Intelligent analysis, prediction and early warning method and system for health status of chronic kidney disease

Abstract

The present invention discloses a method and system for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, and relates to the technical field of medical data analysis and prediction. The method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease obtains several historical health measurement data of the patient, and the historical health measurement data includes historical blood data, historical urine data, and historical physiological data; the historical health measurement data of each time of the patient is evaluated and analyzed respectively. The present invention integrates and dynamically analyzes the historical blood, urine and physiological data to construct a health assessment index for each time, and combines these indexes to form a comprehensive view of the health status of the kidney. Compared with traditional methods, this method can more accurately predict changes in renal function and potential lesions by considering multiple health dimensions and using trend analysis of historical data, and solves the problem of misjudgment that may be caused by a single data point in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data analysis and prediction, and specifically to a method and system for intelligent analysis, prediction and early warning of the health status of chronic kidney disease. Background Art

[0002] Chronic kidney disease (CKD) is a major public health problem worldwide, with an increasing incidence and prevalence, especially among the elderly. The progression of CKD leads to a gradual loss of kidney function, and may eventually require dialysis or kidney transplantation. Therefore, early diagnosis and timely treatment are crucial to delay disease progression and improve patient prognosis.

[0003] In the existing chronic kidney disease management strategy, doctors mainly rely on regular blood and urine tests to monitor the patient's renal function status. These methods include the determination of blood creatinine and urea nitrogen levels, as well as qualitative and quantitative analysis of urine protein. However, these traditional monitoring methods have the limitations of lag, discontinuity, and non-comprehensiveness. In view of these challenges in the management of chronic kidney disease, an intelligent analysis, prediction and early warning method for the health status of chronic kidney disease has emerged.

[0004] Prior art, such as the invention patent application with announcement number: CN116564511A, discloses a method, device and equipment for predicting the health status of chronic diseases, wherein the prediction method includes: fusing the basic information feature representation and the dynamic follow-up data feature representation to form fused data; processing the fused data through a multi-head self-attention mechanism to form processed data; processing the processed data based on the first fully connected layer to form a chronic disease health prediction result. Targetedly separating basic information and follow-up data, and modeling the follow-up data into a time series form, provides a complete solution based on time series data mining for the prediction of chronic disease follow-up patients, designs a personalized self-attention fusion mechanism and applies it to the model, and effectively improves the prediction accuracy.

[0005] Based on the above scheme, it is found that the limitations of the existing technology include at least the following problems. First, the existing chronic kidney disease monitoring methods often rely on single or intermittent health assessments, which makes it difficult to fully capture the dynamic changes in the patient's health status. Especially in chronic disease management, slight changes in the condition may have a significant impact on the patient's long-term health. Second, the existing assessment methods fail to comprehensively consider the patient's multi-dimensional health data, which can easily lead to limitations and deviations in the assessment results, making it difficult to fully reflect the patient's true health status. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, which solves the problem that the existing chronic kidney disease monitoring methods often rely on single or intermittent health assessments, making it difficult to fully capture the dynamic changes in the patient's health status, especially in chronic disease management, where slight changes in the condition may have a significant impact on the patient's long-term health. Secondly, the existing evaluation methods fail to comprehensively consider the patient's multi-dimensional health data, which can easily lead to limitations and deviations in the evaluation results, making it difficult to fully reflect the patient's true health status.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, comprising the following steps: obtaining historical health measurement data of the patient for several times in history, wherein the historical health measurement data includes historical blood data, historical urine data and historical physiological data; evaluating and analyzing the historical health measurement data of the patient for each time in history, respectively, to obtain the patient's historical blood health assessment index, historical urine health assessment index and historical physiological health assessment index for each time in history; comprehensively analyzing the patient's historical blood health assessment index, historical urine health assessment index and historical physiological health assessment index for each time in history, respectively, to obtain the patient's kidney health status assessment index for each time in history; performing difference analysis on the patient's kidney health status assessment index for each time in history with a preset kidney health status assessment threshold, and judging whether a warning is needed based on the difference analysis results.

[0008] Furthermore, the historical blood data specifically include historical creatinine concentration values, historical urea nitrogen concentration values, historical blood calcium concentration values, historical blood phosphorus concentration values, and historical albumin concentration values; the historical urine data specifically include historical urine protein concentration values ​​and historical urine sodium concentration values; and the historical physiological data specifically include historical blood pressure values ​​and historical BMI index.

[0009] Furthermore, the specific steps for obtaining the patient's historical blood health assessment index for each time in history are as follows: obtain the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value; comprehensively analyze the patient's historical creatinine concentration value, historical urea nitrogen concentration value, historical blood calcium concentration value, historical blood phosphorus concentration value, and historical albumin concentration value in history, combined with the creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value, to obtain the patient's historical blood health assessment index for each time in history.

[0010] Furthermore, the specific formula for calculating the patient's historical blood health assessment index at each time is as follows: ;in, Patient history Historical blood health assessment index, Patient history The historical creatinine concentration values ​​of is the patient's creatinine concentration reference value, is the creatinine concentration coefficient, Patient history The historical urea nitrogen concentration values, is the reference value of urea nitrogen concentration in patients, is the urea nitrogen concentration coefficient, Patient history The historical blood calcium concentration values ​​of is the patient's blood calcium concentration reference value, is the blood calcium concentration coefficient, Patient history The historical blood phosphorus concentration values, is the patient's blood phosphorus concentration reference value, is the blood phosphorus concentration coefficient, Patient history The historical albumin concentration values ​​of is the reference value of albumin concentration in patients, is the albumin concentration coefficient, , , The number of historical times obtained.

[0011] Furthermore, the specific steps for obtaining the patient's historical urine health assessment index for each time in history are as follows: obtain the patient's urine protein concentration reference value and urine sodium concentration reference value; comprehensively analyze the patient's historical urine protein concentration value and historical urine sodium concentration value in combination with the urine protein concentration reference value and urine sodium concentration reference value to obtain the patient's historical urine health assessment index for each time in history.

[0012] Furthermore, the specific formula for calculating the patient's historical urine health assessment index for each time is as follows: ;in, Patient history The historical urine health assessment index, Patient history The historical urine protein concentration values ​​of is the reference value of urine protein concentration of the patient, is the urine protein concentration coefficient, Patient history The historical urine sodium concentration values, is the reference value of urine sodium concentration for patients, is the urine sodium concentration coefficient, is a natural constant, , , The number of historical times obtained.

[0013] Furthermore, the specific steps for obtaining the patient's historical physiological health assessment index for each time in history are as follows: obtaining the patient's blood pressure reference value and BMI reference index; comprehensively analyzing the patient's historical blood pressure value and historical BMI index for each time in history in combination with the blood pressure reference value and BMI reference index, respectively, to obtain the patient's historical blood pressure assessment value and historical BMI assessment value for each time in history; performing weighted analysis on the patient's historical blood pressure assessment value and historical BMI assessment value for each time in history, respectively, to obtain the patient's historical physiological health assessment index for each time in history; wherein, the specific formula for calculating the patient's historical physiological health assessment index for each time in history is as follows: ;in, Patient history Historical blood pressure assessment values, Patient history The historical blood pressure values ​​of is the patient's blood pressure reference value, Patient history Historical BMI assessment values, Patient history The historical BMI index, is the patient's BMI reference index, Patient history The historical physiological health assessment index, is the blood pressure coefficient, is the BMI coefficient, , , The number of historical times obtained.

[0014] Furthermore, the specific formula for calculating the patient's kidney health status assessment index at each time in history is as follows: ;in, Patient history The kidney health status assessment index is Patient history Historical blood health assessment index, is the blood health coefficient, Patient history The historical urine health assessment index, is the urine health factor, Patient history The historical physiological health assessment index, is the physiological health coefficient, is a natural constant, , , The number of historical times obtained.

[0015] Furthermore, the specific steps of performing difference analysis on the patient's historical kidney health status assessment indicators for each time and the preset kidney health status assessment threshold, and judging whether an early warning is needed based on the difference analysis results are as follows: performing difference analysis on the patient's historical kidney health status assessment indicators for each time and the preset kidney health status assessment threshold, and obtaining the difference in the patient's historical kidney health status assessment for each time; comparing and analyzing the difference in the patient's historical kidney health status assessment for each time and the preset difference threshold, and counting the number of times the kidney health status assessment difference is higher than the preset difference threshold; if the number of times the kidney health status assessment difference is higher than the preset difference threshold is higher than the preset number threshold, a chronic kidney disease health warning is sent.

[0016] The intelligent analysis, prediction and early warning system for the health status of chronic kidney disease includes: a data acquisition module, an index analysis module, a health assessment module and an early warning judgment module; the data acquisition module is used to obtain several historical health measurement data of the patient, and the historical health measurement data includes historical blood data, historical urine data and historical physiological data; the index analysis module is used to evaluate and analyze the historical health measurement data of the patient each time in history, and obtain the historical blood health assessment index, historical urine health assessment index and historical physiological health assessment index of the patient each time in history; the health assessment module is used to comprehensively analyze the historical blood health assessment index, historical urine health assessment index and historical physiological health assessment index of the patient each time in history, and obtain the kidney health status assessment index of the patient each time in history; the early warning judgment module is used to perform difference analysis on the kidney health status assessment index of the patient each time in history with the preset kidney health status assessment threshold, and judge whether a warning is needed based on the difference analysis result.

[0017] The present invention has the following beneficial effects:

[0018] (1) This intelligent analysis, prediction and early warning method for the health status of chronic kidney disease integrates and dynamically analyzes historical blood, urine and physiological data to construct a health assessment index for each time, and combines these indices to form a comprehensive view of the health status of the kidneys. Compared with traditional methods, this method can more accurately predict changes in renal function and potential lesions by considering multiple health dimensions and using trend analysis of historical data, solving the problem of misjudgment that may be caused by a single data point in existing technologies.

[0019] (2) This intelligent analysis, prediction and early warning method for the health status of chronic kidney disease can automatically trigger a health warning by comparing the patient's current kidney health assessment indicators with the preset thresholds, and promptly notify medical personnel and patients of potential health risks. This data-driven early warning method overcomes the delay problem of existing technologies in early warning response and improves the agility of dealing with possible acute attacks of chronic kidney disease, thereby taking necessary medical or lifestyle intervention measures at an early stage.

[0020] (3) The intelligent analysis, prediction and early warning method for the health status of chronic kidney disease allows continuous monitoring of the patient's health status and adjustment of the treatment plan based on the specific data of each patient, thereby achieving personalized health management. By continuously evaluating and updating health status assessment indicators, medical providers can better understand the patient's health trends, accurately adjust treatment plans, and minimize the impact of chronic kidney disease on the patient's quality of life.

[0021] (4) The intelligent analysis, prediction and early warning system for the health status of chronic kidney disease has achieved the systematization and automation of chronic kidney disease management by establishing a comprehensive system including a data acquisition module, an index analysis module, a health assessment module and an early warning judgment module. The system not only automatically collects and processes the patient's multi-dimensional health data, but also comprehensively evaluates the kidney health status through intelligent algorithms and automatically performs early warning judgments. This fully automatic process reduces the workload of medical personnel in data processing and preliminary diagnosis, allowing them to devote more time and resources to direct care and complex decision-making for patients, thereby improving the efficiency and quality of medical services. Through real-time data updates and processing, the system ensures that medical decisions are based on the latest health information, increases the timeliness and accuracy of treatment, and thus improves the success rate of patient treatment and the continuity of health management.

[0022] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of the method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease of the present invention.

[0024] Figure 2 This is a flowchart of the specific steps of obtaining the patient's historical blood health assessment index for each time in the intelligent analysis, prediction and early warning method for chronic kidney disease health status of the present invention.

[0025] Figure 3 The present invention is a flowchart of the specific steps of obtaining the patient's historical urine health assessment index for each time in the intelligent analysis, prediction and early warning method for chronic kidney disease health status.

[0026] Figure 4This is a block diagram of the intelligent analysis, prediction and early warning system for the health status of chronic kidney disease of the present invention. DETAILED DESCRIPTION

[0027] The embodiments of the present application solve the problem that existing chronic kidney disease monitoring methods often rely on single or intermittent health assessments, which makes it difficult to fully capture the dynamic changes in the patient's health status, especially in chronic disease management. Minor changes in the condition may have a significant impact on the patient's long-term health. Secondly, the existing assessment methods fail to comprehensively consider the patient's multi-dimensional health data, which can easily lead to limitations and deviations in the assessment results, making it difficult to fully reflect the patient's true health status.

[0028] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0029] First, collect the patient's historical health measurement data, including historical blood data, urine data and physiological data. These data include creatinine concentration, urea nitrogen concentration, blood calcium concentration, blood phosphorus concentration, albumin concentration, urine protein concentration, urine sodium concentration, blood pressure and BMI index. Perform a detailed analysis of the collected historical health measurement data, calculate the historical blood health assessment index, urine health assessment index and physiological health assessment index. Then, conduct a comprehensive analysis of these indexes to form a comprehensive kidney health status assessment index. Perform a difference analysis between the obtained kidney health status assessment index and the preset health threshold, and determine whether to trigger a health warning based on the analysis results. If the assessment index shows potential health risks, the system will automatically send a warning to notify medical staff and patients to take necessary intervention measures.

[0030] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, comprising the following steps: using an electronic health record system to obtain a patient's historical health measurement data for several times in history, the historical health measurement data including historical blood data, historical urine data, and historical physiological data; evaluating and analyzing each of the patient's historical health measurement data in history, respectively, to obtain the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index for each time in history; comprehensively analyzing the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index for each time in history, respectively, to obtain the patient's kidney health status assessment index for each time in history; performing difference analysis on the patient's kidney health status assessment index for each time in history and a preset kidney health status assessment threshold, and judging whether a warning is needed based on the difference analysis result.

[0031] The historical blood data specifically include historical creatinine concentration values ​​(creatinine is a product of muscle metabolism, filtered and excreted through the kidneys. The creatinine concentration in the blood can reflect the filtration function of the kidneys, usually expressed in milligrams per deciliter or micromoles per liter), historical urea nitrogen concentration values ​​(urea nitrogen is a waste product formed after protein metabolism in the body, mainly excreted through the kidneys. It is an indicator for evaluating kidney function. A high level may indicate renal insufficiency, usually expressed in milligrams per deciliter), historical blood calcium concentration values ​​(blood calcium refers to the concentration of calcium ions in the blood, an important electrolyte, which is crucial for a variety of biological processes, such as nerve conduction, muscle contraction, bone health, etc. Abnormal blood calcium levels may affect heart function and bone health, usually expressed in milligrams per deciliter or millimoles per liter), historical blood phosphorus concentration values ​​(blood phosphorus is the concentration of phosphorus ions in the blood, which is necessary for maintaining bones and teeth. A mineral essential for dental health, it interacts with calcium and is involved in energy metabolism. Abnormal blood phosphorus levels may indicate kidney function problems, usually expressed in milligrams per deciliter or millimoles per liter), historical albumin concentration values ​​(albumin is one of the most abundant proteins in plasma, responsible for maintaining the colloidal osmotic pressure of the blood, transporting hormones, drugs and other substances, low albumin levels can be an indicator of malnutrition, liver disease or kidney disease, usually expressed in grams per liter), historical urine data specifically includes historical urine protein concentration values ​​(urine protein is the protein content in urine, high levels indicate kidney damage, usually expressed in milligrams per deciliter), historical urine sodium concentration values ​​(urine sodium is the sodium content in urine, reflecting the kidney's ability to handle electrolytes and its role in the body's water balance, usually expressed in millimoles per liter), historical physiological data specifically includes historical blood pressure values ​​and historical BMI index.

[0032] Specifically, Figure 2 As shown, the specific steps for obtaining the patient's historical blood health assessment index for each time in history are as follows: obtain the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value; comprehensively analyze the patient's historical creatinine concentration value, historical urea nitrogen concentration value, historical blood calcium concentration value, historical blood phosphorus concentration value, and historical albumin concentration value in history, combined with the creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value, to obtain the patient's historical blood health assessment index for each time in history.

[0033] The specific formula for calculating the patient's historical blood health assessment index for each time is as follows: ;in, Patient history Historical blood health assessment index, Patient history The historical creatinine concentration values ​​of is the patient's creatinine concentration reference value, is the creatinine concentration coefficient, Patient history The historical urea nitrogen concentration values, is the reference value of urea nitrogen concentration in patients, is the urea nitrogen concentration coefficient, Patient history The historical blood calcium concentration values ​​of is the patient's blood calcium concentration reference value, is the blood calcium concentration coefficient, Patient history The historical blood phosphorus concentration values, is the patient's blood phosphorus concentration reference value, is the blood phosphorus concentration coefficient, Patient history The historical albumin concentration values ​​of is the reference value of albumin concentration in patients, is the albumin concentration coefficient, , , The number of historical times obtained.

[0034] It needs to be explained that the specific steps for obtaining the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value are: obtain the patient's creatinine concentration reference range, urea nitrogen concentration reference range, blood calcium concentration reference range, blood phosphorus concentration reference range, and albumin concentration reference range from the hospital or clinic's electronic health record (EHR) system, and analyze them to obtain, for example: take the middle value of the patient's creatinine concentration reference range as the patient's creatinine concentration reference value.

[0035] , , , , The specific calculation process is: standardize the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value, and perform sum analysis after standardization to obtain the blood reference sum value, and then perform ratio analysis on the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value after standardization with the blood reference sum value, and the ratio result is the corresponding coefficient.

[0036] In this embodiment, by obtaining the patient's specific biochemical index reference values ​​and comparing the actual measurement values ​​each time with these reference values, the patient's health status can be evaluated more accurately. This method not only takes into account the individual differences of patients, but also can dynamically adjust the evaluation criteria according to the specific circumstances of each patient, thereby realizing truly personalized medical services. Such accuracy and personalization are particularly important for chronic disease management, because the health status of patients may vary greatly due to individual differences. By continuously monitoring the patient's historical health data and comparing these data with the set thresholds, the method can issue timely warnings when there are significant changes in the patient's health status. This timely warning mechanism can enable doctors and patients to take quick action, such as adjusting treatment plans or taking preventive measures, thereby preventing the condition from worsening and reducing the risk of acute attacks. By analyzing a large amount of historical data, long-term trends and potential risk factors in health status can be revealed. This data-driven approach not only increases the transparency and reliability of decision-making, but also helps medical providers discover health problems that are not easily perceived. In addition, systematic data analysis can provide in-depth insights to help medical teams optimize treatment strategies and improve treatment outcomes and patient satisfaction.

[0037] Specifically, Figure 3 As shown, the specific steps for obtaining the patient's historical urine health assessment index for each time in history are as follows: obtain the patient's urine protein concentration reference value and urine sodium concentration reference value; comprehensively analyze the patient's historical urine protein concentration value and historical urine sodium concentration value in combination with the urine protein concentration reference value and urine sodium concentration reference value to obtain the patient's historical urine health assessment index for each time in history.

[0038] The specific formula for calculating the patient's historical urine health assessment index for each time is as follows: ;in, Patient history The historical urine health assessment index, Patient history The historical urine protein concentration values ​​of is the reference value of urine protein concentration of the patient, is the urine protein concentration coefficient, Patient history The historical urine sodium concentration values, is the reference value of urine sodium concentration for patients, is the urine sodium concentration coefficient, is a natural constant, , , The number of historical times obtained.

[0039] It needs to be explained that the specific steps for obtaining the patient's urine protein concentration reference value and urine sodium concentration reference value are: obtain the patient's urine protein concentration reference range and urine sodium concentration reference range from the hospital or clinic's electronic health record (EHR) system, and analyze them to obtain, for example: take the middle value of the patient's urine protein concentration reference range as the patient's urine protein concentration reference value.

[0040] , The specific calculation process is: standardize the patient's urine protein concentration reference value and urine sodium concentration reference value, and perform sum analysis after standardization to obtain the urine reference sum value, and then perform ratio analysis on the patient's urine protein concentration reference value and urine sodium concentration reference value after standardization with the urine reference sum value, and the ratio result is the corresponding coefficient.

[0041] In this embodiment, using urine protein and urine sodium concentration as key indicators, combined with the patient's individual reference values ​​for evaluation, can more accurately reflect the state of renal function. Abnormal urine protein usually indicates glomerular damage, while changes in urine sodium concentration reflect the kidney's ability to regulate electrolyte balance. Through accurate monitoring of these indicators, doctors can detect potential kidney problems earlier, so as to intervene before the condition becomes serious and improve the effectiveness of treatment. By comparing historical data with individualized reference values, this method can not only identify subtle changes in health status, but also adjust treatment plans according to individual circumstances. This personalized data processing method allows medical providers to customize more refined management plans for each patient, including adjustments to drug dosages and lifestyle change recommendations, thereby improving the targetedness and efficiency of treatment. Through systematic data analysis, the method can continuously monitor the patient's urine health status and trigger warnings when key indicators show important changes. This timely warning system can significantly reduce the occurrence of acute kidney injury events, alleviate the condition or prevent the condition from worsening through early intervention. In addition, continuous data tracking also helps to evaluate the effectiveness of treatment. Doctors can adjust treatment strategies based on these data feedback to achieve the best treatment effect.

[0042] Specifically, the specific steps for obtaining the patient's historical physiological health assessment index for each time in history are as follows: obtain the patient's blood pressure reference value and BMI reference index; conduct a comprehensive analysis of the patient's historical blood pressure value and historical BMI index in combination with the blood pressure reference value and BMI reference index to obtain the patient's historical blood pressure assessment value and historical BMI assessment value for each time in history; conduct a weighted analysis of the patient's historical blood pressure assessment value and historical BMI assessment value for each time in history to obtain the patient's historical physiological health assessment index for each time in history.

[0043] The specific formula for calculating the patient's historical physiological health assessment index is as follows: ;in, Patient history Historical blood pressure assessment values, Patient history The historical blood pressure values ​​of is the patient's blood pressure reference value, Patient history Historical BMI assessment values, Patient history The historical BMI index, is the patient's BMI reference index, Patient history The historical physiological health assessment index, is the blood pressure coefficient, is the BMI coefficient, , , The number of historical times obtained.

[0044] It needs to be explained that the specific steps for obtaining the patient's blood pressure reference value and BMI reference index are: obtain the patient's blood pressure reference range and BMI reference range from the hospital or clinic's electronic health record (EHR) system, and analyze them, for example: take the middle value of the patient's blood pressure reference range as the patient's blood pressure reference value.

[0045] , The specific calculation process is: standardize the patient's blood pressure reference value and BMI reference index, and perform sum analysis after standardization to obtain the physiological reference and value, and then perform ratio analysis on the patient's blood pressure reference value and BMI reference index after standardization with the physiological reference and value, and the ratio result is the corresponding coefficient.

[0046] In this embodiment, by combining blood pressure and BMI for analysis, a more comprehensive perspective is provided to evaluate the patient's physiological health status. Both blood pressure and BMI are important physiological indicators that affect the progression of chronic kidney disease, and they have a profound impact on the patient's overall health. Through this comprehensive assessment, doctors can better understand the patient's health status, especially in cardiovascular health and weight management, two areas that are closely related to kidney disease. By continuously monitoring these physiological indicators and comparing them with historical data, this method can help doctors promptly detect small changes in the patient's health status, so that they can intervene before the problem becomes a serious health threat. For example, for small changes in blood pressure or abnormal changes in BMI, early identification and treatment can prevent possible complications such as heart disease and other kidney disease-related conditions. By specifically analyzing each patient's historical data and calculating a personalized physiological health assessment index, doctors can develop a more personalized treatment plan based on the specific situation of each patient. This personalized treatment method takes into account not only the patient's medical needs, but also their lifestyle and other health factors, thereby optimizing the treatment effect and improving the patient's quality of life.

[0047] Specifically, the specific formula for calculating the patient's kidney health status assessment index at each time in history is as follows: ;in, Patient history The kidney health status assessment index is Patient history Historical blood health assessment index, is the blood health coefficient, Patient history The historical urine health assessment index, is the urine health factor, Patient history The historical physiological health assessment index, is the physiological health coefficient, is a natural constant, , , The number of historical times obtained.

[0048] It needs to be explained that , , The specific calculation process of is: the standardized patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value are respectively combined with the creatinine concentration coefficient, urea nitrogen concentration coefficient, blood calcium concentration coefficient, blood phosphorus concentration coefficient, and albumin concentration coefficient for weighted analysis to obtain the blood health reference index; the standardized patient's urine protein concentration reference value and urine sodium concentration reference value are respectively combined with the urine protein concentration coefficient and the urine sodium concentration coefficient for weighted analysis to obtain the urine health reference index; the standardized patient's blood pressure reference value and BMI reference index are respectively combined with the blood pressure coefficient and the BMI coefficient for weighted analysis to obtain the physiological health reference index; then the blood health reference index, urine health reference index, and physiological health reference index are summed and analyzed to obtain the health reference sum value; then the blood health reference index, urine health reference index, and physiological health reference index are ratio analyzed with the health reference sum value, and the ratio analysis result is the corresponding coefficient.

[0049] In this embodiment, a comprehensive health snapshot is provided by integrating data from blood, urine, and physiological health indicators into a single assessment model. This comprehensive assessment allows for more accurate identification of a patient's health risks and disease states because it covers multiple physiological aspects that are directly related to kidney health. This comprehensiveness is particularly critical in assessing chronic disease states and can help medical providers make more comprehensive diagnostic and treatment decisions. By comparing each patient's measured values ​​with personalized reference values ​​and using coefficients to weigh the impact of each indicator, this method is able to provide a highly personalized health assessment, which not only improves the accuracy of the assessment, but also ensures that treatment recommendations can be optimized for the specific needs of individual patients. For example, if a patient's urine protein index is abnormally high, it significantly affects Impact on overall health assessment results, treatment can place special emphasis on the management and control of proteinuria, by continuously tracking these comprehensive health assessment indices, medical providers can identify changes in health status early, especially those that may lead to worsening renal function, early warning systems can prompt earlier intervention, thereby possibly preventing the disease from progressing to a more serious stage, such early identification and intervention are the key to improving long-term health outcomes and reducing the need for advanced medical care, through accurate health status assessment and timely warning, medical resources can be allocated more efficiently, for example, those patients who show signs of potential health problems can be given priority for further examination and treatment, while those stable patients can reduce unnecessary medical visits, which not only improves the efficiency of medical services, but also reduces overall medical costs.

[0050] Specifically, the specific steps of performing difference analysis on the patient's historical kidney health status assessment indicators for each time and the preset kidney health status assessment threshold, and judging whether an early warning is needed based on the difference analysis results are as follows: performing difference analysis on the patient's historical kidney health status assessment indicators for each time and the preset kidney health status assessment threshold, to obtain the difference in the patient's historical kidney health status assessment for each time; comparing and analyzing the difference in the patient's historical kidney health status assessment for each time with the preset difference threshold, and counting the number of times the kidney health status assessment difference is higher than the preset difference threshold; if the number of times the kidney health status assessment difference is higher than the preset difference threshold is higher than the preset number threshold, a chronic kidney disease health warning is sent to relevant staff, and medical advice is sent to the patient.

[0051] In this implementation scheme, the patient's historical kidney health status assessment indicators are obtained. These indicators are obtained by analyzing historical health measurement data, including the comprehensive results of blood health assessment index, urine health assessment index and physiological health assessment index. Preset kidney health status assessment thresholds are obtained. These thresholds are set based on clinical experience and related research, and represent the boundaries of kidney function under different health states. By using specific preset thresholds, the system can be adjusted according to individual differences of different patients, thereby improving the accuracy and personalization of the assessment. By combining multiple health status assessment indexes, this method provides a comprehensive health status assessment model that is more predictive and sensitive than a single indicator. The difference between each measured kidney health status assessment indicator and the corresponding preset threshold is calculated to obtain the kidney health status assessment difference. This difference reflects the degree of deviation between the patient's current health status and the normal range. Difference analysis can provide an intuitive metric to help identify abnormal changes in the patient's health status and help to more quickly identify the deterioration of kidney function. This method overcomes the lag problem in the prior art and, through refined Difference calculation can identify health problems earlier and provide timely warnings. The difference of each kidney health status assessment is compared with the preset difference threshold. The difference threshold indicates the degree of deviation that should cause vigilance. Through multiple difference comparisons, false alarms caused by single abnormalities can be prevented, and the reliability and stability of the early warning system can be improved. The warning will only be triggered when the deviation reaches a certain number of times, which can reduce unnecessary intervention. This process solves the "over-sensitivity" problem in traditional early warning systems, that is, it avoids unnecessary alarms caused by one-time abnormal data and ensures that warnings are only issued when real health risks exist. If the number of times the difference is higher than the preset difference threshold exceeds the preset number threshold, the system will automatically send a chronic kidney disease health warning to relevant staff and patients, and provide medical advice. This early warning mechanism ensures that patients can get timely medical advice and intervention before their condition worsens, helping to delay the progression of the disease and improve the patient's long-term health prognosis. Through the automated early warning system, continuous monitoring and early intervention of chronic kidney disease patients are achieved, which significantly improves the efficiency of chronic disease management and reduces the burden on patients and the medical system.

[0052] See also Figure 4The embodiment of the present invention provides a technical solution: an intelligent analysis, prediction and early warning system for the health status of chronic kidney disease, including: a data acquisition module, an index analysis module, a health assessment module, and an early warning judgment module; the data acquisition module is used to obtain the patient's historical health measurement data for several times in history, and the historical health measurement data includes historical blood data, historical urine data, and historical physiological data; the index analysis module is used to evaluate and analyze the patient's historical health measurement data for each time in history, and obtain the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index for each time in history; the health assessment module is used to comprehensively analyze the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index for each time in history, and obtain the patient's historical kidney health status assessment index for each time; the early warning judgment module is used to perform difference analysis on the patient's historical kidney health status assessment index for each time with a preset kidney health status assessment threshold, and judge whether a warning is needed based on the difference analysis result.

[0053] In summary, this application has at least the following effects:

[0054] By integrating and dynamically analyzing historical blood, urine and physiological data to construct each health assessment index, and combining these indices to form a comprehensive view of kidney health status, this method can more accurately predict changes in kidney function and potential lesions by considering multiple health dimensions and using trend analysis of historical data compared to traditional methods, solving the problem of misjudgment that may be caused by a single data point in existing technologies.

[0055] By comparing the patient's current kidney health assessment indicators with preset thresholds, it can automatically trigger health warnings and promptly notify medical staff and patients of potential health risks. This data-driven warning method overcomes the delay problem of existing technologies in warning response and improves the agility of dealing with possible acute attacks of chronic kidney disease, thereby taking necessary medical or lifestyle interventions in the early stages.

[0056] It allows continuous monitoring of the patient's health status and adjusts the treatment plan based on the specific data of each patient, thereby achieving personalized health management. By continuously evaluating and updating health status assessment indicators, medical providers can better understand the patient's health trends, accurately adjust treatment plans, and minimize the impact of chronic kidney disease on the patient's quality of life.

[0057] By establishing a comprehensive system including data acquisition module, index analysis module, health assessment module and early warning judgment module, the systematization and automation of chronic kidney disease management is achieved. The system not only automatically collects and processes the patient's multi-dimensional health data, but also comprehensively evaluates the kidney health status through intelligent algorithms and automatically performs early warning judgments. This fully automatic process reduces the workload of medical staff in data processing and preliminary diagnosis, allowing them to devote more time and resources to direct care and complex decision-making for patients, thereby improving the efficiency and quality of medical services. Through real-time data updates and processing, the system ensures that medical decisions are based on the latest health information, increases the timeliness and accuracy of treatment, and thus improves the success rate of patient treatment and the continuity of health management.

[0058] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0059] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, characterized in that: The following steps are involved: Acquire a number of historical health measurement data of the patient, wherein the historical health measurement data includes historical blood data, historical urine data, and historical physiological data; Evaluate and analyze the patient's historical health measurement data at each time, and obtain the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index; Comprehensively analyze the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index to obtain the patient's historical kidney health status assessment index; Perform differential analysis on the patient's historical kidney health status assessment indicators and the preset kidney health status assessment thresholds, and determine whether an early warning is needed based on the differential analysis results; The historical blood data specifically include historical creatinine concentration values, historical urea nitrogen concentration values, historical blood calcium concentration values, historical blood phosphorus concentration values, and historical albumin concentration values; the historical urine data specifically include historical urine protein concentration values ​​and historical urine sodium concentration values; and the historical physiological data specifically include historical blood pressure values ​​and historical BMI index; The specific steps to obtain the patient's historical blood health assessment index at each time are as follows: Obtain the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value; The patient's historical creatinine concentration value, historical urea nitrogen concentration value, historical blood calcium concentration value, historical blood phosphorus concentration value, and historical albumin concentration value are combined with the creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value for comprehensive analysis to obtain the patient's historical blood health assessment index for each time; The specific formula for calculating the patient's historical blood health assessment index at each time is as follows: Among them, Lx i is the patient's historical blood health assessment index for the i-th time, Lj i is the patient's historical creatinine concentration value for the i-th time, Cj is the patient's creatinine concentration reference value, α1 is the creatinine concentration coefficient, Ln i is the patient's historical urea nitrogen concentration value for the i-th time, Cn is the patient's urea nitrogen concentration reference value, α2 is the urea nitrogen concentration coefficient, Lg i is the patient's historical blood calcium concentration value for the i-th time, Cg is the patient's blood calcium concentration reference value, α3 is the blood calcium concentration coefficient, Lp i is the patient's historical blood phosphorus concentration value for the i-th time, Cp is the patient's blood phosphorus concentration reference value, α4 is the blood phosphorus concentration coefficient, Lb i is the patient's historical albumin concentration value at the i-th time, Cb is the patient's albumin concentration reference value, α5 is the albumin concentration coefficient, α1+α2+α3+α4+α5=1, i=1,2,3,…,i0, i0 is the number of historical acquisitions; Among them, the specific calculation process of α1, α2, α3, α4, and α5 is: standardize the patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value, and perform sum analysis after standardization to obtain the blood reference sum value, and then perform ratio analysis on the standardized patient's creatinine concentration reference value, urea nitrogen concentration reference value, blood calcium concentration reference value, blood phosphorus concentration reference value, and albumin concentration reference value with the blood reference sum value, and the ratio result is the corresponding coefficient; The specific steps for obtaining the patient's historical urine health assessment index for each time are as follows: Obtain the patient's urine protein concentration reference value and urine sodium concentration reference value; The patient's historical urine protein concentration value and historical urine sodium concentration value are combined with the urine protein concentration reference value and urine sodium concentration reference value for comprehensive analysis to obtain the patient's historical urine health assessment index; The specific formula for calculating the patient's historical urine health assessment index for each time is as follows: Among them, Ly i is the patient's historical urine health assessment index for the i-th time, Ld i is the patient's historical urine protein concentration value for the i-th time, Cd is the patient's urine protein concentration reference value, β1 is the urine protein concentration coefficient, LnN i is the patient's historical urine sodium concentration value for the i-th time, LnC is the patient's urine sodium concentration reference value, β2 is the urine sodium concentration coefficient, e is a natural constant, β1+β2=1, i=1,2,3,…,i0, i0 is the number of historical acquisitions; The specific calculation process of β1 and β2 is as follows: the reference values ​​of urine protein concentration and urine sodium concentration of the patient are standardized, and then summed and analyzed after the standardization to obtain the urine reference sum value, and then the reference values ​​of urine protein concentration and urine sodium concentration of the patient after the standardization are respectively analyzed with the urine reference sum value, and the ratio result is the corresponding coefficient; The specific steps to obtain the patient's historical physiological health assessment index for each time are as follows: Obtain the patient's blood pressure reference value and BMI reference index; The patient's historical blood pressure values ​​and historical BMI index are combined with the blood pressure reference value and BMI reference index for comprehensive analysis to obtain the patient's historical blood pressure assessment value and historical BMI assessment value; Perform weighted analysis on the patient's historical blood pressure assessment values ​​and historical BMI assessment values ​​to obtain the patient's historical physiological health assessment index; The specific formula for calculating the patient's historical physiological health assessment index is as follows: Among them, XyP i is the patient's historical blood pressure assessment value for the i-th time, LxY i is the patient's historical blood pressure value for the i-th time, LxC is the patient's blood pressure reference value, BmP i is the patient's historical BMI assessment value at the i-th time, LbM i is the patient's historical BMI index for the i-th time, LbC is the patient's BMI reference index, Ls i is the patient's historical physiological health assessment index for the i-th time, ω1 is the blood pressure coefficient, ω2 is the BMI coefficient, ω1+ω2=1,i=1,2,3,…,i0,i0 is the number of historical acquisitions; The specific formula for calculating the patient's kidney health status assessment index at each time in history is as follows: Among them, SzP i is the patient's history of kidney health status assessment index for the i-th time, Lx i is the patient's historical blood health assessment index for the i-th time, ξ1 is the blood health coefficient, Ly i is the patient's historical urine health assessment index for the i-th time, ξ2 is the urine health coefficient, Ls i is the patient's historical physiological health assessment index for the i-th time, ξ3 is the physiological health coefficient, e is a natural constant, ξ1+ξ2+ξ3=1, i=1,2,3,…,i0, i0 is the number of historical acquisitions; The specific steps of performing differential analysis on the patient's historical kidney health status assessment indicators and the preset kidney health status assessment thresholds, and judging whether an early warning is needed based on the differential analysis results are as follows: Performing difference analysis on the patient's kidney health status assessment index at each time in history and the preset kidney health status assessment threshold, to obtain the difference of the patient's kidney health status assessment at each time in history; Compare and analyze the difference in the patient's kidney health status assessment at each time in history with the preset difference threshold, and count the number of times the difference in the kidney health status assessment is higher than the preset difference threshold; If the difference in the kidney health status assessment is higher than the preset difference threshold number of times, and higher than the preset number threshold, a chronic kidney disease health warning is sent.

2. A system for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, using the method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease according to claim 1, characterized in that: include: Data acquisition module, index analysis module, health assessment module, early warning judgment module; The data acquisition module is used to acquire the patient's historical health measurement data for several times, wherein the historical health measurement data includes historical blood data, historical urine data, and historical physiological data; The index analysis module is used to evaluate and analyze the patient's historical health measurement data at each time, and obtain the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index at each time; The health assessment module is used to comprehensively analyze the patient's historical blood health assessment index, historical urine health assessment index, and historical physiological health assessment index to obtain the patient's historical kidney health status assessment index; The early warning judgment module is used to perform difference analysis on the patient's historical kidney health status assessment indicators and preset kidney health status assessment thresholds, and judge whether an early warning is needed based on the difference analysis results.

Images