WO2017073713A1 - 血糖値予測装置、血糖値予測方法及びコンピュータ読み取り可能な記録媒体 - Google Patents

血糖値予測装置、血糖値予測方法及びコンピュータ読み取り可能な記録媒体 Download PDF

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WO2017073713A1
WO2017073713A1 PCT/JP2016/082017 JP2016082017W WO2017073713A1 WO 2017073713 A1 WO2017073713 A1 WO 2017073713A1 JP 2016082017 W JP2016082017 W JP 2016082017W WO 2017073713 A1 WO2017073713 A1 WO 2017073713A1
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blood glucose
glucose level
user
fasting blood
fasting
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PCT/JP2016/082017
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English (en)
French (fr)
Japanese (ja)
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一平 上村
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Ｎｅｃソリューションイノベータ株式会社
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Priority to JP2017547880A priority Critical patent/JP6659049B2/ja
Priority to CN201680063221.0A priority patent/CN108352193A/zh
Publication of WO2017073713A1 publication Critical patent/WO2017073713A1/ja

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements

Definitions

  • the present invention relates to a blood sugar level predicting device for predicting a user's future blood sugar level, a blood sugar level predicting method, and a computer-readable recording medium on which a program for realizing these is recorded.
  • Patent Document 1 discloses that border type diabetes and diabetes are determined according to a blood glucose level.
  • Such blood sugar level management is important not only for the treatment of diabetes, but also for preventing the onset of diabetes or the severity of diabetes.
  • blood sugar level management is important in determining the dosage of insulin for diabetic patients, and is also useful for improving lifestyles such as diet and exercise.
  • performing blood glucose measurement many times places a heavy burden on the subject.
  • a method for predicting the blood glucose level is considered.
  • Patent Document 2 based on a user's fasting blood glucose level, one pattern is selected from preset time-series blood glucose levels, and the pattern is obtained by optical measurement.
  • a blood glucose level predicting device that corrects using the measured value is disclosed.
  • Patent Document 3 blood glucose level and insulin level are measured at each time point in an oral glucose tolerance test, and the measurement results are represented in a graph of blood glucose level and insulin level.
  • a diabetes testing apparatus for determining which region belongs is disclosed.
  • the blood glucose level changes depending on factors other than the time, and it has been more difficult to estimate the future blood glucose level from the current blood glucose level of the user.
  • An object of the present invention is to obtain a blood sugar level predicting apparatus capable of accurately predicting a user's future blood sugar level.
  • a blood sugar level predicting apparatus is a blood sugar level predicting apparatus for predicting a user's blood sugar level.
  • the blood glucose level prediction apparatus includes: an acquisition unit that acquires a measurement value of the user's blood glucose level, a measurement value of the user's HbA1c, and a health check result of the user; a measurement value of the blood glucose level; a measurement value of the HbA1c And a layer discriminating unit for discriminating whether the user is a normal type, a boundary type, or a diabetes type based on the health check result, and the fasting blood glucose level at the past time point of the discrimination result and the user And a predicting unit that predicts the future fasting blood glucose level of the user using the measured value.
  • the blood sugar level predicting method is a blood sugar level predicting method for predicting the blood sugar level of the user.
  • the blood glucose level prediction method includes an acquisition step of acquiring a measured value of the user's blood glucose level, a measured value of the user's HbA1c, and a result of a health check of the user, a measured value of the blood glucose level, and a measured value of the HbA1c And a layer discrimination step for discriminating whether the user is a normal type, a boundary type or a diabetes type based on the health check result, and the fasting blood glucose level at the past time of the discrimination result and the user And a prediction step of predicting the future fasting blood glucose level of the user using the measured value.
  • a computer-readable recording medium for executing a blood sugar level prediction method for predicting a blood sugar level of a user.
  • the computer-readable recording medium includes an acquisition step of acquiring a measured value of the blood glucose level of the user, a measured value of the user's HbA1c, and a result of the health check of the user, a measured value of the blood glucose level, A layer discrimination step for discriminating whether the user is a normal type, a border type, or a diabetes type based on the measurement value of the HbA1c and the health check result, the discrimination result, and the user's past time point And a predicting step for predicting a future fasting blood glucose level of the user using the measured value of the fasting blood glucose level at.
  • a blood sugar level predicting device capable of accurately predicting a user's future blood sugar level can be obtained.
  • FIG. 1 It is a figure which shows schematic structure of a blood glucose level prediction apparatus. It is a block diagram which shows the detailed structure of an onset risk prediction apparatus. It is a graph which shows an example of the statistical data used for calculation of the statistical average value of the fasting blood glucose level in a user's age. It is a figure which shows an example of the standard normal distribution used when predicting the onset risk. It is a flow which shows an example of operation
  • FIG. 1 is a diagram showing a schematic configuration of a blood glucose level prediction apparatus 1 according to an embodiment of the present invention.
  • the blood glucose level prediction device 1 obtains a determination result regarding diabetes of the user, a past fasting blood glucose level, and a statistical average value of fasting blood glucose levels at the user's age at the time of measurement of the fasting blood glucose level. Use to predict the user's future fasting blood glucose level.
  • the blood glucose level prediction device 1 determines whether the user is normal type, boundary type, or diabetic type based on the measured value of the user's blood glucose level, the measured value of the user's HbA1c, and the result of the user's health checkup. Is determined. And the blood glucose level prediction apparatus 1 calculates
  • the blood glucose level prediction device 1 includes an acquisition unit 11, a layer determination unit 12, and a prediction unit 13.
  • the acquisition unit 11 acquires a result of a health check of a user who predicts a blood sugar level from a database or the like.
  • the acquisition part 11 acquires the measurement result of a user's blood glucose level, and the measurement result of a user's HbA1c from a blood glucose level measuring apparatus or a database.
  • the acquisition unit 11 measures the measured value of the fasting blood glucose level, the measured blood glucose level 1 hour after the meal (hereinafter referred to as the blood glucose level 1 h after the meal), and 2 hours after the meal.
  • the measured value of the blood glucose level (hereinafter referred to as the blood glucose level 2 hours after meal) is obtained.
  • the measurement value of the fasting blood glucose level acquired by the acquisition unit 11 includes not only the latest measurement result but also the past measurement result.
  • the blood glucose level measuring device is a blood glucose level measuring device having a conventional configuration for collecting blood and measuring the blood glucose level, an optical blood glucose level measuring device for measuring blood glucose level using light, etc.
  • a simple measuring device may be used.
  • the layer discriminating unit 12 uses the user's health check result, the user's blood glucose level measurement result, and the user's HbA1c measurement value acquired by the acquisition unit 11 to determine whether the user is normal type, border type, and diabetes Determine which type. As the measurement result of the user's blood glucose level, the fasting blood glucose measurement value, the 1 h post-meal blood glucose measurement value, and the post-meal 2 h blood glucose measurement value are input to the layer determination unit 12.
  • the prediction unit 13 obtains a difference between the measured value of the user's past fasting blood glucose level and the statistical average value of the fasting blood glucose level at the user's age at the time of measuring the fasting blood glucose level. In addition, the prediction unit 13 calculates a time-series change of the difference and corrects the time-series change of the calculated difference based on the determination result by the layer determination unit 12. The prediction unit 13 obtains the user's future fasting blood glucose level using the correction result.
  • the statistical average value of fasting blood glucose level at the user's age is the average fasting blood glucose level at the user's age, and statistical data such as that shown in FIG. The average value obtained from the statistical value by category) is used.
  • the statistical data shown in FIG. 3 is an example, and the average fasting blood glucose level at the user's age may be obtained using other statistical data.
  • the user's future fasting blood sugar level can be accurately predicted. That is, the blood sugar level prediction device 1 more accurately calculates the future fasting blood glucose level for each user in order to predict the user's future fasting blood sugar level using the time series change of the past fasting blood sugar level. Is possible. Thus, by predicting the user's future fasting blood glucose level with the blood glucose level prediction device 1 with high accuracy, it becomes possible to accurately determine the possibility of the user's future diabetes.
  • FIG. 2 is a block diagram showing a detailed configuration of the onset risk prediction apparatus 10 including the blood sugar level prediction apparatus 1 according to the embodiment of the present invention.
  • the onset risk prediction device 10 predicts the risk of developing diabetes of the user using the future blood glucose level of the user predicted by the blood glucose level prediction device 1.
  • the onset risk prediction device 10 is configured by a computer device such as a server connected to a network.
  • the onset risk prediction device 10 includes a blood glucose level prediction device 1, a layer discrimination prediction unit 2, and a risk prediction unit 3. First, the blood glucose level prediction device 1 will be described below.
  • the blood glucose level prediction device 1 includes an acquisition unit 11, a layer determination unit 12, and a prediction unit 13.
  • the acquisition unit 11 loads the data of the user's health check result and blood glucose level measurement result stored in the data server 5 into the onset risk prediction device 10.
  • the data server 5 that stores the user's health check result and blood glucose level measurement result is configured by a computer device different from the onset risk prediction device 10. Therefore, the acquisition unit 11 acquires data from the data server 5 via the Internet.
  • the health check result and blood glucose level measurement result of the user are stored in the data server 5, but this is not restrictive, and a storage unit is provided in the onset risk prediction device 10, and the health is stored in the storage unit. You may make it memorize
  • the acquisition unit 11 acquires, for example, the user's BMI and age as the health check result.
  • the acquisition unit 11 acquires, as the measurement result of the blood glucose level of the user, for example, the measurement value of the fasting blood glucose level, the measurement value of the blood glucose level 1 h after meal, and the measurement value of the blood glucose level 2 h after the meal.
  • the measurement value of the fasting blood glucose level acquired by the acquisition unit 11 includes not only the latest measurement result but also the past measurement result.
  • the past measurement results are used when the prediction unit 13 described later predicts the user's future fasting blood glucose level.
  • past measurement results used in predicting the user's future fasting blood glucose level are within the past 5 years. It is preferable that this is the result.
  • the layer discriminating unit 12 discriminates whether the user is a normal type, a border type, or a diabetic type using the user's health check result and blood glucose level measurement result acquired from the data server 5 by the acquiring unit 11. Specifically, the layer determination unit 12 uses the fasting blood glucose level, the blood glucose level 1 h after meal, the blood glucose level 2 h after meal, and the measured values of HbA1c, and the BMI and age obtained in the health examination, It is discriminated whether it is a type, a border type or a diabetes type. A specific flow is shown in FIG.
  • the layer determination unit 12 determines that the user is a normal type if the measured values of fasting blood glucose level, blood glucose level 2 h after meal, and blood glucose level 1 h after meal are smaller than specified values, respectively. . In addition, the layer determination unit 12 determines that the user is diabetic when the fasting blood glucose level and the measured values of Hba1c are larger than the threshold values and the BMI and age satisfy the predetermined conditions. A detailed description of the flow shown in FIG. 6 will be described later.
  • the prediction unit 13 predicts the future fasting blood glucose level of the user using the layer discrimination result by the layer discrimination unit 12. In the present embodiment, the prediction unit 13 predicts the fasting blood glucose level of the user from the present to five years later. Note that the predicting unit 13 may be configured to predict fasting blood glucose levels after one to four years and after six years as long as the user's future fasting blood sugar levels can be predicted.
  • the prediction unit 13 includes a difference calculation unit 21 and a blood sugar level calculation unit 22.
  • the difference calculating unit 21 calculates the difference between the measured value of the fasting blood glucose level for the past five years of the user and the average fasting blood glucose level at each age of the user at the time of measuring the fasting blood glucose level. That is, the difference calculation unit 21 calculates the difference ⁇ Y i ⁇ n using the following equations (1) to (5). In each of the following formulas, Y i-n (i age of the user, n represents 1-5 years) shows the fasting blood glucose level of the past five years users, X i-n the past 5 The average fasting blood glucose level in each age of the user of the year is shown.
  • the difference calculation unit 21 calculates an average value ⁇ Y for the past five years using ⁇ Y i ⁇ n calculated as described above, and uses the ⁇ Y to calculate the user's fasting time as shown in the following equation (6).
  • the difference calculation unit 21 calculates an estimated value Z i + m (m is 1 to 5 years) of the user's fasting blood glucose level in each year up to five years later using the above equation (6).
  • the fasting blood glucose level of the user for the next five years can be predicted using the fasting blood sugar level of the user for the past five years.
  • the user's future fasting blood glucose level can be accurately obtained.
  • the blood glucose level prediction apparatus 1 corrects the estimated value of the fasting blood glucose level using the discrimination result by the layer discrimination unit 12, it depends on whether the user is a normal type, boundary type or diabetic type layer. The future fasting blood glucose level can be obtained accurately.
  • the layer discrimination prediction unit 2 uses the user's future fasting blood glucose level predicted by the blood glucose level prediction device 1 to predict whether the user will be in the normal type, boundary type, or diabetes type in the future. Specifically, if the predicted fasting blood glucose level is 126 mg / dl or more, the layer discrimination prediction unit 2 predicts that the user is diabetic at that time. In addition, when the predicted fasting blood glucose level is 110 mg / dl or more and smaller than 126 mg / dl, the layer discrimination prediction unit 2 predicts that the user is a boundary type at that time. If the predicted fasting blood glucose level is smaller than 110 mg / dl, the layer discrimination prediction unit 2 predicts that the user is normal at that time.
  • the risk prediction unit 3 creates a standard normal distribution using variation in fasting blood glucose level variation within a predetermined period, and the value of the fasting blood glucose level 126 mg / dl, which is a threshold for determining diabetes, is the standard normal distribution. Diabetes risk determination is performed according to the position within the 95% confidence interval in the above.
  • the risk prediction unit 3 creates a standard normal distribution in consideration of variations in fasting blood glucose levels within a predetermined period of the user.
  • the risk prediction unit 3 sets the threshold value (fasting blood glucose level 126 mg / dl) determined to be diabetes as the dividing line P for the 95% confidence interval of the standard normal distribution shown in FIG.
  • the risk prediction unit 3 multiplies the area ratio of the 95% confidence interval divided by the dividing line P by 95% to calculate the disease risk of diabetes.
  • the 95% confidence interval when the 95% confidence interval is divided into the regions A and B by the dividing line P, the area within the 95% confidence interval obtained by the standard normal distribution curve (the hatched line in FIG. 4).
  • the value obtained by multiplying the area ratio S of the area A to 95% by the area ratio S to the range indicated by (95) ⁇ 95%, that is, 95% ⁇ S is the risk of diabetes of the user.
  • the onset risk prediction apparatus 10 With the configuration of the onset risk prediction apparatus 10 as described above, it is possible to predict a user's risk of suffering from diabetes using the user's future fasting blood glucose level accurately predicted by the blood glucose level prediction apparatus 1. Moreover, since the onset risk prediction apparatus 10 calculates the risk of morbidity of diabetes taking into account the variation of the user's future fasting blood glucose level, the morbidity risk can be obtained with high accuracy.
  • FIG. 5 is a flowchart showing the operation of the onset risk prediction register 10.
  • FIG. 6 is a flowchart showing the layer discrimination operation of the blood sugar level predicting apparatus 1 included in the onset risk predicting apparatus 10.
  • FIGS. 1 to 4 are referred to as appropriate.
  • the blood sugar level prediction method is implemented by operating the blood sugar level prediction apparatus 1 in the onset risk prediction apparatus 10. Therefore, the description of the blood sugar level prediction method in the present embodiment is replaced with the following description of the operation of the blood sugar level prediction apparatus 1.
  • the acquisition unit 11 of the blood sugar level prediction apparatus 1 acquires the health check result of the user from the data server 5 (step S1).
  • the acquisition unit 11 acquires, for example, the user's BMI and age as the health check result.
  • the acquisition unit 11 acquires the blood glucose level measurement result of the user from the data server 5 (step S2).
  • the acquisition unit 11 acquires, as the measurement result of the blood glucose level of the user, for example, the measurement value of the fasting blood glucose level, the measurement value of the blood glucose level 1 h after meal, and the measurement value of the blood glucose level 2 h after the meal.
  • the measurement value of the fasting blood glucose level acquired by the acquisition unit 11 includes not only the latest measurement result but also the past measurement result.
  • the past measurement results are used in the calculation of ⁇ Y in step S4.
  • the layer discriminating unit 12 discriminates whether the user is a normal type, a boundary type, or a diabetic type using the health check result and blood glucose level measurement result acquired by the acquiring unit 11 (step S3).
  • FIG. 6 shows a flow of layer discrimination by the layer discrimination unit 12. Details of the flow shown in FIG. 6 will be described later.
  • the difference calculating unit 21 statistically determines the past fasting blood glucose level and the user's age when measuring the fasting blood glucose level. ⁇ Y is calculated using the average fasting blood glucose level. Specifically, the difference calculating unit 21 calculates the fasting blood glucose level measured value Y i ⁇ n for the past 5 years and the statistical average fasting blood glucose level X i ⁇ n for the user's age over the past 5 years. After obtaining the difference ⁇ Y i ⁇ n , the average value ⁇ Y for the past five years is obtained using the calculated ⁇ Y i ⁇ n .
  • the blood sugar level calculating unit 22 uses the fasting blood sugar level estimation model Z (the above-described equation (6)) obtained in step S5, and fasting blood sugar until a predetermined period (for example, five years later). Find the value every year.
  • determination prediction part 2 discriminate
  • the risk prediction unit 3 obtains the standard normal distribution shown in FIG. 4 using the fasting blood glucose level obtained after the predetermined period obtained in step S6. Further, the risk prediction unit 3 obtains the area ratio of the region A divided by the threshold value (fasting blood glucose level 126 mg / dl) determined to be diabetes in the 95% confidence interval of the standard normal distribution, and then the area ratio The disease risk is calculated by multiplying by 95%.
  • the layer determination unit 12 when the layer determination flow by the layer determination unit 12 is started (start), the layer determination unit 12 first has a fasting blood glucose level of the user smaller than 100 mg / dl and HbA1c is 6.0%. If it is determined that the blood glucose level is smaller than (YES in step SA1), the process proceeds to step SA2 to determine whether or not the blood glucose level in 2h after meal is smaller than 140 mg / dl.
  • step SA1 when the user's fasting blood glucose level is 100 mg / dl or higher or HbA1c is 6.0% or higher (NO in step SA1), the layer determination unit 12 proceeds to step SA4 and the subsequent steps, It is determined whether the value is 100 mg / dl or more and 126 mg / dl or less.
  • step SA2 determines in step SA2 that the blood glucose level in 2 hours after meal is smaller than 140 mg / dl (YES in step SA2), the process proceeds to step SA3, where the blood glucose level in 1 h after meal is 140 mg / dl. It is determined whether it is smaller than dl.
  • step SA2 determines in step SA2 that the blood glucose level in 2h after meal is 140 mg / dl or more (in the case of NO in step SA2)
  • the layer determination unit 12 proceeds to step SA9 and the user is a boundary type Is determined. That is, even if the fasting blood glucose level is smaller than 100 mg / dl and HbA1c is smaller than 6.0%, the user is determined to be the boundary type if the blood glucose level after 2 hours after eating is 140 mg / dl or higher.
  • step SA3 determines that the blood glucose level in 1 h after meal is smaller than 140 mg / dl (YES in step SA3)
  • the layer determination unit 12 proceeds to step SA10 and determines that the user is a normal type. To do. That is, when the fasting blood glucose level is smaller than 100 mg / dl and HbA1c is smaller than 6.0%, and the blood glucose level in 2 h after meal and the blood glucose level in 1 h after meal are each smaller than 140 mg / dl, Determined as normal.
  • step SA3 when it is determined in step SA3 that the blood glucose level after 1 h after meal is 140 mg / dl or more (NO in step SA3), the layer determination unit 12 proceeds to step SA7, where the blood glucose level after 1 h after meal is Determine if greater than 200 mg / dl.
  • step SA7 when the layer determination unit 12 determines that the blood glucose level after 1 h after meal is greater than 200 mg / dl (YES in step SA7), the process proceeds to step SA8, where the user is diabetic. judge. That is, even when the fasting blood glucose level is smaller than 100 mg / dl and HbA1c is smaller than 6.0%, and the blood glucose level after 2 hours after meal is smaller than 140 mg / dl, the blood glucose level after 1 hour after meal is 200 mg / dl. If greater than, the user is determined to be diabetic.
  • step SA7 determines in step SA7 that the blood glucose level after 1 h after meal is 200 mg / dl or less (NO in step SA7)
  • the process proceeds to step SA9, where the user is a boundary type.
  • the user is a boundary type.
  • step SA4 when the layer determination unit 12 determines that the fasting blood glucose level is 100 mg / dl or more and 126 mg / dl or less (YES in step SA4), the process proceeds to step SA9, and the user Is determined to be boundary type. That is, even when HbA1c is 6.0% or more, if the fasting blood glucose level is 100 mg / dl or more and 126 mg / dl or less, the user is determined to be the boundary type.
  • step SA5 when the layer determination unit 12 determines that the fasting blood glucose level is greater than 126 mg / dl in step SA4 described above (NO in step SA4), the process proceeds to step SA5, where HbA1c is 6. Judge whether it is 5% or less.
  • step SA5 when the layer determination unit 12 determines that HbA1c is 6.5% or less (YES in step SA5), the process proceeds to step SA9 and determines that the user is a boundary type. . That is, even when the fasting blood glucose level is greater than 126 mg / dl, if HbA1c is 6.5% or less, the user is determined to be the boundary type.
  • step SA5 determines in step SA5 that HbA1c is greater than 6.5% (NO in step SA5)
  • the process proceeds to step SA6, and the user's BMI is determined from the health check result. It is determined whether it is 24.5 or more and the age is greater than 40 years old.
  • step SA6 when the layer determination unit 12 determines that the BMI is 24.5 or more and the age is greater than 40 (YES in step SA6), the process proceeds to step SA9, where the user Judged to be boundary type. That is, even when the fasting blood glucose level is greater than 126 mg / dl and HbA1c is greater than 6.5, if the BMI is 24.5 or greater and the age is greater than 40 years old, the user is It is determined.
  • step SA6 determines in step SA6 that the user's BMI is smaller than 24.5 or the age is 40 years old or less (NO in step SA6)
  • the process proceeds to step SA8.
  • the user is determined to be diabetic. That is, when the fasting blood glucose level is greater than 126 mg / dl, HbA1c is greater than 6.5%, and the BMI is less than 24.5 or the age is 40 years old or less, the user Determined to be diabetic.
  • the future fasting blood glucose level is predicted using the measured value of the user's past fasting blood glucose level, the future fasting blood glucose level is accurately adjusted for each user. Can be predicted well.
  • the current state of the user is accurately determined. Can be judged well. That is, not only the conventional blood glucose level and the measured value of HbA1c but also the health check result is used to determine the current state of the user, thereby making it possible to make a determination that also considers the user's steady state of health. .
  • the determination result can also be used to predict the future fasting blood glucose level more accurately. it can.
  • the program in the embodiment of the present invention may be a program that causes a computer to execute steps S1 to S8 and SA1 to SA10 shown in FIGS.
  • a CPU Central Processing Unit
  • the blood sugar level predicting apparatus 1 and the blood sugar level predicting method according to the present embodiment can be realized.
  • a CPU Central Processing Unit
  • the acquisition unit 11 the layer determination unit 12, and the prediction unit 13, and performs processing.
  • FIG. 7 is a block diagram illustrating an example of a computer that implements the blood sugar level predicting apparatus 1 according to the embodiment of the present invention.
  • the computer 110 includes a CPU 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These units are connected to each other via a bus 121 so that data communication is possible.
  • the CPU 111 performs various operations by developing the program (code) in the present embodiment stored in the storage device 113 in the main memory 112 and executing them in a predetermined order.
  • the main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory).
  • the program in the present embodiment is provided in a state of being stored in a computer-readable recording medium 120. Note that the program in the present embodiment may be distributed on the Internet connected via the communication interface 117.
  • the storage device 113 includes a hard disk drive and a semiconductor storage device such as a flash memory.
  • the input interface 114 mediates data transmission between the CPU 111 and an input device 118 such as a keyboard and a mouse.
  • the display controller 115 is connected to the display device 119 and controls display on the display device 119.
  • the data reader / writer 116 mediates data transmission between the CPU 111 and the recording medium 120, and reads a program from the recording medium 120 and writes a processing result in the computer 110 to the recording medium 120.
  • the communication interface 117 mediates data transmission between the CPU 111 and another computer.
  • the recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic storage media such as a flexible disk (CD), or CD- An optical storage medium such as ROM (Compact Disk Only Memory) may be used.
  • CF Compact Flash
  • SD Secure Digital
  • magnetic storage media such as a flexible disk (CD)
  • CD- An optical storage medium such as ROM (Compact Disk Only Memory) may be used.
  • the risk prediction unit 3 performs prediction of diabetes morbidity risk using a standard normal distribution. However, as long as the risk can be predicted, other methods may be used to predict the morbidity of diabetes.
  • the risk The prediction unit 3 predicts the risk of suffering from diabetes of the user.
  • the risk prediction unit 3 may predict the risk of suffering from diabetes without predicting whether the user will fall into the normal type, boundary type, or diabetes type in the future. In addition, it is not necessary to predict the risk of developing diabetes.
  • the acquisition unit 11 of the blood glucose level prediction device 1 is configured to acquire the blood glucose level measurement result from the data server 5.
  • the acquiring unit 11 may acquire a blood glucose level measurement result from the blood glucose level measuring device.
  • the blood glucose level measurement unit may be provided integrally with the blood glucose level prediction device 1, and the acquisition unit 11 may acquire the blood glucose level measurement result from the blood glucose level measurement unit.
  • the blood glucose level prediction device 1 uses the measured values of the blood glucose level for 1 h after meal and the blood glucose level for 2 h after meal when performing the layer discrimination of the user. However, if the blood glucose level prediction device 1 is a blood glucose level that has passed for a predetermined time after meal, the blood glucose level measurement value after the passage of time other than 1 hour and 2 hours may be used to determine the layer of the user. .
  • a blood sugar level predicting device for predicting a blood sugar level of a user, An acquisition unit that acquires a measurement value of the blood glucose level of the user, a measurement value of the user's HbA1c, and a result of the health check of the user; A layer discriminating unit for discriminating whether the user is a normal type, a boundary type or a diabetic type based on the measured value of the blood glucose level, the measured value of the HbA1c, and the health check result; A blood glucose level prediction apparatus comprising: a prediction unit that predicts a future fasting blood glucose level of the user using the determination result and a measured value of the fasting blood glucose level of the user in the past.
  • Appendix 2 The blood glucose level prediction apparatus according to appendix 1, wherein the layer determination unit uses, as the blood glucose level measurement values, the fasting blood glucose level and the blood glucose level after a predetermined time has elapsed since meals.
  • the prediction unit A difference calculating unit for obtaining a difference between a measured value of fasting blood glucose level at the user's past time point and a statistical average value of fasting blood glucose level at the user's age at the past time point;
  • the blood glucose level according to appendix 1 or 2 further comprising: a blood glucose level calculation unit that calculates a future fasting blood glucose level of the user using the difference calculated by the difference calculation unit and the determination result by the layer determination unit Prediction device.
  • the difference calculation unit uses fasting blood glucose levels at a plurality of past times as the fasting blood glucose levels of the user in the past, and measures the fasting blood glucose levels at the plurality of past times as the differences. Obtaining a time-series change of a difference between a value and a statistical average value of fasting blood glucose levels in the user's age at the plurality of time points, The supplemental blood glucose level calculation unit calculates the future fasting blood glucose level of the user using the time series change of the difference obtained by the difference calculation unit and the determination result by the layer determination unit. Blood glucose level prediction device.
  • a blood sugar level prediction method for predicting a blood sugar level of a user An acquisition step of acquiring a measurement value of the blood glucose level of the user, a measurement value of the user's HbA1c, and a result of the health check of the user; A layer determining step of determining whether the user is a normal type, a boundary type, or a diabetic type based on the measured value of the blood glucose level, the measured value of the HbA1c, and the health check result;
  • a blood glucose level prediction method comprising: a prediction step of predicting a future fasting blood glucose level of the user by using a result of the determination and a measured value of the fasting blood glucose level of the user in the past.
  • the prediction step includes A difference calculating step for obtaining a difference between a measured value of fasting blood glucose level at the user's past time point and a statistical average value of fasting blood glucose level at the user's age at the past time point;
  • the difference calculating step uses fasting blood glucose levels at a plurality of past times as the fasting blood glucose levels of the user in the past, and measures fasting blood glucose levels at the plurality of past times as the differences. Obtaining a time-series change of a difference between a value and a statistical average value of fasting blood glucose levels in the user's age at the plurality of time points, The blood glucose level calculating step calculates the future fasting blood glucose level of the user using the time series change of the difference obtained in the difference calculating step and the determination result in the layer determining step. Blood glucose level prediction method.
  • a computer-readable recording medium storing a program for executing a blood sugar level prediction method for predicting a blood sugar level of a user, On the computer, An acquisition step of acquiring a measurement value of the blood glucose level of the user, a measurement value of the user's HbA1c, and a result of the health check of the user; A layer determining step of determining whether the user is a normal type, a boundary type, or a diabetic type based on the measured value of the blood glucose level, the measured value of the HbA1c, and the health check result; A computer readable comprising instructions for performing a prediction step of predicting the user's future fasting blood glucose level using the determination result and the measured value of the user's past fasting blood glucose level in the past recoding media.
  • Appendix 12 The computer-readable recording medium according to appendix 11, wherein the layer discrimination step uses, as the blood glucose level measurement values, the fasting blood glucose level and the blood glucose level after a predetermined time has elapsed since meals.
  • the prediction step includes A difference calculating step for obtaining a difference between a measured value of fasting blood glucose level at the user's past time point and a statistical average value of fasting blood glucose level at the user's age at the past time point;
  • the difference calculating step uses fasting blood glucose levels at a plurality of past times as the fasting blood glucose levels of the user in the past, and measures fasting blood glucose levels at the plurality of past times as the differences. Obtaining a time-series change of a difference between a value and a statistical average value of fasting blood glucose levels in the user's age at the plurality of time points, The blood glucose level calculating step calculates the future fasting blood glucose level of the user using the time-series change of the difference obtained in the difference calculating step and the determination result in the layer determining step.
  • Computer-readable recording media Computer-readable recording media.
  • Appendix 15 The computer-readable recording medium according to any one of appendices 11 to 14, wherein the health check result is BMI and age.
  • the present invention can be used for a blood sugar level prediction apparatus for predicting a user's future blood sugar level.

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