JP2015102381A - Diabetes index value estimation system and diabetes index value estimation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately estimate a diabetes index value without sampling blood.SOLUTION: A diabetes index value estimation device 10 included in a diabetes index value estimation system 1, comprises: an acetone concentration input unit 11 for inputting a concentration value of acetone discharged from a subject; a subject type input unit 12 for inputting information representing a type of the subject; an index value estimation unit 13 that selects any of analytical curve from a plurality of analytical curves representing a relationship between the concentration value of the acetone and a blood diabetes index value according to the type of the subject stored in advance on the basis of the information representing the type of the subject, and estimates the blood diabetes index value of the subject from the selected analytical curve and the concentration value of the acetone; and an output unit 14 for outputting the estimated index value.

Description

  The present invention relates to a diabetes index value estimation system and a diabetes index value estimation method for estimating a blood diabetes index value of a subject.

  Diabetes is one of the metabolic syndromes that become chronically hyperglycemic due to decreased insulin action. It is said that 8.9 million people are suspected of having diabetes in Japan (National Health and Nutrition Survey 2007, Ministry of Health, Labor and Welfare), and diabetes is widely known as a lifestyle-related disease. There are blood glucose level (blood glucose concentration) and blood HbA1c concentration as main index values representing the symptoms of diabetes, and it is generally measured by blood sampling. However, since blood collection is accompanied by pain or a risk of getting an infection, a technique for measuring the above index value without blood collection is desired. For example, Patent Document 1 discloses a device that irradiates a living body with near-infrared light and estimates a blood glucose level from the obtained optical spectrum.

  On the other hand, acetone contained in the gas component released from the living body is one of the metabolites produced by the burning and decomposition of body fat, and after it is produced in the blood, it expires through the lungs and skin. It is discharged outside the body as gas or skin gas. For healthy people who are not diabetic, sugar is first consumed as energy, then fat is used as energy. It is known that diabetic patients have abnormal sugar metabolism and fat tends to be used as energy as a whole because fat is used as energy even if sugar remains. Acetone is expected as a non-invasive indicator for monitoring the presence or absence of diabetes and the success or failure of control, and the correlation between the acetone concentration and blood glucose level has been verified.

  Non-Patent Document 1 discloses a result of verifying the correlation between the breath acetone concentration of a diabetic patient and the above index value. Four diabetic patients (low blood glucose level with glucose concentration 40-100 mg / dl, boundary blood glucose level with 101-150 mg / dl, hyperglycemia with 151-200 mg / dl depending on the level of blood glucose concentration or blood HbA1c concentration Value, 201-419 mg / dl ultra-high blood glucose level) or 3 (standard HbA1c concentration of 5.9-6.9%, 7.0-9.9% high, 10-13% ultra-high) When the average breath acetone concentration of diabetic patients in each group is calculated, it is disclosed that there is a positive correlation in which the higher the index value, the higher the average breath acetone concentration tends to be.

International Publication No. 2011-013694

C. Wang, et al., IEEE Sensors J. vol.10, pp.54-63, 2010.

  In all of the conventional techniques based on the above-mentioned documents, the index value can be estimated without blood collection, but there is a problem in the estimation accuracy. The method according to Patent Document 1 has a problem that since the change in the optical spectrum with respect to the change in the blood glucose level is small, it is easily influenced by the measurement environment light and the skin condition, and the measurement error tends to increase. The method according to Non-Patent Document 1 has a problem that the index value can only be roughly estimated by three or four levels.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a diabetes index value estimation system and a diabetes index value estimation method capable of accurately estimating a diabetes index value without performing blood collection. And

  In order to achieve the above object, a diabetes index value estimation system according to the present invention inputs acetone concentration input means for inputting a concentration value of acetone released from a subject, and information indicating the type of the subject. Based on the information indicating the type of the subject input by the subject type input means and the subject type input means, a plurality of acetone concentration values corresponding to the type of the subject stored in advance Select one of the calibration curves from the calibration curve indicating the relationship between the blood diabetes index value and the blood diabetes index value, and the blood diabetes index value of the subject from the selected calibration curve and the concentration value input by the acetone concentration input means An index value estimating means for estimating, and an output means for outputting the index value estimated by the index value estimating means.

  In the diabetes index value estimation system according to the present invention, the concentration value of acetone released from the subject is used to estimate the blood diabetes index value of the subject. Thereby, an index value can be estimated without performing blood collection. In the diabetes index value estimation system according to the present invention, the index value is estimated using a calibration curve selected based on the type of the subject. Thereby, since the estimation of an appropriate index value according to the type of the subject is performed, the index value can be estimated with high accuracy. That is, according to the diabetes index value estimation system of the present invention, it is possible to accurately estimate the diabetes index value without blood collection.

  The subject type input means may input information indicating a treatment for diabetes of the subject as information indicating the type of the subject. More specifically, the information indicating the treatment for diabetes of the subject is whether or not there is treatment for diabetes, whether or not the treatment is only for diet therapy, and whether or not the medicine for diabetes is being taken. Information indicating either the number of types of antidiabetic drugs and the type of antidiabetics being taken may be included. According to this configuration, the diabetes index value can be estimated appropriately and accurately with high accuracy.

  Furthermore, the information indicating the treatment for diabetes of the subject includes the number of types of antidiabetic drugs being taken and the information indicating the types of antidiabetics being taken. Select the calibration curve based on the number of types of diabetes therapeutics being taken, and the concentration input by the acetone concentration input means based on the pre-stored correction criteria according to the type of diabetes therapeutics being taken The value may be corrected, and the blood diabetes index value of the subject may be estimated from the corrected concentration value. According to this configuration, it is possible to estimate the diabetes index value appropriately and accurately with high accuracy according to the number of types of anti-diabetic drugs taken by the subject and the types.

  The diabetes index value estimation system may further include an acetone concentration measurement unit that measures the concentration value of acetone released from the subject. According to this configuration, the concentration value of acetone can be reliably input, and the present invention can be reliably implemented.

  The acetone concentration input means is a concentration value of acetone measured based on a gas component emitted from any one or more of exhaled breath, mucous membrane and skin of the subject as a concentration value of acetone released from the subject. A value may be input. According to this configuration, a concentration value of acetone suitable for estimating the diabetes index value can be input, and the diabetes index value can be estimated appropriately.

  The index value estimation means may estimate the blood glucose concentration or blood HbA1c concentration of the subject as the blood diabetes index value of the subject. According to this configuration, the diabetes index value can be estimated appropriately and reliably.

  By the way, the present invention can be described as an invention of a diabetes index value estimation system as described above, and can also be described as an invention of a diabetes index value estimation method as follows. This is substantially the same invention only in different categories, and has the same operations and effects.

  That is, a diabetes index value estimation method according to the present invention is a diabetes index value estimation method that is an operation method of a diabetes index value estimation system, and an acetone concentration input step of inputting a concentration value of acetone released from a subject. A subject type input step for inputting information indicating the type of the subject, and a subject stored in advance based on the information indicating the type of the subject input in the subject type input step. A calibration curve is selected from a plurality of calibration curves indicating the relationship between the concentration value of acetone and the blood diabetes index value according to the type, and the concentration value input in the selected calibration curve and acetone concentration input step The index value estimation step for estimating the blood diabetes index value of the subject and the output step for outputting the index value estimated in the index value estimation step.

  In the present invention, the blood diabetes index value of the subject is estimated by using the concentration value of acetone released from the subject. Thereby, an index value can be estimated without performing blood collection. In the present invention, an index value is estimated using a calibration curve selected based on the type of the subject. Thereby, since the estimation of an appropriate index value according to the type of the subject is performed, the index value can be estimated with high accuracy. That is, according to the present invention, it is possible to accurately estimate the diabetes index value without collecting blood.

It is a figure which shows the structure of the diabetes index value estimation system which concerns on embodiment of this invention. It is a graph which shows the relationship between the breath acetone concentration and blood glucose level of all the diabetic subjects. It is a graph which shows the relationship between the breath acetone concentration and the blood HbA1c density | concentration of all diabetic subjects. It is a graph which shows the relationship between the breath acetone concentration and blood glucose level of a non-diabetic subject and a diabetic subject only of diet therapy. It is a graph which shows the relationship between the breath acetone concentration and the blood HbA1c density | concentration of the diabetic subject only of diet therapy. It is a graph which shows the relationship between the measured value of the breath acetone concentration of a diabetic subject who is taking one kind of antidiabetic drug, and the blood glucose concentration. It is a graph which shows the relationship between the breath acetone density | concentration correction | amendment value and blood glucose level of the diabetic subject who is taking one kind of diabetes therapeutic agent. It is a graph which shows the relationship between the breath acetone concentration measurement value and blood HbA1c density | concentration of the diabetic subject who is taking one kind of diabetes therapeutic agent. It is a graph which shows the relationship between the breath acetone concentration correction value and the blood HbA1c density | concentration of the diabetic subject who is taking one type of diabetes therapeutic agent. It is a graph which shows the relationship between the measured value of the breath acetone concentration of a diabetic subject who is taking multiple types of antidiabetic drugs and the blood glucose concentration. It is a graph which shows the relationship between the breath acetone density | concentration correction value and blood glucose level of the diabetic subject who is taking the multiple types of diabetes therapeutic agent. It is a graph which shows the relationship between the breath acetone concentration measured value and blood HbA1c density | concentration of the diabetic subject who is taking the multiple types of diabetes therapeutic agent. It is a graph which shows the relationship between the breath acetone concentration correction value and the blood HbA1c density | concentration of the diabetic subject who is taking the multiple types of diabetes therapeutic agent. It is a figure which shows the hardware constitutions of the diabetes index value estimation apparatus contained in the diabetes index value estimation system which concerns on embodiment of this invention. It is a flowchart which shows the process (diabetes index value estimation method) performed with the diabetes index value estimation system which concerns on embodiment of this invention.

  Hereinafter, embodiments of a diabetes index value estimation system and a diabetes index value estimation method according to the present invention will be described in detail with reference to the drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and redundant description is omitted.

  FIG. 1 shows a diabetes index value estimation system 1 according to this embodiment. The diabetes index value estimation system 1 is a system that estimates a blood diabetes index value (physical quantity of a specific component contained in blood) of a subject from the concentration value of acetone released from the subject. Specifically, the diabetes index value estimated by the diabetes index value estimation system 1 is a blood glucose level (blood glucose concentration) and a blood HbA1c concentration.

  As shown in FIG. 1, the diabetes index value estimation system 1 includes a diabetes index value estimation device 10 and an acetone measurement device 20. The diabetes index value estimation device 10 and the acetone measurement device 20 can exchange information with each other via the network 30. The network 30 includes, for example, a mobile communication network or the Internet. In FIG. 1, the acetone measuring device 20 is directly connected to the network 30, but may be connected to the network 30 via a communication terminal device. That is, information indicating the measurement result by the acetone measuring device 20 may be output to the network 30 via the communication terminal device and transmitted to the diabetes index value estimating device 10.

  Here, the communication terminal device is, for example, a portable electronic device such as a mobile phone possessed by the user (subject) of the diabetes index value estimation system 1. The communication terminal device may be other than a cellular phone, and may be, for example, a smartphone, a tablet computer, a personal digital assistant (PDA), a portable personal computer, a palmtop computer, a laptop computer, or the like. Further, the communication terminal device is not necessarily limited to the above. Communication between the acetone measuring device 20 and the communication terminal device may be performed by wireless LAN (local area network) or near field communication such as Bluetooth (registered trademark) and ZigBee (registered trademark). In addition, the communication may be performed using wired communication such as a USB (Universal Serial Bus) or an audio cable.

  The diabetes index value estimation device 10 is a device that estimates the blood diabetes index value of the subject by performing information processing based on information received from the acetone measurement device 20. Specifically, the diabetes index value estimation device 10 corresponds to an information processing device such as a server device, a workstation, a personal computer, or a portable terminal. In the present embodiment, the diabetes index value estimation device 10 is realized by a single device, but information configured by connecting a plurality of information processing devices (for example, a mobile terminal and a server device) to each other via a network. It may be realized by a processing system. The function according to this embodiment of the diabetes index value estimation apparatus 10 will be described later.

  The acetone measuring device 20 is a device that measures a concentration value of acetone contained in a gas component released from a living body as a subject. That is, the acetone measuring device 20 corresponds to an acetone concentration measuring unit. Specifically, the acetone measuring device 20 includes a sensor unit that detects the breath of the subject, detects acetone from the detected breath, and calculates (measures) the concentration value of acetone. In addition, the conventional thing can be used about the measurement function (hardware structure of the acetone measuring apparatus 20) of the density | concentration value of acetone. The measurement of the concentration value of acetone is performed using, for example, an operation on the operation unit of the subject's acetone measurement apparatus 20 as a trigger. Alternatively, the measurement of the concentration value of acetone may be automatically performed at a preset time. The measurement of the concentration of acetone is most preferably performed immediately after waking up and before breakfast. However, it may be measured at any other timing. The measured concentration value of acetone is, for example, a numerical value in ppm as in the conventional acetone measuring device (however, other units may be used). The acetone measuring device 20 transmits information indicating the calculated concentration value of acetone to the diabetes index value estimating device 10 via the network 30.

  Further, the acetone measuring device 20 receives the estimation result from the diabetes index value estimating device 10 in response to the transmission of the acetone concentration value. For example, the acetone measurement device 20 includes a display unit, and may display the received estimation result or the operation result performed through the operation unit on the display unit.

  As the acetone measuring device 20, various types of devices such as a type in which the subject can be in close contact with the body, a type that can be carried by the user, and a type that is left at home can be used. For example, the acetone measuring device 20 is a portable measuring device (for example, T. Toyooka et al., J. Breath Res., Vol. 7, 036005, 2013) that can be easily measured at home or on the go. Can do. In addition, the acetone measuring device 20 may be other semiconductor gas sensors, gas chromatography devices, ion mobility spectrometers, or the like.

  In the above description, the acetone concentration value is detected from the exhalation of the subject, but it may be not only exhalation but also skin acetone naturally released from the skin and mucous membranes. Moreover, the release site | part of skin acetone is not specifically limited, As long as skin acetone is discharge | released, it may be anywhere. It is known that there is a correlation between breath acetone concentration and skin acetone concentration (for example, C. Turner et al., Rapid Commun. Mass Spectrom., Vol.22, pp.526-532, 2008).

  Subsequently, the function of the diabetes index value estimation apparatus 10 will be described in detail. As shown in FIG. 1, the diabetes index value estimation device 10 includes an acetone concentration input unit 11, a subject type input unit 12, an index value estimation unit 13, and an output unit 14.

  The acetone concentration input unit 11 is an acetone concentration input unit that inputs a concentration value of acetone released from a subject who is a target for calculating a diabetes index value. The acetone concentration input unit 11 receives the information indicating the concentration value of acetone from the acetone measuring device 20 and inputs the concentration value of acetone released from the subject. The acetone concentration input unit 11 may receive information related to the acetone concentration value (a subject identifier or measurement time that is information for identifying the subject) from the acetone measuring device 20 together with information indicating the acetone concentration value. Good. The acetone concentration input unit 11 stores information indicating the received acetone concentration value in a database included in the diabetes index value estimation device 10 in association with the subject identifier, and estimates the index value. It may be read and used. The acetone concentration input unit 11 outputs the input acetone concentration value to the index value estimation unit 13.

  The subject type input unit 12 is a subject type input unit that inputs information indicating the type of a subject for which a diabetes index value is to be calculated. The information indicating the type of the subject is information indicating, for example, treatment of the subject with respect to diabetes. The information on the treatment of diabetes in the subject specifically includes the presence / absence of treatment for diabetes, whether or not only dietary treatment is taken, whether or not a diabetes therapeutic agent is being taken, and the diabetes therapeutic agent being taken Information indicating the number of types and the type of antidiabetic agent being taken. In this embodiment, all the above information is included. The number of types of anti-diabetic drugs being taken indicates, for example, whether the type of anti-diabetic drugs being taken is one type or multiple types. The types of anti-diabetic drugs include, for example, pioglitazone hydrochloride (Actos), glimepiride (Amaril), sitagliptin phosphate hydrate (Gractive, Shanubia), alogliptin benzoate (Nessina), voglibose (Baissin), epalrestat (Kinedacks) And oral injections such as novolin (intermediate insulin), novolapit (super fast-acting insulin), lantus (long-acting insulin), and novolin 30R (mixed insulin).

  For example, the diabetes index value estimation device 10 receives the above information from a communication terminal device or the like used by the subject, and stores it in a database provided in association with the subject identifier. Transmission of the above information (information for grouping the subjects described later) from the subject may be performed based on the self-report of the subject himself / herself, such as a doctor or nurse It may be performed based on the judgment of a third party. The subject type input unit 12 inputs information indicating the type of the subject by reading the information. In addition to the above information, the database includes, for example, the subject's gender, age, height, weight, BMI (Body Mass Index), body fat percentage, chronic disease, electronic medical record, medication history, electronic scheduler, food and beverage history Such information may be stored. Also, the stored contents are not limited to these.

  The subject type input unit 12 receives information from the communication terminal device used by the subject or the acetone measuring device 20 to input information indicating the type of the subject, in addition to reading the information from the database. It is good to do. Further, the information indicating the type of the subject is not limited to the information described above, and for example, a subject identifier that is information for specifying each subject may be information indicating the type of the subject. The subject type input unit 12 outputs information indicating the type of the input subject to the index value estimation unit 13.

  The index value estimation unit 13 is an index value estimation unit that estimates the blood diabetes index value of a subject using information input from the acetone concentration input unit 11 and the subject type input unit 12. The estimated index value is, for example, the blood glucose concentration or the blood HbA1c concentration as described above. Moreover, you may estimate both of these. The blood glucose concentration is usually estimated as a numerical value in mg / dl as in the case of being used as a diabetes index value. The blood HbA1c concentration is usually estimated as a numerical value in% as in the case of being used as a diabetes index value. However, you may estimate as a numerical value of units other than the above. The index value estimation unit 13 stores, in advance, a plurality of calibration curves indicating the relationship between the acetone concentration value and the blood diabetes index value according to the type of the subject in a database provided in the diabetes index value estimation apparatus 10. This is memorized. The calibration curve is, for example, a function (for example, a linear function indicated by a straight line) with the acetone concentration value as a variable and an index value as an output value.

  Specifically, a plurality of groups are set in advance according to the type of the subject. In this embodiment, (I) a non-diabetic subject, (II) a diabetic subject who is performing only diet therapy, (III) a diabetic subject who is taking one kind of diabetes therapeutic agent, and ( IV) Four groups of diabetic subjects taking multiple types of antidiabetic drugs are set in advance. The index value estimation unit 13 stores a calibration curve indicating the relationship between the acetone concentration value and the index value for each group. A calibration curve is prepared for each index value (blood glucose concentration and blood HbA1c concentration). A calibration curve can be created by analyzing sample data of acetone concentration values and index values of subjects in each group prepared in advance. The analysis of the sample data may be performed by the diabetes index value estimation apparatus 10 or may be performed by another apparatus. When the analysis is performed by another device, information on the calibration curve obtained by the analysis is transmitted from the other device to the diabetes index value estimation device 10.

  The index value estimation unit 13 selects any calibration curve from a plurality of calibration curves stored in advance based on the information indicating the type of the subject input from the subject type input unit 12. Specifically, the index value estimation unit 13 selects a calibration curve stored in association with a group corresponding to the type of the subject. The index value estimation unit 13 estimates the index value from the selected calibration curve and the concentration value input from the acetone concentration input unit 11. Specifically, the index value estimation unit 13 inputs the concentration value into the calibration curve, and uses the output value from the calibration curve as the estimated value of the index value.

  In the case where the calibration curve is selected based on the number of types of antidiabetic drugs being taken, the index value estimation unit 13 is based on a correction criterion stored in advance according to the type of antidiabetics being taken. Then, the concentration value input from the acetone concentration input unit 11 may be corrected, and the blood diabetes index value of the subject may be estimated from the corrected concentration value. For example, the index value estimation unit 13 holds information on the correction magnification for each type of diabetes therapeutic agent as the correction reference. The index value estimation unit 13 uses the concentration value input from the acetone concentration input unit 11 as the value of the correction magnification according to the type of the diabetes therapeutic drug being taken, and inputs the value to the calibration curve, thereby indicating the index value. Is estimated. The correction magnification can be created by analyzing sample data of the acetone concentration value and the index value of the subject prepared for each antidiabetic agent being taken in advance.

  Here, the estimation of the index value will be described in detail using a specific example. First, the graphs of FIGS. 2 and 3 show the relationship between the breath acetone concentration, blood glucose concentration, and blood HbA1c concentration of all 77 diabetic subjects. In the graph, the horizontal axis represents the breath acetone concentration, the vertical axis represents the blood glucose concentration or the blood HbA1c concentration, and R in the graph is a correlation coefficient value (the same applies hereinafter). As shown in these figures, the relationship between the breath acetone concentration and the blood glucose concentration of all diabetic subjects and the relationship between the breath acetone concentration and the blood HbA1c concentration are low in correlation. Therefore, it is difficult to estimate the blood glucose concentration and the blood HbA1c concentration from the breath acetone concentration. However, accurate estimation is possible by performing estimation as in the present embodiment.

Hereinafter, a specific example of index value estimation according to the present embodiment will be described.
I. In the case of non-diabetic subject The graph of FIG. 4 shows the relationship between the breath acetone concentration and the blood glucose concentration of the non-diabetic subject group. By extracting only non-diabetic subjects from all subjects and grouping them, the present inventor shows that there is a negative first-order correlation between breath acetone concentration and blood glucose concentration. I found it. As described above, after sugar is consumed as energy in the body, fat is consumed as energy. Therefore, when the blood sugar level is high, that is, when there is a lot of sugar in the body, the breath acetone concentration tends to be low. Presumed to be a negative primary correlation. That is, in order to estimate the blood glucose concentration of the non-diabetic subject from the breath acetone concentration, the calibration curve shown in FIG. 4 (the calibration value stored in association with the group of non-diabetic subjects in the index value estimation unit 13) is shown. The measured value of the breath acetone concentration (concentration value input from the acetone concentration input unit 11) may be substituted for (line). For example, the blood glucose concentration of the subject whose measurement result of the breath acetone concentration is 0.7 ppm is estimated to be 91 mg / dl from the calibration curve. Since the measurement result of the blood glucose concentration based on the blood test was 90 mg / dl, it can be seen that the blood glucose concentration can be accurately estimated.

II. In the case of a diabetic subject who is performing only diet therapy The graph of FIG. 4 shows the relationship between the breath acetone concentration and blood glucose concentration of the diabetic subject group performing only diet therapy. The present inventor extracts only a group of diabetic subjects who are only dieting from all subjects and groups them so that a positive primary between the breath acetone concentration and the blood glucose concentration. We found that there is a correlation. As mentioned above, because there is an abnormality in glucose metabolism in diabetic subjects, fat is more likely to be used as energy, and as diabetes progresses and blood glucose levels are higher, the breath acetone concentration tends to increase. Yes, it is presumed to have a positive primary correlation opposite to that of non-diabetic subjects. That is, as in the case of a non-diabetic subject, in order to estimate the blood glucose concentration of a diabetic subject who is performing only diet therapy from the breath acetone concentration, the calibration curve (index value estimation unit shown in FIG. 13, the measured value of the breath acetone concentration (concentration value input from the acetone concentration input unit 11) may be substituted into a calibration curve stored in association with the group of diabetic subjects who are only performing diet therapy in FIG. . For example, the blood glucose concentration of a subject whose breath acetone concentration measurement result is 1 ppm is estimated to be 155 mg / dl from a calibration curve. Since the measurement result of the blood glucose concentration based on the blood test was 150 mg / dl, it can be seen that the blood glucose concentration can be accurately estimated.

  In addition, like the blood glucose concentration, the blood HbA1c concentration can also be estimated from the breath acetone concentration. The graph of FIG. 5 shows the relationship between the breath acetone concentration and the blood HbA1c concentration in a group of diabetic subjects who are only on a diet. The present inventor extracts only the diabetic subjects who are only dieting from all the subjects and groups them so that the positive primary between the breath acetone concentration and the blood HbA1c concentration. We found that there is a correlation. That is, in order to estimate the blood HbA1c concentration of a diabetic subject who is only taking diet therapy from the breath acetone concentration, the calibration curve shown in FIG. The measured value of the breath acetone concentration (the concentration value input from the acetone concentration input unit 11) may be substituted into the calibration curve stored in association with the examiner's group. For example, the blood HbA1c concentration of the subject whose measurement result of the breath acetone concentration is 0.4 ppm is estimated to be 5.4% from the calibration curve. Since the measurement result of the blood HbA1c concentration based on the blood test was 5.2%, it can be seen that the blood HbA1c concentration can be accurately estimated.

III. In the case of a diabetic subject taking one type of anti-diabetic drug The graph in FIG. 6 shows the measured values of breath acetone and blood glucose concentration of the diabetic subject taking one type of diabetic drug. Shows the relationship. Here, the antidiabetic agent used is glimepiride, alogliptin benzoate, sitagliptin phosphate hydrate, voglibose, novolin, novolin 30R, novolapit, or Lantus. From the figure, it is found that the correlation between the measured value of breath acetone concentration and the blood glucose concentration is low, and it is difficult to estimate the blood glucose concentration from the measured value of breath acetone concentration. This is due to the change in the concentration of breath acetone due to the effect of the therapeutic agent taken.

  Therefore, the present inventor has found that the measured value can be corrected by obtaining an influence on the breath acetone concentration for each therapeutic drug being taken. For example, the breath acetone concentration of a diabetic subject taking glimepiride is preferably corrected by 0.4 times. In addition, it is preferable to correct by sitagliptin phosphate hydrate: 0.5 times, novolapit: 6.8 times, novolin: 2.5 times, and lantus: 2 times. A calibration curve after correcting the measured value of breath acetone concentration according to the correction magnification is shown in the graph of FIG. For example, a subject who is taking novolapit and whose measured value of breath acetone concentration (concentration value input from the acetone concentration input unit 11) is 0.3 ppm, applies a correction magnification of 6.8 times to 2.04 ppm. And substituting into the calibration curve shown in FIG. 7 (the calibration curve stored in association with the group of diabetic subjects taking one type of diabetes therapeutic agent in the index value estimation unit 13). Is estimated to be 211 mg / dl. Since the measurement result of the blood glucose concentration based on the blood test was 229 mg / dl, it can be seen that the blood glucose concentration can be accurately estimated.

  The graph of FIG. 8 shows the relationship between the measured value of breath acetone concentration and the blood HbA1c concentration of a diabetic subject taking one type of antidiabetic drug. Similar to the blood glucose concentration, the correlation between the measured value of the breath acetone concentration and the blood HbA1c concentration is low, and it is found that it is difficult to estimate the blood HbA1c concentration from the measured value of the breath acetone concentration. The present inventor has found that the measured value can be corrected by determining the influence on the breath acetone concentration for each therapeutic agent being taken. For example, it is preferable to correct with glimepiride: 0.5 times, sitagliptin phosphate hydrate: 0.5 times, novolapit: 6.8 times, novolin: 3 times, lantus: 8 times. A calibration curve after correcting the measured value of breath acetone concentration according to the correction magnification is shown in the graph of FIG. For example, a subject who is taking sitagliptin phosphate hydrate and whose measured value of breath acetone concentration (concentration value input from the acetone concentration input unit 11) is 0.6 ppm has a correction magnification of 0.5 times. Is set to 0.3 ppm, and is substituted into the calibration curve shown in FIG. 9 (a calibration curve stored in association with a group of diabetic subjects taking one kind of diabetes therapeutic agent in the index value estimation unit 13). Thus, the blood HbA1c concentration is estimated to be 6.5%. Since the measurement result of the blood HbA1c concentration based on the blood test was 6.8%, it can be seen that the blood HbA1c concentration can be accurately estimated.

IV. In the case of a diabetic subject taking multiple types of antidiabetic drugs, the graph of FIG. 10 shows the measured values of breath acetone concentration and blood glucose concentration of diabetic subjects taking multiple types of diabetic therapeutic agents. Shows the relationship. Here, the antidiabetic agent being taken is any one or more of pioglitazone hydrochloride, glimepiride, sitagliptin phosphate hydrate, alogliptin benzoate, voglibose, epalrestat, novolin, novolapit, and novolin 30R. In this example as well, the blood glucose concentration can be estimated by correcting the acetone concentration in the same manner. For example, glimepiride: 2.4 times, sitagliptin phosphate hydrate: 1.3 times, alogliptin benzoate: 1.5 times, voglibose 0.7 times, epalrestat 1.6 times, novolapit: 1.2 times, Novolin 30R: It is preferable to correct by 2 times. FIG. 11 shows a calibration curve after correcting the measured value of breath acetone concentration according to the correction magnification. For example, a subject who is taking glimepiride, alogliptin benzoate and epalrestat and whose breath acetone concentration (concentration value input from the acetone concentration input unit 11) is 0.7 ppm is corrected to a correction magnification of 2.4 × 1. 5 × 1.6 = 5.76 times to 4.03 ppm, corresponding to the calibration curve shown in FIG. 11 (group of diabetic subjects taking multiple types of diabetes therapeutic agents in the index value estimation unit 13) When the blood glucose concentration is determined by substituting it into the stored calibration curve, it is estimated to be 214 mg / dl. Since the measurement result of the blood glucose concentration based on the blood test was 252 mg / dl, it can be seen that the blood glucose concentration can be accurately estimated.

  The graph of FIG. 12 shows the relationship between the measured value of breath acetone concentration and the blood HbA1c concentration of diabetic subjects taking multiple types of antidiabetic drugs. The results show that the correlation between the measured value of breath acetone concentration and the blood HbA1c concentration is low, and it is difficult to estimate the blood HbA1c concentration from the measured value of breath acetone concentration. In this example as well, the blood concentration of HbA1c can be estimated by correcting the acetone concentration in the same manner. For example, glimepiride: 1.4 times, sitagliptin phosphate hydrate: 6 times, alogliptin benzoate: 2.7 times, voglibose 0.1 times, epalrestat: 3 times, novolapit: 5 times, novolin 30R: 1. It is preferable to correct by 5 times. FIG. 13 shows a calibration curve after correcting the breath acetone concentration measurement value according to the correction magnification. For example, a subject who is taking glimepiride and sitagliptin phosphate hydrate and whose measured value of breath acetone concentration (concentration value input from the acetone concentration input unit 11) is 0.3 ppm has a correction factor of 1.4. X6 = 8.4 times multiplied to 2.52 ppm, and stored in association with a calibration curve shown in FIG. 13 (a group of diabetic subjects who are taking multiple types of diabetes therapeutic agents in the index value estimation unit 13) The calculated HbA1c concentration in the blood by substituting it into the calibration curve is estimated to be 7.5%. Since the measurement result of the blood HbA1c concentration based on the blood test was 7.8%, it can be seen that the blood HbA1c concentration can be accurately estimated.

  In addition, the kind of medicine correct | amended by said III and IV, and the correction method containing correction magnification are not limited to said example, It can change according to the difference in a subject group, and the difference in measurement conditions. The index value estimation unit 13 outputs the estimated blood diabetes index value of the subject to the output unit 14.

  The output unit 14 is an output unit that outputs the index value estimated by the index value estimation unit 13. Specifically, the output unit 14 performs output by transmitting the index value input from the index value estimation unit 13 to the acetone measuring device 20 via the network 30. For example, the acetone measuring device 20 receives and displays the index value. The subject can grasp the index value by referring to this display, and the output unit 14 may transmit the index value to a device other than the acetone measuring device 20. For example, the output unit 14 may be transmitted to the communication terminal device. Moreover, when the diabetes index value estimation apparatus 10 is provided with a display device such as a display, the output unit 14 may output an index value to the display device. Thereby, the index value can be displayed in the diabetes index value estimation apparatus 10. The above is the function of the diabetes index value estimation apparatus 10.

  FIG. 14 shows a hardware configuration of the diabetes index value estimation device 10 included in the diabetes index value estimation system 1 according to the present embodiment. As shown in FIG. 14, a diabetes index value estimation device 10 includes a CPU (Central Processing Unit) 101, a RAM (Random Access Memory) 102 and a ROM (Read Only Memory) 103, which are main storage devices, and a communication module 104 for performing communication. And a computer including hardware such as an auxiliary storage device 105 such as a hard disk. The functions of the above-described diabetes index value estimation device 10 are exhibited by the operation of these components by a program or the like. The above is the configuration of the diabetes index value estimation system 1 according to the present embodiment.

  Subsequently, a diabetes index value estimation method which is a process (an operation method of the diabetes index value estimation system 1) executed in the diabetes index value estimation system 1 according to the present embodiment will be described using the flowchart of FIG. In this processing, first, the acetone measurement device 20 measures the concentration value of acetone contained in the gas component released from the subject (S01, acetone concentration measurement step). The measured acetone concentration value is transmitted from the acetone measuring device 20 to the diabetes index value estimating device 10 via the network 30.

  In the diabetes index value estimation apparatus 10, the acetone concentration input unit 11 receives and inputs the acetone concentration value (S02, acetone concentration input step). The input acetone concentration value is output from the acetone concentration input unit 11 to the index value estimation unit 13. Subsequently, information indicating the type of the subject is input by the subject type input unit 12 (S03, subject type input step). The information indicating the type of the subject input here is information related to the subject related to the acetone concentration value input in S02. The input of the information indicating the type of the subject by the subject type input unit 12 is performed, for example, by reading the information from the database provided in the diabetes index value estimation apparatus 10 as described above. Information indicating the type of the subject is output from the subject type input unit 12 to the index value estimation unit 13.

  Subsequently, the index value estimating unit 13 determines whether or not the subject has diabetes based on the information indicating the type of the subject input from the subject type input unit 12 ( S04, index value estimation step). Here, when it is determined that the subject is suffering from diabetes (YES in S04), the index value estimation unit 13 determines that the subject has only diet therapy based on information indicating the type of the subject. (S05, index value estimation step). Here, when it is determined that the subject is not only dietary (takes a therapeutic drug) (NO in S05), the index value estimation unit 13 uses the diabetes therapeutic drug that the subject is taking. The concentration value of acetone is corrected based on the correction magnification stored in advance according to the type (S06, index value estimation step).

  If it is determined in S04 that the subject does not have diabetes (NO in S04), if it is determined in S05 that the subject is only dietary (YES in S05), and acetone in S06. Then, a calibration curve corresponding to the type of the subject is selected by the index value estimation unit 13 (S07, index value estimation step). As described above, for example, (I) a non-diabetic subject, (II) a diabetic subject who is performing only diet therapy, and (III) a diabetic subject who is taking one type of antidiabetic agent. This is performed according to four groups (types) of examiners and (IV) diabetic subjects taking multiple types of antidiabetic drugs.

  Subsequently, the index value estimation unit 13 inputs the concentration value of acetone to the selected calibration curve, and estimates the blood diabetes index value of the subject (S08, index value estimation step). Here, the acetone concentration value input to the calibration curve is the correction value when the concentration value is corrected in S06. Further, when the density value is not corrected in S06 (when the process does not go through the process in S06), the density value input in S02. The estimated index value is output from the index value estimation unit 13 to the output unit 14.

  Subsequently, the index value is output by the output unit 14 (S09, output step). Specifically, for example, the index value is transmitted to the acetone measuring device 20 via the network 30. In the acetone measuring device 20, the index value is received and displayed. By referring to this display, the subject can grasp the index value. The above is the processing executed by the diabetes index value estimation system 1 according to the present embodiment.

  As described above, in this embodiment, the concentration value of acetone released from the subject, which can be easily and non-invasively collected and measured, is used to estimate the blood diabetes index value of the subject. The Thereby, an index value can be estimated without performing blood collection. In the present embodiment, an index value is estimated using a calibration curve selected based on the type of the subject. Thereby, since the estimation of an appropriate index value according to the type of the subject is performed, the index value can be estimated with high accuracy. That is, according to this embodiment, once a calibration curve predetermined for each type of subject is obtained, the diabetes index value can be accurately estimated without blood collection thereafter.

  In addition, the information indicating the type of the subject as in the present embodiment may be information indicating treatment for diabetes of the subject. More specifically, the information indicating the type of the subject is the presence or absence of treatment for diabetes as in this embodiment, whether or not the treatment is only for diet therapy, whether or not the medicine for treating diabetes is being taken, It includes information on the number of types of antidiabetics being taken, and information on the types of antidiabetics being taken, (I) non-diabetic subjects, and (II) diabetic subjects who are only taking diet therapy. Be divided into four groups: examiners, (III) diabetic subjects taking one type of diabetes medication, and (IV) diabetic subjects taking multiple types of diabetes medication. May be. With this configuration, the diabetes index value can be estimated appropriately and accurately with high accuracy. However, only a part of the information described above may be used, and what information is set as the type of the subject may be arbitrarily set.

  Also, as in this embodiment, when a calibration curve is selected based on the number of types of antidiabetics being taken, the concentration value of acetone is set according to the type of antidiabetics being taken. It is good also as correcting. According to this configuration, it is possible to estimate the diabetes index value appropriately and accurately with high accuracy according to the number of types of anti-diabetic drugs taken by the subject and the types. Further, according to this configuration, since a calibration curve may be prepared and held for each number of types of diabetes therapeutic drugs being taken (in this embodiment, one type or a plurality of types), the therapeutic drug for diabetes There is no need to prepare and maintain a calibration curve for each type. In this embodiment, the correction criterion is the value of the correction magnification according to the type of antidiabetic agent being taken. However, in estimating the index value, the concentration value of acetone is appropriately corrected. For example, a value other than the correction magnification value may be used.

  Further, as in the present embodiment, the diabetes index value estimation system 1 may include an acetone measuring device 20 that measures the concentration value of acetone. According to this configuration, the concentration value of acetone can be reliably input, and the present invention can be reliably implemented. However, the diabetes index value estimation system 1 does not necessarily include the acetone measuring device 20. In that case, the diabetes index value estimation system 1 should just be the structure which can acquire the density | concentration value of acetone of a subject from the outside.

  Further, as in this embodiment, the concentration value of acetone used for estimating the index value is measured based on the gas component emitted from any one or more of the subject's breath, mucous membrane and skin It is good to do. According to this configuration, an acetone concentration value suitable for estimating the diabetes index value can be input, and the index value can be estimated appropriately.

  In the present embodiment, the blood glucose concentration or the blood HbA1c concentration of the subject is estimated as the diabetes index value. According to this configuration, the diabetes index value can be estimated appropriately and reliably. However, a value other than the above may be estimated as long as it becomes the blood diabetes index value of the subject.

  Subsequently, a modification of the present embodiment will be described. In the embodiment described above, subjects are divided into groups according to the presence or absence of diabetes, differences in diabetes treatment, and the like, and a calibration curve indicating the relationship between the concentration value of acetone and the index value is used for each group. However, a calibration curve may be prepared for each subject, that is, for each individual, and the index value may be estimated using the calibration curve. In that case, the information indicating the type of the subject is information for specifying the individual of the subject.

  In the above-described embodiment, the subjects are grouped according to the number of types of diabetes therapeutic drugs being taken. Grouping may be performed. In that case, a calibration curve is prepared for each type of anti-diabetic drug being taken, and the index value is estimated using the calibration curve. For example, a calibration curve can be obtained only for subjects taking only glimepiride, and index values can be estimated using them, or calibration can be performed only for subjects taking both pioglitazone hydrochloride and voglibose. A line may be obtained and an index value may be estimated using the line.

  In the above-described embodiment, the diabetes index value estimation device 10 and the acetone measurement device 20 are configured as separate bodies, but may be configured as a single unit. That is, a function for estimating the index value based on the acetone concentration value may be added to the acetone measuring device. In addition, the diabetes index value estimation apparatus 10 does not necessarily have to be configured to input the acetone concentration value via the network 30. For example, the acetone concentration value may be input by a user operation on the diabetes index value estimation apparatus 10.

  In addition, the above-described embodiments and modifications may be used in combination as necessary as long as they do not contradict each other.

  DESCRIPTION OF SYMBOLS 1 ... Diabetes index value estimation system, 10 ... Diabetes index value estimation apparatus, 11 ... Acetone concentration input part, 12 ... Subject type input part, 13 ... Index value estimation part, 14 ... Output part, 101 ... CPU, 102 ... RAM 103 ... ROM 104 Communication module 105 Auxiliary storage device 20 Acetone measuring device 30 Network

Claims (8)

Acetone concentration input means for inputting the concentration value of acetone released from the subject;
A subject type input means for inputting information indicating the type of the subject;
Based on information indicating the type of the subject input by the subject type input means, a plurality of acetone concentration values and blood diabetes index values stored in advance according to the type of the subject, An index value for selecting one of the calibration curves from the calibration curve showing the relationship between the selected calibration curve and the concentration value input by the acetone concentration input means to estimate the blood diabetes index value of the subject An estimation means;
Output means for outputting the index value estimated by the index value estimation means;
A diabetes index value estimation system comprising:   2. The diabetes index value estimation system according to claim 1, wherein the subject type input unit inputs information indicating a treatment for diabetes of the subject as information indicating the type of the subject.   Information on the treatment of diabetes of the subject includes the presence / absence of treatment for diabetes, whether or not diet therapy alone, whether or not the patient is taking diabetes medication, and the number of types of diabetes medications being taken The diabetes index value estimation system according to claim 2, comprising information indicating any of the types of antidiabetic drugs being taken. The information indicating the treatment of diabetes of the subject includes information indicating the number of types of antidiabetic drugs being taken and the type of antidiabetics being taken,
The index value estimating means selects a calibration curve based on the number of types of diabetes therapeutic drugs being taken, and based on correction criteria stored in advance according to the type of diabetes therapeutic drugs being taken. The diabetes index value estimation system according to claim 3, wherein the concentration value input by the acetone concentration input means is corrected, and the blood diabetes index value of the subject is estimated from the corrected concentration value.   The diabetes index value estimation system according to any one of claims 1 to 4, further comprising acetone concentration measurement means for measuring a concentration value of acetone released from the subject.   The acetone concentration input means measures the acetone as a concentration value of acetone released from the subject based on a gas component emitted from any one or more of exhaled breath, mucous membrane and skin of the subject. The diabetes index value estimation system according to any one of claims 1 to 5, wherein a concentration value is input.   The said index value estimation means estimates the blood glucose level of the said subject, or the blood HbA1c density | concentration as the said subject's blood diabetes index value, The any one of Claims 1-6 Diabetes index value estimation system. A diabetes index value estimation method, which is an operation method of a diabetes index value estimation system,
An acetone concentration input step for inputting a concentration value of acetone released from the subject;
A subject type input step for inputting information indicating the type of the subject;
Based on the information indicating the type of the subject input in the subject type input step, a plurality of acetone concentration values and blood diabetes index values stored in advance according to the type of the subject, An index value for estimating a blood diabetes index value of the subject from the selected calibration curve and the concentration value input in the acetone concentration input step. An estimation step;
An output step of outputting the index value estimated in the index value estimation step;
Diabetes index value estimation method including

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