Hemodialysis on-line monitoring system and method

Abstract

The invention relates to the technical field of hemodialysis monitoring, and provides a hemodialysis on-line monitoring system and method, and the system comprises a data acquisition module which is used for collecting blood physiological parameters in a dialysis pipeline in real time; the blood component analysis module is connected with a blood loop of the dialysis machine and is used for detecting serum iron, ferritin and ferritin saturation indexes on line; and the data processing module is used for calculating the risk index of anemia, evaluating the iron utilization rate, constructing a model for measuring the iron deficiency erythropoiesis trend according to the collected and analyzed data, and training and optimizing the model. According to the method, individual parameters of patients are fused, personalized calculation is performed for iron metabolism rates and dialysis parameters of different patients, and data such as iron content, blood flow and dialysis fluid volume are acquired online in real time, so that iron concentration and infusion rate are accurately matched with real-time iron metabolism requirements of the patients, and anemia of the patients in the dialysis process is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of hemodialysis monitoring, and particularly to an online hemodialysis monitoring system and method. Background Art

[0002] Hemodialysis is the core treatment method for maintaining the life of end-stage renal disease patients. By removing metabolic wastes in the body and regulating the balance of water, salts and electrolytes, the internal environment stability of patients is maintained. During the dialysis process, the monitoring of patients' physiological indicators is the key to ensuring the treatment effect. Especially the iron content monitoring directly affects the anemia treatment effect and iron metabolism balance. Precise iron content monitoring and iron agent regulation are important links to optimize the dialysis quality and improve the patients' quality of life.

[0003] However, the existing technology has obvious deficiencies in monitoring the iron content in the blood of dialysis patients. Patients will have their blood iron content checked before hemodialysis, which leads to low detection frequency and lag, relying on regular laboratory tests and being unable to capture the dynamic changes of iron content during dialysis in real time, resulting in delays in adjusting the iron agent concentration and infusion rate, and it is difficult to meet the timely needs of patients. Moreover, in the face of the rough control method of patients' blood iron concentration, using fixed empirical doses without accurately calculating dynamic parameters such as blood flow rate, dialysate volume, and individual iron metabolism rate, it is easy to cause iron deficiency or overdose, increasing the risk of complications such as organ damage and unable to meet the clinical requirements of precision and safety in treatment. Summary of the Invention

[0004] Aiming at the problems existing in the prior art, the purpose of the present invention is to provide an online hemodialysis monitoring system and method to solve the problems raised in the above background art.

[0005] To solve the above problems, the present invention adopts the following technical solutions: An online hemodialysis monitoring system, including: A data acquisition module for real-time collecting blood physiological parameters in the dialysis pipeline. The blood physiological parameters include but are not limited to hemoglobin concentration, blood oxygen saturation, and hematocrit, and the collection frequency is dynamically adjusted in real time within 1 - 60 times per minute; A blood component analysis module connected to the blood circuit of the dialysis machine for online detecting serum iron, ferritin, and ferritin saturation index; A data processing module for calculating the risk index of anemia, evaluating the iron utilization rate, constructing a model for measuring the trend of iron-deficient erythropoiesis based on the collected and analyzed data, and training and optimizing the model; An early warning output module for generating hierarchical early warning information and transmitting it to users and medical staff through data transmission technology; A dialysis parameter adjustment module for adjusting the parameters of the dialysis machine by the system after receiving the early warning signal; An adaptive sampling module, which is used to dynamically adjust the detection frequency by using an adaptive sampling algorithm according to the iron metabolism kinetic curve and the dynamic prediction result of iron content; An iron supplementation control module, which is used to adjust the concentration and infusion rate of iron in the dialysate in real time according to the dynamic predicted value of iron content and the iron metabolism demand of the patient.

[0006] Preferably, the calculation formula for the adaptive sampling module to dynamically adjust the sampling frequency in real time is , where is the adjusted sampling frequency, is the initial sampling frequency, is the influence coefficient of the risk score on the frequency, is the risk score of the patient's physical basic condition.

[0007] Preferably, the formula for the data processing module to calculate the risk index of the patient during dialysis is , where is the risk index of anemia of the patient during dialysis, is the change gradient of the patient's hemoglobin concentration, is the sampling time interval, is the oxygen saturation at the venous end, is the hematocrit, is the risk score of the patient's physical basic condition.

[0008] Preferably, the formula for the data processing module to construct a model for predicting the trend of iron deficiency erythropoiesis is , where is the probability of iron deficiency, is the linear combination value, and , where is the intercept term, is the serum iron content, is the ferritin content, is the transferrin saturation, is the hemoglobin content, is the reticulocyte count, is C-reactive protein, is the dialysis vintage, , , , , , , are all influence factor coefficients multiplied by them.

[0009] Preferably, the formula for the iron supplementation control module to calculate the adjustment amount of the patient's iron metabolism demand is , where is the adjusted amount of iron metabolism demand, is the proportionality coefficient, and the value range is [0.1 - 0.5], is the integral coefficient, and the value range is [0.01 - 0.1], is the differential coefficient, and the value range is [0.001 - 0.01], is the time interval, and the value range is [10min - 15min], is the cumulative value of errors in the previous 4 cycles, is the error of the current iron content.

[0010] The on - line hemodialysis monitoring method is applied to the on - line hemodialysis monitoring system described in any one of the above, and is characterized by including the following steps: S1. Continuously collect the optical characteristic values of hemoglobin in the venous line through an optical fiber sensor. The collection process uses an adaptive sampling technique to dynamically adjust the sampling frequency according to the change of the optical characteristic values of hemoglobin; S2. Activate on - line iron metabolism detection every 15 - 30min to obtain the dynamic concentration spectrum of serum iron; S3. Compare the hemoglobin change rate with the preset patient baseline data to calculate the anemia progression index; S4. Analyze the spatio - temporal distribution characteristics of iron metabolism parameters based on a reinforcement learning model, and continuously interact with the environment to learn the optimal decision - making strategy; S5. When an anemia warning is triggered during the patient's dialysis process, automatically generate a visual warning report and send it to the APP terminals of the patient and medical staff, and at the same time adaptively adjust the infusion rate and infusion concentration of iron agents in the dialysate according to the algorithm model.

[0011] Preferably, in the step S5, the generated visual warning report includes: The real - time trend curve of hemoglobin concentration is superimposed with the EPO usage mark. Using real - time dynamic update technology, the change of hemoglobin concentration is displayed in real - time, and the usage time and dose of EPO are clearly shown through different colors and marks; The radar chart of iron metabolism parameters shows the dynamic balance of ferritin, transferrin saturation, and serum iron, intuitively demonstrating the mutual relationship and dynamic changes among iron metabolism parameters; The risk heat map shows the anemia development probability in different time windows. Using color - coding technology, the high and low of the anemia development probability are intuitively represented by the depth of different colors.

[0012] The beneficial effects of the on - line hemodialysis monitoring system and method provided by the present invention are: 1. By integrating the individual parameters of patients, personalized calculations are performed on the iron metabolism rate and dialysis parameters of different patients, breaking through the limitations of traditional unified schemes, achieving precise treatment of "one policy for one person", and online real-time collection of data such as iron content, blood flow rate, and dialysis fluid volume. Combining the iron agent concentration and infusion rate dynamic adjustment formula, the iron agent supply parameters are calculated and optimized in a timely manner, so that the iron agent concentration and infusion rate accurately match the real-time iron metabolism needs of patients, reducing the occurrence of anemia in patients during dialysis, significantly improving the hemoglobin level of patients, reducing the possibility of other complications during dialysis, and ensuring the safety of patients during dialysis.

[0013] 2. Through the automated operation of the system, the workload of manual calculation and parameter adjustment by medical staff is reduced. At the same time, visual data such as the iron concentration trend chart and predicted remaining iron supplement amount are output in real time to assist medical staff in making quick decisions and optimizing the dialysis treatment process. It not only focuses on iron content monitoring, but also integrates multi-dimensional parameters such as blood flow rate and dialysis fluid volume. Through the formula model, the correlations between parameters are comprehensively analyzed to comprehensively evaluate the iron metabolism status, providing richer diagnostic and treatment information for clinical practice, supporting more scientific treatment adjustment strategies, and maintaining the iron metabolism balance of patients through continuous real-time monitoring and precise regulation, reducing dialysis-related complications caused by iron metabolism disorders, improving the long-term prognosis of patients, enhancing the quality of life, and reducing the repeated treatment costs caused by iron metabolism problems in the long term. Brief Description of the Drawings

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 It is a schematic diagram of the system module of the hemodialysis online monitoring system and method provided by this application. Detailed Embodiments

[0016] The following will further describe in detail the specific embodiments of the present invention in conjunction with the drawings in the specification and the embodiments. The following embodiments are only used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0017] As Figure 1 shown, this embodiment proposes a hemodialysis online monitoring system, including: A data acquisition module for real-time collection of blood physiological parameters in the dialysis pipeline. The blood physiological parameters include but are not limited to hemoglobin concentration, blood oxygen saturation, and hematocrit, and the collection frequency is dynamically adjusted in real time between 1 and 60 times per minute; A blood component analysis module, connected to the blood circuit of the dialysis machine, for on-line detection of serum iron, ferritin and ferritin saturation index; A data processing module, for calculating the anemia risk index, evaluating iron utilization rate, constructing a model for measuring the trend of iron-deficient erythropoiesis, and training and optimizing the model based on the collected and analyzed data; An early warning output module, for generating graded early warning information and transmitting it to users and medical staff through data transmission technology; A dialysis parameter adjustment module, for adjusting the parameters of the dialysis machine by the system after receiving the early warning signal; An adaptive sampling module, for dynamically adjusting the detection frequency by using an adaptive sampling algorithm according to the iron metabolism kinetic curve and the dynamic prediction result of iron content; A iron supplement control module, for adjusting the concentration and infusion rate of iron agent in the dialysate in real time according to the dynamic predicted value of iron content and the iron metabolism demand of the patient.

[0018] In this embodiment, the calculation formula for the adaptive sampling module to dynamically adjust the sampling frequency in real time is , where is the adjusted sampling frequency, is the initial sampling frequency, is the influence coefficient of the risk score on the frequency, is the risk score of the patient's physical basic condition, and , where , , , are the weight coefficients of each parameter, is the mapping function of the patient's age, is the mapping function of the severity of the patient's underlying disease, is the patient's gender, taking values of 0 or 1, is the early warning information, taking values of 0 or 1.

[0019] In this embodiment, the formula for the data processing module to calculate the risk index of the patient during dialysis is , where is the anemia risk index of the patient during dialysis, is the change gradient of the patient's hemoglobin concentration, is the sampling time interval, is the oxygen saturation at the venous end, is the hematocrit, is the risk score of the patient's physical basic condition, and the formula for evaluating iron utilization rate is , where is the iron utilization rate, is the amount of iron supplemented, is the blood volume, and , where is the height, is the weight, , are the calculation coefficients related to height and weight respectively, is a constant, supplementing other influencing factors not covered by height and weight. For men, , , , for women, , , .

[0020] In this embodiment, the formula for the data processing module to construct the model of the trend of iron-deficient erythropoiesis is , where is the probability of iron deficiency, is the linear combination value, and , where is the intercept term, is the serum iron content, is the ferritin content, is the transferrin saturation, is the hemoglobin content, is the reticulocyte count, is C-reactive protein, is the dialysis vintage, , , , , , , are all the influencing factor coefficients multiplied by them.

[0021] In this embodiment, the formula for the iron supplementation control module to calculate the adjustment amount of the patient's iron metabolism demand is , where is the adjustment amount of the iron metabolism demand, is the proportionality coefficient, and the value range is [0.1 - 0.5], is the integral coefficient, and the value range is [0.01 - 0.1], is the differential coefficient, and the value range is [0.001 - 0.01], is the time interval, and the value range is [10min - 15min], is the cumulative value of the errors in the previous 4 cycles, is the error of the current iron content, and , where is the target iron concentration, is the current iron concentration. The adjusted formula for calculating the iron infusion concentration is based on the adjusted amount result of the patient's iron metabolism requirement. , where is the concentration of iron in the dialysate, is the volume of the dialysate, is the blood flow rate, and The safe range is [1mg / L - 5mg / L]. The adjusted formula for calculating the iron infusion rate is based on the adjusted amount result of the patient's iron metabolism requirement. , where is the iron infusion rate, is the bioavailability of the iron agent, and The safe range of is [0mg / min - 2mg / min].

[0022] Specifically, by integrating the individual parameters of the patient, personalized calculations are performed for the iron metabolism rate and dialysis parameters of different patients, breaking through the limitations of the traditional unified plan, achieving precise treatment of "one policy for one person", and online real-time collection of data such as iron content, blood flow rate, and dialysate volume. Combining the dynamic adjustment formulas of iron agent concentration and infusion rate, timely calculation and optimization of iron agent supply parameters are carried out to make the iron agent concentration and infusion rate precisely match the real-time iron metabolism requirements of the patient, reduce the occurrence of anemia in the patient during dialysis, significantly improve the patient's hemoglobin level, reduce the possibility of other complications during dialysis, and ensure the safety of the patient during dialysis.

[0023] A method for online monitoring of hemodialysis, applied to the online monitoring system for hemodialysis in any of the above, is characterized by including the following steps: S1. Continuously collect the optical characteristic values of hemoglobin in the venous pipeline through an optical fiber sensor. The adaptive sampling technology is adopted during the collection process, and the sampling frequency is dynamically adjusted according to the change of the optical characteristic values of hemoglobin; S2. Activate the online iron metabolism detection every 15 - 30 minutes to obtain the dynamic concentration spectrum of serum iron; S3. Compare the hemoglobin change rate with the preset baseline data of the patient to calculate the anemia progression index; S4. Analyze the spatio-temporal distribution characteristics of iron metabolism parameters based on the reinforcement learning model, and continuously interact with the environment to learn the optimal decision-making strategy; S5. When an anemia warning is triggered during the patient's dialysis process, automatically generate a visual warning report and send it to the APP terminals of the patient and medical staff, and at the same time adaptively adjust the infusion rate and infusion concentration of the iron agent in the dialysate according to the algorithm model.

[0024] In this embodiment, in step S5, the generated visual warning report includes: The real-time trend curve of hemoglobin concentration is overlaid with EPO usage markers. Using real-time dynamic update technology, it shows the changes in hemoglobin concentration in real time, and clearly displays the usage time and dosage of EPO through different colors and markers; The radar chart of iron metabolism parameters shows the dynamic balance of ferritin, transferrin saturation, and serum iron, intuitively demonstrating the interrelationships and dynamic changes among iron metabolism parameters; The risk heat map shows the probability of anemia development in different time windows. Using color coding technology, it intuitively represents the high or low probability of anemia development through the shades of different colors.

[0025] Specifically, through the automated operation of the system, it reduces the workload of manual calculation and parameter adjustment by medical staff. At the same time, it outputs visual data such as the iron concentration trend chart and prediction of remaining iron supplementation in real time, assisting medical staff in making quick decisions and optimizing the dialysis treatment process. It not only focuses on iron content monitoring but also integrates multi-dimensional parameters such as blood flow rate and dialysate volume, comprehensively analyzes the correlations among parameters through a formula model, comprehensively evaluates the iron metabolism status, provides richer diagnosis and treatment information for clinical practice, supports more scientific treatment adjustment strategies, and through continuous real-time monitoring and precise regulation, maintains the iron metabolism balance of patients, reduces dialysis-related complications caused by iron metabolism disorders, improves the long-term prognosis of patients, enhances the quality of life, and reduces the repeated treatment costs caused by iron metabolism problems in the long term.

[0026] The above embodiments are only used to illustrate the present invention, rather than limiting the present invention. Although the present invention has been described in detail with reference to the embodiments, those of ordinary skill in the art should understand that various combinations, modifications, or equivalent replacements of the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and should all be covered within the scope of the claims of the present invention.

Claims

1. An online monitoring system for hemodialysis, characterized in that, Comprising: A data acquisition module for real-time collection of blood physiological parameters in the dialysis tubing. The blood physiological parameters include, but are not limited to, hemoglobin concentration, blood oxygen saturation, and hematocrit, and the collection frequency is dynamically adjusted in real time within 1 - 60 times per minute; A blood component analysis module connected to the blood circuit of the dialysis machine for on-line detection of serum iron, ferritin, and ferritin saturation index; A data processing module for calculating the anemia risk index, evaluating iron utilization rate, constructing a model for measuring the trend of iron-deficient erythropoiesis based on the collected and analyzed data, and training and optimizing the model; An early warning output module for generating hierarchical early warning information and transmitting it to users and medical staff through data transmission technology; A dialysis parameter adjustment module for adjusting the parameters of the dialysis machine by the system after receiving the warning signal; An adaptive sampling module for dynamically adjusting the detection frequency using an adaptive sampling algorithm based on the iron metabolism kinetic curve and the dynamic prediction result of iron content; A iron supplement control module for adjusting the concentration and infusion rate of iron in the dialysis fluid in real time according to the dynamic predicted value of iron content and the iron metabolism requirements of the patient.

2. The online blood dialysis monitoring system according to claim 1, characterized in that, The calculation formula for the adaptive sampling module to dynamically adjust the acquisition frequency in real time is , where is the adjusted acquisition frequency,[[]] is the initial acquisition frequency,[[]] is the influence coefficient of the risk score on the frequency,[[]] is the risk score of the patient's physical basic condition.[[]] 3. The hemodialysis online monitoring system according to claim 2, wherein, The formula for the data processing module to calculate the risk index of a patient during dialysis is , where is the risk index of anemia of the patient during dialysis, is the change gradient of the patient's hemoglobin concentration, is the sampling time interval, is the oxygen saturation at the venous end, is the hematocrit, is the risk score of the patient's physical basic condition.

4. The on-line blood dialysis monitoring system according to claim 2, wherein The formula for the data processing module to construct the iron deficiency erythropoiesis trend model is , where is the iron deficiency probability, is the linear combination value.

5. The online blood dialysis monitoring system according to claim 1, wherein The formula for the iron supplementation control module to calculate the adjustment amount of the patient's iron metabolism demand is , where is the adjustment amount of iron metabolism demand, is the proportionality coefficient, and its value range is [0.1 - 0.5], is the integral coefficient, and its value range is [0.01 - 0.1], is the differential coefficient, and its value range is [0.001 - 0.01], is the time interval, and its value range is [10 min - 15 min], is the cumulative value of errors in the previous 4 cycles, is the error of the current iron content.

6. A method for on-line monitoring of hemodialysis, applied to the on-line hemodialysis monitoring system according to any one of claims 1-5, characterized in that, Including the following steps: S1. Continuously collect the hemoglobin optical characteristic values in the venous tubing through an optical fiber sensor. The adaptive sampling technology is adopted during the collection process, and the sampling frequency is dynamically adjusted according to the change of the hemoglobin optical characteristic values; S2. Activate the on-line iron metabolism detection every 15 - 30 minutes to obtain the dynamic concentration spectrum of serum iron; S3. Compare the hemoglobin change rate with the preset patient baseline data to calculate the anemia progression index; S4. Analyze the spatio-temporal distribution characteristics of iron metabolism parameters based on the reinforcement learning model, and continuously interact with the environment to learn the optimal decision-making strategy; S5. When an anemia warning is triggered during the patient's dialysis process, automatically generate a visual warning report and send it to the APP terminals of the patient and medical staff, and at the same time adaptively adjust the infusion rate and infusion concentration of iron in the dialysis fluid according to the algorithm model.

7. The online blood dialysis monitoring method according to claim 6, wherein In the step S5, the generated visual warning report includes: The real-time trend curve of hemoglobin concentration is superimposed with the EPO usage mark. The real-time dynamic update technology is adopted to display the change of hemoglobin concentration in real time, and the usage time and dose of EPO are clearly shown through different colors and marks; The radar chart of iron metabolism parameters shows the dynamic balance of ferritin, transferrin saturation, and serum iron, intuitively demonstrating the mutual relationship and dynamic changes among iron metabolism parameters; The risk heat map shows the anemia development probability in different time windows, and the color coding technology is adopted to intuitively represent the high and low anemia development probability through the depth of different colors.

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