JP7748698B2 - Sarcopenia diagnostic device and program - Google Patents

Description

Article 30, Paragraph 2 of the Patent Act applies. Website: https://www.journals.elsevier.com/journal-of-cardiology https://www.sciencedirect.com/science/article/abs/pii/S0914508721000733 https://doi.org/10.1016/j.jjcc.2021.03.009 https://www.journal-of-cardiology. com/article/S0914-5087(21)00073-3/fulltext Publication date: April 16, 2021

The present invention relates to a sarcopenia diagnostic device and program.

In an aging society, measures to extend healthy life expectancy are desirable. Healthy life expectancy 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 life expectancy. Sarcopenia is a condition in which skeletal muscle mass and muscle function decrease due to aging or disease.

When diagnosing sarcopenia using global diagnostic criteria, it is essential to measure appendicular skeletal muscle mass 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 literature 1 and 2).

Measurement using the DXA method requires the installation of large, dedicated equipment in an X-ray examination room, and although it is relatively rare, radiation exposure during measurement 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 principles, it is not possible to measure patients with implanted devices such as pacemakers.

Because sarcopenia increases overall and cardiovascular mortality rates, early diagnosis and prevention are desirable, but the rate of diagnostic testing in clinical settings remains low. One reason for this is the difficulty of measuring appendicular skeletal muscle mass and calculating skeletal muscle index, both of which are essential for diagnosis, namely the DXA and BIA methods.

Ken Yamauchi, "Basics and Applications of Body Composition Analysis: Principles of BIA and Body Composition Evaluation," Surgery, Metabolism and Nutrition, Vol. 53, No. 4, August 2019 Yuki Yanagimachi, Hirofumi Nakayama, Masahiko Yamaichi, Tomoyuki Fujita, 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

As mentioned above, measuring the skeletal muscle mass required to diagnose sarcopenia requires large, expensive, specialized equipment. This has the disadvantage of making early and simple diagnosis difficult.

The present invention was 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.

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;
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 .

A sarcopenia diagnostic device according to a 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, 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.

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.

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.
This may also be the case.

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.
This may also be the case.

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.
This may also be the case.

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

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;
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.

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;
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 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.

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 skeletal muscle index, which requires special equipment. As a result, sarcopenia can be diagnosed early and easily.

FIG. 1 shows a sarcopenia diagnostic chart based on the 2014 Asian criteria diagnostic criteria. 1 is a block diagram showing the functional configuration of a sarcopenia diagnostic device according to a first embodiment of the present invention. FIG. FIG. 3 is a block diagram showing the configuration of a determination unit of the sarcopenia diagnostic device of FIG. 2. FIG. 3 is a block diagram showing the hardware configuration of the sarcopenia diagnostic device of FIG. 2. 3 is a flowchart showing the operation of the sarcopenia diagnostic device of FIG. 2. FIG. 10 is a diagram illustrating an example of an information input screen. 10A and 10B are diagrams showing an example of a display screen for the determination result. (A) is a diagram showing the correlation between skeletal muscle index and surrogate index in general health examinees, and (B) is a diagram showing the correlation between skeletal muscle index and surrogate index in cardiovascular disease patients. This figure shows the Asian criteria sarcopenia diagnostic chart according to the 2019 diagnostic criteria. 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. FIG. 10 is a block diagram showing the functional configuration of a sarcopenia diagnostic device according to a second embodiment of the present invention. 12 is a flowchart showing the operation of the sarcopenia diagnostic device of FIG. 11. FIG. 10 is a diagram illustrating an example of an information input screen. 10A, 10B, and 10C are diagrams showing examples of display screens for determining results.

Embodiments of the present invention will now be described in detail with reference to the drawings. In each drawing, the same or equivalent parts are designated by the same reference numerals.

[Asian Standard Sarcopenia Diagnostic Chart]
First, a conventional method for diagnosing sarcopenia will be described. This diagnostic method follows the Asian sarcopenia diagnostic chart shown in FIG. 1. This chart was created based on the sarcopenia diagnostic criteria published in 2014. As shown in FIG. 1, this diagnostic chart diagnoses sarcopenia in elderly individuals if their walking speed is 0.8 m/sec or less, or if their grip strength is less than 26 kg for men and less than 18 kg for women (Step S1; Yes), and their muscle mass (skeletal muscle index, SMI) is less than 7.0 kg/ ^m2 for men and less than 5.4 kg/ ^m2 for women.

Skeletal muscle index (SMI) is the sum of muscle mass in the limbs divided by the square of height (m). Muscle mass can be obtained by measuring body composition using the DXA or BIA methods, as described above.

First Embodiment
[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 (a first age) and 89 years or younger (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).

[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 .

The input unit 10 inputs information indicating the subject's grip strength, walking speed, gender, weight, and lower leg circumference. The information indicating the subject's grip strength, walking speed, weight, and lower leg circumference uses numerical 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.

The determination unit 11 determines whether 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 the calculation formula described below to determine the value of the substitute index AI, and determines that the subject has sarcopenia if the value of the substitute index AI is less than the reference value. In this embodiment, the reference value is set to 5.78.

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.

[Determination process]
The sarcopenia determination process performed by the determination unit 11 will now be described in more detail. 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.

The assessment procedure execution unit 20 determines whether the subject has sarcopenia in accordance with a predetermined assessment procedure based on information indicating the subject's walking speed, grip strength, gender, weight, and lower leg circumference. The assessment procedure execution unit 20 calculates the value of the proxy index AI, for example, if the subject's walking speed is equal to or less than a reference value (0.8 m/sec) or if the subject's grip strength is less than a reference value (26 kg for men; 18 kg for women). The assessment procedure execution unit 20 determines that the subject has sarcopenia if the value of the proxy index AI calculated by the proxy index calculation unit 21 is less than a threshold value (5.78). The assessment procedure execution unit 20 outputs a determination result indicating whether the subject has sarcopenia to the output unit 12.

More specifically, the assessment 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, and a term for lower leg circumference. In this equation, 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 equation (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 calculation formula (2).
AI = a2 + b1 × weight + c1 × lower leg circumference (2)
When the unit of body weight is kg and the unit of the circumference of the lower leg is cm, a1 is 2.01, a2 is 1.25, b1 is 0.06, and c1 is 0.05.

The personal data storage unit 22 stores information indicating the subject's walking speed, grip strength, gender, weight, and lower leg circumference input to the input unit 10. The judgment procedure execution unit 20 executes a judgment procedure to determine whether the subject has sarcopenia based on the information stored in the personal data storage unit 22.

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 for the proxy 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 for walking speed and grip strength stored in the judgment condition data storage unit 23, and calculates the proxy index AI for which real numbers a1, a2, b1, and c1 are set. Furthermore, the judgment procedure execution unit 20 judges the subject to have sarcopenia if the value of the proxy index AI is less than the reference value (5.78).

As described above, the determination unit 11 determines that the subject has sarcopenia if the subject's walking speed is equal to or less than the reference value or if the subject's grip strength is less than the reference value, and if the value of calculation formula (1) or (2) is less than the reference value.

[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.

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

The memory 31 is, for example, RAM (Random Access Memory). As described above, the judgment program 41 and judgment condition data 42 executed by the CPU 30 are loaded into the memory 31, and the judgment results resulting from the execution of the judgment program 41 by the CPU 30 are also stored in the memory 31. The sarcopenia diagnostic device 1 also includes 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.

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 executed by the CPU 30. The judgment program 41 is stored on 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 in Figure 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.

The man-machine interface 33 includes an operation input unit through which the operator inputs operations, and a display with a display screen. In this embodiment, the man-machine interface 33 is a touch panel. However, a keyboard and pointing device may be provided as the operation input unit, and a display may be provided separately. The functions of the input unit 10 and output unit 12 are realized by the man-machine interface 33.

The communication interface 34 is a communication interface that conforms to a communication network such as the Internet. The judgment program 41 and judgment condition data 42 can be stored in the auxiliary storage device 32 via the communication interface 34.

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 this input/output interface 35 and can be stored in the auxiliary storage device 32.

Next, the processing of the sarcopenia diagnostic device 1 according to an embodiment of the present invention, i.e., the flow of the judgment program 41, will be described. When this processing begins, 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, loaded into memory 31, and is in an executable state. Furthermore, 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 memory 31.

As shown in FIG. 5, the input unit 10 inputs information indicating the subject's grip strength, walking speed, gender, 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 for this information (see FIG. 6) on the man-machine interface 33, and the operator's input to the input screen is input via the man-machine interface 33. The CPU 39 stores the input information in the memory 31.

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

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 (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 (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 (Step S15). In Step S13, as shown in FIG. 4, the CPU 30 makes a determination based on the gender of the subject loaded into memory 31. In addition, in Steps S14 and S15, the CPU 30 performs a comparison calculation between the walking speed and grip strength of the subject and the reference values for walking speed and grip strength loaded into memory 31.

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 judgment procedure execution unit 20 judges whether the subject is male (Step S16). Here, as shown in FIG. 4, the CPU 30 makes the judgment based on the subject's gender stored in memory 31.

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 calculation formula (1) for men (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 calculation formula (2) for women (step S18). Here, the CPU 30 performs calculation using calculation formula (1) or calculation formula (2) based on the values of real numbers a1, a2, b1, and c1 loaded into memory 31.

After steps S17 and S18, the judgment 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 a judgment result indicating 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 a judgment result indicating no sarcopenia (step S21).

In addition, if the gender is male and the grip strength is less than 26 kg (step S14; No) or if the gender is female and the grip strength is less than 18 kg (step S15; No), the output unit 12 also outputs a 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).

Here, the CPU 30 displays the sarcopenia assessment result on the display screen of the man-machine interface 33. For example, in step S20, as shown in Figure 7 (A), the text "Sarcopenia is suspected" is displayed on the man-machine interface 33. Also, in step S21, as shown in Figure 7 (B), the text "Not sarcopenia" is displayed on the man-machine interface 33.

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. Furthermore, 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.

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.

[How to generate a 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.

The following factors are expected to influence AI, a proxy index for 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 (one of the bone mineral density indexes), grip strength, knee extension strength, usual walking speed, functional reach test, five repetition chair stand test, timed up and go test (the above three are tests to evaluate athletic ability), blood albumin concentration, GNRI (Geriatric Nutritional Risk Index). Index; an index that indicates 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 that indicates bone metabolism status), blood zinc concentration

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

Next, in step 2, univariate analysis was used to extract from the above evaluation items other than the skeletal muscle index (SMI) items that showed a statistically significant correlation with the skeletal muscle index (SMI). As a result, eight items were extracted: age, height, weight, upper arm circumference, thigh circumference, lower leg circumference, grip strength, and GNRI.

Next, in step 3, grip strength corresponds to the first stage of the diagnostic criteria in the Asian criteria sarcopenia diagnostic flowchart. Therefore, multivariate analysis (stepwise analysis) was performed on 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 shown in Figure 1, and a regression line equation was calculated using the three significantly extracted parameters: gender, weight, and calf circumference. Here, the stepwise analysis is also known as the variable addition/deletion method. In the stepwise analysis, a significant regression model is created by incorporating and removing significant explanatory variables (independent variables) one by one. Thus, the 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).

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.

As explained in detail above, 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, which requires special equipment. As a result, sarcopenia can be diagnosed early and easily.

The sarcopenia diagnostic device 1 according to this embodiment allows a subject to be diagnosed with sarcopenia by narrowing down the factors from a large number of factors to the subject's gender, weight, and lower leg circumference. This feature is the result of findings obtained through the inventor's own research and experiments, and is not something that could be easily conceived.

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

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

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.

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 SPBB are evaluation items for "physical function." If sarcopenia is suspected based on these evaluation criteria for muscle strength or physical function (Step S3; Yes), if DXA indicates a skeletal muscle mass of less than 7.0 kg/ ^m2 for men and less than 5.4 kg/ ^m2 for women, or if BIA indicates a skeletal muscle mass of less than 7.0 kg/ ^m2 for men and less than 5.7 kg/ ^m2 for women (Step S4; Yes), sarcopenia or severe sarcopenia is diagnosed. Here, sarcopenia refers to a condition in which skeletal muscle mass is below the standard value and either muscle strength or physical function is below the standard value, and severe sarcopenia refers to a condition in which skeletal muscle mass is below the standard value and both physical function and muscle strength are below the standard value.

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 five-time chair stand test exceed the standard time (NG), sarcopenia is suspected.
(3) If the walking speed is below the standard value (NG), sarcopenia is suspected.
(4) If the grip strength is below the standard value (NG) and the result of the five-time chair stand test exceeds 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 results of the five-time chair stand test exceed the standard time (normal), the patient is considered normal.
As shown in Figure 10, according to the 2019 sarcopenia criteria, in addition to these judgment results, if skeletal muscle mass meets the criteria, it is judged to be sarcopenia or severe sarcopenia.

In addition, the 2019 sarcopenia diagnostic criteria also use the SPPB score results as a criterion for assessment. However, in the table shown in Figure 10, the SPPB score results are not included in the assessment criteria. The sarcopenia diagnostic device 1 according to this embodiment assesses normal, sarcopenia, and severe sarcopenia using assessment criteria that do not include SPPB.

As shown in FIG. 11, the sarcopenia diagnostic device 1 is an information processing device that includes an input unit 10, a determination unit 11, and an output unit 12, just like in the first embodiment.

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 the input screen for this information. The five-time chair stand test examines the time (seconds) required to sit down and stand from a chair five times.

The determination unit 11 determines whether 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 the calculation formula described below to determine the value of the substitute index AI, and if the value of the substitute index AI is less than the reference value, determines that the subject has sarcopenia or severe sarcopenia. In this embodiment, the reference value is set to 6.02.

The output unit 12 outputs the determination result as to whether the subject has sarcopenia or severe sarcopenia, just as in the above embodiment.

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

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 proxy 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 proxy 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; 18 kg for women), the assessment procedure execution unit 20 determines that sarcopenia is suspected and calculates the value of the proxy index AI. If the walking speed is less than 1.0 m/s, the assessment procedure execution unit 20 determines that sarcopenia is suspected and calculates the value of the proxy index AI. Furthermore, if the result of the five-time chair stand test is 12 seconds or longer, the assessment procedure execution unit 20 determines that sarcopenia is suspected and calculates the value of the proxy index AI.

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 severe sarcopenia is suspected and calculates the value of the proxy 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 severe sarcopenia is suspected and calculates the value of the proxy index AI. If the value of the proxy index AI calculated by the proxy 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.

More specifically, the assessment 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 gender term is a real number a3 or a4, the coefficient of the weight term is a real number b2, the coefficient of the lower leg circumference term is a real number c2, and the coefficient of the thigh circumference term 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.

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

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 for 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).

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

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 Figure 4.

Next, we will explain the processing of the sarcopenia diagnostic device 1 according to an embodiment of the present invention, i.e., the flow of the judgment program 41 (see Figure 4).

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

Next, the assessment procedure execution unit 20 of the assessment unit 11 determines whether the results of the subject's grip strength, walking speed, and five-time 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 a judgment is made that sarcopenia is suspected, this fact is stored; if a judgment is made that severe sarcopenia is suspected, this fact is stored.

If the results of the subject's grip strength, walking speed, and five-time chair stand test do not indicate a suspicion of sarcopenia or severe sarcopenia (Step S32; No), the output unit 12 displays "Not sarcopenic" (FIG. 14(C)) (Step S38). On the other hand, if the results of the subject's grip strength, walking speed, and five-time 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 proxy index calculation unit 21 to calculate the value of the proxy 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 proxy index calculation unit 21 to calculate the value of the proxy index AI using the calculation formula (4) for women (Step S35).

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

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 (Figure 14(C)) that sarcopenia is not present (step S38). After steps S37, S38, and S39 are completed, the processing ends.

As with the above-mentioned formulas (1) and (2), formulas (3) and (4) can be regression line equations generated by performing multivariate analysis on data for 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.

As described in detail above, 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 the 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.

In addition, the sarcopenia diagnostic device 1 according to the above embodiment determines whether a subject has sarcopenia using calculation formulas (1), (2), or (3), (4), which are regression line formulas 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 calculation formulas (1) or (2) or (3), (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 calculation formulas (1), (2), or (3), (4) were obtained, it is possible to prevent a decrease in the reliability of the determination. In this way, if the subject is not an adult or falls outside the target age range, processing may be performed such that sarcopenia is not determined.

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

Furthermore, the age of the subject from which data is acquired to determine calculation formulas (1) and (2) or calculation formulas (3) and (4) is not limited to 40 years or older and 89 years or younger. The first age and 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.

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 below the standard value. In this case, the sarcopenia diagnostic device 1 will make a diagnosis of sarcopenia using only the proxy index AI.

In this way, the calculation formula can be modified, 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 modify the calculation formula by having the computer execute the determination program 41.

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

The sarcopenia assessment using the above-mentioned formulas (1), (2) or (3), (4) was conducted for Japanese subjects. If the subject is not Japanese, a process that does not involve assessment may be performed. Furthermore, if the subject is an Asian or Westerner other than Japanese, it is necessary to calculate the surrogate index AI using a formula different from formulas (1), (2) or (3), (4), for example, a formula with different coefficients or linearly combined factors. In particular, if the subject is a Westerner, it is desirable to use a formula in accordance with the diagnostic criteria of the European Working Group on Sarcopenia in Older People (EWGSOP). According to these criteria, for example, a grip strength assessment using the surrogate index AI would be conducted for grip strengths of less than 30 kg for men and less than 20 kg for women.

Furthermore, the hardware and software configurations of the sarcopenia diagnostic device 1 are examples and can be changed and modified as desired.

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 a normal 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 communications network such as the Internet, and downloading it to a normal computer system.

If 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 collaboration between an OS and an application program, then only the application program portion may be stored on a recording medium or storage device.

It is also possible to superimpose a computer program onto 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. This computer program may then be launched and run under the control of the OS in the same way as any other application program, thereby enabling the above-mentioned processing to be performed.

This invention allows for various embodiments and modifications without departing from the broad spirit and scope of the invention. Furthermore, the above-described embodiments are intended to explain the invention and do not limit the scope of the invention. In other words, the scope of the 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 deemed to be within the scope of the invention.

The present invention can be applied to the assessment of sarcopenia.

1 Sarcopenia diagnostic device, 10 Input unit, 11 Determination unit, 12 Output unit, 20 Determination procedure execution unit, 22 Personal data storage unit, 23 Determination 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 Determination program, 42 Determination condition data, 50 Recording medium, AI Substitute index, SMI Skeletal muscle index

Claims (9)

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