Glycosylated hemoglobin chromatographic detection method for pregnancy risk assessment

Abstract

The invention relates to the technical field of glycosylated hemoglobin detection, in particular to a glycosylated hemoglobin chromatographic detection method for pregnancy risk assessment, which comprises the following steps: acquiring serum ferritin concentration, glycosylated hemoglobin concentration and C-reactive protein concentration of a pregnant woman; according to the distribution condition of the serum ferritin concentration and the C-reactive protein concentration of each pregnant woman and the body mass index of each pregnant woman, analyzing the reference value weight of each pregnant woman, and further obtaining a data correction coefficient; obtaining a serum ferritin reference value according to the serum ferritin concentration, the C-reactive protein concentration and the glycosylated hemoglobin concentration of the pregnant woman; and adjusting the glycosylated hemoglobin concentration of the target pregnant woman according to the data correction coefficient, the serum ferritin reference value and the serum ferritin concentration of the target pregnant woman to obtain a glycosylated hemoglobin detection result of the target pregnant woman. According to the invention, interference caused by iron deficiency or anemia can be eliminated, so that the detection result of glycosylated hemoglobin is more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of glycated hemoglobin detection, and particularly relates to a glycated hemoglobin chromatographic detection method for pregnancy risk assessment. BACKGROUND

[0002] Gestational diabetes mellitus can increase the risk of complications for both the pregnant woman and the fetus, including macrosomia, preterm birth, and maternal hypertension. Glycated hemoglobin reflects the average level of blood glucose in the pregnant woman over the past 2-3 months. By detecting glycated hemoglobin through chromatographic technology, it can quickly and accurately determine whether the pregnant woman has potential diabetes risk, so as to take preventive and intervention measures. Compared with traditional fasting blood glucose detection, it can more comprehensively reflect the blood glucose control of the pregnant woman, has high clinical value, helps pregnancy management, reduces adverse outcomes caused by gestational diabetes mellitus, and protects the health of mother and infant.

[0003] The glycated hemoglobin chromatographic detection method generally used for pregnancy risk assessment is as follows: first, collect fasting venous blood samples and store them in anticoagulant tubes; then, perform hemolysis agent treatment on the blood samples, inject the treated samples into a high-performance liquid chromatography system, separate HbA1C, HbA0 and other components according to the residence time difference of hemoglobin molecules with different degrees of glycation in the mobile phase; further, integrate the peak areas of each component in the detection chromatogram, calculate the percentage concentration of glycated hemoglobin (HbA1c), and calibrate using the internal standard method or standard curve method; the doctor determines whether the detection result is outside the normal range according to the reference interval standard of glycated hemoglobin concentration of pregnant women in early, middle and late pregnancy and clinical experience, and prompts the pregnant woman to have pregnancy risks such as gestational diabetes mellitus, macrosomia, and placental dysfunction.

[0004] However, in the glycated hemoglobin (HbA1c) chromatographic detection method for pregnancy risk assessment, iron deficiency often occurs in pregnant women, which can cause changes in the structure of hemoglobin, thereby prolonging the life span of red blood cells (due to a decrease in newly formed red blood cells), and causing false elevation of HbA1c. This phenomenon is common in pregnant women, especially in the case of iron deficiency anemia, which can affect the accuracy of HbA1c, resulting in low accuracy of glycated hemoglobin chromatographic detection results. SUMMARY

[0005] In order to solve the technical problem of low accuracy of glycated hemoglobin chromatographic detection results due to iron deficiency in pregnant women in practice, the purpose of the present application is to provide a glycated hemoglobin chromatographic detection method for pregnancy risk assessment, and the technical solution adopted is as follows: Obtain the serum ferritin concentration, glycated hemoglobin concentration and C-reactive protein concentration of each pregnant woman, wherein the pregnant women include a target pregnant woman and reference pregnant women under the same conditions as the target pregnant woman; According to the distribution of serum ferritin concentration and C-reactive protein concentration of each pregnant woman and the body mass index of each pregnant woman, the reference value weight of each pregnant woman is analyzed, and the data correction coefficient is obtained by combining the difference in serum ferritin concentration and the difference in glycosylated hemoglobin concentration between different pregnant women. According to the distribution of serum ferritin concentration and C-reactive protein concentration of the target pregnant woman and the glycosylated hemoglobin concentration of each reference pregnant woman, the serum ferritin reference value of the reference pregnant woman to the target pregnant woman is obtained. According to the data correction coefficient, the serum ferritin reference value and the serum ferritin concentration of the target pregnant woman, the glycosylated hemoglobin concentration of the target pregnant woman is adjusted to obtain the glycosylated hemoglobin detection result of the target pregnant woman.

[0006] Preferably, according to the distribution of serum ferritin concentration and C-reactive protein concentration of each pregnant woman and the body mass index of each pregnant woman, the reference value weight of each pregnant woman is analyzed, and the data correction coefficient is obtained by combining the difference in serum ferritin concentration and the difference in glycosylated hemoglobin concentration between different pregnant women. For any pregnant woman, the serum ferritin concentration and C-reactive protein concentration are standardized respectively to obtain serum ferritin data and C-reactive protein data. The product of the negative correlation coefficient of serum ferritin data and the negative correlation coefficient of C-reactive protein data is taken as the deficiency characteristic factor of the pregnant woman. The reference value weight of the pregnant woman is obtained according to the deficiency characteristic factor of the pregnant woman and the body mass index of the pregnant woman.

[0007] Preferably, the reference value weight of the pregnant woman is obtained according to the deficiency characteristic factor of the pregnant woman and the body mass index of the pregnant woman, and specifically includes: Based on the height and weight of the pregnant woman, the body mass index of the pregnant woman is determined; based on the normalized result of the difference between the body mass index of the pregnant woman and the preset normal body mass index and the deficiency characteristic factor, the reference value weight of the pregnant woman is determined.

[0008] Preferably, according to the distribution of serum ferritin concentration and C-reactive protein concentration of each pregnant woman and the body mass index of each pregnant woman, the reference value weight of each pregnant woman is analyzed, and the data correction coefficient is obtained by combining the difference in serum ferritin concentration and the difference in glycosylated hemoglobin concentration between different pregnant women. The difference in serum ferritin concentration and the difference in glycosylated hemoglobin concentration between each two pregnant women are weighted by using the reference value weight of each two pregnant women to obtain the correlation contribution degree between each two pregnant women. The cumulative sum of the correlation contribution degrees corresponding to all pregnant women is taken as the data correction coefficient.

[0009] Preferably, the difference between the serum ferritin concentration and the difference between the glycated hemoglobin concentration of each two pregnant women are weighted by the weight of the reference value of each two pregnant women to obtain the correlation contribution degree between each two pregnant women, specifically comprising: For any two pregnant women, the proportion of the cumulative sum of the reference value weight of the two pregnant women is taken as the weight value; the absolute value of the difference between the glycated hemoglobin concentrations of the two pregnant women is taken as the first difference coefficient; the absolute value of the difference between the reciprocals of the serum ferritin concentrations of the two pregnant women is taken as the second difference coefficient; The ratio of the first difference coefficient and the second difference coefficient is weighted by the weight value to obtain the correlation contribution degree between the two pregnant women.

[0010] Preferably, the serum ferritin reference value of the reference pregnant woman to the target pregnant woman is obtained according to the distribution of the serum ferritin concentration and the C-reactive protein concentration of the target pregnant woman and the glycated hemoglobin concentration of each reference pregnant woman, specifically comprising: The glycated hemoglobin concentration of each pregnant woman is standardized to obtain the glycated hemoglobin data of each pregnant woman; The true data characteristic value of each reference pregnant woman to the target pregnant woman is obtained according to the deficiency characteristic factor of the target pregnant woman and the glycated hemoglobin data of each reference pregnant woman; The serum ferritin reference value of the reference pregnant woman to the target pregnant woman is obtained according to the corresponding true data characteristic value of each reference pregnant woman and the serum ferritin concentration of the same reference pregnant woman.

[0011] Preferably, the true data characteristic value of each reference pregnant woman to the target pregnant woman is obtained according to the deficiency characteristic factor of the target pregnant woman and the glycated hemoglobin data of each reference pregnant woman, specifically comprising: The product of the negative correlation coefficient of the deficiency characteristic factor of the target pregnant woman and the negative correlation coefficient of the glycated hemoglobin data of each reference pregnant woman is taken as the true data characteristic value of each reference pregnant woman to the target pregnant woman.

[0012] Preferably, the serum ferritin reference value of the reference pregnant woman to the target pregnant woman is obtained according to the corresponding true data characteristic value of each reference pregnant woman and the serum ferritin concentration of the same reference pregnant woman, specifically comprising: The proportion of the corresponding true data characteristic value of each reference pregnant woman is taken as the data weight corresponding to each reference pregnant woman, and the serum ferritin concentration of each reference pregnant woman is weighted and summed by using the data weight to obtain the serum ferritin reference value of the reference pregnant woman to the target pregnant woman.

[0013] Preferably, the glycosylated hemoglobin concentration of the target pregnant woman is adjusted according to the data correction coefficient, the serum ferritin reference value and the serum ferritin concentration of the target pregnant woman, and a glycosylated hemoglobin detection result of the target pregnant woman is obtained, specifically comprising: obtaining a data adjustment degree according to the difference between the serum ferritin concentration of the target pregnant woman and the serum ferritin reference value and the data correction coefficient; taking the difference between the glycosylated hemoglobin concentration of the target pregnant woman and the data adjustment degree as a correction value of the glycosylated hemoglobin concentration of the target pregnant woman, and obtaining the glycosylated hemoglobin detection result of the target pregnant woman.

[0014] Preferably, the data adjustment degree is obtained according to the difference between the serum ferritin concentration of the target pregnant woman and the serum ferritin reference value and the data correction coefficient, specifically comprising: calculating the difference between the reciprocal of the serum ferritin concentration of the target pregnant woman and the reciprocal of the serum ferritin reference value, and taking the product of the data correction coefficient and the difference as the data adjustment degree.

[0015] The embodiments of the present application have at least the following beneficial effects: The present application firstly collects the serum ferritin concentration, the glycosylated hemoglobin concentration and the C-reactive protein concentration of the pregnant woman, and sets a reference sample, i.e., a reference pregnant woman, under the same conditions for the correction of the detection result of the target pregnant woman. Then, considering the relatively high change of the glycosylated hemoglobin concentration of the iron-deficient pregnant woman, the data correction coefficient is used to reflect the linear relationship between the difference of the glycosylated hemoglobin concentration and the difference of the serum ferritin concentration. Further, the iron deficiency reflected by the glycosylated hemoglobin concentration of the reference sample and the data distribution of the iron deficiency of the target pregnant woman are combined to quantify the data performance of the serum ferritin of the target pregnant woman under normal conditions, i.e., to obtain the serum ferritin reference value. Finally, the correction term of the glycosylated hemoglobin concentration is obtained by using the data correction coefficient to adjust the detection value of the glycosylated hemoglobin concentration of the target pregnant woman, and a more accurate glycosylated hemoglobin detection result of the target pregnant woman is obtained. Compared with the prior art, the present application corrects the glycosylated hemoglobin concentration by the chromatographic detection value of the serum ferritin concentration of the pregnant woman, eliminates the interference caused by iron deficiency or anemia, and makes the glycosylated hemoglobin detection result more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings required to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0017] Figure 1 is a step flow chart of a glycosylated hemoglobin chromatography detection method for pregnancy risk assessment provided by the present application; Figure 2 is a step flow chart of a data correction coefficient acquisition method provided by the present application; Figure 3 is a step flow chart of a serum ferritin reference value acquisition method provided by the present application. DETAILED DESCRIPTION

[0018] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object of the present application, the following describes the specific embodiments, structure, features and effects of a glycosylated hemoglobin chromatography detection method for pregnancy risk assessment according to the present application in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0020] The specific scheme of the glycosylated hemoglobin chromatography detection method for pregnancy risk assessment provided by the present application is described in detail below in combination with the drawings.

[0021] The main purpose of the present application is that iron deficiency in pregnant women can prolong the life of red blood cells, thereby causing false elevation of glycosylated hemoglobin (HbA1c), and the life of red blood cells is negatively correlated with iron reserves, while serum ferritin (SF) is positively correlated with the degree of iron deficiency, i.e. the lower the SF, the more serious the iron deficiency. Therefore, the characteristic performance of serum ferritin data can be used to construct a correction term to correct the detection results of the target measured HbA1c, which can offset the false elevation phenomenon caused by iron deficiency, and obtain a more accurate HbA1c chromatography detection result.

[0022] Please refer to Figure 1Fig. 1 shows a flow chart of a method for detecting the glycosylated hemoglobin chromatography for pregnancy risk assessment according to an embodiment of the present application, which comprises the following steps: In step S100, the serum ferritin concentration, the glycosylated hemoglobin concentration and the C-reactive protein concentration of each pregnant woman are obtained, wherein the pregnant women include the target pregnant woman and the reference pregnant women under the same conditions.

[0023] Firstly, the target pregnant woman who needs to be detected by the glycosylated hemoglobin chromatography is determined, and then other pregnant women with the same conditions as the target pregnant woman are screened from the database as reference samples, and are recorded as the reference data set corresponding to the target pregnant woman, which includes a plurality of reference pregnant women.

[0024] Further, the serum ferritin concentration, the glycosylated hemoglobin concentration and the C-reactive protein concentration of each pregnant woman are obtained. The serum ferritin concentration and the glycosylated hemoglobin concentration are obtained by chromatography detection method, and the C-reactive protein (CRP) concentration is determined by enzyme-linked immunosorbent assay (ELISA). The specific acquisition method is a known technology and will not be described in detail here. It should be understood that the data of the glycosylated hemoglobin concentration is in percentage, the unit of the serum ferritin concentration is generally μg / L, and the unit of the C-reactive protein concentration is generally mg / L.

[0025] It should be noted that the gestational age directly affects the iron demand and metabolic state of the pregnant woman, and the iron reserves and serum ferritin levels of pregnant women at different gestational ages may differ greatly. Secondly, the body mass index (BMI) reflects the physical state of the pregnant woman and has a significant impact on the serum ferritin concentration. Obese pregnant women may have lower serum ferritin concentrations due to plasma volume expansion, while low-BMI pregnant women may have abnormal gastrointestinal absorption function, affecting iron absorption and storage. Therefore, when obtaining the reference data set of the target user, comparison between pregnant women with the same gestational age and BMI value is needed to effectively exclude the interference of these factors and ensure that the determined serum ferritin reference analysis results are comparable, thereby providing accurate basis for individualized assessment.

[0026] It should be noted that the body mass index is calculated by the height and weight of the pregnant woman, which is a known technology and will not be described in detail here. As a specific example, other pregnant women with the same gestational age, the same BMI value and the same age as the target pregnant woman are screened from the hospital database to constitute the reference data set.

[0027] In other embodiments, a condition neighborhood range of different dimensions can also be set, for example, a maximum difference of one week in gestational age from the target pregnant woman, a maximum difference of 1 in BMI value from the target pregnant woman, a maximum difference of two years in age from the target pregnant woman, and the implementer can set it according to clinical experience and specific implementation. The reference data set characterizes a data set consisting of pregnant women with the same or similar physiological conditions as the target pregnant woman. It should be understood that the reference data set is generally a normal reference sample without other complications.

[0028] Step S200, according to the distribution of serum ferritin concentration and C-reactive protein concentration of each pregnant woman and the body mass index of each pregnant woman, the reference value weight of each pregnant woman is analyzed, and the difference between the serum ferritin concentrations and the difference between the glycosylated hemoglobin concentrations of different pregnant women are combined to obtain a data correction coefficient.

[0029] Serum ferritin concentration is a marker for evaluating iron reserves in the body, and low serum ferritin concentration is often used to diagnose iron deficiency in pregnant women. However, serum ferritin is not only a reflection of iron storage, and in the case of infection, chronic disease or inflammation, the serum ferritin concentration will also be falsely elevated. Therefore, this step constructs a data correction coefficient as a correction term to ensure that the serum ferritin concentration accurately reflects the iron deficiency state and excludes the interference of other factors on the serum ferritin concentration.

[0030] As a specific example, as shown in Figure 2 The method for obtaining the data correction coefficient can be implemented by steps S201 to S201 to S203.

[0031] Step S201, according to the distribution of serum ferritin concentration and C-reactive protein concentration of each pregnant woman, the deficiency characteristic factor of each pregnant woman is obtained.

[0032] Specifically, for any pregnant woman, the serum ferritin concentration and the C-reactive protein concentration are standardized to obtain serum ferritin data and C-reactive protein data; the product of the negative correlation coefficient of the serum ferritin data and the negative correlation coefficient of the C-reactive protein data is taken as the deficiency characteristic factor of the pregnant woman. It should be noted that the standardization method is a known technology, for example, the Z-score standardization method can be used for processing, the purpose is to avoid the influence of the dimension of different parameter indicators on the characteristic analysis result, and in other embodiments, the implementer can process according to the specific implementation scene.

[0033] In view of the fact that iron deficiency may be misjudged only according to the low serum ferritin concentration, especially in the presence of infection or chronic disease. Pregnancy is often accompanied by mild inflammatory response, especially the increase of C-reactive protein concentration. C-reactive protein is an acute-phase protein synthesized by the liver in the inflammatory state, which can rapidly increase in the body inflammatory response. Therefore, if the serum ferritin concentration is low, but the C-reactive protein concentration is low, it means that there is no significant inflammatory response, and the low serum ferritin concentration can truly reflect the iron deficiency. If the C-reactive protein concentration is high, it means that there may be infection or inflammation, which will affect the interpretation of serum ferritin concentration, resulting in false negative iron deficiency.

[0034] Therefore, by analyzing the data distribution of the serum ferritin concentration and the C-reactive protein concentration of each pregnant woman, the true deficiency represented by the serum ferritin concentration of each pregnant woman can be quantified, and the true deficiency degree represented by the serum ferritin concentration of each pregnant woman can be quantified.

[0035] As a specific example, the i-th pregnant woman is taken as an example, and the deficiency characteristic factor of the i-th pregnant woman can be expressed by the formula: ; wherein, represents the deficiency characteristic factor of the i-th pregnant woman, represents the C-reactive protein data of the i-th pregnant woman, represents the serum ferritin data of the i-th pregnant woman, represents the exponential function with the natural constant e as the base.

[0036] The serum ferritin data is positively correlated with the body iron reserve degree, that is, the lower the serum ferritin data, the more serious the iron deficiency. The reciprocal of the serum ferritin data is used to represent the negative correlation coefficient of the serum ferritin data, reflecting the original quantitative trend of the iron deficiency degree of the current pregnant woman.

[0037] Further considering the interference phenomenon of non-iron deficiency increase of serum ferritin, the negative correlation coefficient of C-reactive protein data is used to realize interference suppression. When there is inflammation, the C-reactive protein data is large, the value of is small, indicating that the initial serum ferritin is greatly interfered by inflammation, and the reliability of the real deficiency reflected by the serum ferritin is low, and the value of the corresponding deficiency characteristic factor is small. In the absence of inflammation, the C-reactive protein data is small, the value of is large, indicating that the serum ferritin can truly reflect the iron reserve, and the value of the deficiency characteristic factor is large.

[0038] At this point, the lack of characteristic factors of each pregnant woman can be obtained by the same method, which represents whether the serum ferritin data of each pregnant woman can truly reflect the current iron deficiency, and the greater the value, the greater the true iron deficiency, that is, the data is true and serious, and the glycosylated hemoglobin of the pregnant woman needs to be corrected. The smaller the value, the smaller the iron deficiency of the pregnant woman, or the serum ferritin is not reliable due to inflammation interference, and the glycosylated hemoglobin does not need to be corrected.

[0039] Further, the serum ferritin concentration needs to truly reflect the iron reserve, rather than the increase caused by inflammation or infection and other physiological factors. In the case of low C-reactive protein concentration and no inflammation, the serum ferritin concentration can accurately represent the iron reserve status of the pregnant woman, which provides a reliable basis for correcting the glycosylated hemoglobin concentration.

[0040] In step S202, the reference value weight of the pregnant woman is obtained according to the lack of characteristic factors of the pregnant woman and the body mass index of the pregnant woman.

[0041] It should be noted that the body mass index of the pregnant woman is also very important. Obese pregnant women may cause relative reduction of serum ferritin concentration due to expansion of plasma volume, thereby affecting accurate diagnosis of iron deficiency. In this case, low serum ferritin concentration may not fully reflect the actual iron reserve, but is due to the dilution effect caused by increased blood volume. In addition, low BMI pregnant women may have abnormal gastrointestinal function (such as celiac disease, etc.), which can affect iron absorption and cause iron deficiency. Therefore, too high or too low BMI will increase the measurement error of serum ferritin concentration, so that it cannot accurately reflect the iron deficiency state of the pregnant woman, thereby affecting the correction of the glycosylated hemoglobin concentration. Therefore, on the basis of the analysis result of excluding the interference of inflammation and the true iron deficiency, the interference of abnormal BMI on the serum ferritin concentration is further excluded, and the data reference value reflected by the data performance of each pregnant woman is quantified.

[0042] Specifically, the body mass index of the pregnant woman is determined based on the height and weight of the pregnant woman, and the reference value weight of the pregnant woman is determined based on the normalized result of the difference between the body mass index of the pregnant woman and the preset normal body mass index and the lack of characteristic factors. The calculation method of the body mass index is a known technology, and will not be described in detail here. At the same time, the body mass index of the pregnant woman in the normal state needs to be determined by the doctor according to the clinical experience and the gestational age of the pregnant woman, and will not be described in detail here. The purpose is to measure the size of the deviation of the BMI index of the pregnant woman from the normal state under the corresponding gestational age.

[0043] As a specific example, the reference value weight of the i-th pregnant woman can be expressed by the formula: ; wherein represents the reference value weight of the i-th pregnant woman, a normalized result of an absolute value of a difference between a body mass index of the i-th pregnant woman and a preset normal body mass index, a lack of characteristic factor of the i-th pregnant woman, an exponential function with a natural constant e as a base.

[0044] It should be noted that the normalization method can adopt a maximum-minimization normalization method, which is a known technology and will not be described in detail here. The implementer can calculate according to the specific implementation scene.

[0045] The greater the value of the body mass index of the pregnant woman, the greater the degree of deviation of the body mass index of the pregnant woman from the normal condition, and the smaller the reference value weight of the data performance of the pregnant woman for the subsequent correction process. Therefore, the reference value weight of each pregnant woman represents the true availability of each pregnant woman for the subsequent calculation of the correction term.

[0046] In step S203, according to the reference value weight of each pregnant woman, the difference between the serum ferritin concentrations and the difference between the glycosylated hemoglobin concentrations of different pregnant women are combined to obtain a data correction coefficient.

[0047] Due to iron deficiency, the life of red blood cells is prolonged, thereby increasing the generation of glycosylated hemoglobin. Therefore, the glycosylated hemoglobin (HbA1c) concentration of the pregnant woman with iron deficiency is relatively high, and when the SF concentration (serum ferritin concentration) decreases, the reciprocal of the serum ferritin concentration increases, and the glycosylated hemoglobin concentration also shows a false increase. Therefore, there is a linear relationship between HbA1c and SF, that is when the SF concentration increases, the HbA1c concentration also increases.

[0048] Based on this feature, by comparing the difference between the glycosylated hemoglobin concentrations of any two pregnant women and the difference between the two, the linear relationship between the current pregnant woman and HbA1c is quantified according to the data true availability of the corresponding pregnant woman.

[0049] Specifically, the difference between the serum ferritin concentrations and the difference between the glycosylated hemoglobin concentrations between each two pregnant women are weighted by using the weight of the reference value of each two pregnant women to obtain the correlation contribution degree between each two pregnant women. The cumulative sum of the correlation contribution degrees of all pregnant women is taken as the data correction coefficient.

[0050] ​More specifically, for any two pregnant women, the proportion of the cumulative sum of the reference value weights of the two pregnant women is taken as the weight value; the absolute value of the difference between the glycated hemoglobin concentrations of the two pregnant women is taken as the first difference coefficient; the absolute value of the difference between the reciprocals of the serum ferritin concentrations of the two pregnant women is taken as the second difference coefficient; the ratio of the first difference coefficient and the second difference coefficient is weighted using the weight value to obtain the correlation contribution degree between the two pregnant women.

[0051] As a specific example, taking the a th pregnant woman and the b th pregnant woman as an example, the calculation method of the correlation contribution degree between the a th pregnant woman and the b th pregnant woman can be expressed by the formula: wherein, represents the correlation contribution degree between the a th pregnant woman and the b th pregnant woman, represents the reference value weight of the a th pregnant woman, represents the reference value weight of the b th pregnant woman, represents the data set composed of all pregnant women. represents the glycated hemoglobin concentration of the a th pregnant woman, represents the glycated hemoglobin concentration of the b th pregnant woman, represents the serum ferritin concentration of the a th pregnant woman, represents the serum ferritin concentration of the b th pregnant woman.

[0052] is the weight value, represents the proportion of the cumulative sum of the reference value weights of the two pregnant women, and reflects the proportion of the data reliability of the two pregnant women. The correlation contribution degree is quantified by weighting using the weight value, which represents that higher weight is assigned to the pregnant woman sample with reliable data (without inflammation and BMI interference), so that it has greater influence on calculating the data correction coefficient, and ensures that the data correction coefficient can truly reflect the correlation between iron deficiency and the false increase of HbA1c concentration.

[0053] is the first difference coefficient, which reflects the difference between the glycated hemoglobin concentrations of the two pregnant women, is the second difference coefficient, which reflects the difference between the serum ferritin concentrations of the two pregnant women. The ratio of the first difference coefficient and the second difference coefficient is taken as the correlation term, which represents the linear correlation strength between the difference in the iron deficiency degree of the a th pregnant woman and the b th pregnant woman and the difference in the false increase of their HbA1c concentration.

[0054] The corresponding association contribution degree between two pregnant women represents the difference in the degree of iron deficiency for a sample pair, and the difference in the corresponding HbA1c concentration pseudo-increase difference per unit difference in the degree of iron deficiency, that is, the association proportion between the two. Based on this, each association contribution degree between the sample pairs represented by each of the two different pregnant women is obtained, and the association contribution degrees of all sample pairs are integrated to quantitatively integrate the data correction coefficient The linear relationship between HbA1c and iron deficiency is quantified, and the data reliability is constrained to avoid interference of abnormal samples.

[0055] It should be noted that in the process of quantifying the association contribution degree between any two pregnant women, due to the small differences between different individuals, The value of 0 is a very small probability event. Furthermore, considering that the pseudo-increase in HbA1c concentration is due to iron deficiency, if there is no difference in the degree of iron deficiency between the two pregnant women, the pseudo-increase in HbA1c concentration of the two pregnant women should also be no difference. At this time, the ratio calculation result is 0 / 0, which is not a meaningless value of a non-zero numerator and a zero denominator. Therefore, the ratio of the difference in the two aspects is directly used to measure The linear association relationship between HbA1c and iron deficiency.

[0056] In step S300, the serum ferritin reference value of the reference pregnant woman to the target pregnant woman is obtained according to the distribution of the serum ferritin concentration and the C-reactive protein concentration of the target pregnant woman and the glycosylated hemoglobin concentration of each reference pregnant woman.

[0057] If the glycosylated hemoglobin concentration of the other pregnant woman is low, and the degree of iron deficiency is also low on this basis, it proves that it is likely not affected by the increase in glycosylated hemoglobin concentration caused by iron deficiency, and the normality is high, and the data reliability is high. Based on this feature, the data performance of serum ferritin under normal conditions is quantified through the data feature performance of each reference pregnant woman.

[0058] As a specific example, as Figure 3 shown, the method for obtaining the serum ferritin reference value can be implemented by steps S301 to S303.

[0059] In step S301, the glycosylated hemoglobin concentration of each pregnant woman is standardized to obtain the glycosylated hemoglobin data of each pregnant woman.

[0060] In this embodiment, the Z-score standardization method is used for processing, and the standardization method is a known technology, which will not be described in detail here.

[0061] In step S302, the true data feature value of each reference pregnant woman to the target pregnant woman is obtained according to the deficiency characteristic factor of the target pregnant woman and the glycosylated hemoglobin data of each reference pregnant woman.

[0062] Specifically, the product of the negative correlation coefficient of the lack of characteristic factors of the target pregnant woman and the negative correlation coefficient of the glycated hemoglobin data of each reference pregnant woman is used as the true data characteristic value of each reference pregnant woman relative to the target pregnant woman.

[0063] As a concrete example, Lack of characteristic factors in target pregnant women The negative correlation coefficient, with Glycated hemoglobin data as the nth reference pregnant woman The negative correlation coefficient. The true data characteristic values ​​reflect the true comparability of each reference pregnant woman to the target pregnant woman's normal true reference value of serum ferritin, that is, the reliability of the data.

[0064] This indicates an iron deficiency background in pregnant women targeting specific populations. This excludes interference from iron deficiency in the reference pregnant woman. When the target pregnant woman lacks characteristic factors... The higher the value, the more severe the iron deficiency in the target pregnant woman. The smaller the value, the stricter the requirements for the normality of the reference pregnant woman's data, that is... The larger the value, the more reliable the data for the reference pregnant woman.

[0065] Step S303: Obtain the reference value of serum ferritin for the target pregnant woman based on the real data feature value corresponding to each reference pregnant woman and the serum ferritin concentration of the same reference pregnant woman.

[0066] Specifically, the proportion of the real data feature values ​​corresponding to each reference pregnant woman is used as the data weight for each reference pregnant woman. The serum ferritin concentration of each reference pregnant woman is weighted and summed using the data weight to obtain the serum ferritin reference value of the reference pregnant woman relative to the target pregnant woman.

[0067] As a concrete example, the method for obtaining the serum ferritin reference value for target pregnant women from the reference pregnant women can be expressed by the formula: ;in, This indicates the reference value for serum ferritin in pregnant women relative to the target pregnant women. This represents the true data feature value of the nth reference pregnant woman relative to the target pregnant woman, where N represents the total number of reference pregnant women. The serum ferritin concentration of the nth reference pregnant woman.

[0068] This represents the sum of the real data feature values ​​corresponding to all reference pregnant women, using... This represents the proportion of the actual data feature values ​​corresponding to each reference pregnant woman, reflecting the weight of the data's reliability for each reference pregnant woman. In other words, the data weight reflects the degree of data contribution of the corresponding reference pregnant woman, and using a weighted summation method allows for a more accurate measurement of the overall data result.

[0069] The reference values ​​for serum ferritin in target pregnant women represent normal serum ferritin levels consistent with the physiological characteristics of the target pregnant women and free from iron deficiency interference. It should be understood that the units of the serum ferritin reference values ​​are consistent with the units of serum ferritin concentration in pregnant women.

[0070] Step S400: Adjust the glycated hemoglobin concentration of the target pregnant woman according to the data correction coefficient, serum ferritin reference value and serum ferritin concentration of the target pregnant woman, and obtain the glycated hemoglobin test result of the target pregnant woman.

[0071] Iron deficiency in pregnant women can lead to prolonged red blood cell lifespan, causing a false increase in HbA1c concentration. Furthermore, red blood cell lifespan is negatively correlated with iron reserves, while serum ferritin (SF) is positively correlated with the degree of iron deficiency; that is, the lower the SF, the more severe the iron deficiency. The reciprocal of serum ferritin concentration... The larger it is, the more it can pass through. Linear relationship with HbA1c (data correction factor) ), construct a correction term for HbA1c concentration, that is Correcting the detection results of the target HbA1c concentration can offset the false increase caused by iron deficiency, resulting in more accurate HbA1c chromatographic detection results. Among these, This indicates the measured value of serum ferritin. This indicates the true value of serum ferritin.

[0072] Based on this characteristic, the degree of data adjustment is obtained by considering the difference between the target pregnant woman's serum ferritin concentration and the serum ferritin reference value, as well as the data correction coefficient. The difference between the target pregnant woman's glycated hemoglobin concentration and the data adjustment degree is used as the correction value for the target pregnant woman's glycated hemoglobin concentration, thus obtaining the target pregnant woman's glycated hemoglobin test result. Specifically, the method for obtaining the degree of data adjustment is as follows: calculate the difference between the reciprocal of the target pregnant woman's serum ferritin concentration and the reciprocal of the serum ferritin reference value, and multiply the data correction coefficient by this difference as the degree of data adjustment.

[0073] As a specific example, the formula for calculating the corrected value of the glycated hemoglobin concentration of the target pregnant woman can be expressed as: in, This indicates a correction value for the glycated hemoglobin concentration of the target pregnant woman. represents the glycosylated hemoglobin concentration of the target pregnant woman, represents the data correction coefficient, represents the serum ferritin concentration of the target pregnant woman, represents the serum ferritin reference value of the target pregnant woman with respect to the reference pregnant woman.

[0074] The serum ferritin reference value characterizes the referenceable true SF value of the target pregnant woman without iron deficiency and physiological background interference, and the data correction coefficient characterizes the linear relationship between the HbA1c concentration difference of the target pregnant woman and the difference, which can be expressed as wherein represents the HbA1c concentration difference, represents the difference.

[0075] is the data adjustment degree, accurately quantifies the abnormal degree of SF caused by iron deficiency of the target pregnant woman, and then calculates the false HbA1c concentration increase value that needs to be offset through the data correction coefficient K, and then subtracts the data adjustment degree from the true measured value of the serum ferritin concentration of the target pregnant woman, to finally obtain the true HbA1c concentration, and obtain accurate glycosylated hemoglobin chromatography detection results, to provide accurate basis for assisting doctors in assessing pregnancy risks (such as gestational diabetes mellitus judgment).

[0076] It should be noted that in other embodiments, the true detection value and the corrected value of the glycosylated hemoglobin concentration of the pregnant woman are recorded at the same time for reference analysis by doctors, and through the construction of a mathematical model, the interference caused by iron deficiency or anemia can be eliminated to some extent, and the doctor's work can be effectively assisted in some aspects.

[0077] In addition, the corrected HbA1c value can also help to evaluate pregnancy complications and long-term health risks. If gestational diabetes mellitus is not effectively controlled, it may develop into type 2 diabetes or other metabolic diseases after delivery. By monitoring the corrected HbA1c concentration, doctors can develop individualized intervention programs based on the blood glucose control status of pregnant women to keep blood glucose within a normal range and reduce the incidence of fetal developmental abnormalities, premature birth, or other pregnancy complications. This part is not the focus of the present application, and only a simple description is made, and the implementer needs to rely on the doctor to perform relevant analysis according to the specific implementation situation, and will not be introduced in detail here.

[0078] In summary, compared with the prior art, the iron deficiency of the pregnant woman causes the structure of hemoglobin to change, the HbA1c is falsely increased, and the abnormal synthesis of hemoglobin may change the chromatographic peak shape and interfere with the detection. The present embodiment corrects the concentration of glycosylated hemoglobin by determining the serum ferritin concentration of the pregnant woman, eliminates the interference caused by iron deficiency or anemia, makes the detection result of glycosylated hemoglobin more accurate, and can better assist the doctor in the risk assessment of pregnancy.

[0079] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A chromatographic detection method for glycated hemoglobin for pregnancy risk assessment, characterized in that, The method includes: The serum ferritin concentration, glycated hemoglobin concentration, and C-reactive protein concentration of each pregnant woman were obtained, wherein the pregnant women included the target pregnant women and reference pregnant women under the same conditions; Based on the distribution of serum ferritin and C-reactive protein concentrations and the body mass index of each pregnant woman, the reference value weight of each pregnant woman was analyzed. Combined with the differences in serum ferritin concentration and glycated hemoglobin concentration among different pregnant women, the data correction coefficient was obtained. Based on the distribution of serum ferritin and C-reactive protein concentrations in the target pregnant woman and the glycated hemoglobin concentration of each reference pregnant woman, the serum ferritin reference value of the reference pregnant woman relative to the target pregnant woman is obtained. Based on the data correction coefficient, serum ferritin reference value, and serum ferritin concentration of the target pregnant woman, the glycated hemoglobin concentration of the target pregnant woman is adjusted to obtain the glycated hemoglobin test result of the target pregnant woman.

2. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 1, characterized in that, The reference value weighting for each pregnant woman is analyzed based on the distribution of serum ferritin and C-reactive protein concentrations and her body mass index. Specifically, this includes: For any pregnant woman, serum ferritin concentration and C-reactive protein concentration were standardized to obtain serum ferritin data and C-reactive protein data, respectively. The product of the negative correlation coefficients of serum ferritin data and C-reactive protein data was used as the deficiency characteristic factor of the pregnant woman. The reference value weight of the pregnant woman is obtained based on the pregnant woman's lack of characteristic factors and her body mass index.

3. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 2, characterized in that, The reference value weighting of the pregnant woman, based on her lack of characteristic factors and body mass index, specifically includes: Based on the pregnant woman's height and weight, the pregnant woman's body mass index (BMI) is determined; based on the normalized result of the difference between the pregnant woman's BMI and the preset normal BMI and the lack of feature factors, the reference value weight of the pregnant woman is determined.

4. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 2, characterized in that, The reference value weight for each pregnant woman is analyzed based on the distribution of serum ferritin and C-reactive protein concentrations and her body mass index. Combined with the differences in serum ferritin and glycated hemoglobin concentrations among different pregnant women, a data correction coefficient is obtained, specifically including: By using the reference value weights of each pair of pregnant women, the differences in serum ferritin concentration and glycated hemoglobin concentration between each pair of pregnant women were weighted to obtain the degree of association contribution between each pair of pregnant women. The sum of the correlation contributions of all pregnant women is used as the data correction coefficient.

5. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 4, characterized in that, The method utilizes the reference value weights of each pair of pregnant women to weight the differences in serum ferritin concentration and glycated hemoglobin concentration between each pair of pregnant women, thereby obtaining the degree of association contribution between each pair of pregnant women, specifically including: For any two pregnant women, the weight is the sum of the reference value weights of the two pregnant women; the absolute value of the difference between the glycated hemoglobin concentrations of the two pregnant women is the first difference coefficient; and the absolute value of the difference between the reciprocals of the serum ferritin concentrations of the two pregnant women is the second difference coefficient. Using the weights, the ratio of the first difference coefficient and the second difference coefficient is weighted to obtain the degree of association contribution between any two pregnant women.

6. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 5, characterized in that, The reference value for serum ferritin in the reference pregnant woman relative to the target pregnant woman is obtained based on the distribution of serum ferritin and C-reactive protein concentrations in the target pregnant woman and the glycated hemoglobin concentration of each reference pregnant woman. Specifically, this includes: The glycated hemoglobin concentration of each pregnant woman was standardized to obtain glycated hemoglobin data for each pregnant woman; Based on the missing characteristic factors of the target pregnant woman and the glycated hemoglobin data of each reference pregnant woman, the true data characteristic value of each reference pregnant woman relative to the target pregnant woman is obtained; The reference value of serum ferritin for the target pregnant woman is obtained based on the actual data characteristic value corresponding to each reference pregnant woman and the serum ferritin concentration of the same reference pregnant woman.

7. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 6, characterized in that, The process of obtaining the true data feature values ​​of each reference pregnant woman relative to the target pregnant woman based on the lack of characteristic factors of the target pregnant woman and the glycated hemoglobin data of each reference pregnant woman specifically includes: The product of the negative correlation coefficient of the lack of characteristic factors of the target pregnant woman and the negative correlation coefficient of the glycated hemoglobin data of each reference pregnant woman is used as the true data characteristic value of each reference pregnant woman relative to the target pregnant woman.

8. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 6, characterized in that, The step of obtaining the serum ferritin reference value for the target pregnant woman based on the real data feature values ​​corresponding to each reference pregnant woman and the serum ferritin concentration of the same reference pregnant woman specifically includes: The proportion of the real data feature values ​​corresponding to each reference pregnant woman is used as the data weight for each reference pregnant woman. The serum ferritin concentration of each reference pregnant woman is weighted and summed using the data weight to obtain the serum ferritin reference value of the reference pregnant woman relative to the target pregnant woman.

9. The chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 1, characterized in that, The glycated hemoglobin concentration of the target pregnant woman is adjusted based on the data correction coefficient, serum ferritin reference value, and serum ferritin concentration of the target pregnant woman to obtain the glycated hemoglobin test result of the target pregnant woman, specifically including: The degree of data adjustment is determined based on the difference between the serum ferritin concentration of the target pregnant woman and the serum ferritin reference value, as well as the data correction coefficient. The difference between the glycated hemoglobin concentration of the target pregnant woman and the data adjustment level is used as the correction value for the glycated hemoglobin concentration of the target pregnant woman, thus obtaining the glycated hemoglobin test result of the target pregnant woman.

10. A chromatographic detection method for glycated hemoglobin for pregnancy risk assessment according to claim 9, characterized in that, The degree of data adjustment is determined based on the difference between the serum ferritin concentration of the target pregnant woman and the serum ferritin reference value, as well as the data correction coefficient. Specifically, this includes: The difference between the reciprocal of the serum ferritin concentration of the target pregnant woman and the reciprocal of the serum ferritin reference value is calculated, and the product of the data correction factor and this difference is used as the degree of data adjustment.

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