Method, apparatus and program for predicting total sodium excretion amount (na _ xh) within a predetermined time of subject

Abstract

To provide a technique for predicting the total excretion amount of sodium in a predetermined time of a subject with higher accuracy.SOLUTION: A prediction technique including at least one selected from the group consisting of (1) considering the sex of the subject or the sex of the subject and the amount of urine, (2) using a coefficient determined for each of the sodium concentration, the creatinine concentration, and the total creatinine excretion within a predetermined time, and (3) considering the time from the intake of sodium time before urine collection to the urine collection time in the step c.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method, an apparatus, a program, etc. for predicting the total sodium excretion (Na_Xh) within a predetermined time period of a subject. [Background technology]

[0002] High salt intake has been reported to increase the incidence and mortality of cardiovascular diseases, including stroke. Therefore, it is important to evaluate salt intake from the perspective of preventing these diseases.

[0003] A known method for assessing salt intake is the dietary survey method, which examines dietary content, but this method relies on the subject's reporting, which may result in under- or over-reporting. It has also been proposed that 24-hour total sodium excretion is suitable for estimating salt intake, but collecting urine for 24 hours to measure 24-hour total sodium excretion is difficult in clinical practice. For this reason, a method has been proposed for predicting 24-hour total sodium excretion from spot urine or the second urine after waking (Non-Patent Documents 1 and 2). [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Tanaka T, Okamura T, Miura K, et al. J Hum Hypertens. 2002;16(2):97-103. [Non-patent document 2] Kawasaki T, Ueno M, Uezono K. et al. Jpn Circ J. 1982;46(9):948-53. Summary of the Invention [Problem to be solved by the invention]

[0005] Conventional methods for predicting 24-hour total sodium excretion, such as those described in Non-Patent Documents 1 and 2, are excellent at predicting the average value of a group (small mean bias), but do not have sufficient predictive power for an individual's 24-hour total sodium excretion. This means that the correlation coefficient between the theoretical value obtained by regression analysis and the observed value is low, and there is a large systematic bias, which leads to overestimation in areas where 24-hour total sodium excretion is small and underestimation in areas where 24-hour total sodium excretion is large.

[0006] An object of the present invention is to provide a technique for predicting the total sodium excretion amount (Na_Xh) of a subject within a predetermined time period with higher accuracy. [Means for solving the problem]

[0007] As a result of intensive research conducted by the present inventors in view of the above problems, A method for predicting a total sodium excretion amount (Na_Xh) within a predetermined time period in a subject, comprising: a step a1 of measuring the sodium concentration (NaSpot) and the creatinine concentration (CreSpot) in urine collected from the subject; a step b1 of calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on attribute information of the subject; and a step c1 of calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred), or a step a2 of measuring the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) in urine collected from the subject, as well as the BMI of the subject; and step c2 of calculating a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, (1) in step c1 or c2, calculating a predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) further based on the sex of the subject and / or the amount of urine; (2) in the step c1, calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred); (3) in step c1 or c2, calculating a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) further based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); At least one selected from the group consisting of: method, The inventors have found that the above-mentioned problems can be solved by the above-mentioned method. Based on this finding, the present inventors have conducted further research and have completed the present invention. That is, the present invention includes the following aspects.

[0008] Item 1. A method for predicting a subject's total sodium excretion within a predetermined time period (Na_Xh), comprising: a step a1 of measuring the sodium concentration (NaSpot) and the creatinine concentration (CreSpot) in urine collected from the subject; a step b1 of calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on attribute information of the subject; and a step c1 of calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred), or a step a2 of measuring the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) in urine collected from the subject, as well as the BMI of the subject; and step c2 of calculating a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, (1) in step c1 or c2, calculating a predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) further based on the sex of the subject and / or the amount of urine; (2) in the step c1, calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred); (3) in step c1 or c2, calculating a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) further based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); At least one selected from the group consisting of: method.

[0009] Item 2. The method according to Item 1, wherein the predetermined time period is 12 to 48 hours.

[0010] Item 3. The method according to Item 1 or 2, wherein the urine is a single urine collection.

[0011] Item 4. The method according to any one of Items 1 to 3, wherein the attribute information used in step b1 is height, weight, and age.

[0012] Item 5. The coefficient in step c1 is a value determined by regression analysis that predicts the predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), and a predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a subject population, and the total sodium excretion amount within a predetermined time period (Na_Xh) that has been previously measured for the subject population, or the coefficient in step c2 is a value determined by regression analysis that predicts a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), a potassium concentration (KSpot), a BMI, and an age that have been measured and calculated in advance in a subject population, and a total sodium excretion within a predetermined time period (Na_Xh) that has been measured in advance in the subject population; The method according to any one of Items 1 to 4.

[0013] Item 6. The method according to Item 5, comprising (1) above, wherein the variables include the sex of the subject and / or the amount of urine.

[0014] Item 7. The method according to Item 5 or 6, including (3) above, wherein the variables include the time from the time of the last salt intake before the urine collection to the time of the urine collection (TAM1) and the time from the time of the second-to-last salt intake before the urine collection to the time of the urine collection (TAM2).

[0015] Item 8. The method according to any one of Items 5 to 7, wherein the coefficient is calculated for each of the variables.

[0016] Item 9. If the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated in step c1 or c2 is within a range determined by a predetermined threshold, a step d1 of calculating again in step c1 the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using optimization coefficients determined by regression analysis for predicting the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the subject population; or a step d2 of calculating again in step c2 the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using optimization coefficients determined by regression analysis for predicting the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the subject population; Item 9. The method according to any one of Items 1 to 8, comprising:

[0017] Item 10. The method according to any one of Items 1 to 9, comprising at least two selected from the group consisting of (1) to (3).

[0018] Item 11. A device for predicting a subject's total sodium excretion (Na_Xh) within a predetermined time period, a urine information acquiring unit a11 that acquires information about the urine, including a measured value of a sodium concentration (NaSpot) and a measured value of a creatinine concentration (CreSpot) in the urine collected from the subject; an attribute information acquiring unit a12 for acquiring attribute information of the subject; a total creatinine excretion amount calculation unit b1 for calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on the attribute information of the subject; a total sodium excretion calculation unit c1 that calculates the predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); or a urine information acquiring unit a21 that acquires information about the urine collected from the subject, including a measured value of a sodium concentration (NaSpot), a measured value of a creatinine concentration (CreSpot), and a measured value of a potassium concentration (KSpot); an attribute information acquiring unit a12 for acquiring attribute information of the subject; a total sodium excretion calculation unit c2 that calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, The total sodium excretion calculation unit c1 or c2 (1) calculating a predicted total sodium excretion amount (Na_Xh_Pred) within a predetermined time period based on the sex of the subject or the sex of the subject and the amount of urine in the total sodium excretion calculation unit c1 or c2; (2) the total sodium excretion calculation unit c1 calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); (3) calculating a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) in the total sodium excretion calculation unit c1 or c2 based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); Perform at least one selected from the group consisting of: Device.

[0019] Item 12. The coefficient in the total sodium excretion calculation unit c1 is a value determined by regression analysis that predicts the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), and a predicted total creatinine excretion within a predetermined time period (CreXh_Pred) that have been measured and calculated in advance for a subject population, and the total sodium excretion within a predetermined time period (Na_Xh) that has been measured in advance for the subject population, or the coefficient in the total sodium excretion calculation unit c2 is a value determined by regression analysis that predicts a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), a potassium concentration (KSpot), a BMI, and an age, which are previously measured and calculated in a subject population, and a total sodium excretion within a predetermined time period (Na_Xh) previously measured in the subject population; Item 12. The device according to item 11.

[0020] Item 13. The device according to Item 12, wherein the total sodium excretion calculation unit c1 or c2 performs (1) above, and the variables include the sex of the subject or the sex of the subject and the amount of urine.

[0021] Item 14. The device described in Item 12, wherein the total sodium excretion calculation unit c1 or c2 performs (3) above, and the variables include the time from the last sodium chloride intake time before the urine collection to the time the urine is collected (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time the urine is collected (TAM2).

[0022] Item 15. When the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated by the total sodium excretion amount calculation unit c1 or c2 is within a range determined by a predetermined threshold, the total sodium excretion calculation unit c1 again calculates the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using an optimization coefficient determined by regression analysis that predicts the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) that has been previously measured for the subject population; or the total sodium excretion calculation unit c2 again calculates the predicted value of the total sodium excretion within a predetermined time (Na_Xh_Pred) using optimization coefficients determined by regression analysis that predicts the total sodium excretion within a predetermined time (Na_Xh) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age that are previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time (Na_Xh_Pred) is within the range, and the total sodium excretion within a predetermined time (Na_Xh) that is previously measured for the subject population; Item 15. The device according to any one of items 11 to 14.

[0023] Item 16. A program for causing a computer to execute each part of the device described in any one of Items 11 to 15. [Effects of the Invention]

[0024] According to the present invention, it is possible to provide a technique for predicting the total sodium excretion amount (Na_Xh) of a subject within a predetermined time period with higher accuracy. [Brief explanation of the drawings]

[0025] [Figure 1] This is a schematic diagram explaining the time from the last salt intake time before urine collection to the time of urine collection (TAM1) and the time from the second-to-last salt intake time before urine collection to the time of urine collection (TAM2). [Figure 2] FIG. 1 is a diagram illustrating a schematic configuration of a prediction system according to an embodiment. [Figure 3] FIG. 2 is a block diagram illustrating functions of a prediction device according to an embodiment. [Figure 4] 10 is a flowchart illustrating a procedure of data processing performed by a prediction device according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0026] In this specification, the expressions "contain" and "comprise" include the concepts of "contain," "comprise," "consist essentially of," and "consist only of."

[0027] 1. Forecasting method In one aspect, the present invention comprises: A method for predicting a total sodium excretion amount (Na_Xh) within a predetermined time period in a subject, comprising: a step a1 of measuring the sodium concentration (NaSpot) and the creatinine concentration (CreSpot) in urine collected from the subject; a step b1 of calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on attribute information of the subject; and a step c1 of calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred), or a step a2 of measuring the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) in urine collected from the subject, as well as the BMI of the subject; and step c2 of calculating a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, (1) in step c1 or c2, calculating a predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) further based on the sex of the subject and / or the amount of urine; (2) in the step c1, calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred); (3) in step c1 or c2, calculating a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) further based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); At least one selected from the group consisting of: The present invention relates to a method for predicting a phenotype of a phenotype (sometimes referred to as the "prediction method of the present invention" in this specification), which will be described below.

[0028] In the prediction method of the present invention, the predetermined time is not particularly limited, but from the viewpoint of enhancing the significance of the prediction method of the present invention because it is difficult to measure the total sodium excretion amount in collected urine, and from the viewpoint of prediction accuracy, the predetermined time is, for example, 8 to 72 hours, preferably 12 to 48 hours, more preferably 16 to 36 hours, even more preferably 20 to 30 hours, particularly preferably 22 to 26 hours, and especially preferably 24 hours.

[0029] The total sodium excretion within a predetermined time (Na_Xh), which is the target of prediction by the prediction method of the present invention, is the total amount of sodium excreted from the body in urine within a predetermined time. The unit of the total excretion to be predicted is not particularly limited, and may be, for example, molar amount or mass.

[0030] The subject is a human, and is not particularly limited in this respect. The subject may be either male or female. Attribute information of the subject, such as age, height, weight, etc., is also not particularly limited.

[0031] Urine collection from a subject is not particularly limited and can be carried out according to known methods. The collected urine can be used as is, or can be used after storing it for a certain period of time (e.g., refrigerated storage). If necessary (especially in the latter case), additives (e.g., preservatives) can be added to the urine.

[0032] The urine to be measured in steps a1 and a2 can be, for example, a single collection of urine, or a mixture of urine collected multiple times (for example, 2 to 4 times, 2 to 3 times, or 2 times). From the viewpoint of simplicity, it is particularly preferable that the urine be a single collection of urine. In this case, the timing of urine collection is not particularly limited, and spot urine collected at any time can be used.

[0033] The measurement of the urinary sodium concentration (NaSpot) and creatinine concentration (CreSpot) in steps a1 and a2, and the measurement of the potassium concentration (KSpot) and BMI in step a2 are not particularly limited and can be performed according to known methods. The sodium concentration and potassium concentration can be measured, for example, by an ion selective electrode method or a flame photometry. The creatinine concentration can be measured, for example, by an enzymatic method, an HPLC method, an ELISA method, etc. BMI can be calculated based on height and weight information using the formula: BMI = weight (unit: kg) / [height (unit: m)] 2 It can be calculated as follows.

[0034] The units of the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) are not particularly limited and may be, for example, molar concentration, mass concentration, etc. Furthermore, the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) used in steps c1 and c2 and thereafter may be the actual measured values ​​themselves, or modified values ​​such as values ​​obtained by multiplying the measured values ​​by any value other than 1 (for example, greater than 0 and less than 100, 2 or more and less than 50, or 5 or more and less than 20), or the natural logarithm of the measured values.

[0035] The predicted value of the total creatinine excretion amount within a predetermined time (CreXh_Pred) in step b1 is considered to be almost constant for each subject unless there is shock or bleeding, and is hardly affected by dietary factors or urine volume. Therefore, it is known that the predicted value of the total creatinine excretion amount within a predetermined time (CreXh_Pred) can be calculated based on the attribute information of the subject.

[0036] The attribute information used in step b1 may be, for example, information about the size of all or part of the body (preferably height), information about the weight of all or part of the body (preferably weight), or all or part of the time since birth (preferably age). From the viewpoint of calculation accuracy of the predicted value of total creatinine excretion within a predetermined time (CreXh_Pred), it is preferable to use all of these, and it is particularly preferable to use height, weight, and age. The calculation formula for the predicted value of total creatinine excretion within a predetermined time (CreXh_Pred) may be, for example, a known formula (e.g., the calculation formulas described in Non-Patent Documents 1 and 2), or a calculation formula obtained by regression analysis using attribute information as a variable using an arbitrary subject population.

[0037] The unit of the predicted value of the total creatinine excretion amount within a predetermined time (CreXh_Pred) is not particularly limited and may be, for example, molar concentration, mass concentration, etc. Furthermore, the predicted value of the total creatinine excretion amount within a predetermined time (CreXh_Pred) used in step c1 and thereafter may be the calculated value obtained by the calculation formula itself, or may be a modified value such as a value obtained by multiplying the calculated value by any value other than 1 (for example, more than 0 and 100 or less, 2 or more and 50 or less, or 5 or more and 20 or less), or the natural logarithm of the measured value.

[0038] In this specification, "calculating B based on A" means calculating B using an arithmetic formula including A.

[0039] In a more specific preferred embodiment of step b1, the causal relationship between the measured value of the total creatinine excretion amount within a specified time (CreXh_Pred) and the subject's attribute information is estimated by regression analysis, and then the estimated value of the coefficient (optimal coefficient) is used to calculate the predicted value of the total creatinine excretion amount within a specified time (CreXh_pred).

[0040] In step c1, a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) is calculated using coefficients based on the sodium concentration (NaSpot) measured in step a1, the creatinine concentration (CreSpot) measured in step a1, and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred) calculated in step b1.

[0041] In a more specific preferred embodiment of step c1, the measured value of the total sodium excretion within a predetermined time (Na_Xh) is regressed on variables such as the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time (CreXh_Pred), which have been measured and calculated in advance for a subject population, to calculate coefficient estimates (optimization coefficients) for each variable, and the predicted value of the total sodium excretion within a predetermined time (Na_Xh_pred) is calculated using these.

[0042] In step c2, a predicted total sodium excretion amount within a specified time period (Na_Xh_Pred) is calculated using a coefficient based on the sodium concentration (NaSpot) measured in step a2, the creatinine concentration (CreSpot) measured in step a2, the potassium concentration (KSpot) measured in step a2, the BMI measured in step a2, and the age of the subject.

[0043] In a more specific preferred embodiment of step c2, The sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, age, and other variables previously measured and calculated in a subject population are regressed to calculate coefficient estimates (optimized coefficients) for each variable, and these are used to calculate the predicted total sodium excretion amount within a specified time period (Na_Xh_pred).

[0044] The coefficient is a coefficient suitable for predicting the total sodium excretion within a predetermined time period (Na_Xh), and can be determined appropriately using any analysis method. Typically, the coefficient in step c1 is a value determined by regression analysis that predicts the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), and predicted total creatinine excretion within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a subject population, as well as the total sodium excretion within a predetermined time period (Na_Xh) that has been previously measured for the subject population. Furthermore, typically, the coefficient in step c2 is a value determined by regression analysis that predicts the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age that have been measured and calculated in advance in a subject population, as well as the total sodium excretion within a predetermined time period (Na_Xh) that has been measured in advance in the subject population.

[0045] The subject population used in any analytical method, such as regression analysis, performed to determine coefficients is not particularly limited and is a population containing multiple subjects as described above. From the viewpoint of the accuracy of the prediction method of the present invention, the number of subjects in the subject population is preferably 10 or more, more preferably 100 or more, even more preferably 300 or more, even more preferably 500 or more, and particularly preferably 1000 or more. The upper limit is not particularly limited and is, for example, 1,000,000, 500,000, 200,000, 100,000, 50,000, 20,000, 10,000, or 5,000. The subject population may be unchanged, or may be one in which subjects are added as needed, for example, during the implementation of the prediction method of the present invention.

[0046] The method for measuring (actually measuring) the total sodium excretion within a predetermined time period (Na_Xh) is not particularly limited. Usually, the measurement is performed using urine collected within a predetermined time period.

[0047] In the regression analysis in step c1, the explanatory variables include the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time (CreXh_Pred), and the response variable includes the total sodium excretion amount within a predetermined time (Na_Xh) measured in advance. In the regression analysis in step c2, the explanatory variables include the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), BMI, and age, and the response variable includes the total sodium excretion amount within a predetermined time (Na_Xh) measured in advance. In these regression analyses, it is preferable to perform regression analysis using each variable as an independent variable and calculate a coefficient for each variable. However, regression analysis may also be performed using a combined value of two or more variables (for example, a value calculated using an arithmetic formula including these two or more variables) as a variable.

[0048] In the prediction method of the present invention, (1) in step c1 or c2, calculating the total sodium excretion within a predetermined time (Na_Xh) further based on the sex of the subject or the sex of the subject and / or the amount of urine; (2) in the step c1, calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred); (3) in step c1 or c2, calculating the total sodium excretion within a predetermined time period (Na_Xh) further based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); This allows the prediction accuracy (e.g., adjusted R 2, AIC, correlation, Mean±SE, Mean bias, and Systematic bias) can be improved.

[0049] Regarding (1), the sex of the subject is converted from the sex (e.g., male or female) to an arbitrary number. For example, 0 is used for males, and any number other than 0 (e.g., 1) is used for females. The unit of urine volume is not particularly limited, and may be, for example, volume, mass, etc. The urine volume may be the measured value itself, or a modified value such as the measured value multiplied by any value other than 1 (e.g., greater than 0 and less than 100, 2 to 50, or 5 to 20). When the subjects are all male or all female, only the urine volume is considered in (1).

[0050] When the prediction method of the present invention includes (1), the coefficients can be determined preferably by the regression analysis. In this case, it is preferable that the explanatory variables in the regression analysis include the sex of the subject and / or the amount of urine (more preferably, each of them is included as an independent variable).

[0051] In a more specific preferred embodiment of (1), the measured value of the total sodium excretion within a predetermined time (Na_Xh) is regressed on the variables including the sex of the subject and / or the amount of urine to calculate coefficient estimates (optimized coefficients) for each variable, and the predicted value of the total sodium excretion within a predetermined time (Na_Xh_pred) is calculated using these coefficient estimates.

[0052] (2) In other words, instead of combining the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a specified time period (CreXh_Pred), these three variables are used as independent variables to calculate a coefficient for each variable, and the obtained coefficients are used to calculate the predicted total sodium excretion amount within a specified time period (Na_Xh_Pred).

[0053] In a more specific preferred embodiment of (2), the total sodium excretion within a predetermined time period (Na_Xh) is regressed on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) to calculate coefficient estimates (optimization coefficients) of each variable, and the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_pred) is calculated using these coefficient estimates.

[0054] Regarding (3), a schematic diagram illustrating the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2) is shown in Figure 1. TAM1 and TAM2 may be the time itself, or a modified value such as a value obtained by multiplying the measured value by any value other than 1 (for example, more than 0 and 100 or less, 1 / 50 or more and 1 / 10 or less, or 1 / 30 or more and 1 / 20 or less).

[0055] In a more specific preferred embodiment of (3), the total sodium excretion within a predetermined time period (Na_Xh) is added to the time from the last salt intake before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake before the urine collection to the time of the urine collection (TAM2), and regressed on these variables to calculate coefficient estimates (optimization coefficients) for each variable, thereby calculating the predicted sodium excretion within a predetermined time period (Na_Xh_pred).

[0056] In this specification, "salt" refers to sodium chloride, and its form of existence is not particularly limited, and it may be, for example, any of purified salt, unpurified salt, and crudely purified salt.

[0057] When the prediction method of the present invention includes (3), the coefficients can preferably be determined by the regression analysis described above. In this case, it is preferable that the explanatory variables in the regression analysis include (more preferably, each includes as an independent variable) the time from the last sodium chloride intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2), and it is particularly preferable that in addition to TAM1 and TAM2, values ​​calculated based on these (for example, the square of TAM1 (TAM1_sq), the square of TAM2 (TAM2_sq)) are included (more preferably, each includes as an independent variable).

[0058] From the viewpoint of prediction accuracy, the prediction method of the present invention preferably includes at least two selected from the group consisting of (1) to (3) (e.g., (1) and (2), (1) and (3), or (2) and (3)), and particularly preferably includes all of (1) to (3).

[0059] The calculation formula used in step c of the prediction method of the present invention may include a constant. The constant can be set from the perspective of prediction accuracy and can be determined by regression analysis.

[0060] When the prediction method of the present invention includes all of (1) to (3), a preferred example of a formula for calculating the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) is shown below.

[0061]

number

[0062] In the above calculation formula, a to i represent coefficients. These coefficients can be determined by regression analysis, and for example, the values ​​of the 90% confidence intervals shown in Table 2 in the Examples described later can be used. Furthermore, j represents a constant, which can be determined by regression analysis.

[0063] From the viewpoint of prediction accuracy, the prediction method of the present invention preferably includes: If the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated in step c1 or c2 is within a range determined by a predetermined threshold, a step d1 of calculating again in step c1 a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using an optimization coefficient determined by regression analysis for predicting total sodium excretion within a predetermined time period (Na_Xh) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), and a predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred) previously measured and calculated for a population of subjects whose total sodium excretion within a predetermined time period (Na_Xh) is within the range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the population; or a step d2 of calculating again in step c2 the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using optimization coefficients determined by regression analysis for predicting the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the subject population; Includes:

[0064] In a more specific preferred embodiment of step d1, when the predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) calculated in step c1 is within a range defined by a predetermined threshold, the predicted value of total sodium excretion within a predetermined time period (Na_Xh_pred) is calculated again in step c1 using variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), and predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred) that have been measured and calculated in advance for a group of subjects whose predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the range. Similarly, if the predicted value of total sodium excretion within a specified time period (Na_Xh_pred) calculated in step c1 is outside the range defined by the predetermined threshold, the total sodium excretion within a specified time period (Na_Xh_pred) is calculated again in step c1 using variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), and predicted value of total creatinine excretion within a specified time period (CreXh_Pred) that have been measured and calculated in advance for a group of subjects whose predicted value of total sodium excretion within a specified time period (Na_Xh_pred) is outside the range defined by the predetermined threshold.

[0065] In a more specific preferred embodiment of step d2, when the predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) calculated in step c2 is within a range defined by a predetermined threshold, the predicted value of total sodium excretion within a predetermined time period (Na_Xh_pred) is calculated again in step c2 using variables including sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age that have been measured and calculated in advance for a group of subjects whose predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the range. Similarly, if the predicted value of total sodium excretion within a specified time period (Na_Xh_pred) calculated in step c2 is outside the range defined by the predetermined threshold, the total sodium excretion within a specified time period (Na_Xh_pred) is calculated again in step c2 using variables including sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age that have been measured and calculated in advance for a group of subjects whose predicted value of total sodium excretion within a specified time period (Na_Xh_pred) is outside the range defined by the predetermined threshold.

[0066] The "range determined by a predetermined threshold" in steps d1 and d2 can be determined by any method. From the viewpoint of prediction accuracy, it is preferable to divide the subject population used in the regression analysis into multiple populations (e.g., 2 to 10, 2 to 5, 2 to 4, 2 to 3, or 2) based on the predicted or measured total sodium excretion within a predetermined time (Na_Xh), and set the boundary between the populations as the threshold.

[0067] Step d1 or d2 can improve the systematic bias of overestimating in a region where the total sodium excretion amount within a predetermined time is small and underestimating in a region where the total sodium excretion amount within a predetermined time is large.

[0068] 2. Prediction device In one aspect, the present invention comprises: An apparatus for predicting a total sodium excretion amount (Na_Xh) of a subject within a predetermined time, comprising: a urine information acquiring unit a11 that acquires information about the urine, including a measured value of a sodium concentration (NaSpot) and a measured value of a creatinine concentration (CreSpot) in the urine collected from the subject; and an attribute information acquiring unit a12 that acquires attribute information about the subject. a total creatinine excretion amount calculation unit b1 for calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on the attribute information of the subject; a total sodium excretion calculation unit c1 that calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); or a urine information acquiring unit a21 that acquires information about the urine collected from the subject, including a measured value of a sodium concentration (NaSpot), a measured value of a creatinine concentration (CreSpot), and a measured value of a potassium concentration (KSpot); an attribute information acquiring unit a12 for acquiring attribute information of the subject; a total sodium excretion calculation unit c2 that calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, The total sodium excretion calculation unit c1 or c2 (1) calculating a predicted total sodium excretion amount (Na_Xh_Pred) within a predetermined time period based on the sex of the subject or the sex of the subject and the amount of urine in the total sodium excretion calculation unit c1 or c2; (2) the total sodium excretion calculation unit c1 calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); (3) calculating a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) in the total sodium excretion calculation unit c1 or c2 based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); Perform at least one selected from the group consisting of: The present invention relates to a prediction device (sometimes referred to as the "prediction device of the present invention" in this specification), which will be described below.

[0069] The prediction device of the present invention is a device that processes data in accordance with the prediction method of the present invention. Unless otherwise specified, the processing performed by the prediction device of the present invention is the same as that performed by the prediction method of the present invention, and therefore, redundant explanations will be omitted.

[0070] 2.1.Device configuration FIG. 2 is a diagram illustrating a schematic configuration of a prediction system according to an embodiment.

[0071] A prediction system 100 according to one embodiment includes a prediction device 1 and a server device 90. The prediction device 1 and the server device 90 are connected to each other via a network 9 so as to be able to communicate data with each other. The server device 90 records various data related to subjects, which have been measured or acquired at medical institutions such as clinics, general hospitals, and health centers, or at research institutions such as companies and universities. The various data related to the subjects are recorded as clinical information or medical information of the subjects in the form of, for example, medical records (charts). The server device 90 may be installed inside the medical institutions or research institutions described above, or may be cloud-based and installed outside the medical institutions or research institutions described above.

[0072] In this embodiment, the prediction device 1 acquires various data related to the subject, which is used to predict the total sodium excretion within a predetermined time period (Na_Xh) of the subject, from the server device 90. The prediction device 1 acquires, as the various data related to the subject, urine information data 21, attribute information data 22, and dietary information data 23, which will be described later, from the server device 90.

[0073] FIG. 3 is a block diagram illustrating the function of the prediction device according to an embodiment.

[0074] A prediction device 1 according to one embodiment of the present invention includes a data processing unit 10, an auxiliary storage device 20, an input unit 31, a display unit 32, and a communication interface unit (communication I / F unit) 33. The prediction device 1 can be configured using, for example, a general-purpose computer such as a notebook computer, or, for example, a tablet terminal or a smartphone (hereinafter referred to as a tablet terminal or the like).

[0075] In this embodiment, the prediction device 1 includes, as hardware components, an auxiliary storage device 20, an input unit 31, a display unit 32, and a communication I / F unit 33. Although not shown, the prediction device 1 also includes, as hardware components, a processor such as a CPU that performs data processing, and a memory that the processor uses as a working area for data processing.

[0076] The auxiliary storage device 20 is a non-volatile storage device that stores an operating system (OS), various control programs, data generated by the programs, etc., and is configured, for example, by a flash memory, an eMMC (embedded multi media card), an SSD (solid state drive), etc. In this embodiment, the auxiliary storage device 20 stores urine information 21, attribute information 22, dietary intake information 23, calculation formula coefficients 24, and a prediction program 29.

[0077] The urine information 21 is information about urine collected from a subject. In this embodiment, the urine information 21 includes information about a measured sodium concentration (NaSpot), a measured potassium concentration (KSpot), a measured creatinine concentration (CreSpot), the amount of urine, and the time the urine was collected. The attribute information 22 is information about the attributes of the subject. In this embodiment, the attribute information 22 includes information about the subject's height, weight, age, and sex. The dietary information 23 is information about the food and drink ingested by the subject. In this embodiment, the dietary information 23 includes information about the time the subject ingested salt. The calculation formula coefficients 24 are information about the coefficients of a calculation formula used to calculate the total sodium excretion within a predetermined time (Na_Xh). The coefficients of the calculation formula are determined in advance by regression analysis.

[0078] The prediction program 29 is a computer program for implementing the software functional blocks of the units 11 to 16 in the data processing unit 10 (described later). These functional blocks are implemented by installing the prediction program 29 in the auxiliary storage device 20 or memory of the prediction device 1 and having the processor execute the prediction program 29. The prediction program 29 may be installed in the prediction device 1 via a network 9 such as the Internet connected via the communication I / F unit 33. Alternatively, the prediction program 29 may be installed in the prediction device 1 by having the prediction device 1 read a computer-readable, non-transitory, tangible recording medium, such as a memory card, on which the prediction program 29 is recorded. The prediction program 29 may be implemented as an application on, for example, a tablet terminal. The prediction program 29 may also be implemented using spreadsheet software such as Microsoft Excel (registered trademark) or Google (registered trademark) Spreadsheet.

[0079] The input unit 31 can be configured, for example, by a mouse, a keyboard, etc., and the display unit 32 can be configured, for example, by a liquid crystal display, an organic EL display, etc. The input unit 31 and the display unit 32 can also be integrated as a touch panel.

[0080] The communication I / F unit 33 transmits and receives data to and from an external device such as a server device 90 via a wired or wireless network 9. The communication I / F unit 33 may be connected via various wireless or wired connections such as Bluetooth (registered trademark), Wi-Fi (registered trademark), and Ethernet (registered trademark).

[0081] In this embodiment, the prediction device 1 includes, as a software configuration, a data processing unit 10. The data processing unit 10 is a functional block that is realized when a processor executes a prediction program 29.

[0082] The urinary information acquiring unit 11 acquires urinary information 21 of the subject. The attribute information acquiring unit 12 acquires attribute information 22 of the subject. The dietary information acquiring unit 13 acquires information 23 about food and drink ingested by the subject. In this embodiment, these acquiring units 11, 12, and 13 acquire the urinary information 21, attribute information 22, and dietary information 23 about the subject from the server device 90 via the network 9. In other embodiments, the acquiring units 11, 12, and 13 acquire the urinary information 21, attribute information 22, and dietary information 23 about the subject via the input unit 31 in response to input by an operator.

[0083] The total creatinine excretion calculation unit 14 calculates a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on the acquired attribute information 22 of the subject.

[0084] The total sodium excretion calculation unit 15 calculates the total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the calculated predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred), or based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the subject's age. The sodium concentration (NaSpot), the potassium concentration (KSpot), and the creatinine concentration (CreSpot) use measured values ​​included in the acquired urine information 21. The predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) uses the value calculated by the total creatinine excretion calculation unit 14. The coefficients of the calculation formula use data from the calculation formula coefficients 24.

[0085] In the prediction device of the present invention, The total sodium excretion calculation unit 15 (1) calculating a predicted total sodium excretion amount (Na_Xh_Pred) within a predetermined time period based on the subject's sex or the subject's sex and urine volume; (2) Calculating the total sodium excretion within a specified time (Na_Xh) using coefficients determined for the sodium concentration (NaSpot), creatinine concentration (CreSpot), and predicted total creatinine excretion within a specified time (CreXh_Pred); (3) Calculating a predicted total sodium excretion amount within a specified time period (Na_Xh_Pred) based further on the time from the last salt intake time before urine collection to the time of urine collection (TAM1) and the time from the second-to-last salt intake time before urine collection to the time of urine collection (TAM2).

[0086] For (1), the gender is determined using information included in the attribute information 22. The amount of urine is determined using the measurement value included in the urine information 21. For (3), the salt intake time is determined using information included in the dietary information 23. The urine collection time is determined using the measurement value included in the urine information 21.

[0087] When the prediction device of the present invention includes all of (1) to (3), the total sodium excretion calculation unit 15 calculates the predicted total sodium excretion within a specified time period (Na_Xh_Pred) using calculation formula coefficients 24 based on the subject's urine information 21, attribute information 22, dietary intake information 23, and the calculated predicted total creatinine excretion within a specified time period (CreXh_Pred).

[0088] From the viewpoint of prediction accuracy, the prediction device of the present invention preferably includes: When the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated by the total sodium excretion amount calculation unit 15 is within a range determined by a predetermined threshold, The total sodium excretion calculation unit 15 can re-calculate the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) using an optimization coefficient determined by regression analysis that predicts the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a population of subjects whose total sodium excretion within a predetermined time period (Na_Xh) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) that has been previously measured for the subject population; or The total sodium excretion calculation unit c2 can re-calculate the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using optimization coefficients determined by regression analysis that predicts the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age that are previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, as well as the total sodium excretion within a predetermined time period (Na_Xh) that is previously measured for the subject population.

[0089] The prediction result output unit 16 outputs the calculated predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) as the prediction result. In this embodiment, the prediction result output unit 16 displays the prediction result on, for example, the display unit 32. In another embodiment, the prediction result output unit 16 transmits the prediction result to, for example, a server device 90. The server device 90 records the calculated value of the predicted value of total sodium excretion within a predetermined time of the subject (Na_Xh_Pred), output from the prediction device 1, in the form of, for example, a medical record (chart), in association with, for example, clinical information or medical information of the subject.

[0090] This allows medical professionals involved in the medical treatment and health guidance of subjects at medical institutions and research institutions such as clinics, general hospitals, and health centers to provide more appropriate medical treatment and health guidance by referring to the subject's predicted total sodium excretion within a specified time period (Na_Xh_Pred), which is predicted with greater accuracy.

[0091] 2.2. Processing Procedure FIG. 4 is a flowchart illustrating a data processing procedure performed by a prediction device according to an embodiment.

[0092] In step S1, the urine information acquiring unit 11 acquires urine information 21 of the subject. In step S2, the attribute information acquiring unit 12 acquires attribute information 22 of the subject. In step S3, the dietary information acquiring unit 13 acquires dietary information 23 of the subject. In step S4, the total creatinine excretion calculation unit 14 calculates a predicted value of the total creatinine excretion amount within a predetermined time period (CreXh_Pred) of the subject based on the acquired attribute information 22 of the subject.

[0093] In step S5, the total sodium excretion calculation unit 15 calculates the predicted total sodium excretion within a specified time period (Na_Xh_Pred) using coefficients based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the calculated predicted total creatinine excretion within a specified time period (CreXh_Pred).

[0094] In this embodiment, the total sodium excretion calculation unit 15 calculates the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) using a calculation formula and coefficients that include all of (1) to (3) in the prediction method of the present invention. The total sodium excretion calculation unit 15 calculates the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) using calculation formula coefficients 24 based on the subject's urine information 21, attribute information 22, dietary intake information 23, and the calculated predicted total creatinine excretion within a predetermined time period (CreXh_Pred).

[0095] In step S6, the prediction result output unit 16 outputs the calculated predicted value of the total sodium excretion amount within a predetermined time (Na_Xh_Pred) as a prediction result. The prediction result is displayed on the display unit 32, for example.

[0096] As described above, according to the prediction method and prediction device of one embodiment, it is possible to predict with higher accuracy the predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) of a subject. As a result, medical professionals involved in the medical treatment and health guidance of subjects at medical institutions and research institutions such as clinics, general hospitals, and health centers can provide more appropriate medical treatment and health guidance by referring to the predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) of the subject that has been predicted with higher accuracy.

[0097] 3. Other forms Although the present invention has been described above with reference to specific embodiments, the present invention is not limited to the above-described embodiments.

[0098] In the above embodiment, the prediction device 1 is realized as an integrated device, but the prediction device 1 does not need to be an integrated device, and the processor, memory, auxiliary storage device 20, etc. may be located in different locations and connected to each other via a network. The input unit 31 and the display unit 32 also do not necessarily need to be located in the same place, and may be located in different locations and connected to each other so that they can communicate with each other via a network.

[0099] In the above embodiment, the functional blocks 11 to 16 constituting the data processing unit 10 are realized by software, but some or all of these functional blocks 11 to 16 may be realized as hardware. The processing of the functional blocks 11 to 16 constituting the data processing unit 10 does not need to be performed by a single processor, but may be distributed among multiple processors. Some or all of the functions of the data processing unit 10 and the data items in the auxiliary storage device 20 may be cloud-based in another server device (not shown) connected via the communication I / F unit 33. [Example]

[0100] The present invention will be described in detail below based on examples, but the present invention is not limited to these examples.

[0101] The concept of Test Example 1 will be explained below.

[0102] This paper describes an extension of the regression analysis method using spot urine. Kawasaki and Tanaka (KT) are distinguished by their theoretical approach. Kawasaki's formula incorporates gender differences in the first stage of the formula to estimate predicted 24-hour urinary Creatinine excretion (mg / day). The key variable in the second stage is raised to the 0.5th power. Tanaka's formula estimates predicted 24-hour urinary Creatinine excretion (mg / day) without gender differences, and the key variable in the second stage is raised to the 0.392th power. Kawasaki assumed that the second formula applies to the second urine after waking, while Tanaka assumed it applies regardless of time of day. Kawasaki's idea focuses on the fact that 24-hour creatinine excretion varies between individuals but is stable within individuals (cited PMID 8432042). He also assumes that the 24-hour fluctuation patterns of Na_Spot and Cre_Spot are similar. Specifically, Na_Spot / Na_24h and Cre_Spot / Cre_24h change stably in the same direction. From the latter, if Cre_24h is known, Na_24h can be estimated from the Na_Spot / Cre_Spot ratio measured in spot urine. On the other hand, from the former, the Cre_24h estimation formula can be estimated experimentally by obtaining Cre_24h data and participant demographic data. Therefore, Tanaka (PMID 11850766) estimated equations (1) and (2) using their experimental data.

[0103]

number

[0104] where Cre_24h_Pred is the predicted value of Cre_24h from Eq. (1), and v and u are disturbance terms. Using these estimated values ​​of α, β, a, and b, we can estimate Na_24h from participants' spot urine.

[0105] Although KT's two hypotheses are bold, the use of their formulas suggests they are superior hypotheses. Indeed, a study comparing eight different estimation formulas reported that Tanaka's formula was the best for estimating Na_24h (PMID 30517605, PMID 30517722), and a US study reported that estimation using Tanaka's formula from nighttime spot urine samples yielded the least bias (PMID 24047921). However, while the KT formula is accurate on average across a population, it has been criticized for being unsuitable for use at the individual level (PMID 11850766, PMID 31087778, PMID 34196446). This includes the low correlation coefficient between predicted and observed values ​​and the overestimation of Na_24h when Na_24h (the key variable in the second formula, being a linear function) is low and the underestimation when it is high. For example, Bland-Altman plots clearly show this tendency. Based on these findings, our research aims to develop an estimation formula that basically follows the ideas of KT but has more predictive power. Examples of research with this goal include Intersalt, Brown, Mage, and Toft. Specifically, we extend Tanaka's method in the following four ways.

[0106] First extension: Adding explanatory variables such as attribute variables In this study, the first-stage equation uses three variables, age, weight, and height, similar to Tanaka's formula, to regress Cre_24h and calculate the respective coefficients. Cre_24h has been reported to be affected by age, gender, and physique (cited). Therefore, a multiple regression analysis was performed adding variables such as fat mass, muscle mass, and gender. The goodness of fit was evaluated to determine the first-stage equation.

[0107] Regarding equation (2), K attribute variables including age, height, weight, potassium (K), systolic blood pressure (SBP), diastolic blood pressure (DBP), and spot urine volume are added and estimated.

[0108]

number

[0109] Second extension: Using the components of the Key variable individually Regarding equation (2), the following equation was estimated, taking into consideration that the fit would be better if the three variables that make up the key variables were used individually. The INTERSALT equation does not go through the first stage of the equation, but instead separates the formula for men and women, and uses a linear function calculation with the variables Na, Cre, K (potassium), BMI, and age. Here, following the example of INTERSALT, concentration is used.

[0110]

number

[0111] If the theoretical assumptions about the key variables are correct, then b = -c = d.

[0112] Third extension: Formulation taking into account discharge time Na_24h is the total amount of Na excreted in the spot urine over 24 hours (Na_Spot). Therefore, unless Na_Spot is constant regardless of the time of excretion, the time of excretion must be taken into account when estimating Na_24h. Therefore, first examine the hourly fluctuations in Na_Spot, and if this fluctuation is large, perform an analysis taking the time of excretion into account.

[0113] When considering time, we assume that there is a pattern in which the amount of excretion differs depending on the time elapsed since the time of salt intake, as a factor in how Na_Spot changes over time, and add the time elapsed since the most recent and previous meal (TAM1, TAM2) to the explanatory variables. In addition, since it is not thought that the amount of excretion changes monotonically after a meal, we also take into account the square of the elapsed time (TAM1_sq, TAM2_sq). Therefore, the estimation formula is

[0114]

number

[0115] Of course, we also consider a formulation that incorporates all three extensions.

[0116] Fourth extension: Segmentation estimation of observation area The reason for the poor fit of the estimation equation, resulting in biases such as overestimation in the low sodium region and underestimation in the high sodium region, may be that the functional form is not flexible enough.In this study, rather than searching for a new functional form to address this problem, we take the approach of dividing the set of observations into two groups based on the magnitude of sodium excretion.

[0117] First, the three expanded formulas above are estimated using all observed values, and then all observed values ​​are divided into two groups based on the resulting Na_24h_Pred values. Next, the final Na_24h_Pred is estimated using only the data from each group.

[0118] Test Example 1. Prediction of 24-hour total sodium excretion (Na_24h, unit: mEq) 1 The sodium concentration (NaSpot, unit: mEq / L) and creatinine concentration (CreSpot, unit: mg / dL) were measured in spot urine (a single urine collection) collected from 104 subjects (37 men and 67 women). The creatinine concentration was multiplied by 10 and used in the following predictions. In addition, the 24-hour total sodium excretion (Na_24h, unit: mEq) and 24-hour total creatinine excretion (Cre_24h, unit: mg) were measured for each subject using all urine collected within the 24-hour period including the time of collection of the spot urine.

[0119] Next, the predicted 24-hour total creatinine excretion value (Cre24h_Pred, unit: mg) of the subject was calculated based on the subject's height (Height, unit: cm), weight (Weight, unit: kg), and age (Age). The calculation formula is as follows: This calculation formula was derived by regression analysis based on the height, weight, and age of the subject group and the measured values ​​of the 24-hour total creatinine excretion.

[0120]

number

[0121] Based on the sodium concentration (NaSpot, unit: mEq / L), creatinine concentration (CreSpot, unit: (mg / dL)*10) measured above, and the predicted 24-hour total creatinine excretion (Cre24h_Pred), the predicted 24-hour total sodium excretion (Na_24h_Pred) was calculated using coefficients.

[0122] The coefficients were determined by regression analysis to predict the total sodium excretion within a specified time period (Na_24h) ​​based on variables including the sodium concentration (NaSpot, unit: mEq / L) and creatinine concentration (CreSpot, unit: (mg / dL)*10) measured above, and the total 24-hour sodium excretion (Na_24h, unit: mEq) measured above.

[0123] The above calculation was performed under different conditions for the following six patterns.

[0124] Pattern 1 Regression analysis was performed using the sum of NaSpot, CreSpot, and Cre24h_Pred values ​​(key variables) as variables to calculate coefficients (using the same method as the conventional Tanaka formula). The Na_24h prediction formula using the obtained coefficients is shown below.

[0125]

number

[0126] Pattern 2 The same procedure as in Pattern 1 was repeated, except that the subject's sex (Female: 1 for females, 0 for males) and the volume of spot urine (Vol, unit: mL) were added as variables and a coefficient was calculated for each variable. The Na_24h prediction formula using the obtained coefficients is shown below.

[0127]

number

[0128] Pattern 3 Regression analysis was performed using NaSpot, CreSpot, and Cre24h_Pred as independent variables, and coefficients were calculated for each variable. The Na_24h prediction formula using the obtained coefficients is shown below.

[0129]

number

[0130] Pattern 4 The procedure was the same as in pattern 1, except that the time from the last salt intake before spot urine collection to the time of spot urine collection (TAM1, unit: hour / 24), the squared value of TAM1 (TAM1_sq), the time from the second-to-last salt intake before spot urine collection to the time of spot urine collection (TAM2, unit: hour / 24), and the squared value of TAM2 (TAM2_sq) were each added as variables, and a coefficient was calculated for each variable. The Na_24h prediction formula using the obtained coefficients is shown below.

[0131]

number

[0132] Pattern 5 The conditions of Pattern 2 and Pattern 4 were combined. The Na_24h prediction formula using the obtained coefficients is shown below.

[0133]

number

[0134] Pattern 6 The experiment was carried out by combining the conditions of Pattern 2, Pattern 3, and Pattern 4. The Na_24h prediction formula using the obtained coefficients is shown below.

[0135]

number

[0136] In Eq.(2)~(7), exp is exponential and log is natural logarithm.

[0137] For Eq. (2) to (7), the variables used in the regression analysis and their coefficients, constants, the number of subjects used (Observations), and the evaluation index (adjusted R) for the analysis results. 2, AIC, correlation, Mean±SE, Mean bias, and Systematic bias are shown in Table 1.

[0138] [Table 1]

[0139] The attribute variables (urine volume) and gender were significant in all equations, but urine volume was only significant in Eq. (7). The time variables TAM1 and TAM2 were significant at the 1% level in all equations. Splitting the key variables improved the fit, but compared to NaSpot and CreSpot, only Cre24h_Pred had a coefficient that was about twice as large. This indicates that the theory behind key variables is incorrect. Eq. (7) provided a better fit than any other equation.

[0140] Table 2 also shows the 90% confidence intervals of the coefficients for each variable in Eq. (7).

[0141] [Table 2]

[0142] Next, the subject group was divided into two groups based on the predicted values ​​of Eq. (7), and a similar regression analysis was performed.

[0143] The Na_24h prediction formula when Na24h_Eq.(7) is in the range below the threshold (108.7 mEq / 24h) is shown below.

[0144]

number

[0145] The Na_24h prediction formula for when Na24h_Eq.(7) is greater than 108.7 mEq / 24h is shown below.

[0146]

number

[0147] For the above two equations, the variables and their coefficients, constants, number of subjects used (Observations), and adjusted R 2 is shown in Table 3.

[0148] [Table 3]

[0149] All attribute variables except for gender in the minimum domain were significant at the 1% level. Both equations for the time variables TAM1 and TAM2 were significant at the 1% level. The correlation coefficient between Na24h and the theoretical value was 0.669, which is larger than the 0.656 in Eq. (7) before splitting. The systematic bias of the unsplit equation was 0.474, smaller (i.e., improved) than the 0.717 in Eq. (1) and 0.497 in Eq. (7).

[0150] Test Example 2. Prediction of 24-hour total sodium excretion (Na_24h, unit: mEq) 2 By adding the method used in Test Example 1 to the INTERSALT equation (Brown IJ, Dyer AR, Chan Q, Cogswell ME, Ueshima H, Stamler J, et al; INTERSALT Co-Operative Research Group. Estimating 24-hour urinary sodium excretion from casual urinary sodium concentrations in Western populations: the INTERSALT study. Am J Epidemiol 2013; 177(11): 1180-92), the accuracy of estimating 24-hour urinary sodium excretion (Na_24h) ​​was improved.

[0151] The estimation formula for male subjects only is as follows:

[0152]

number

[0153] The estimation formula for female subjects only is as follows:

[0154]

number

[0155] Test Example 3. Prediction of 24-hour total sodium excretion (Na_24h, unit: mEq) 3 The 24-hour urinary sodium excretion (Na_24h) ​​was estimated for only male subjects or only female subjects, and the estimation was performed in the same manner as in Test Example 1, except for excluding gender-related variables.The method used in Test Example 1 similarly improved the estimation accuracy.

[0156] The estimation formula for male subjects only is as follows:

[0157]

number

[0158] The estimation formula for female subjects only is as follows:

[0159]

number

[0160] Test Example 4. Prediction of 24-hour total sodium excretion (Na_24h, unit: mEq) 4 The estimation was performed in the same manner as in Test Example 1, except that the predicted 24-hour total creatinine excretion amount and the creatinine concentration in spot urine were combined into one variable. The estimation formula is as follows:

[0161]

number

[0162] 1 Prediction device 9 Network 10 Data Processing Unit 11 Urine information acquisition department 12 Attribute information acquisition section 13. Food intake information acquisition unit 14 Creatinine total excretion calculation section 15 Total sodium excretion calculation section 16 Prediction result output section 20 Auxiliary storage 21 Urine information data 22 Attribute information data 23 Dietary Information Data 24 Calculation formula coefficients 29 Prediction Program 31 Input section 32 Display section 33 Communication interface section (communication I / F section) 90 Server equipment

Claims

1. A method for predicting total sodium excretion (Na_Xh) within a predetermined time period in a subject, comprising: a step a1 of measuring the sodium concentration (NaSpot) and the creatinine concentration (CreSpot) in urine collected from the subject; a step b1 of calculating a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on attribute information of the subject; and a step c1 of calculating a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred), or a step a2 of measuring the sodium concentration (NaSpot), creatinine concentration (CreSpot), and potassium concentration (KSpot) in urine collected from the subject, as well as the BMI of the subject; and step c2 of calculating a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject, (1) in step c1 or c2, calculating a predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) further based on the sex of the subject and / or the amount of urine; (2) in the step c1, calculating a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of total creatinine excretion within a predetermined time period (CreXh_Pred); (3) in step c1 or c2, calculating a predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) further based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2); At least one selected from the group consisting of: method.

2. 2. The method of claim 1, wherein the predetermined time period is 12 to 48 hours.

3. 2. The method of claim 1, wherein the urine is a single urine collection.

4. The method according to claim 1 , wherein the attribute information used in step b1 is height, weight, and age.

5. The coefficient in step c1 is a value determined by regression analysis that predicts the predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), and a predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a subject population, and the total sodium excretion amount within a predetermined time period (Na_Xh) that has been previously measured for the subject population, or the coefficient in step c2 is a value determined by regression analysis that predicts a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), a potassium concentration (KSpot), a BMI, and an age that have been measured and calculated in advance in a subject population, and a total sodium excretion within a predetermined time period (Na_Xh) that has been measured in advance in the subject population; The method of claim 1.

6. The method of claim 5, comprising (1) above, and wherein the variables include the subject's gender and / or the urine volume.

7. 6. The method of claim 5, including (3), wherein the variables include the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2).

8. The method according to any one of claims 5 to 7, wherein the coefficients are calculated for each of the variables.

9. If the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated in step c1 or c2 is within a range defined by a predetermined threshold, a step d1 of calculating again in step c1 the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using an optimization coefficient determined by regression analysis for predicting the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the subject population; or a step d2 of calculating again in step c2 the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using optimization coefficients determined by regression analysis for predicting the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), creatinine concentration (CreSpot), potassium concentration (KSpot), BMI, and age previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) previously measured for the subject population; The method of claim 1 , comprising:

10. The method of claim 1, comprising at least two selected from the group consisting of (1) to (3).

11. An apparatus for predicting a total sodium excretion amount (Na_Xh) of a subject within a predetermined time, comprising: a urine information acquiring unit a11 that acquires information about the urine, including a measured value of a sodium concentration (NaSpot) and a measured value of a creatinine concentration (CreSpot) in the urine collected from the subject; an attribute information acquiring unit a12 for acquiring attribute information of the subject; a total creatinine excretion amount calculation unit b1 that calculates a predicted total creatinine excretion amount (CreXh_Pred) of the subject within a predetermined time based on the attribute information of the subject; a total sodium excretion calculation unit c1 that calculates the predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); or a urine information acquiring unit a21 that acquires information about the urine collected from the subject, including a measured value of a sodium concentration (NaSpot), a measured value of a creatinine concentration (CreSpot), and a measured value of a potassium concentration (KSpot); an attribute information acquiring unit a12 for acquiring attribute information of the subject; a total sodium excretion calculation unit c2 that calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using a coefficient based on the sodium concentration (NaSpot), the creatinine concentration (CreSpot), the potassium concentration (KSpot), the BMI, and the age of the subject; The total sodium excretion calculation unit c1 or c2 (1) calculating a predicted total sodium excretion amount (Na_Xh_Pred) within a predetermined time period based on the sex of the subject or the sex of the subject and the amount of urine in the total sodium excretion calculation unit c1 or c2; (2) the total sodium excretion calculation unit c1 calculates a predicted total sodium excretion amount within a predetermined time period (Na_Xh_Pred) using coefficients determined for the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted total creatinine excretion amount within a predetermined time period (CreXh_Pred); (3) In the total sodium excretion calculation unit c1 or c2, a predicted value of total sodium excretion within a predetermined time (Na_Xh_Pred) is calculated based on the time from the last salt intake time before the urine collection to the time of the urine collection (TAM1) and the time from the second-to-last salt intake time before the urine collection to the time of the urine collection (TAM2). Perform at least one selected from the group consisting of: Device.

12. The coefficient in the total sodium excretion calculation unit c1 is a value determined by regression analysis that predicts the predicted total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), and a predicted total creatinine excretion within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a subject population, and the total sodium excretion within a predetermined time period (Na_Xh) that has been previously measured for the subject population, or the coefficient in the total sodium excretion calculation unit c2 is a value determined by regression analysis that predicts a predicted value of total sodium excretion within a predetermined time period (Na_Xh_Pred) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), a potassium concentration (KSpot), a BMI, and an age that have been measured and calculated in advance in a subject population, and a total sodium excretion within a predetermined time period (Na_Xh) that has been measured in advance in the subject population; 12. The apparatus of claim 11.

13. The apparatus according to claim 12, wherein the total sodium excretion calculation unit c1 or c2 performs (1), and the variables include the sex of the subject or the sex of the subject and the amount of urine.

14. The device of claim 12, wherein the total sodium excretion calculation unit c1 or c2 performs (3), and the variables include the time from the last sodium chloride intake time before the urine collection to the urine collection time (TAM1) and the time from the second-to-last salt intake time before the urine collection to the urine collection time (TAM2).

15. When the predicted total sodium excretion amount within a predetermined time (Na_Xh_Pred) calculated by the total sodium excretion amount calculation unit c1 or c2 is within a range determined by a predetermined threshold, the total sodium excretion calculation unit c1 recalculates the predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) using an optimization coefficient determined by regression analysis that predicts the total sodium excretion within a predetermined time period (Na_Xh) based on variables including the sodium concentration (NaSpot), the creatinine concentration (CreSpot), and the predicted value of the total creatinine excretion within a predetermined time period (CreXh_Pred) that have been previously measured and calculated for a population of subjects whose predicted value of the total sodium excretion within a predetermined time period (Na_Xh_Pred) is within the above range, and the total sodium excretion within a predetermined time period (Na_Xh) that has been previously measured for the subject population; or the total sodium excretion calculation unit c2 again calculates the predicted value of the total sodium excretion within a predetermined time (Na_Xh_Pred) using optimization coefficients determined by regression analysis that predicts the total sodium excretion within a predetermined time (Na_Xh) based on variables including a sodium concentration (NaSpot), a creatinine concentration (CreSpot), a potassium concentration (KSpot), a BMI, and age that have been measured and calculated in advance for a population of subjects whose predicted value of the total sodium excretion within a predetermined time (Na_Xh_Pred) is within the range, and the total sodium excretion within a predetermined time (Na_Xh) that has been measured in advance for the subject population; 12. The apparatus of claim 11.

16. A program for causing a computer to execute each unit of the device according to any one of claims 11 to 15.

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