the judgment condition data storage unit 23.

[0044] The man-machine interface 33 includes an operation input unit through which an operator inputs operations, and a display having a display screen. In this embodiment, the man-machine interface 33 is a touch panel. Note that a keyboard and a pointing device may be provided as the operation input unit, and the display may be provided separately. The man-machine interface 33 realizes the functions of the input unit 10 and the output unit 12.

[0045] The communication interface is a communication interface that complies with a communication network such as the Internet. The judgment program 41 and the judgment condition data can be stored in the auxiliary storage device 32 via the communication interface .

[0046] The input / output interface 35 is an interface with the recording medium 50. The judgment program 41 and judgment condition data 42 are input via the input / output interface 35 and can be stored in the auxiliary storage device 32.

[0047] Next, the processing of the sarcopenia diagnostic device 1 according to the embodiment of the present invention, i.e., the flow of the judgment program 41, will be described. Before starting this processing, as shown in FIG. 3, judgment condition data is stored in the judgment condition data storage unit 23. Furthermore, the sarcopenia diagnostic device 1 has already been started by a startup program, and as shown in FIG. 4, the judgment program 41 is installed in the auxiliary storage device 32, and the judgment program 41 has been loaded into the memory 31 and is in an executable state. Furthermore, the judgment condition data 42 stored in the auxiliary storage device 32 in FIG. 4, which corresponds to the judgment condition data stored in the judgment condition data storage unit 23, has been loaded into the memory 31.

[0048] As shown in Fig. 5, the input unit 10 inputs information indicating the subject's grip strength, walking speed, sex, weight, and lower leg circumference (step S11). Here, as shown in Fig. 3, the information input to the input unit 10 is stored in the personal data storage unit 22 of the determination unit 11. In other words, as shown in Fig. 4, the CPU 30 displays an input screen (see Fig. 6) for this information on the man-machine interface 33, and the operator inputs operation inputs to the input screen via the man-machine interface 33. The CPU 39 stores the input information in the memory 31.

[0049] Next, the determination procedure execution unit 20 of the determination unit 11 determines whether the walking speed is 0.8 m / sec or less (step S12). Specifically, as shown in FIG. 3, the determination procedure execution unit 20 determines whether the walking speed of the subject stored in the personal data storage unit 22 is equal to or less than the walking speed reference value 0.8 m / sec stored in the determination condition data storage unit 23. This walking speed reference value 0.8 m / sec is the same as the walking speed reference value in the Asian standard sarcopenia diagnosis chart of FIG. 1. In other words, the CPU 30 performs a comparison operation between the walking speed of the subject stored in the memory 31 and the walking speed reference value 0.8 m / sec also stored in the memory 31.

[0050] If the walking speed is not 0.8 m / sec or less (step S12; No), the determination procedure execution unit 20 determines whether the gender is male or not (step S13). If the gender is male (step S13; Yes), the determination procedure execution unit 20 determines whether the grip strength is less than 26 kg or not (step S14). On the other hand, if the gender is not male (step S13; No), the determination procedure execution unit 20 determines whether the grip strength is less than 18 kg or not (step S15). In step S13, as shown in FIG. 4, the CPU 30 makes the determination according to the gender of the subject read into the memory 31. Furthermore, in steps S14 and S15, the CPU 30 performs a comparison operation between the walking speed and grip strength of the subject and the reference values ​​of the walking speed and grip strength read into the memory 31.

[0051] If the subject is male and the grip strength is less than 26 kg (step S14; Yes), or if the subject is female and the grip strength is less than 18 kg (step S15; Yes), the determination procedure execution unit 20 determines whether the subject is male or not (step S16). Here, as shown in FIG. 4, the CPU 30 makes the determination according to the subject's gender stored in the memory 31.

[0052] If the gender is male (step S16; Yes), the determination procedure execution unit 20 causes the substitute index calculation unit 21 to calculate the value of the substitute index AI using the calculation formula (1) for males (step S17). On the other hand, if the gender is female (step S16; No), the determination procedure execution unit 20 causes the substitute index calculation unit 21 to calculate the value of the substitute index AI using the calculation formula (2) for females (step S18). Here, the CPU 30 performs the calculation of the calculation formula (1) or the calculation formula (2) based on the values ​​of the real numbers a1, a2, b1, and c1 read into the memory 31.

[0053] After steps S17 and S18, the determination procedure execution unit 20 determines whether the value of the calculation formula is less than the threshold value (5.78) (step S19). If the value of the calculation formula is less than the threshold value (step S19; Yes), the output unit 12 outputs the determination result that the patient has sarcopenia (step S20). On the other hand, if the value of the calculation formula is equal to or greater than the threshold value (step S19; No), the output unit 12 outputs the determination result that the patient does not have sarcopenia (step S21).

[0054] Note that even if the sex is male and the grip strength is less than 26 kg (step S14; No) or if the sex is female and the grip strength is less than 18 kg (step S15; No), the output unit 12 outputs the determination result that the subject does not have sarcopenia (step S21). Here, the CPU 30 displays the determination result that the subject does not have sarcopenia on the display screen of the man-machine interface 33 (step S21).

[0055] Here, the CPU 30 displays the sarcopenia determination result on the display screen of the man-machine interface 33. For example, in step S20, as shown in FIG. 7(A), the character string "Sarcopenia is suspected" is displayed on the man-machine interface 33. In addition, in step S21, as shown in FIG. 7(B), the character string "Not sarcopenia" is displayed on the man-machine interface 33.

[0056] In this embodiment, steps S12 to S16 are considered to be the first stage of evaluation, and steps S17 to S21 are considered to be the second stage of evaluation. Also, step S1 of the Asian standard sarcopenia diagnostic chart in Figure 1 is considered to be the first stage of evaluation, and step S2 is considered to be the second stage of evaluation.

[0057] As shown in Figure 8(A), there is a high correlation (r = 0.857) between the skeletal muscle index SMI and the proxy index AI in general health checkup subjects (CD adults). Furthermore, as shown in Figure 8(B), there is also a high correlation (r = 0.782) between the skeletal muscle index SMI and the proxy index AI in cardiovascular disease patients (CVD patients). Therefore, it has become clear that sarcopenia can be diagnosed in both general health checkup subjects and cardiovascular disease patients by calculating the proxy index AI using the above formula, just as with the skeletal muscle index SMI.

[0058] [How to generate the calculation formula] Next, we will explain how the calculation formulas (1) and (2) for the substitute index AI were generated. In order to generate the calculation formulas (1) and (2), it is first necessary to identify the factors of the substitute index AI for the skeletal muscle index SMI. Below, we will explain the procedure for identifying the factors of the substitute index AI, which is executed by an information processing device.

[0059] The following factors are expected to influence AI, a proxy index for the skeletal muscle index (SMI). Therefore, these factors are listed as evaluation items. Age, sex, mean blood pressure, pulse pressure, height, weight, body mass index, upper arm circumference, thigh circumference, calf circumference, skeletal muscle index (SMI) of the limbs, body fat percentage, visceral fat area, bone base mass, t-score (a bone mineral density index), grip strength, knee extension strength, usual walking speed, functional reach test, five repetition chair stand test, timed up and go test (the above three tests are used to evaluate exercise capacity), blood albumin concentration, GNRI (Geriatric Nutritional Risk Index; an index of nutritional status), blood LDL cholesterol concentration, blood HDL cholesterol concentration, blood triglyceride concentration, HBA1c, blood calcium concentration, blood phosphorus concentration, blood vitamin D concentration, blood TRACP-5b (tartrate-resistant acid phosphatase) concentration (an index of bone metabolism status), and blood zinc concentration

[0060] After listing the evaluation items, in step 1, measurement or calculation data for the above-mentioned evaluation items was collected for each subject, targeting general health checkup participants and hospitalized patients with cardiovascular disease aged 40 years or older and 89 years or younger.

[0061] Next, in step 2, among the above evaluation items other than the skeletal muscle index SMI, items showing a statistically significant correlation with the skeletal muscle index SMI were extracted using univariate analysis. As a result, eight items were extracted: age, height, weight, upper arm circumference, thigh circumference, lower leg circumference, grip strength, and GNRI.

[0062] Next, in step 3, grip strength corresponds to the first stage of the diagnostic criteria in the Asian criteria sarcopenia diagnostic flowchart. Therefore, we performed multivariate analysis (stepwise analysis) to examine the correlation between the remaining seven parameters (excluding grip strength) and the skeletal muscle index (SMI) for subjects who met the criteria for the first stage of the Asian criteria sarcopenia diagnostic flowchart (Figure 1). We then calculated a regression line equation for the three significantly extracted parameters: gender, weight, and calf circumference. The stepwise analysis is also known as the variable addition / deletion method. In this stepwise analysis, significant explanatory variables (independent variables) are added and removed one by one to create a significant regression model. Thus, the above calculation formulas (1) and (2) for the proxy index AI are regression line equations generated through statistical analysis of data on Japanese adults aged 40 years or older (first age) and 89 years or younger (second age).

[0063] Next, in step 4, a logistic regression analysis was performed on the bivariate relationship between the calculated proxy index AI for the skeletal muscle index SMI and individuals with sarcopenia, and the cutoff value obtained from the ROC (receiver operating characteristic) curve was determined as the standard value of 5.78 for determining sarcopenia using the proxy index AI.

[0064] As described above in detail, the sarcopenia diagnostic device 1 according to this embodiment determines whether a subject has sarcopenia based on the subject's gender, weight, lower leg circumference, grip strength, and walking speed. This makes it possible to determine whether a subject has sarcopenia using only easily measurable items, without the need for a skeletal muscle index that requires special equipment. As a result, sarcopenia can be diagnosed early and simply.

[0065] The sarcopenia diagnostic device 1 according to the present embodiment allows a subject to be diagnosed with sarcopenia by narrowing down the factors from among many others to the subject's gender, weight, and lower leg circumference. This feature is a finding obtained through the inventor's own research and experiments, and is not easily conceivable.

[0066] The sarcopenia diagnostic device 1 according to this embodiment can be implemented on a mobile terminal such as a smartphone or a tablet computer, or on a personal computer, thereby enabling diagnosis not only in a hospital but also at home.

[0067] The above calculation formulas (1) and (2) can be applied to both general health examinees and patients with cardiovascular disease. Therefore, it is possible to diagnose patients with implanted devices such as pacemakers. This makes it possible to significantly expand the range of subjects who can be diagnosed.

[0068] Embodiment 2 The sarcopenia diagnostic device 1 according to the first embodiment diagnoses sarcopenia according to the diagnostic criteria of 2014. The diagnostic criteria for sarcopenia were updated in 2019. The sarcopenia diagnostic device 1 according to the second embodiment corresponds to the updated diagnostic criteria for sarcopenia.

[0069] As shown in Figure 9, the 2019 diagnostic criteria for sarcopenia include a grip strength of less than 28 kg for men and less than 18 kg for women, a walking speed of less than 1.0 m / s when walking 6 m, a time required for five chair rises of 12 seconds or more, and a Short Physical Performance Battery (SPPB) score of 9 or less. Grip strength is an evaluation item for "muscle strength," while walking speed, five chair rises, and SPPB are evaluation items for "physical function." If sarcopenia is suspected based on these evaluation criteria for muscle strength or physical function (Step S3; Yes), DXA should be performed if skeletal muscle mass is 7.0 kg / m for men and 8.0 kg / m for women. 2 less than 5.4 kg / m for women 2 or if the skeletal muscle mass measured by BIA is less than 7.0 kg / m 2 less than 5.7 kg / m for women 2If the result is less than the reference value (Step S4; Yes), the condition is judged to be sarcopenia or severe sarcopenia. Here, sarcopenia refers to a condition in which skeletal muscle mass is below the reference value and either muscle strength or physical function is below the reference value, and severe sarcopenia refers to a condition in which skeletal muscle mass is below the reference value and both physical function and muscle strength are below the reference value.

[0070] More specifically, in step S3, the determination of normal, sarcopenia, or severe sarcopenia is performed according to the table shown in Fig. 10. The table shown in Fig. 10 can be summarized as follows. (1) If grip strength is below the standard value (NG), sarcopenia is suspected. (2) If the results of the 5-time chair stand test exceed the standard time (NG), sarcopenia is suspected. (3) If walking speed is below the standard value (NG), sarcopenia is suspected. (4) If grip strength is below the standard value (NG) and the results of the 5-time chair stand test exceed the standard time (NG), severe sarcopenia is suspected. (5) If grip strength is below the standard value (NG) and walking speed is below the standard value (NG), severe sarcopenia is suspected. (6) If the grip strength exceeds the standard value (normal), the walking speed exceeds the standard value (normal), and the result of the five-time chair stand test exceeds the standard time (normal), the patient is considered normal. As shown in Figure 10, the 2019 sarcopenia criteria state that, in addition to these assessment results, if skeletal muscle mass also meets the criteria, the patient is diagnosed with sarcopenia or severe sarcopenia.

[0071] In the 2019 sarcopenia diagnostic criteria, the SPPB score results are also used as a criterion for judgment. However, in the table shown in Fig. 10, the SPPB score results are not included in the judgment criteria. The sarcopenia diagnostic device 1 according to this embodiment judges normal, sarcopenia, and severe sarcopenia using judgment criteria that do not include the SPPB.

[0072] As shown in FIG. 11, the sarcopenia diagnostic device 1 is an information processing device including an input unit 10, a determination unit 11, and an output unit 12, which is the same as in the first embodiment.

[0073] The input unit 10 inputs information indicating the subject's grip strength, walking speed, results of the five-time chair stand test, gender, weight, lower leg circumference, and thigh circumference. The information indicating the subject's grip strength, walking speed, results of the five-time chair stand test, weight, lower leg circumference, and thigh circumference uses pre-measured values. Here, thigh circumference refers to the circumference at the midpoint between the inguinal skin sulcus (groin crease) and the upper edge of the patella. Figure 13 shows an input screen for this information. The five-time chair stand test measures the time (seconds) required to sit down and stand from a chair five times.

[0074] The determination unit 11 determines whether or not the subject has sarcopenia based on the information input to the input unit 10. Specifically, the determination unit 11 substitutes the information input to the input unit 10 into an arithmetic formula described below to determine the value of a substitute index AI, and determines that the subject has sarcopenia or severe sarcopenia if the value of the substitute index AI is less than a reference value. In this embodiment, the reference value is set to 6.02.

[0075] The output unit 12 outputs the determination result as to whether or not the subject has sarcopenia or severe sarcopenia, as in the above embodiment.

[0076] In this embodiment, the determination unit 11 is similar to the above embodiment in that it includes a determination procedure execution unit 20, a personal data storage unit 22, and a determination condition data storage unit 23 (see FIG. 3).

[0077] The assessment procedure execution unit 20 determines whether the subject has sarcopenia or severe sarcopenia according to a predetermined assessment procedure based on information indicating the subject's grip strength, walking speed, results of a five-time chair stand test, gender, weight, lower leg circumference, and thigh circumference. Specifically, the assessment procedure execution unit 20 calculates a value of a substitute index AI used in place of a skeletal muscle index, and determines that the subject has sarcopenia or severe sarcopenia if the value of the substitute index AI is less than a reference value. For example, if the subject's grip strength is less than a reference value (28 kg for men and 18 kg for women), the assessment procedure execution unit 20 determines that the subject is suspected of having sarcopenia and calculates the value of the substitute index AI. If the walking speed is less than 1.0 m / s, the assessment procedure execution unit 20 determines that the subject is suspected of having sarcopenia and calculates the value of the substitute index AI. Furthermore, when the result of the five-time chair standing test is 12 seconds or more, the assessment procedure execution unit 20 determines that sarcopenia is suspected and calculates the value of the proxy index AI.

[0078] Furthermore, if the subject's grip strength is less than the reference value (28 kg for men, 18 kg for women) and the five-time chair stand test takes 12 seconds or more, the assessment procedure execution unit 20 determines that the subject is suspected of having severe sarcopenia and calculates the value of the surrogate index AI. If the subject's grip strength is less than the reference value (28 kg for men, 18 kg for women) and the walking speed is less than 1.0 m / s, the assessment procedure execution unit 20 determines that the subject is suspected of having severe sarcopenia and calculates the value of the surrogate index AI. If the value of the surrogate index AI calculated by the surrogate index calculation unit 21 is less than the threshold value (6.02), the assessment procedure execution unit 20 determines that the subject has sarcopenia or severe sarcopenia. The assessment procedure execution unit 20 outputs a determination result indicating whether the subject has sarcopenia or severe sarcopenia to the output unit 12.

[0079] More specifically, the determination procedure execution unit 20 calculates the value of the substitute index AI. The substitute index AI is a linear combination equation having a term for gender, a term for weight, a term for lower leg circumference, and a term for thigh circumference. In this equation, the term for gender is a real number a3 or a4, the coefficient of the term for weight is a real number b2, the coefficient of the term for lower leg circumference is a real number c2, and the coefficient of the term for thigh circumference is a real number d2. When the gender of the subject is male, the value of the substitute index AI is calculated using the following calculation equation (3). AI = a3 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (3) Furthermore, when the subject is female, the proxy index value AI is calculated using the following calculation formula (4). AI = a4 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (4) When the unit of body weight is kg and the unit of lower leg circumference is cm, a3 is 0.67, a4 is -0.08, b2 is 0.04, c2 is 0.04, and d2 is 0.08.

[0080] The personal data storage unit 22 (see FIG. 3) stores information indicating the walking speed, grip strength, five-time chair stand test results, gender, weight, lower leg circumference, and thigh circumference of the subject input to the input unit 10. The determination procedure execution unit 20 executes a determination procedure to determine whether the subject has sarcopenia or severe sarcopenia based on the information stored in the personal data storage unit 22.

[0081] The judgment condition data storage unit 23 stores the judgment condition data input to the input unit 10. The judgment condition data includes, for example, walking speed, grip strength, the results of the five-time chair stand test, the reference value of the surrogate index AI, and the real numbers a3, a4, b2, c2, and d2 used for judgment in the judgment procedure. The judgment procedure execution unit 20 makes a judgment based on the walking speed, the reference value of grip strength, and the results of the five-time chair stand test stored in the judgment condition data storage unit 23, and calculates the surrogate index AI to which the real numbers a3, a4, b2, c2, and d2 are set. Furthermore, the judgment procedure execution unit 20 judges the subject to have sarcopenia or severe sarcopenia if the value of the surrogate index AI is less than the reference value (6.02).

[0082] As described above, the judgment unit 11 judges that the subject has sarcopenia or severe sarcopenia if the results of the grip strength, walking speed, and five-times chair stand test of the subject are NG and the value of the proxy index AI calculated by the calculation formula (3) or (4) is less than the reference value.

[0083] The hardware configuration of the sarcopenia diagnostic device 1 according to this embodiment is the same as the hardware configuration according to the first embodiment shown in FIG.

[0084] Next, the processing of the sarcopenia diagnostic device 1 according to the embodiment of the present invention, that is, the flow of the determination program 41 (see FIG. 4), will be described.

[0085] 12, first, the input unit 10 inputs information indicating the subject's grip strength, walking speed, sex, weight, lower leg circumference, thigh circumference, and the results of a five-time chair stand test (step S31). As shown in FIG. 4, the CPU 30 displays an input screen (see FIG. 13) for this information on the man-machine interface 33, and the operator inputs operation inputs to the input screen via the man-machine interface 33. The CPU 39 stores the input information in the memory 31.

[0086] Next, the determination procedure execution unit 20 of the determination unit 11 determines whether the results of the subject's grip strength, walking speed, and five-times chair stand test indicate a suspicion of sarcopenia or severe sarcopenia according to the Asian standard sarcopenia diagnostic chart shown in Figure 10 (step S32). If it is determined that sarcopenia is suspected, this fact is stored, and if it is determined that severe sarcopenia is suspected, this fact is stored.

[0087] If the results of the subject's grip strength, walking speed, and five-times chair stand test do not indicate a suspicion of sarcopenia or severe sarcopenia (step S32; No), the output unit 12 displays a message saying "Not sarcopenia" (FIG. 14(C)) (step S38). On the other hand, if the results of the subject's grip strength, walking speed, and five-times chair stand test meet the above conditions (1) to (5) (step S32; Yes), the determination procedure execution unit 20 determines whether the subject is male (step S33). If the subject is male (step S33; Yes), the determination procedure execution unit 20 causes the surrogate index calculation unit 21 to calculate the value of the surrogate index AI using the calculation formula (3) for men (step S34). On the other hand, if the subject is female (step S33; No), the determination procedure execution unit 20 causes the surrogate index calculation unit 21 to calculate the value of the surrogate index AI using the calculation formula (4) for women (step S35).

[0088] After steps S34 and S35, the judgment procedure execution unit 20 determines whether the value of the substitute index AI is less than the threshold value (6.02) (step S36). If the value of the substitute index AI is less than the threshold value (step S36; Yes), the judgment procedure execution unit 20 determines whether the judgment result of step S32 is sarcopenia (step S40). If it is sarcopenia (step S40; Yes), the output unit 12 outputs the judgment result (FIG. 14(A)) that it is sarcopenia ("sarcopenia is suspected") (step S37). If it is not sarcopenia (step S40; No), the output unit 12 outputs the judgment result (FIG. 14(B)) that it is severe sarcopenia ("severe sarcopenia is suspected") (step S39).

[0089] On the other hand, if the value of the calculation formula is equal to or greater than the threshold value (step S36; No), the output unit 12 outputs a determination result (FIG. 14(C)) that the patient does not have sarcopenia (step S38). After steps S37, S38, and S39 are completed, the process ends.

[0090] Similarly to the above-described formulas (1) and (2), formulas (3) and (4) can be regression line equations generated by performing multivariate analysis on data of multiple subjects who are at least a first age and at most a second age, where the first age can be 40 years old and the second age can be 89 years old. However, the ages are not limited to this.

[0091] As described above in detail, the sarcopenia diagnostic device 1 according to this embodiment determines whether a subject has sarcopenia or severe sarcopenia based on the subject's gender, weight, lower leg circumference, thigh circumference, grip strength, walking speed, and the results of a five-time chair stand test. This makes it possible to determine whether a subject has sarcopenia or severe sarcopenia using only easily measurable items, without the need for a skeletal muscle index that requires special equipment. As a result, sarcopenia or severe sarcopenia can be diagnosed early and easily.

[0092] Furthermore, the sarcopenia diagnostic device 1 according to the above embodiment determines whether a subject has sarcopenia using the regression line formulas (1) and (2) or (3) and (4) generated by performing multivariate analysis on data from multiple subjects aged 40 or more and 89 or less. In this case, the determination unit may determine whether a subject has sarcopenia using the formulas (1) and (2) or (3) and (4) when the subject is aged 40 or more and 89 or less. That is, the sarcopenia diagnostic device 1 may input the subject's age and perform processing such that sarcopenia is not determined if the subject is not aged 40 or more and 89 or less. By limiting the subjects to the ages at which the data used to generate the formulas (1) and (2) or (3) and (4) was obtained, it is possible to prevent a decrease in the reliability of the determination. In this way, if the subject is not an adult, for example, and is outside the target age range, processing may be performed in which no judgment is made.

[0093] However, even for subjects in their 30s or subjects aged 90 or over, it is possible to assess sarcopenia using the above calculation formulas (1) and (2) or calculation formulas (3) and (4) based on data from subjects aged 40 or over and 89 or under. The sarcopenia diagnostic device 1 according to this embodiment can be applied to subjects of an age at which sarcopenia assessment is necessary.

[0094] Furthermore, the age of the subject from which data is acquired to determine the calculation formulas (1) and (2) or the calculation formulas (3) and (4) is not limited to 40 years or older and 89 years or younger. The first age and the second age can be changed as appropriate. For example, the first age may be 30 years old. Furthermore, calculation formulas with different coefficients or factors for linear combination may be used depending on the age of the subject.

[0095] Furthermore, in the sarcopenia diagnostic device 1 according to the above embodiment, after making a diagnosis based on walking speed and grip strength, a diagnosis based on the proxy index AI is made. However, the sarcopenia diagnostic device 1 may also be configured to make a diagnosis on subjects whose walking speed is known to be below the standard value or whose grip strength is known to be less than the standard value. In this case, the sarcopenia diagnostic device 1 will make a diagnosis of sarcopenia using only the proxy index AI.

[0096] In this way, the calculation formula can be changed, and other factors can be incorporated. For example, terms for age and GNRI can be incorporated into calculation formulas (1) and (2) or (3) and (4). The sarcopenia diagnostic device 1 can easily change the calculation formula by having the computer execute the determination program 41.

[0097] In the above embodiment, the calculation formula is different for men and women, but the present invention is not limited to this. The calculation formula may be the same for men and women, and the reference value to be compared with the value of the calculation formula may be different for men and women.

[0098] The sarcopenia assessment using the above-mentioned formulas (1), (2), and (3), (4) was conducted for Japanese subjects. If the subject is not Japanese, the assessment may be omitted. Furthermore, if the subject is an Asian or Westerner, the surrogate index AI must be calculated using a formula different from formulas (1), (2), (3), and (4), for example, a formula with different coefficients or linear combination factors. In particular, when the subject is a Westerner, it is desirable to use a formula based on the diagnostic criteria of the European Working Group on Sarcopenia in Older People (EWGSOP). According to these criteria, for example, grip strength is assessed using the surrogate index AI when it is less than 30 kg for men and less than 20 kg for women.

[0099] Furthermore, the hardware configuration and software configuration of the sarcopenia diagnostic device 1 are merely examples and can be changed and modified as desired.

[0100] The core processing section of the sarcopenia diagnostic device 1, which is composed of the input unit 10, determination unit 11, output unit 12, etc., can be realized using an ordinary computer system rather than a dedicated system. For example, a computer program for executing the above operations may be stored and distributed on a computer-readable recording medium (flexible disk, CD-ROM, DVD-ROM, etc.), and the sarcopenia diagnostic device 1 that executes the above processing may be configured by installing the computer program on a computer. Alternatively, the sarcopenia diagnostic device 1 may be configured by storing the computer program in a storage device of a server device on a communication network such as the Internet, and downloading it into an ordinary computer system.

[0101] When the functions of the sarcopenia diagnostic device 1 are realized by sharing the functions between an OS (operating system) and an application program, or by cooperation between the OS and the application program, only the application program portion may be stored in a recording medium or storage device.

[0102] It is also possible to superimpose a computer program on a carrier wave and distribute it over a communications network. For example, the computer program may be posted on a bulletin board system (BBS) on the communications network and distributed over the network. The computer program may then be started and executed under the control of an OS in the same way as any other application program, thereby enabling the above-described processing to be performed.

[0103] This invention allows various embodiments and modifications without departing from the broad spirit and scope of this invention. Furthermore, the above-described embodiments are intended to explain this invention and do not limit the scope of this invention. That is, the scope of this invention is defined by the claims, not the embodiments. Various modifications made within the scope of the claims and the meaning of the invention equivalent thereto are considered to be within the scope of this invention. [Industrial Applicability]

[0104] The present invention can be applied to the assessment of sarcopenia. [Explanation of symbols]

[0105] 1 Sarcopenia diagnostic device, 10 Input unit, 11 Judgment unit, 12 Output unit, 20 Judgment procedure execution unit, 22 Personal data storage unit, 23 Judgment condition data storage unit, 30 CPU, 31 Memory, 32 Auxiliary storage device, 33 Man-machine interface, 34 Communication interface, 35 Input / output interface, 40 Internal bus, 41 Judgment program, 42 Judgment condition data, 50 Recording medium, AI proxy index, SMI Skeletal muscle index

Claims

1. an input unit for inputting information indicating the sex, weight, and lower leg circumference of an adult subject; A determination unit that calculates a value of a substitute index to be used instead of a skeletal muscle index based on information indicating the sex, weight, and lower leg circumference of the subject inputted to the input unit, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value; Equipped with The value of the substitute index is expressed as follows, where the term for sex is a real number a1 or a2, the coefficient for the term for weight is a real number b1, and the coefficient for the term for lower leg circumference is a real number c1: When the subject is male, the value is calculated by the formula (1), Substitute index = a1 + b1 × weight + c1 × lower leg circumference (1) When the subject is a woman, the value is calculated by the formula (2), Substitute index = a2 + b1 × weight + c1 × lower leg circumference (2) When the unit of the body weight is kg and the unit of the lower leg circumference is cm, a1 is 2.01 and a2 is 1.25; b1 is 0.06, c1 is 0.05, The reference value is 5.

78. Sarcopenia diagnostic device.

2. an input unit for inputting information indicating the sex, weight, lower leg circumference, and thigh circumference of an adult subject; A determination unit that calculates a value of a substitute index to be used in place of a skeletal muscle index based on information indicating the sex, weight, lower leg circumference, and thigh circumference of the subject inputted to the input unit, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value; Equipped with The value of the substitute index is expressed as follows, where the term for sex is a real number a3 or a real number a4, the coefficient for the term for weight is a real number b2, the coefficient for the term for lower leg circumference is a real number c2, and the coefficient for the term for thigh circumference is a real number d2: When the subject is male, the value is calculated by the formula (3), Substitute index = a3 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (3) When the subject is a woman, the value is calculated by the formula (4), Substitute index = a4 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (4) If the unit of weight is kg and the unit of lower leg circumference is cm, a3 is 0.67 and a4 is −0.08; b2 is 0.04, c2 is 0.04, and d2 is 0.08; The reference value is 6.

02. Sarcopenia diagnostic device.

3. The determination unit When the walking speed of the subject is equal to or less than a reference value or the grip strength of the subject is less than a reference value, Using the calculation formula (1) or (2), determine whether the subject has sarcopenia. The sarcopenia diagnostic device according to claim 1.

4. The determination unit When the grip strength of the subject is less than the reference value, when the result of the five-time chair stand test of the subject is equal to or longer than the reference time, or when the walking speed of the subject is equal to or lower than the reference value, Using the calculation formula (3) or (4), determine whether the subject has sarcopenia. The sarcopenia diagnostic device according to claim 2.

5. The determination unit If the grip strength of the subject is less than the reference value and the result of the five-time chair stand test of the subject is equal to or longer than the reference time, if the grip strength of the subject is less than the reference value and the walking speed of the subject is equal to or lower than the reference value, Using the calculation formula (3) or (4), determine whether the subject has severe sarcopenia. The sarcopenia diagnostic device according to claim 2.

6. The calculation formulas (1) and (2) or the calculation formulas (3) and (4) are a regression line equation generated by performing multivariate analysis on data of a plurality of subjects who are equal to or greater than a first age and equal to or less than a second age; The determination unit When the age of the subject is equal to or greater than the first age and equal to or less than the second age, Using the calculation formula (1) or (2) or the calculation formula (3) or (4), determine whether the subject has sarcopenia. The sarcopenia diagnostic device according to claim 1 or 2.

7. The first age is 40 years old and the second age is 89 years old. The sarcopenia diagnostic device according to claim 6.

8. Computer, an input unit for inputting information indicating the sex, weight, and lower leg circumference of an adult subject; a determination unit that calculates a value of a substitute index to be used in place of a skeletal muscle index based on information indicating the sex, weight, and lower leg circumference of the subject inputted to the input unit, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value; It functions as The value of the substitute index is expressed as follows, where the term for sex is a real number a1 or a2, the coefficient for the term for weight is a real number b1, and the coefficient for the term for lower leg circumference is a real number c1: When the subject is male, the value is calculated by the formula (1), Substitute index = a1 + b1 × weight + c1 × lower leg circumference (1) When the subject is a woman, the value is calculated by the formula (2), Substitute index = a2 + b1 × weight + c1 × lower leg circumference (2) When the unit of the body weight is kg and the unit of the lower leg circumference is cm, a1 is 2.01 and a2 is 1.25; b1 is 0.06, c1 is 0.05, The reference value is 5.

78. program.

9. Computer, an input unit for inputting information indicating the sex, weight, lower leg circumference, and thigh circumference of an adult subject; a determination unit that calculates a value of a substitute index to be used in place of a skeletal muscle index based on information indicating the sex, weight, lower leg circumference, and thigh circumference of the subject inputted to the input unit, and determines that the subject has sarcopenia when the value of the substitute index is less than a reference value; It functions as The value of the substitute index is expressed as follows, where the term for sex is a real number a3 or a real number a4, the coefficient for the term for weight is a real number b2, the coefficient for the term for lower leg circumference is a real number c2, and the coefficient for the term for thigh circumference is a real number d2: When the subject is male, the value is calculated by the formula (3), Substitute index = a3 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (3) When the subject is a woman, the value is calculated by the formula (4), Substitute index = a4 + b2 × weight + c2 × lower leg circumference + d2 × thigh circumference (4) If the unit of weight is kg and the unit of lower leg circumference is cm, a3 is 0.67 and a4 is −0.08; b2 is 0.04, c2 is 0.04, and d2 is 0.08; The reference value is 6.

02. program.

Images