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CN113488173A - Method and device for determining physiological age of human immune system - Google Patents

Method and device for determining physiological age of human immune system Download PDF

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CN113488173A
CN113488173A CN202110880789.4A CN202110880789A CN113488173A CN 113488173 A CN113488173 A CN 113488173A CN 202110880789 A CN202110880789 A CN 202110880789A CN 113488173 A CN113488173 A CN 113488173A
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CN113488173B (en
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魏伟
许超
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Guangzhou Ruiplatinum Health Technology Co Ltd
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Abstract

The application discloses a method and a device for determining the physiological age of the immune system of a human body, wherein the method comprises the steps of obtaining the detection data of the immune system of a current detected person, wherein the detection data of the immune system comprises the detection data of one or more detected indexes related to the sex of the detected person; acquiring the index weight of the one or more detected indexes; respectively comparing the detection data of each detected index with preset reference data of each detected index, and determining the physiological age of each detected index according to the comparison result of each detected index; and determining the final physiological age of the immune system of the examinee according to the physiological age of each detected index and the corresponding index weight. Therefore, the physiological age of the immune system of the human body can be detected in real time, the aging degree of the organism can be accurately and quantitatively evaluated, the anti-aging effect of various anti-aging intervention measures can be evaluated, and a personalized and accurate anti-aging scheme based on aging monitoring is further established.

Description

Method and device for determining physiological age of human immune system
Technical Field
The embodiment of the application relates to the field of medical equipment, in particular to a method and a device for determining the physiological age of a human immune system.
Background
With the increasing prominence of aging problems, objective assessment of aging conditions of the body is also more and more important. The physiological age can be measured by measuring the body function state through some biochemical markers, and the objective and accurate detection of the physiological age of the human immune system plays an important role in delaying senility, preventing diseases or treating diseases.
At present, there are a number of existing methods for measuring aging and evaluating the physiological age of the immune system of a human body, but most detection methods still stay in conventional indexes such as the number and proportion of single immune cell subsets, and the reflected result is mostly in a numerical range, or the numerical range of the body indexes needs to be passed through in the measurement and calculation process, so that the real physiological age of the immune system and the current state of aging of the body cannot be accurately quantified.
Disclosure of Invention
The application provides a method and a device for determining the physiological age of a human immune system, which are used for overcoming the problem that the physiological age of the immune system reflected in the prior art depends on the numerical range of body indexes, and the real physiological age and the aging current situation of the immune system of a body cannot be accurately quantified.
In a first aspect, the present embodiments provide a method for determining a physiological age of a human immune system, the method including:
obtaining immune system detection data of a current subject, the immune system detection data comprising detection data of one or more detected indicators related to the gender of the subject;
acquiring the index weight of the one or more detected indexes;
respectively comparing the detection data of each detected index with preset reference data of each detected index, and determining the physiological age of each detected index according to the comparison result of each detected index;
and determining the final physiological age of the immune system of the examinee according to the physiological age of each detected index and the corresponding index weight.
In a second aspect, the present application provides a device for determining a physiological age of a human immune system, the device including:
the immune system detection data acquisition module is used for acquiring immune system detection data of a current examinee, wherein the immune system detection data comprises detection data of one or more detected indexes related to the sex of the examinee;
the index weight acquisition module is used for acquiring the index weight of the one or more detected indexes;
the detected index comparison module is used for respectively comparing the detection data of each detected index with the preset reference data of each detected index;
the physiological age determining module of each index is used for determining the physiological age of each detected index according to the comparison result of each detected index;
and the immune system physiological age determining module is used for determining the final immune system physiological age of the detected person according to the physiological age of each detected index and the corresponding index weight.
In a third aspect, an embodiment of the present application further provides an apparatus for determining a physiological age of a human immune system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method when executing the program.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method described above.
The application has the following beneficial effects:
the method comprises the steps of obtaining immune system detection data of a detected person, wherein the immune system detection data comprises detection data of one or more detected indexes related to the sex of the detected person, obtaining index weights of all detected indexes, comparing the monitoring data of all detected indexes with preset reference data of all detected indexes, calculating and determining the physiological age of all detected indexes according to a comparison result, calculating according to the physiological age of all detected indexes and the corresponding index weights, determining the final physiological age of the immune system of the detected person, detecting the physiological age of the immune system of a human body in real time, accurately and quantitatively evaluating the aging degree of the body, evaluating the anti-aging effect of various anti-aging intervention measures, and further establishing a personalized and accurate anti-aging scheme based on aging monitoring.
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FIG. 1 is a flowchart of an embodiment of a method for determining a physiological age of a human immune system according to an embodiment of the present disclosure;
FIG. 2 is a graph illustrating an analysis of correlation between male subject indicators and age according to an embodiment of the present disclosure;
FIG. 3 is a graph of an age-related analysis of female subject indicators according to an embodiment of the present disclosure;
fig. 4 is a block diagram of an embodiment of an apparatus for determining a physiological age of a human immune system according to a second embodiment of the present application;
fig. 5 is a schematic structural diagram of an apparatus for determining a physiological age of a human immune system according to a third embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of an embodiment of a method for determining a physiological age of a human immune system according to an embodiment of the present disclosure, in this embodiment, a linear regression curve is formed for an age based on related indexes of the immune system in a routine physical examination item through multiple linear regression analysis, then an index highly related to the age is selected as a detected index through the correlation analysis, the linear regression analysis further outputs a correlation coefficient of each detected index, and finally, the physiological age of the human immune system is calculated according to a calculation logic of the physiological age.
As shown in fig. 1, the present embodiment may include the following steps:
step 110, obtaining immune system detection data of a current subject, wherein the immune system detection data comprises detection data of one or more detected indexes related to the sex of the subject.
For example, the immune system detection data of the examinee can be from conventional physical examination items, and also can be from a human body whole body system scanner which can collect hundreds of parameters for evaluating the human body homeostasis, carry out omnibearing and multi-angle stereotactic scanning on the functions of various systems, tissues, organs and parts of the human body and comprehensively and systematically analyze the human homeostasis. The subject's immune system test data may include blood routine, blood biochemistry, and the like.
In one embodiment, the one or more detected indexes are determined by performing multiple linear regression analysis based on the relevant immune indexes according to a plurality of groups of ages and detection data of a plurality of conventional indexes of different sexes to obtain physiological index coefficients of the conventional indexes, and selecting physiological indexes related to the corresponding ages and sexes as the detected indexes according to the physiological index coefficients of the conventional indexes.
During implementation, the volunteers with different ages and the data tables or databases of the corresponding conventional physiological detection data of the volunteers are established, the conventional physiological detection indexes are subjected to a multiple linear regression curve for the ages based on the related immune indexes, and then the indexes highly related to the ages are screened as the detected indexes through correlation analysis.
In the multiple linear regression analysis, the larger the absolute value of the correlation coefficient is, the stronger the correlation is, the closer the correlation coefficient is to 1 or-1, the stronger the correlation is, the closer the correlation coefficient is to 0, and the weaker the correlation is. To facilitate use and understanding, negative numbers are avoided, and the square of the correlation coefficient (R) is typically used2) Here, we refer to the square of the correlation coefficient of each index with age as an index coefficient.
It should be noted that, because the change of some cells and parameters related to the immune system in the aging process of men and women is not completely consistent, for example, studies show that although the total number of leukocytes in men and women is reduced in the aging process, the lymphocyte reduction rate of T cells and B cells in the leukocytes of men is obviously faster than that of women. Therefore, when the multiple linear regression analysis is performed on the ages by using each conventional physiological detection index based on the related immune indexes, the data of the female and the male are required to be analyzed separately so that the finally obtained physiological ages of the immune system are more accurate, and the immune system indexes respectively conforming to the high correlation between the ages of the male and the female are screened out, so that the male detected index and the female detected index are obtained.
In another embodiment, fig. 2 and 3 are graphs of correlation analysis of male and female test indicators with age, respectively, wherein the male test indicators include: serum albumin, total protein, albumin/globulin ratio, peripheral blood NK cell ratio, red blood cell count, hemoglobin concentration, red blood cell hematocrit, thymus function, spleen function, immune system risk; female test indices included: serum albumin, total protein, globulin, peripheral blood NK cell fraction, red blood cell count, hemoglobin concentration, RDW-SD (red blood cell distribution width-SD), thymus function, spleen function, immune system risk.
Referring to fig. 2, the male subject indexes specifically included in this embodiment are the results of linear regression analysis, the square of the correlation coefficient R is 0.1 to 0.33, and the significance test F value is between 4.06E-06 to 2.03E-02, indicating that the human immune system indexes such as serum Albumin (ALB), Total Protein (TP), albumin/globulin ratio, peripheral blood NK cell ratio, red blood cell count (RBC), hemoglobin concentration (HGB), Hematocrit (HCT), thymus function, spleen function, immune system risk, etc. have a significant linear relationship with age, and these indexes can be used to establish a human immune system physiological age analysis model to predict the human immune system physiological age and aging degree.
In addition, in the step of the multiple linear regression analysis, the detected index can be screened in an off-line manner, for example, by using a regression analysis module carried in Excel, the specific operation is as follows: selecting a 'tool' -data analysis '-regression', taking an age value as a dependent variable Y value input region and a corresponding conventional physical examination index value as an independent variable X value input region, performing multiple linear regression analysis, outputting a result, and obtaining a multiple linear regression age analysis model and significance statistics of the model based on each relevant immune index, and regression coefficients and significance statistics of independent variable X values of each relevant index in the linear model.
And 120, acquiring the index weight of the one or more detected indexes.
In this step, since the correlation between different detected indexes and age is different, it is easy to understand that the more strongly correlated index to age among the detected indexes should be considered more heavily when calculating the physiological age of the immune system. Therefore, it is necessary to assign weights to different detected indexes, and the indexes having stronger correlation have larger weights.
In one embodiment, step 120 may further include the steps of:
and step 120-1, acquiring index coefficients corresponding to all detected indexes.
In this step, the index coefficient corresponding to each detected index, that is, the square of the correlation coefficient between each detected index and the age, may be directly obtained from the output result of the multiple linear regression analysis, for example, refer to a correlation coefficient column in fig. 2 and fig. 3, which is a specific value directly output from the multiple linear regression analysis.
And step 120-2, calculating the sum of all index coefficients.
In this step, the obtained index coefficients of each detected index are added to obtain the sum S of all the index coefficients. Assuming that there are 10 detected indexes, the index coefficients of the 10 detected indexes are M1,M2……M10Then S is equal to M1+M2+……+M10. Illustratively, referring to fig. 2, there are 10 detected indexes, each of which has its corresponding correlation coefficient R2(table correlation coefficient one column of values is the square of the correlation coefficient), the index coefficient sum of the examined index of fig. 2:
S=0.33+0.12+0.13+0.15+0.15+0.22+0.23+0.16+0.19+0.15=1.83
and 120-3, calculating the ratio of the index coefficient of each detected index to the sum to obtain the index weight of each detected index.
In this step, since the index coefficient represents the close correlation degree between the detected index and the age, the weight of each detected index can be directly determined according to the percentage of the index coefficient of each detected index in the total index coefficient sum S. For example, S ═ M1+M2+……+M10Index coefficient of M1The calculation of the weight ratio corresponding to the detected index is as follows:
Figure BDA0003192211270000071
exemplarily, referring to fig. 2, S in fig. 2 is 1.83, the index coefficient of spleen function of number 9 is 0.19, and the weight of this index of spleen function is:
0.19÷1.83×100%=10.38%
in another embodiment, since the multiple linear regression equation may be performed offline when determining the detected indicators, and all the parameters used for calculating the weights of the detected indicators are derived from the results output by the linear regression analysis, the step of obtaining the weights of the detected indicators may also be performed offline, and then the weights are preset corresponding to the determined detected indicators, for example, refer to the weight column in fig. 2 and fig. 3, which are weight values obtained by directly calculating the correlation coefficients output by the linear regression.
And step 130, comparing the detection data of each detected index with preset reference data of each detected index, and determining the physiological age of each detected index according to the comparison result of each detected index.
In this step, the preset reference data of each detected index may be set according to clinical experience values, or may be set according to an average value of healthy people of a certain age group. Through big data analysis, the deviation rate of the detected data of the detected person and the reference data is calculated by taking the detected value of a healthy young population of 20 years old as the reference data, the deviation rate is gradually increased along with the increase of the age, the calculation logic of the physiological age of the immune system can be obtained based on the deviation rate, the deviation age is determined according to the deviation rate of the deviation rate and the reference data, then the physiological age of each detected index is calculated, and the whole physiological age of the immune system is determined according to the physiological age of each detected index.
It should be noted that the detected indexes are divided into male detected indexes and female detected indexes, and correspondingly, the preset reference data is also different corresponding to different physiological characteristics of the male and the female, that is, the preset reference data of each detected index is divided into male preset reference data and female preset reference data.
In one embodiment, the preset reference data of each detected index is set according to the detected data of healthy people of a specified age, and the step 130 of comparing the detected data of each detected index with the preset reference data of each detected index further includes the following steps:
and step 130-1, determining the difference value between the detection data of each detected index and the preset reference data of each detected index.
In this step, the detection data of each detected index is subtracted from the preset reference data of each detected index to obtain a difference value, that is, the difference value of each detected index is: (detection data of each detected index-preset reference data of each detected index).
And step 130-2, calculating the percentage of each difference value in the preset reference data of each detected index according to each difference value to obtain the deviation rate of each detected index.
In this step, the deviation ratio is the percentage of the difference between the actual data and the target data to the target data, and the deviation ratio can be further divided into a positive deviation ratio and a negative deviation ratio. If the actual data is larger than the target data, the actual data is positive deviation; if the actual data is smaller than the target data, the deviation is negative. When the actual data is equal to the target data, the deviation ratio is zero. In one implementation, the following formula may be used to calculate the deviation rate a of each detected index:
a ═ x 100% (detection data of each detected index-preset reference data of each detected index) ÷ preset reference data of each detected index) × 100%
And step 130-3, obtaining the deviating age of each detected index according to the product of the deviation rate of each detected index and the specified age value, wherein the deviating age is the age value deviating on the basis of the specified age as the comparison result.
In this step, the deviating age is a deviating age value based on the designated age, and the deviating age b can be obtained by multiplying the deviating rate a by the designated age as a standard. In one implementation, the following formula may be used to calculate the offset age b:
b is given age a
For example, if the specified age is 20 years, and the deviation rate of a certain detected index is 10% for 20 years, the deviation age of the detected index is: the age of 20 x 10% is 2, that is, the comparison result of the monitored data of the detected index and the preset reference data is 2.
In one embodiment, determining the physiological age of each detected indicator in step 130 according to the comparison result of each detected indicator may further include:
and obtaining the physiological age of each detected index according to the sum of the deviating age and the specified age of each detected index.
In the step, the deviation age b of each detected index is directly added with the specified age, and the physiological age of each detected index can be obtained. In one implementation, the physiological age of each index may be calculated using the following formula:
the physiological age of each index is the deviation age b + the designated age of each detected index
For example, if the age of a subject is 2 years apart and the specified age is 20 years, the physiological age of the subject is 20 + 2-22 years.
Step 140, determining the final physiological age of the immune system of the examinee according to the physiological age of each detected index and the corresponding index weight.
It will be appreciated that for a fully healthy person, the physiological age of the immune system should remain at or below the time age, indicating that the subject is in a poor physical condition if the subject's physiological age of the immune system is greater than the time age. The aging state of the body is judged according to the calculated physiological age of the immune system, and the time age is compared, so that the doctor can know the whole body state of the body conveniently to diagnose, treat and prevent diseases.
In one embodiment, step 140 further comprises:
and carrying out weighted summation on the physiological age of each detected index and the corresponding index weight to obtain the final immune system physiological age of the detected person.
In this step, the index weights of the detected indexes obtained and the calculated physiological ages of the detected indexes are used to calculate the weighted sum of the physiological ages of the detected indexes, and the final result is the physiological age of the immune system of the examinee. Assuming that there are 3 examined indexes, the weights corresponding to the three examined indexes are N1,N2,N3Corresponding to physiological age of b1,b2,b3Then, the calculation formula of the physiological age of the immune system of the subject is as follows:
physiological age of immune system b1*N1+b2*N2+b3*N3
In another implementation, the method for determining the physiological age of the immune system can be applied to other aspects, for example, the method can be used for determining the physiological age of other systems of the human body, when multiple linear regression analysis is performed, a multiple linear regression age analysis model based on the index of a certain system is established, and finally, the correlation coefficient and the significance statistics based on the related index of the system are obtained. By emphasizing the index type on a certain system index when establishing the multiple linear regression analysis, the estimated age value for objectively quantifying a certain system can be obtained.
In this embodiment, by obtaining immune system detection data of a subject, the immune system detection data includes detection data of one or more detected indexes related to the sex of the subject, and obtaining index weights of the detected indexes, comparing the monitoring data of the detected indexes with preset reference data of the detected indexes, calculating and determining the physiological age of the detected indexes according to the comparison result, calculating according to the physiological age of the detected indexes and the corresponding index weights, and determining the final physiological age of the immune system of the subject, the real-time detection of the physiological age of the immune system of the human body is realized, the aging degree of the body is accurately and quantitatively evaluated, and the method can be used for evaluating the anti-aging effect of various anti-aging intervention measures, and further establishing a personalized and accurate anti-aging scheme based on aging monitoring.
Example two
Fig. 4 is a block diagram of a structure of an embodiment of an apparatus for determining a physiological age of a human immune system according to a second embodiment of the present application, where the apparatus includes:
an immune system detection data acquisition module 210, configured to acquire immune system detection data of a current subject, where the immune system detection data includes detection data of one or more detected indicators related to a gender of the subject;
an index weight obtaining module 220, configured to obtain an index weight of the one or more detected indexes;
a detected index comparing module 230, configured to compare the detection data of each detected index with preset reference data of each detected index;
the physiological age determining module 240 for each index is configured to determine the physiological age of each detected index according to the comparison result of each detected index;
and the immune system physiological age determining module 250 is used for determining the final immune system physiological age of the detected person according to the physiological age of each detected index and the corresponding index weight.
In one embodiment, the one or more detected indexes are determined by performing multiple linear regression analysis based on the relevant immune indexes according to a plurality of groups of ages and detection data of a plurality of conventional indexes of different sexes to obtain physiological index coefficients of the conventional indexes, and selecting physiological indexes related to the corresponding ages and sexes as the detected indexes according to the physiological index coefficients of the conventional indexes.
In one embodiment, the index weight obtaining module 220 further includes the following sub-modules:
the index coefficient acquisition submodule is used for acquiring index coefficients corresponding to all detected indexes;
the index coefficient sum calculating module is used for calculating the sum of all index coefficients;
and the index weight determining submodule is used for calculating the ratio of the index coefficient of each detected index to the sum to obtain the index weight of each detected index.
In one embodiment, the preset reference data of each detected index is set according to the detection data of healthy people of a specified age, and the detected index comparing module 230 further includes the following sub-modules:
the difference value determining submodule is used for determining the difference value between the detection data of each detected index and the preset reference data of each detected index;
the deviation rate determining submodule is used for calculating the percentage of each difference value in the preset reference data of each detected index according to each difference value to obtain the deviation rate of each detected index;
and the deviation age determining submodule is used for obtaining the deviation age of each detected index according to the product of the deviation rate of each detected index and the specified age value, and the deviation age is the age value which deviates on the basis of the specified age as a comparison result.
In one embodiment, the physiological age determining module 240 is specifically configured to:
and obtaining the physiological age of each detected index according to the sum of the deviating age and the specified age of each detected index.
In one embodiment, the immune system physiological age determination module 250 is specifically configured to:
and carrying out weighted summation on the physiological age of each detected index and the corresponding index weight to obtain the final immune system physiological age of the detected person.
In another embodiment, the first and second electrodes are, as mentioned,
the male test indexes comprise: serum albumin, total protein, albumin/globulin ratio, peripheral blood NK cell ratio, red blood cell count, hemoglobin concentration, red blood cell hematocrit, thymus function, spleen function, immune system risk;
the female test indicators include: serum albumin, total protein, globulin, peripheral blood NK cell fraction, red blood cell count, hemoglobin concentration, RDW-SD (red blood cell distribution width-SD), thymus function, spleen function, immune system risk.
It should be noted that the apparatus for determining the physiological age of the human immune system provided in the embodiment of the present application can perform the method for determining the physiological age of the human immune system provided in the embodiment of the present application, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE III
Fig. 5 is a schematic structural diagram of an apparatus for determining a physiological age of the immune system of a human body according to a third embodiment of the present application, as shown in fig. 5, the apparatus for determining a physiological age of the immune system of a human body includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of the processors 310 in the device for confirming the physiological age of the human immune system can be one or more, and one processor 310 is taken as an example in fig. 5; the processor 310, the memory 320, the input device 330 and the output device 340 in the apparatus for confirming the physiological age of the human immune system may be connected by a bus or other means, and fig. 5 illustrates the connection by the bus.
Memory 320 is provided as a computer-readable storage medium that can be used to store software programs, computer-executable programs, and modules, such as program instruction modules corresponding to method embodiments in the embodiments of the present application. The processor 310 executes various functional applications of the device for confirming the physiological age of the human immune system and data processing by executing software programs, instructions and modules stored in the memory 320, so as to realize the method.
The memory 320 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 320 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 320 may further include memory remotely located from the processor 310, which may be connected to a confirmation device of the physiological age of the human immune system via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 330 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function controls of the apparatus confirming the physiological age of the human immune system. The output device 340 may include a display device such as a display screen.
Example four
A storage medium containing computer-executable instructions for performing the method in the method embodiments when executed by a computer processor is also provided.
From the above description of the embodiments, it is obvious for those skilled in the art that the present application can be implemented by software and necessary general hardware, and certainly can be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods described in the embodiments of the present application.
It should be noted that, in the embodiment of the foregoing apparatus, the modules and modules included in the apparatus are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional modules are only used for distinguishing one functional module from another, and are not used for limiting the protection scope of the application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims (10)

1. A method for determining the physiological age of the immune system of a human, said method comprising:
obtaining immune system detection data of a current subject, the immune system detection data comprising detection data of one or more detected indicators related to the gender of the subject;
acquiring the index weight of the one or more detected indexes;
respectively comparing the detection data of each detected index with preset reference data of each detected index, and determining the physiological age of each detected index according to the comparison result of each detected index;
and determining the final physiological age of the immune system of the examinee according to the physiological age of each detected index and the corresponding index weight.
2. The method according to claim 1, wherein the one or more detected indexes are determined by performing multiple linear regression analysis based on the relevant immune indexes according to a plurality of groups of ages and detection data of a plurality of conventional indexes thereof for different sexes to obtain physiological index coefficients of the conventional indexes, and selecting physiological indexes related to the corresponding ages and sexes as the detected indexes according to the physiological index coefficients of the conventional indexes.
3. The method of claim 1 or 2, wherein obtaining the metric weight of the one or more detected metrics comprises:
acquiring index coefficients corresponding to all detected indexes;
calculating the sum of each index coefficient;
and calculating the ratio of the index coefficient of each detected index to the sum to obtain the index weight of each detected index.
4. The method according to claim 3, wherein the preset reference data of each detected index is set according to the detection data of healthy people of a specified age;
the comparing the detection data of each detected index with the preset reference data of each detected index respectively comprises the following steps:
determining the difference value between the detection data of each detected index and the preset reference data of each detected index;
calculating the percentage of each difference value in the preset reference data of each detected index according to each difference value to obtain the deviation rate of each detected index;
and obtaining the deviating age of each detected index according to the product of the deviating rate of each detected index and the specified age value, wherein the deviating age is the age value deviating on the basis of the specified age as a comparison result.
5. The method of claim 4, wherein determining the physiological age of each of the detected indicators according to the comparison result of each of the detected indicators comprises:
and obtaining the physiological age of each detected index according to the sum of the deviating age and the specified age of each detected index.
6. The method of claim 5, wherein determining the final physiological age of the subject's immune system based on the physiological ages of the various indicators tested and the corresponding indicator weights comprises:
and carrying out weighted summation on the physiological age of each detected index and the corresponding index weight to obtain the final immune system physiological age of the detected person.
7. The method of claim 2,
the male test indexes comprise: serum albumin, total protein, albumin/globulin ratio, peripheral blood NK cell ratio, red blood cell count, hemoglobin concentration, red blood cell hematocrit, thymus function, spleen function, immune system risk;
the female test indicators include: serum albumin, total protein, globulin, peripheral blood NK cell fraction, red blood cell count, hemoglobin concentration, RDW-SD (red blood cell distribution width-SD), thymus function, spleen function, immune system risk.
8. An apparatus for determining the physiological age of the immune system of a human, said apparatus comprising:
the immune system detection data acquisition module is used for acquiring immune system detection data of a current examinee, wherein the immune system detection data comprises detection data of one or more detected indexes related to the sex of the examinee;
the index weight acquisition module is used for acquiring the index weight of the one or more detected indexes;
the detected index comparison module is used for respectively comparing the detection data of each detected index with the preset reference data of each detected index;
the physiological age determining module of each index is used for determining the physiological age of each detected index according to the comparison result of each detected index;
and the immune system physiological age determining module is used for determining the final immune system physiological age of the detected person according to the physiological age of each detected index and the corresponding index weight.
9. An apparatus for determining the physiological age of the immune system of a human being, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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