Non-invasive early warning method and device for autoimmune gastritis

Abstract

The invention relates to a non-invasive early warning method for autoimmune gastritis. The method comprises the following steps: acquiring serological indexes, basic information indexes, symptom characteristics and past medical history; determining serum risk points, basic risk points, symptom risk points and disease risk points according to serological indexes, basic information indexes, symptom characteristics and past medical history; and evaluating the AIG disease risk according to the serum risk integral, the basic risk integral, the symptom risk integral and the disease risk integral. The problems that in the prior art, the AIG disease risk cannot be evaluated in time through a non-invasive detection means, the evaluation efficiency cannot be improved, the evaluation cost cannot be reduced, and the evaluation accuracy cannot be improved are solved.

Description

Technical Field

[0001] This invention relates to the field of risk assessment technology, and in particular to a non-invasive early warning method and device for autoimmune gastritis. Background Technology

[0002] Autoimmune gastritis (AIG) is a rare form of atrophic gastritis, with a decreasing age of onset globally. Currently, there are no interventions, treatments, or preventative measures. The lack of a unified risk assessment standard for AIG is primarily due to the following reasons: firstly, the disease lacks typical presentations; secondly, almost all cases of anemia are treated with iron supplements and vitamin B12 without further investigation of the underlying cause; and thirdly, clinicians have insufficient understanding of the disease, leading to inaccurate biopsy sites or inadequate biopsy tissue collection, making it impossible to assess the risk of AIG.

[0003] Therefore, how to assess the risk of AIG in a timely manner through non-invasive testing methods, so as to improve assessment efficiency, reduce assessment costs and improve assessment accuracy, is a technical problem that urgently needs to be solved in the clinical field. Summary of the Invention

[0004] Based on this, the purpose of this application is to provide a non-invasive early warning method and device for autoimmune gastritis to solve at least one of the technical problems mentioned in the background art.

[0005] Firstly, this application provides a non-invasive early warning method for autoimmune gastritis, including: Obtain serological markers, basic information markers, symptom characteristics, and past medical history; Serum risk score, basic information score, symptom risk score and disease risk score are determined based on serological indicators, basic information indicators, symptom characteristics and past medical history. The risk of developing AIG is assessed based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

[0006] Further steps for obtaining serological indicators include: extracting gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and iron / ferritin content; The steps for determining a serum risk score include: Determine whether the gastrin-17 content is greater than the gastrin threshold; if so, record the gastrin single item integral. Determine whether the PGI content is less than the first PGI threshold. If so, record the first-class integral of the PGI item. Determine whether the PGI content is less than the second PGI threshold. If so, record the second-class integral of the PGI item. The first PGI threshold is greater than the second PGI threshold. The second-class integral of the PGI item is greater than the first-class integral of the PGI item. Determine whether the PGI / II ratio is less than the first proportional threshold. If so, record the first-class integral of the PGI / II ratio. Determine whether the PGI / II ratio is less than the second proportional threshold. If so, record the second-class integral of the PGI / II ratio. If the first proportional threshold is greater than the second proportional threshold, the second-class integral of the PGI / II ratio is greater than the first-class integral of the PGI / II ratio. Determine whether the hemoglobin content is less than the hemoglobin threshold; if so, record the hemoglobin single item integral. Determine whether the iron / ferritin content is less than the iron / ferritin threshold; if so, record the iron / ferritin single item integral. Serum risk scores are determined based on individual scores for gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, and ferritin / ferritin.

[0007] Furthermore, the steps for determining serum risk scores also include: Based on the correlation strength between each serological indicator and AIG, differentiated serum weighting coefficients were set for gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and iron / ferritin content; among them, the serum weighting coefficients for PGI content and PGI / II ratio were higher than those for gastrin-17 content, hemoglobin content, and iron / ferritin content. Obtain Helicobacter pylori antibody and / or breath test results. If the test result is negative, increase the serum weighting coefficient of the gastrin single item score. If the test result is positive, decrease the serum weighting coefficient of the gastrin single item score. Serum risk scores are determined based on individual scores for gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, ferritin, and the corresponding serum weighting coefficients.

[0008] Further steps for obtaining basic information indicators include: Extract the user's gender and age; The steps to determine the basic risk score include: Determine whether the gender is female. If yes, record the first-order single term integral for gender; if no, record the second-order single term integral for gender. The first-order single term integral for gender is greater than the second-order single term integral for gender. Determine if the age is greater than the age threshold; if so, record the age integral. Obtain the deviation value between age and age threshold, and determine the age weight coefficient of the age single component based on the deviation value. The larger the age deviation value, the higher the age weight coefficient. The basic risk score is determined based on the individual score for gender (either first-class or second-class), the individual score for age, and the age weighting coefficient.

[0009] Further steps in obtaining symptom characteristics include: determining whether the user has symptoms such as loss of appetite, belching, postprandial fullness, and anemia; The steps for determining a symptom risk score include: If the user has poor appetite symptoms, extract the user's current food intake to determine the score for poor appetite. If belching symptoms are present, the frequency of belching is extracted to determine the belching component integral; If postprandial fullness symptoms are present, the duration of fullness is extracted to determine the fullness component score. If symptoms of anemia are present, hemoglobin levels are measured to determine the anemia score. The symptom risk score is determined based on the scores for poor appetite, belching, bloating, and anemia.

[0010] Further steps in obtaining past medical history include: determining whether the user has a past medical history, including any one or more of the following: Hashimoto's thyroiditis, hypothyroidism, Sjögren's syndrome, primary biliary cirrhosis, vitiligo, rheumatoid arthritis, psoriasis, history of anemia, vitamin B12 deficiency, and subacute combined degeneration of the spinal cord. The steps for determining the risk score of past medical history include: If there is a history of illness, then a corresponding disease score and disease weight coefficient are determined for each existing disease; The disease risk score is determined based on the individual disease score and its weight coefficient for each existing disease.

[0011] Furthermore, the steps for determining the corresponding disease-specific score and disease weight coefficient for each existing disease include: Determine if a disease is present and whether it is an immune disease; if so, record the immune single item score; otherwise, record the non-immune single item score; the immune single item score is higher than the non-immune single item score. Extract the disease duration and severity of each existing disease, and determine the disease weight coefficient for each existing disease; the longer the disease duration and the higher the severity, the higher the disease weight coefficient.

[0012] Furthermore, the steps for assessing the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score include: The total score is determined based on the serum risk score, baseline risk score, symptom risk score, and disease risk score. Determine if the total score exceeds the score limit; if so, it is considered high-risk. Determine if the total score is less than the lower limit of the score; if so, it is considered low risk. Determine if the total score is between the upper and lower limits of the score; if so, it is classified as medium risk.

[0013] Furthermore, if the risk level is determined to be medium, the steps for assessing the risk of AIG also include: Obtain the PCA and IF test results, determine whether both are positive. If so, set an additional weighting coefficient greater than 1; otherwise, set an additional weighting coefficient less than 1. Determine the corrected total integral based on the additional weighting coefficient and the total integral. Determine whether the total score after correction is greater than the upper limit of the score; if so, it is judged as medium to high risk. Determine whether the total score after correction is less than the lower limit of the score; if so, it is classified as low to medium risk.

[0014] Secondly, this application also provides a non-invasive early warning device for autoimmune gastritis, used to execute the non-invasive early warning method for autoimmune gastritis described in any one of the first aspects, comprising: The acquisition module is used to acquire serological indicators, basic information indicators, symptom characteristics, and past medical history. The calculation module is used to determine the serum risk score, basic risk score, symptom risk score, and disease risk score based on serological indicators, basic information indicators, symptom characteristics, and past medical history. The assessment module is used to assess the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

[0015] This invention provides a non-invasive early warning method and device for autoimmune gastritis (AIG). By acquiring user serological indicators, basic information indicators, symptom characteristics, and past medical history, it covers four dimensions: biomarkers, demographic characteristics, clinical manifestations, and disease history. This avoids the limitations of single-indicator screening, achieving a panoramic profile from "biomarkers-demographic characteristics-clinical manifestations-historical trajectory," providing a comprehensive data foundation for subsequent steps. Then, based on serological indicators, basic information indicators, symptom characteristics, and past medical history, it determines serum risk scores, baseline risk scores, symptom risk scores, and disease risk scores, decomposing complex risk factors into four independent sub-risk assessments. This avoids weighting confusion and facilitates subsequent univariate analysis. Finally, based on the serum risk score, baseline risk score, symptom risk score, and disease risk score, it assesses the risk of AIG, performing multi-dimensional information fusion decision-making to enhance complementarity, synergy, and redundancy. This allows abnormalities in a single indicator to be corrected by other dimensions, avoiding overdiagnosis. This solves the problems of existing technologies' inability to timely assess AIG risk through non-invasive detection methods, thus improving assessment efficiency, reducing assessment costs, and increasing assessment accuracy. Attached Figure Description

[0016] Figure 1 A flowchart of a non-invasive early warning method for autoimmune gastritis according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the non-invasive early warning device for autoimmune gastritis according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be noted that if the embodiments of the present invention involve directional indications, such as up, down, left, right, front, back, etc., these directional indications are only used to explain the relative positional relationships and movement of the components in a specific posture. If the specific posture changes, the directional indications will also change accordingly. Furthermore, if the embodiments of the present invention involve descriptions such as "first," "second," "S1," "S2," "step one," "step two," etc., these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance, or implicitly indicating the number of technical features indicated or the order of method execution. Those skilled in the art will understand that anything that does not violate the inventive concept and is within the scope of the present invention should be included in the protection scope of the present invention.

[0019] like Figure 1 As shown, this invention provides a non-invasive early warning method for autoimmune gastritis: S1: Obtain serological markers, basic information markers, symptom characteristics, and past medical history; Specifically, options include, but are not limited to, querying existing databases. For example, users can obtain their existing health management records, directly reuse their existing physical examination data, or directly input the above information in a question-and-answer format through apps, software terminals, etc., to provide a data foundation for subsequent steps. This eliminates the need for repeated blood draws or gastroscopy for autoimmune gastritis (AIG) screening, reducing additional trauma and costs for users and achieving non-invasive risk prediction.

[0020] For example, but not limited to, data interfaces from hospital health check centers, regional health cloud platforms, or third-party apps can be used to automatically retrieve complete electronic health check records from the past 12 months using the HL7 / FHIR standard protocol. Users can also upload their records locally in formats such as PDF / CSV / JPG. The health check records may optionally include: ① a questionnaire on chief complaint and symptoms; ② raw serological test values; ③ immunological and microbiological test reports; ④ structured fields for past medical history and medication history; ⑤ anonymized identity fields (age, gender, BMI, etc.). Preferably, if any of the above subfields are missing, the system may trigger a "Record Supplementation" pop-up window, guiding the user or health check institution to supplement more complete data within 72 hours.

[0021] Preferably, the steps for obtaining serological markers, basic information markers, symptom characteristics, and past medical history include: S11: Obtain the medical examination records and classify them into scanned electronic records and structured electronic records; Specifically, since hospitals currently store both paper and electronic records, although electronic storage is now widespread in most areas, simply scanning paper records into electronic records is fundamentally different from directly using electronically stored data (such as WPS spreadsheets). Therefore, the methods for extracting this data also differ, requiring the two types of data to be categorized and extracted separately.

[0022] S12: Segment the scanned electronic files to obtain scanned serum files, scanned basic information files, scanned symptom files, and scanned medical history files; S13: Identify scanned serum records, scanned basic information records, scanned symptom records, and scanned medical history records to obtain scanned serum data, scanned basic information data, scanned symptom data, and scanned medical history data; Specifically, since the locations of various data in the paper archives are known, the scanned electronic archives can be segmented to obtain scanned serum archives, scanned basic information archives, scanned symptom archives, and scanned medical history archives. Data preprocessing such as data cleaning, standardization, and outlier removal can be performed according to the data categories to improve the recognition accuracy and efficiency, and to extract scanned serum data, scanned basic information data, scanned symptom data, and scanned medical history data.

[0023] S14: Segment the structured electronic records to obtain electronic serum data, electronic basic information data, electronic symptom data, and electronic medical history data; Specifically, since electronic records have already categorized and stored various types of data during storage, the corresponding content in the structured electronic records can be directly extracted based on the data category (such as serum data, basic information data, symptom data, and medical history data). This allows for the extraction of electronic serum data, electronic basic information data, electronic symptom data, and electronic medical history data.

[0024] S15: Merge scanned serum data and electronic serum data to extract serological indicators; merge scanned basic information data and electronic basic information data to extract basic information indicators; merge scanned symptom data and electronic symptom data to extract symptom characteristics; merge scanned medical history data and electronic medical history data to extract past medical history.

[0025] Specifically, after data extraction is complete, data of the same category in the scanned electronic archives and structured electronic archives can be spliced ​​and merged. For example, merging scanned serum data and electronic serum data can extract serological indicators; merging scanned basic information data and electronic basic information data can extract basic information indicators; merging scanned symptom data and electronic symptom data can extract symptom characteristics; and merging scanned medical history data and electronic medical history data can extract past medical history, providing a multi-dimensional data foundation for subsequent steps.

[0026] More specifically, serological indicators include gastrin-17 levels, PGI levels, PGI / II ratio, hemoglobin levels, and iron / ferritin levels; basic information data includes the user's gender and age; symptom data includes symptoms such as poor appetite, belching, postprandial fullness, and anemia; and medical history data includes diseases such as Hashimoto's thyroiditis, hypothyroidism, Sjögren's syndrome, primary biliary cirrhosis, vitiligo, rheumatoid arthritis, psoriasis, history of anemia, vitamin B12 deficiency, and subacute combined degeneration of the spinal cord.

[0027] S2: Determine the serum risk score, basic risk score, symptom risk score, and disease risk score based on serological indicators, basic information indicators, symptom characteristics, and past medical history; Specifically, but not limited to, determining serum risk score, basic risk score, symptom risk score, and disease risk score based on serological indicators, basic information indicators, symptom characteristics, and past medical history, provides a data foundation for subsequent steps. This systematically integrates data from the four dimensions of serological indicators, basic information indicators, symptom characteristics, and past medical history to construct a comprehensive assessment system for AIG risk prediction, breaking through the limitations of traditional single-indicator diagnosis.

[0028] Preferably, since serological indicators, including gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and ferritin / ferritin content, are extracted according to step S1, step S21: determining the serum risk score includes: S211: Determine whether the gastrin-17 content is greater than the gastrin threshold; if so, record the gastrin single item integral. Specifically, one can choose to determine whether the gastrin-17 content is greater than the gastrin threshold. If it is, it indicates that due to the lack of gastric acid to relieve negative feedback, G cells continuously release gastrin, and its elevation directly reflects the decline in parietal cell function. Therefore, it suggests that the probability of autoimmune gastritis (AIG) is higher, so it is necessary to record the gastrin single item score. Conversely, it indicates that the probability of autoimmune gastritis (AIG) is lower, or even that it has no effect on the human body. Therefore, it is possible not to record the gastrin single item score to eliminate the interference of this single parameter.

[0029] S212: Determine whether the PGI content is less than the first PGI threshold. If so, record the first-class integral of the PGI item. Determine whether the PGI content is less than the second PGI threshold. If so, record the second-class integral of the PGI item. The first PGI threshold is greater than the second PGI threshold. The second-class integral of the PGI item is greater than the first-class integral of the PGI item. Specifically, it can be determined whether the PGI content is less than the first PGI threshold. If so, it indicates that since PGI is synthesized and secreted by chief cells and neck mucous cells, the number of glands decreases when the gastric mucosa atrophies, resulting in a decrease in the amount of PGI released into the blood. Therefore, it suggests that the probability of having AIG is higher, and a first-class score for PGI needs to be set. It can also be determined whether the PGI content is less than the second PGI threshold. If so, a second-class score for PGI is recorded. By using two thresholds for multiple tiered screenings, the accuracy of risk assessment can be improved. At the same time, the first PGI threshold can be used as a buffer to avoid small fluctuations in parameters causing large changes in the score. Preferably, a PGI < 70 ng / ml and a PG I / II ratio (PGR) < 3 are used as the first cutoff value for predicting atrophic gastritis. Further clinical studies have found that in patients with autoimmune gastritis, approximately 98.8% have a PGI < 70 ng / ml and 95% have a PGR < 3; approximately 65% ​​have a PGI < 22 ng / ml and 72.6% have a PGR < 2.2, which are lower than the first cutoff value. Therefore, a PGI < 22 ng / ml and a PGR < 2.2 are used as the second cutoff value to predict the likelihood of type A gastritis, with a lower chance of missed screening. Thus, the first PGI threshold can be optionally set to 70 ng / ml, and the second PGI threshold can be optionally set to 22 ng / ml.

[0030] S213: Determine whether the PGI / II ratio is less than the first proportional threshold. If so, record the first-class integral of the PGI / II ratio. Determine whether the PGI / II ratio is less than the second proportional threshold. If so, record the second-class integral of the PGI / II ratio. The first proportional threshold is greater than the second proportional threshold. The second-class integral of the PGI / II ratio is greater than the first-class integral of the PGI / II ratio. Specifically, the system can optionally determine whether the PGI / II ratio is less than a first proportional threshold. If so, it indicates that because the PGI decreases much faster than the PGII during the atrophy process, the lower ratio amplifies the lost glandular signal, increasing early detection sensitivity and suggesting a higher probability of AIG. Therefore, a first-order integral for the PGI / II ratio is required. The system can also determine whether the PGI / II ratio is less than a second proportional threshold. If so, a second-order integral for the PGI / II ratio is recorded. Multiple tiered screenings using these two thresholds improve the accuracy of risk assessment. Simultaneously, the first proportional threshold can act as a buffer to prevent small fluctuations in parameters from causing significant changes in the integral. Preferably, the first proportional threshold can be set to 3, and the second proportional threshold can be set to 2.2.

[0031] S214: Determine whether the hemoglobin content is less than the hemoglobin threshold; if so, record the hemoglobin single item integral. Specifically, one option is to determine if the hemoglobin level is below the hemoglobin threshold. If so, it indicates that the deficiency of both intrinsic factor and gastric acid is causing a decline in iron and vitamin B levels. 12 Absorption disorder and limited hemoglobin synthesis indicate the presence of functional anemia, thus suggesting a higher probability of having AIG, requiring the recording of hemoglobin scores.

[0032] S215: Determine whether the iron / ferritin content is less than the iron / ferritin threshold. If so, record the iron / ferritin single item integral. Specifically, one can determine whether the iron / ferritin content is below the ferritin threshold. If so, it indicates that insufficient gastric acid is hindering the reduction of ferric iron, and the lack of intrinsic factor further affects the levels of iron ions and vitamin B. 12 The simultaneous decrease in serum iron and ferritin suggests a higher probability of having AIG, therefore it is necessary to record the iron / ferritin scores separately.

[0033] S216: Determine the serum risk score based on the individual scores of gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, and ferritin.

[0034] Specifically, the serum risk score can be determined by calculating the individual scores of gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, and ferritin / ferritin.

[0035] Preferably, the step of determining the serum risk score further includes: S2161: Based on the correlation strength between each serological indicator and AIG, differentiated serum weighting coefficients are set for gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and iron / ferritin content; among them, the serum weighting coefficients for PGI content and PGI / II ratio are higher than those for gastrin-17 content, hemoglobin content, and iron / ferritin content. Specifically, since the influence of each serological indicator on the risk of AIG varies, differentiated serum weighting coefficients can be set for gastrin-17 level, PGI level, PGI / II ratio, hemoglobin level, and iron / ferritin level based on the correlation strength between each serological indicator and AIG. Among them, since PGI level and PGI / II ratio are strongly correlated with the risk of AIG, the serum weighting coefficients for PGI level and PGI / II ratio are higher than those for gastrin-17 level, hemoglobin level, and iron / ferritin level.

[0036] S2162: Obtain Helicobacter pylori antibody and / or breath test results. If the test result is negative, increase the serum weighting coefficient of the gastrin single item score. If the test result is positive, decrease the serum weighting coefficient of the gastrin single item score. Specifically, since the presence of H. pylori infection also leads to elevated levels of gastrin in the blood, it becomes impossible to distinguish the specific factors causing the elevated gastrin levels. Therefore, it is advisable to obtain H. pylori antibody and / or breath test results, and adjust the weighting coefficient of gastrin-17 levels based on the experimental results. When the experimental result is positive, it indicates the presence of H. pylori infection, so the weighting coefficient of gastrin-17 levels needs to be reduced to avoid interference. When the experimental result is negative, it indicates the absence of H. pylori infection, and the reliability of gastrin-17 levels increases, so the corresponding weighting coefficient needs to be increased.

[0037] Preferably, since Helicobacter pylori antibodies and breath tests are complementary, the Helicobacter pylori antibody test is not affected by drugs but has low accuracy, while the breath test is easily affected by drugs but has high accuracy. Therefore, when both are present but the experimental results are different, the breath test result shall prevail.

[0038] In a further preferred embodiment, when the experimental results of the two tests are different, the results of the breath test shall prevail, but the adjustment range of the serum weight coefficient of the gastrin single item integral shall be reduced; when the experimental results of the two tests are the same, the adjustment range of the serum weight coefficient of the gastrin single item integral shall be increased.

[0039] S2163: The serum risk score is determined based on the individual scores of gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, ferritin, and the corresponding serum weighting coefficients.

[0040] Specifically, after determining the serum weight coefficients corresponding to each serological indicator, the individual scores of each serological indicator can be weighted and summed according to the weight coefficients to determine the serum risk score. The corresponding individual scores can then be corrected using the weight coefficients to improve the accuracy of subsequent assessment steps.

[0041] For example, the following parameters can be selected: whether the gastrin-17 level is greater than a set threshold (one point if yes); whether the hemoglobin level and ferritin / ferritin level are less than a set threshold (one point if yes); whether the PGI level is less than a first PGI threshold (one point if yes); whether the PGI level is less than a second PGI threshold (two points if yes); whether the PGI / II ratio is less than a first proportional threshold (one point if yes); and whether the PGI / II ratio is less than a second proportional threshold (two points if yes). This example is for illustrative purposes only and is not intended to limit the scope of the analysis.

[0042] Preferably, since the basic information indicators, including gender and age, are extracted based on step S1, step S22: determining the basic risk score includes: S221: Determine whether the gender is female. If yes, record the first-order single term integral for gender; if no, record the second-order single term integral for gender. The first-order single term integral for gender is greater than the second-order single term integral for gender. S222: Determine if the age is greater than the age threshold. If so, record the age integral. Specifically, since everyone's basic information is different, the probability of developing AIG will also be affected. According to statistics, the probability of women developing the disease is much higher than that of men. At the same time, when the age is greater than the age threshold, the probability of developing the disease increases sharply. Therefore, it is possible to determine whether the user's gender is female. If so, a first-class gender score is recorded. If not, a second-class gender score is recorded. The first-class gender score is greater than the second-class gender score. It is also necessary to determine whether the user's age is greater than the age threshold. If so, it means that the user has a higher probability of developing the disease and an age score needs to be recorded.

[0043] S223: Obtain the deviation value between age and age threshold, and determine the age weight coefficient of the age single-item integral based on the deviation value. The larger the age deviation value, the higher the age weight coefficient. S224: Determine the basic risk score based on the single-item score of gender (first-class or second-class), the single-item score of age, and the age weighting coefficient.

[0044] Specifically, since the risk of disease increases with age, the deviation between age and age threshold can be obtained to determine the age weight coefficient of the age single-item score. The larger the age deviation, the higher the risk of disease and the higher the age weight coefficient. Finally, the basic risk score can be determined by weighting and summing the gender first-class single-item score or gender second-class single-item score, the age single-item score and the age weight coefficient.

[0045] Preferably, the basic information indicators also include any one or more of the following: unhealthy habits, genetic history, and psychological state: Specifically, unhealthy habits include smoking, drinking, overeating, and drug abuse, which are prone to causing AIG. If any of the above unhealthy habits are present, a single score for the habit item needs to be recorded. Genetic history includes APECED syndrome, LRBA deficiency, RIPK1-induced autoinflammatory syndrome, etc. If any of the above genetic history is present, a single score for the genetic basis item needs to be recorded. Psychological state includes anxiety, depression, or chronic stress. If any of the above psychological states are present, a single score for the psychological item needs to be recorded.

[0046] More specifically, since bad habits increase the risk of AIG, the weighting coefficient of bad habits can be adjusted according to the number of bad habits; the more bad habits, the higher the weighting coefficient. The stronger the association between genetic diseases and AIG, the greater the impact on the risk of disease. Therefore, the weighting coefficient of genetic history can be adjusted according to the existing genetic diseases and the strength of their association with AIG; the more genetic diseases and the stronger their association, the higher the weighting coefficient. Negative psychological states, when severe enough, can become somatized, that is, have a negative impact on the body. Therefore, the weighting coefficient of psychological states can be adjusted according to the severity of the psychological state; the more severe the psychological state, the higher the weighting coefficient. Then, the adjusted basic risk score can be obtained by weighted summing of each individual score and its weighting coefficient.

[0047] Preferably, since the symptom features extracted in step S1 include any one or more of loss of appetite, belching, postprandial fullness, and anemia, step S23: determining the symptom risk score includes: S231: If there is a loss of appetite, extract the user's current food intake to determine the individual score for loss of appetite; Specifically, if there is a loss of appetite, it indicates that the gastric mucosal lesions have affected the appetite center and digestive function. The user's current food intake can be extracted, and the ratio of the user's current food intake to the set food intake threshold can be obtained as the single item integral of the loss of appetite.

[0048] S232: If belching symptoms are present, extract the frequency of belching to determine the belching integral; Specifically, the presence of belching symptoms indicates gastric motility disorders or gastric environmental disturbances, which are significantly more common among AIG users. Therefore, the frequency of belching can be extracted, and the ratio of the belching frequency to a set frequency threshold can be obtained as the belching integral.

[0049] S233: If postprandial fullness symptoms are present, extract the duration of fullness to determine the fullness component score; Specifically, if there is a feeling of fullness after a meal, it reflects that the stomach body has atrophied, resulting in a decrease in the stomach's receptive relaxation function. The duration of the feeling of fullness can be extracted, and the ratio of the duration of the feeling of fullness to the set threshold for the duration of the feeling of fullness is obtained as the single-item integral of the feeling of fullness.

[0050] S234: If symptoms of anemia are present, hemoglobin levels are extracted to determine the anemia score. Specifically, if anemia symptoms are present, it indicates that the user has anemia, which may be caused by a lack of gastric acid and intrinsic factor leading to malabsorption of iron and vitamin B12, significantly increasing the risk of AIG and its complications. Therefore, hemoglobin content can be extracted, and the ratio of hemoglobin content to a set hemoglobin content threshold can be obtained as the anemia score.

[0051] S235: Determine the symptom risk score based on the scores for poor appetite, belching, bloating, and anemia. Specifically, the individual scores for nausea, belching, bloating, and anemia can be calculated to determine the symptom risk score.

[0052] Preferably, the step of determining the symptom risk score may further include: obtaining the deviation values ​​between the user's current food intake, the frequency of belching, the duration of postprandial fullness, and the hemoglobin content and a set threshold, so as to set the weight coefficient of each symptom score according to the deviation value, with the larger the deviation value, the higher the weight coefficient; and then determining the symptom risk score by weighted summation of the appetite deficit score, belching score, fullness score, and anemia score and their corresponding weight coefficients.

[0053] Preferably, since the past medical history extracted according to step S1 includes any one or more of the following diseases: Hashimoto's thyroiditis, hypothyroidism, Sjögren's syndrome, primary biliary cirrhosis, vitiligo, rheumatoid arthritis, psoriasis, history of anemia, vitamin B12 deficiency, and subacute combined degeneration of the spinal cord, therefore, step S24: determining the disease risk score includes: S241: Determine if the user has a history of illness. If so, determine the corresponding disease score and disease weight coefficient for each disease. Specifically, since many diseases can damage the human body and have adverse effects, and some diseases may even accompany patients for life, it is possible to determine whether the user has a pre-existing medical history. If a pre-existing medical history exists, a corresponding disease score and disease weight coefficient are determined for each existing disease to measure the impact of the user's existing diseases on the probability of AIG, providing a basis for judgment in subsequent steps.

[0054] Preferably, the step of determining the corresponding disease-specific score and disease weight coefficient for each existing disease includes: S2411: Determine if a disease exists and whether it is an immune disease; if so, record the immune single item score, otherwise record the non-immune single item score; the immune single item score is higher than the non-immune single item score. Specifically, diseases in the human body can be broadly categorized into immune diseases and non-immune diseases. Different types of immune diseases have roughly equal impacts on the risk of developing AIG, and different types of non-immune diseases also have roughly equal impacts. However, the impact of immune diseases and non-immune diseases on the risk of developing AIG differs. Therefore, it is possible to determine whether the user's disease is an immune disease. If so, an immune score is recorded; otherwise, a non-immune score is recorded. Furthermore, since immune diseases have a greater impact on the risk of developing AIG than non-immune diseases, the immune score is higher than the non-immune score.

[0055] More specifically, immune diseases include Hashimoto's thyroiditis, hypothyroidism, Sjögren's syndrome, primary biliary cirrhosis, vitiligo, rheumatoid arthritis, and psoriasis; Non-immune diseases include a history of anemia, vitamin B12 deficiency, and subacute combined degeneration of the spinal cord (SCD).

[0056] S2412: Extract the disease duration and severity of each existing disease, and determine the disease weight coefficient for each existing disease; the longer the disease duration and the higher the severity, the higher the disease weight coefficient. Specifically, since users may have multiple diseases, and the duration and severity of each disease are different, the impact on the human body is also different. The longer the duration and the higher the severity, the greater the damage and adverse effects on the human body. Therefore, the duration and severity of each disease can be extracted to determine the disease weight coefficient for each disease; the longer the duration and the higher the severity, the higher the disease weight coefficient.

[0057] S242: Determine the disease risk score based on the individual disease score and its weight coefficient for each existing disease.

[0058] Specifically, the disease risk score can be determined by weighting and summing the individual disease scores and their weight coefficients for each existing disease.

[0059] S3: Assess the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

[0060] Specifically, an upper limit and a lower limit for the score can be set. Then, the serum risk score, basic risk score, symptom risk score, and disease risk score are summed to obtain the total score. It is then determined whether the total score is greater than the upper limit. If so, it indicates that the current disease risk is high and is classified as high risk. It is then determined whether the total score is less than the lower limit. If so, it indicates that the disease risk is low and is classified as low risk. Finally, it is determined whether the total score is between the upper and lower limits. If so, it is classified as medium risk.

[0061] Preferably, to improve assessment efficiency, it can be selected to determine whether all of the following conditions are met: PGI content is greater than the first PGI threshold, PGI / II ratio is greater than the first proportion threshold, and serum risk score is less than the serum score threshold; if so, the risk of AIG disease is directly determined to be low.

[0062] For example, the steps for calculating the total integral can be optionally represented by equations 3-1 to 3-5: D1=Z1×z1+Z2×z2+Z3×z3+Z4×z4+Z5×z53-1 D2 = K1 + K2 × X23 - 2 D3 = T1 + T2 + T3 + T4 + T53 - 3 D4 = J1 × d1 + ... + J n ×d n 3-4 D = D1 + D2 + D3 + D43 - 5 Wherein, D1 is the serum risk score, D2 is the basic risk score, D3 is the symptom risk score, D4 ​​is the disease risk score, D is the total score, Z1-Z5 are the individual scores of each serological indicator, and z1-z5 are the weighting coefficients of each serological indicator; K1 is the single score for gender-first or gender-second grade, K2 is the single score for age, and X2 is the age weighting coefficient; T1-T5 are the single scores of each symptom feature, J1-J n For each item in the past medical history, d1-d n The weighting coefficients for each past medical history.

[0063] Preferably, if the risk is determined to be intermediate, the steps for assessing the risk of AIG also include: S31: Obtain the PCA and IF test results, determine whether they are both positive. If so, set an additional weighting coefficient greater than 1; if not, set an additional weighting coefficient less than 1. Determine the corrected total integral based on the additional weighting coefficient and the total integral. S32: Determine whether the total score after correction is greater than the upper limit of the score. If so, it is determined to be of medium to high risk. S33: Determine whether the total integral after correction is less than the lower limit of the integral. If so, it is determined to be of medium to low risk.

[0064] Specifically, when a user has AIG, the sensitivity (the proportion of people who test positive among those who actually have the disease) of anti-gastric parietal cell antibody (PCA) is about 80-97%, but the specificity (the proportion of people who test negative among those who actually have the disease) is only 50%-90.3%, while that of anti-intrinsic factor antibody (anti-intrinsic factor) is much higher. The antibody (IF) is a specific antibody for AIG with pernicious anemia, with a high specificity of approximately 98.6%-100%, but a sensitivity of only 37%-70%. Simultaneously, PCA-positive and IF-negative patients may experience seroconversion in the later stages of the disease. That is, as AIG progresses, in the early stages, PCA is likely to be positive and IF is likely to be negative; in the later stages, both are likely to be positive. Therefore, it is advisable to obtain both PCA and IF test results and set additional weighting coefficients based on these results. When both are positive, the risk of AIG increases significantly, resulting in a higher additional weighting coefficient. Based on the additional weighting coefficient and the total score, a corrected total score is determined. Then, it is determined whether the corrected total score is greater than the upper limit; if so, the test accuracy is high, and the risk is classified as medium-high. Alternatively, it is determined whether the corrected total score is less than the lower limit; if so, there is a probability of misdiagnosis, and the risk is classified as medium-low.

[0065] This embodiment presents a non-invasive early warning method for autoimmune gastritis (AIG) according to the present invention. By acquiring user serological indicators, basic information indicators, symptom characteristics, and past medical history, it covers four dimensions: biomarkers, demographic characteristics, clinical manifestations, and disease history. This avoids the limitations of single-indicator screening, achieving a panoramic profile from "biomarkers-demographic characteristics-clinical manifestations-historical trajectory," providing a comprehensive data foundation for subsequent steps. Then, based on serological indicators, basic information indicators, symptom characteristics, and past medical history, serum risk score, basic risk score, symptom risk score, and disease risk score are determined. Complex risk factors are decomposed into four independent sub-risk assessments, avoiding weight confusion and facilitating subsequent univariate analysis. Finally, based on the serum risk score, basic risk score, symptom risk score, and disease risk score, the risk of AIG is assessed, enabling multi-dimensional information fusion decision-making. This enhances complementarity, synergy, and redundancy, allowing abnormalities in a single indicator to be corrected by other dimensions, avoiding overdiagnosis. This solves the problems of existing technologies being unable to timely assess the risk of AIG through non-invasive detection methods, thus improving assessment efficiency, reducing assessment costs, and increasing assessment accuracy.

[0066] On the other hand, the present invention also provides a non-invasive early warning device for autoimmune gastritis, comprising: The acquisition module 201 is used to acquire serological indicators, basic information indicators, symptom characteristics, and past medical history; The calculation module 202, connected to the acquisition module 201, is used to determine the serum risk score, basic risk score, symptom risk score and disease risk score based on serological indicators, basic information indicators, symptom characteristics and past medical history. The assessment module 203, connected to the calculation module 202, is used to assess the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

[0067] On the other hand, the present invention also provides a computer storage medium storing executable program code; the executable program code is used to execute any of the above-mentioned non-invasive early warning methods for autoimmune gastritis.

[0068] On the other hand, the present invention also provides a terminal device, including a memory and a processor; the memory stores program code that can be executed by the processor; the program code is used to execute any of the above-mentioned non-invasive early warning methods for autoimmune gastritis.

[0069] For example, the program code can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the program code in the terminal device.

[0070] The terminal device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the terminal device may also include input / output devices, network access devices, buses, etc.

[0071] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0072] The memory can be an internal storage unit of the terminal device, such as a hard drive or RAM. The memory can also be an external storage device of the terminal device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units of the terminal device. The memory is used to store the program code and other programs and data required by the terminal device. The memory can also be used to temporarily store data that has been output or will be output.

[0073] The aforementioned computer storage medium and terminal device are created based on the aforementioned non-invasive early warning method for autoimmune gastritis. Their technical functions and beneficial effects will not be elaborated here. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0074] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A non-invasive early warning method for autoimmune gastritis, characterized in that, include: Obtain serological markers, basic information markers, symptom characteristics, and past medical history; Serum risk score, basic information score, symptom risk score and disease risk score are determined based on serological indicators, basic information indicators, symptom characteristics and past medical history. The risk of developing AIG is assessed based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

2. The method according to claim 1, characterized in that, The steps for obtaining serological indicators include: extracting gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and iron / ferritin content; The steps for determining serum risk scores include: Determine whether the gastrin-17 content is greater than the gastrin threshold; if so, record the gastrin single item integral. Determine whether the PGI content is less than the first PGI threshold. If so, record the first-class integral of the PGI item. Determine whether the PGI content is less than the second PGI threshold. If so, record the second-class integral of the PGI item. The first PGI threshold is greater than the second PGI threshold. The second-class integral of the PGI item is greater than the first-class integral of the PGI item. Determine whether the PGI / II ratio is less than the first proportional threshold. If so, record the first-class integral of the PGI / II ratio. Determine whether the PGI / II ratio is less than the second proportional threshold. If so, record the second-class integral of the PGI / II ratio. If the first proportional threshold is greater than the second proportional threshold, the second-class integral of the PGI / II ratio is greater than the first-class integral of the PGI / II ratio. Determine whether the hemoglobin content is less than the hemoglobin threshold; if so, record the hemoglobin single item integral. Determine whether the iron / ferritin content is less than the iron / ferritin threshold; if so, record the iron / ferritin single item integral. Serum risk scores are determined based on individual scores for gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, and ferritin / ferritin.

3. The method according to claim 2, characterized in that, The steps for determining serum risk scores also include: Based on the correlation strength between each serological indicator and AIG, differentiated serum weighting coefficients were set for gastrin-17 content, PGI content, PGI / II ratio, hemoglobin content, and iron / ferritin content; among them, the serum weighting coefficients for PGI content and PGI / II ratio were higher than those for gastrin-17 content, hemoglobin content, and iron / ferritin content. Obtain Helicobacter pylori antibody and / or breath test results. If the test result is negative, increase the serum weighting coefficient of the gastrin single item score. If the test result is positive, decrease the serum weighting coefficient of the gastrin single item score. Serum risk scores are determined based on individual scores for gastrin, PGI (first-class score), PGI (second-class score), PGI / II ratio (first-class score), PGI / II ratio (second-class score), hemoglobin, ferritin, and the corresponding serum weighting coefficients.

4. The method according to claim 1, characterized in that, The steps to obtain basic information indicators include: Extract the user's gender and age; The steps to determine the basic risk score include: Determine whether the gender is female. If yes, record the first-order single term integral for gender; if no, record the second-order single term integral for gender. The first-order single term integral for gender is greater than the second-order single term integral for gender. Determine if the age is greater than the age threshold; if so, record the age integral. Obtain the deviation value between age and age threshold, and determine the age weight coefficient of the age single component based on the deviation value. The larger the age deviation value, the higher the age weight coefficient. The basic risk score is determined based on the individual score for gender (either first-class or second-class), the individual score for age, and the age weighting coefficient.

5. The method according to claim 1, characterized in that, The acquisition steps include: determining whether the user has symptoms such as loss of appetite, belching, postprandial fullness, and anemia; The steps for determining a symptom risk score include: If the user has poor appetite symptoms, extract the user's current food intake to determine the score for poor appetite. If belching symptoms are present, the frequency of belching is extracted to determine the belching component integral; If postprandial fullness symptoms are present, the duration of fullness is extracted to determine the fullness component score. If symptoms of anemia are present, hemoglobin levels are measured to determine the anemia score. The symptom risk score is determined based on the scores for poor appetite, belching, bloating, and anemia.

6. The method according to claim 1, characterized in that, The steps to obtain past medical history include: determining whether the user has a past medical history, including any one or more of the following: Hashimoto's thyroiditis, hypothyroidism, Sjögren's syndrome, primary biliary cirrhosis, vitiligo, rheumatoid arthritis, psoriasis, history of anemia, vitamin B12 deficiency, and subacute combined degeneration of the spinal cord. The steps for determining the risk score of past medical history include: If there is a history of illness, then a corresponding disease score and disease weight coefficient are determined for each existing disease; The disease risk score is determined based on the individual disease score and its weight coefficient for each existing disease.

7. The method according to claim 6, characterized in that, The steps for determining the corresponding disease-specific score and disease weight coefficient for each existing disease include: Determine if a disease is present and whether it is an immune disease; if so, record the immune single item score; otherwise, record the non-immune single item score; the immune single item score is higher than the non-immune single item score. Extract the disease duration and severity of each existing disease, and determine the disease weight coefficient for each existing disease; the longer the disease duration and the higher the severity, the higher the disease weight coefficient.

8. The method according to any one of claims 1-7, characterized in that, The steps for assessing the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score include: The total score is determined based on the serum risk score, baseline risk score, symptom risk score, and disease risk score. Determine if the total score exceeds the score limit; if so, it is considered high-risk. Determine if the total score is less than the lower limit of the score; if so, it is considered low risk. Determine if the total score is between the upper and lower limits of the score; if so, it is classified as medium risk.

9. The method according to claim 8, characterized in that, If the risk level is determined to be medium, the steps for assessing the risk of AIG also include: Obtain the PCA and IF test results, determine whether both are positive. If so, set an additional weighting coefficient greater than 1; otherwise, set an additional weighting coefficient less than 1. Determine the corrected total integral based on the additional weighting coefficient and the total integral. Determine whether the total score after correction is greater than the upper limit of the score; if so, it is judged as medium to high risk. Determine whether the total score after correction is less than the lower limit of the score; if so, it is classified as low to medium risk.

10. A non-invasive early warning device for autoimmune gastritis, characterized in that, For implementing the method of any one of claims 1 to 9, comprising: The acquisition module is used to acquire serological indicators, basic information indicators, symptom characteristics, and past medical history. The calculation module is used to determine the serum risk score, basic risk score, symptom risk score, and disease risk score based on serological indicators, basic information indicators, symptom characteristics, and past medical history. The assessment module is used to assess the risk of AIG based on serum risk score, baseline risk score, symptom risk score, and disease risk score.

Images