Hemodialysis patient glucose metabolism management system based on real-time blood glucose monitoring

Abstract

The invention relates to the technical field of medical equipment, and particularly discloses a hemodialysis patient glucose metabolism management system based on real-time blood glucose monitoring, which comprises a real-time blood glucose monitoring module, a glucose metabolism data analysis module, an individualized treatment scheme generation module, an automatic intervention module, a data management and remote monitoring module, a safety and calibration module and the like. The real-time blood glucose monitoring module collects data through a high-precision sensor, and the data analysis module predicts the blood glucose trend through machine learning in combination with patient information and dialysis parameters. The scheme generation module generates insulin adjustment, dialysate optimization and nutrition suggestion schemes according to the insulin adjustment, dialysate optimization and nutrition suggestion schemes; the automatic intervention module executes the scheme and performs early warning; the data module stores uploaded data, and the security module guarantees accuracy and security. The blood glucose real-time monitoring and dynamic intervention are realized, the blood metabolism management effect of the hemodialysis patient is improved, the complication risk is reduced, and the clinical application value is high.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, specifically to a glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring. Background Technology

[0002] Hemodialysis is an important treatment for end-stage renal disease patients to maintain their lives. Among hemodialysis patients, the proportion of those with diabetes is relatively high. These patients, or other hemodialysis patients with glucose metabolism disorders, often face significant risks of blood glucose fluctuations during and before and after dialysis.

[0003] Traditional blood glucose monitoring methods primarily rely on finger-prick blood glucose testing or intermittent data collection from continuous glucose monitoring (CGM) devices. The former requires frequent punctures, causing pain for patients and failing to reflect real-time blood glucose trends; the latter, while providing relatively continuous data, still suffers from data update delays, making it difficult to meet the real-time blood glucose monitoring needs of the specific treatment scenario of hemodialysis. More importantly, traditional monitoring methods lack a systematic integration with individual patient characteristics (such as age, weight, and history of diabetes) and dialysis parameters (such as dialysate composition and blood flow velocity). Healthcare professionals often rely on experience to develop treatment plans, resulting in insufficient targeting and an inability to dynamically adapt to changes in blood glucose levels. This increases the incidence of hypoglycemia or hyperglycemia, potentially leading to cardiovascular events, infections, and other complications, impacting patient prognosis and quality of life.

[0004] Therefore, developing a system that can monitor blood glucose in real time and accurately, and dynamically adjust treatment plans based on individual patient data to achieve systematic glucose metabolism management is of great practical significance and clinical value for improving the treatment safety and prognosis of hemodialysis patients, especially those with diabetes. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring, so as to realize real-time monitoring, intelligent analysis and individualized intervention of patients' blood glucose, and reduce the risk of complications.

[0006] To solve the above-mentioned technical problems, the technical solution provided by the present invention is: a glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring, including a real-time blood glucose monitoring module, a glucose metabolism data analysis module, an individualized treatment plan generation module, an automatic intervention module, a data management and remote monitoring module, and a safety and calibration module;

[0007] The real-time blood glucose monitoring module uses an electrochemical sensor to collect patients' blood glucose level data in real time through dialysis fluid or blood, and transmits the collected blood glucose data to the central processing system in real time.

[0008] The glucose metabolism data analysis module is connected to the central processing system to obtain real-time blood glucose data from the central processing system, and at the same time collect patient basic information and dialysis parameters. It performs comprehensive analysis on the obtained real-time blood glucose data, patient basic information and dialysis parameters. The glucose metabolism data analysis module has a built-in intelligent algorithm to predict the patient's blood glucose change trend based on the comprehensive analysis results and to assess the patient's glucose metabolism status.

[0009] The individualized treatment plan generation module is connected to the glucose metabolism data analysis module and is used to generate an individualized treatment plan for the patient based on the real-time blood glucose data and glucose metabolism analysis results output by the glucose metabolism data analysis module. The individualized treatment plan includes an insulin dose adjustment plan, a dialysate glucose concentration optimization plan, and nutritional intervention recommendations.

[0010] The automatic intervention module is equipped with an insulin pump and a high-glucose solution injection pump. The automatic intervention module is connected to the individualized treatment plan generation module and is used to automatically adjust the insulin infusion volume of the insulin pump or the high-glucose solution infusion volume of the high-glucose solution injection pump according to the treatment plan generated by the individualized treatment plan generation module. When the patient is detected to have a risk of hypoglycemia, the module automatically controls the high-glucose solution injection pump to push the high-glucose solution. When the patient is detected to have a risk of hyperglycemia, the module automatically controls the insulin pump to adjust the insulin dose.

[0011] The data management and remote monitoring module integrates a data storage unit to record the patient's historical blood glucose data, generated treatment plans, and treatment effect data. At the same time, the data management and remote monitoring module supports uploading the recorded data to the hospital information system to enable doctors to remotely monitor the patient's condition and remotely adjust the treatment plan.

[0012] The safety and calibration module is connected to the real-time blood glucose monitoring module and is used to provide automatic calibration function for the real-time blood glucose monitoring module. The safety and calibration module has multiple built-in safety mechanisms to prevent system misoperation or excessive intervention to patients.

[0013] Furthermore, the patient's basic information includes the patient's age, weight, height, gender, duration of diabetes history, type of diabetes, previous blood glucose control status, presence of other underlying diseases, and medication history; the dialysis parameters include the electrolyte concentration of the dialysate, dialysate temperature, blood flow rate, dialysis time, dialyzer model, and dialysate flow rate.

[0014] Furthermore, the intelligent algorithm built into the glucose metabolism data analysis module adopts a machine learning-based prediction model. The prediction model uses historical blood glucose data, patient basic information, and dialysis parameters as training samples to continuously learn and update the model parameters. Moreover, when assessing the patient's glucose metabolism status, the intelligent algorithm combines the amplitude of blood glucose fluctuations, the proportion of time when blood glucose reaches the target level, and the glycated hemoglobin level for comprehensive evaluation.

[0015] Furthermore, when generating an insulin dosage adjustment plan, the individualized treatment plan generation module calculates the adjustment range of insulin dosage based on the difference between the patient's real-time blood glucose value and the target blood glucose range, the rate of blood glucose change, and the patient's sensitivity coefficient to insulin. When generating an optimized dialysate glucose concentration plan, the individualized treatment plan generation module calculates an appropriate dialysate glucose concentration by combining the patient's blood glucose level, dialysate flow rate, and dialysis time. The nutritional intervention recommendations include daily carbohydrate intake, protein intake, fat intake, and recommendations for meal time and frequency, and these recommendations are dynamically adjusted based on the patient's weight change trend and blood glucose control.

[0016] Furthermore, the automatic intervention module also includes a blood glucose risk warning unit, which is connected to the glucose metabolism data analysis module and is used to receive the blood glucose change trend and glucose metabolism status assessment results output by the glucose metabolism data analysis module. When it is predicted that the patient is likely to experience hypoglycemia or hyperglycemia within the next 30 minutes, a warning signal is issued in advance. The warning signal includes an audible warning and a visual warning, and the warning information is transmitted to the data management and remote monitoring module.

[0017] Furthermore, the data management and remote monitoring module also includes a data query and statistics unit. This unit is used by medical staff to query the patient's historical blood glucose data, treatment plan, and treatment effect data based on the patient's name, hospitalization number, or dialysis time range. It can also perform statistical analysis on the patient's average blood glucose level, blood glucose fluctuation range, number of hypoglycemic events, and number of hyperglycemic events within a selected time period, and generate corresponding statistical reports. These statistical reports can be exported to Excel or PDF formats.

[0018] Furthermore, the security and calibration module incorporates multiple security mechanisms, including:

[0019] (1) Operation permission management mechanism: different levels of operation permissions are set. Only medical staff with the corresponding permissions can modify system parameters and adjust treatment plans. Ordinary operators can only view patient data and system operation status.

[0020] (2) Dosage limit mechanism: Limit the maximum single insulin infusion volume of the insulin pump and the maximum single high glucose solution infusion volume of the high glucose solution injection pump. When the calculated insulin or high glucose solution infusion volume exceeds the set limit, the infusion operation is automatically prohibited and an alarm signal is issued.

[0021] (3) Abnormal data detection mechanism: Real-time monitoring of blood glucose data transmitted by the sensor. When abnormal fluctuations or deviations from the normal physiological range are detected in the blood glucose data, the intervention operation is automatically paused and medical staff are prompted to check and calibrate the sensor.

[0022] (4) Equipment fault alarm mechanism: The operating status of each module of the system is monitored in real time. When a fault is detected in the insulin pump, high sugar solution injection pump or sensor, a fault alarm signal is immediately issued and the fault module and fault type are displayed in the data management and remote monitoring module.

[0023] The advantages of this invention compared to the prior art are:

[0024] The glucose metabolism data analysis module of this invention combines multi-dimensional basic information of patients with dialysis parameters and uses machine learning algorithms to accurately predict blood glucose trends. The individualized treatment plan generation module dynamically adjusts insulin dosage, dialysate glucose concentration and nutritional recommendations based on real-time data, avoiding the limitations of traditional empirical treatment and significantly improving the targeting of treatment.

[0025] The automatic intervention module of this invention realizes automatic early warning and precise intervention when blood glucose is abnormal, reducing the delay of manual operation; the multiple safety mechanisms and automatic calibration function of the safety and calibration module effectively prevent the risks caused by misoperation, excessive intervention and equipment failure, and ensure the stable operation of the system and patient safety.

[0026] The data management and remote monitoring module of this invention supports remote data transmission, query and statistics, allowing medical staff to monitor patients' conditions and adjust treatment plans anytime and anywhere. The touch screen and voice input functions of the human-computer interaction module simplify the operation process and improve the convenience of clinical use.

[0027] This invention forms a complete closed loop from blood glucose monitoring, analysis, and protocol generation to intervention and data management through the collaborative work of multiple modules. It effectively optimizes glucose metabolism management for hemodialysis patients, reduces the incidence of blood glucose-related complications, and improves patient prognosis and quality of life. Attached Figure Description

[0028] Figure 1 This is a system block diagram of the glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring, as described in this invention. Detailed Implementation

[0029] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0030] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0031] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0032] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0033] The following is a detailed description of the glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring, in conjunction with the accompanying drawings.

[0034] Combined with appendix Figure 1 This invention will be described in detail below.

[0035] A glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring includes a real-time blood glucose monitoring module, a glucose metabolism data analysis module, a personalized treatment plan generation module, an automatic intervention module, a data management and remote monitoring module, and a safety and calibration module. To facilitate system operation and human-computer interaction, the invention can also add a human-computer interaction module and a wireless communication module. Each module achieves data interaction through the wireless communication module, forming a complete closed loop for glucose metabolism management.

[0036] 1. Real-time blood glucose monitoring module

[0037] Employing a high-precision electrochemical sensor with a detection error of no more than ±5% and a response time of no more than 10 seconds, the sensor surface features a biocompatible coating (such as a polyethylene glycol coating) to reduce biological reactions (such as protein adsorption and hemolysis) between the sensor and the patient's blood or dialysate, extending the sensor's lifespan (up to 72 hours per use). This module connects to the hemodialysis tubing or dialysate circulation system to collect real-time blood glucose level data and transmits the data to the central processing system via a wireless communication module, ensuring a data transmission delay of no more than 1 second.

[0038] 2. Glucose metabolism data analysis module

[0039] Connected to a central processing system, the system acquires real-time blood glucose data and simultaneously collects basic patient information and dialysis parameters. Basic patient information includes age, weight, height, gender, duration of diabetes history, type of diabetes (type 1 / type 2), previous blood glucose control (e.g., glycated hemoglobin levels over the past 3 months), other underlying diseases (e.g., hypertension, coronary heart disease), and medication history (e.g., whether insulin or oral hypoglycemic agents are used). Dialysis parameters include dialysate electrolyte concentration (e.g., potassium, sodium, calcium concentration), dialysate temperature (36-37℃), blood flow rate (200-300 mL / min), dialysis time (2-4 hours), dialyzer model, and dialysate flow rate (500 mL / min).

[0040] The glucose metabolism data analysis module incorporates a machine learning-based intelligent algorithm. Using historical blood glucose data, basic patient information, and dialysis parameters from over 1000 clinically collected hemodialysis patients as training samples, a predictive model is constructed using a gradient boosting tree algorithm. The model is periodically (quarterly) updated with new clinical data to improve prediction accuracy. Based on real-time, multi-dimensional data, the algorithm predicts the patient's blood glucose trend over the next 30 minutes. It also considers the magnitude of blood glucose fluctuations (the difference between the maximum and minimum blood glucose values ​​within 24 hours), the percentage of time blood glucose reaches the target range (the percentage of time blood glucose is within the target range, set at 4.4-10.0 mmol / L or 3.9-8.3 mmol / L depending on the patient's age and comorbidities), and glycated hemoglobin levels to comprehensively assess the patient's glucose metabolism status (categorized as good, fair, or poor).

[0041] 3. Personalized treatment plan generation module

[0042] Connected to the glucose metabolism data analysis module, based on the real-time blood glucose data and glucose metabolism analysis results output by this module, a personalized treatment plan is generated, specifically including:

[0043] Insulin dose adjustment plan: Based on the difference between the patient's real-time blood glucose value and the target blood glucose range, the rate of blood glucose change (such as the change in blood glucose every 5 minutes), and the patient's sensitivity coefficient to insulin (calculated based on weight and diabetes type), the insulin dose adjustment range is determined by the formula "Insulin adjustment dose = (real-time blood glucose value - target blood glucose value) × sensitivity coefficient - basal insulin dose". The adjustment range for a single adjustment shall not exceed 2U.

[0044] Optimization of dialysate glucose concentration: Based on the patient's real-time blood glucose level, dialysate flow rate, and dialysis time, the appropriate dialysate glucose concentration (range 0-11 mmol / L) is calculated using a dynamic equation. For example, when the patient's blood glucose is below 4.4 mmol / L, the dialysate glucose concentration is increased to 5.6-7.8 mmol / L, and when the blood glucose is above 10.0 mmol / L, glucose-free dialysate is used.

[0045] Nutritional intervention recommendations: Based on the patient's weight change trend (weight fluctuations over the past month), blood glucose control, and nutritional needs before and after dialysis, daily carbohydrate intake (calculated at 3-5g per kilogram of body weight), protein intake (calculated at 1.2-1.5g per kilogram of body weight), and fat intake (accounting for 25%-30% of total calories) recommendations are generated. At the same time, the meal times (1 hour before dialysis, 2 hours during dialysis, and 1 hour after dialysis) and meal frequency (5-6 meals per day) are specified, and the nutritional recommendations are dynamically adjusted according to the patient's weekly blood glucose monitoring results.

[0046] 4. Automatic intervention module

[0047] Equipped with a high-precision insulin pump (infusion accuracy of 0.05U / infusion) and a high-glucose solution injection pump (infusion accuracy of 0.1mL / infusion), it connects to a personalized treatment plan generation module and automatically adjusts the infusion volume according to the generated treatment plan. At the same time, this module has a blood glucose risk warning unit, which connects to the glucose metabolism data analysis module. When it is predicted that the patient may experience hypoglycemia (blood glucose below 3.9mmol / L) or hyperglycemia (blood glucose above 13.9mmol / L) within the next 30 minutes, it immediately issues an audible warning (60-80dB) and a light warning (flashing red light at a frequency of 1 time / second) and transmits the warning information to the data management and remote monitoring module.

[0048] During the intervention, if the patient's blood glucose is below 3.9 mmol / L, the automatic control high glucose solution infusion pump will inject 50% glucose solution at a dose of 0.5 mL / kg body weight. Blood glucose will be re-monitored 5 minutes after the injection is completed until the blood glucose rises to above 4.4 mmol / L. If the patient's blood glucose is above 13.9 mmol / L, the automatic control insulin pump will adjust the dose according to the treatment plan, and blood glucose will be monitored once an hour until the blood glucose drops below 10.0 mmol / L.

[0049] 5. Data Management and Remote Monitoring Module

[0050] The system integrates a data storage unit with a capacity of no less than 1TB and uses encrypted storage technology (AES-256 encryption algorithm) to record the patient's blood glucose history data (one record per minute), treatment plan and treatment effect data (such as blood glucose changes before and after intervention, and the occurrence of complications). The data storage period is no less than 5 years.

[0051] The data management and remote monitoring module supports uploading data to the hospital information system (HIS system) or electronic medical record system (EMR system) via wireless communication module. Medical staff can remotely view patients' real-time blood glucose data, blood glucose change trend curves and treatment plan execution through hospital terminals or mobile terminals (such as doctor workstations and tablets). They can also remotely adjust the treatment plan according to changes in the patient's condition. Adjustment instructions are transmitted to the system after encryption to ensure data security.

[0052] In addition, the data management and remote monitoring module also has a data query and statistics unit. Medical staff can query patient data by patient name, hospital number, or dialysis time range (accurate to the hour). It also supports statistical analysis of patients' average blood glucose, blood glucose fluctuation range (maximum value - minimum value), number of hypoglycemic events (number of times blood glucose < 3.9 mmol / L), and number of hyperglycemic events (number of times blood glucose > 13.9 mmol / L) within a selected time period (such as 1 week or 1 month), generating statistical reports containing data tables and trend charts. The reports can be exported to Excel or PDF format, which is convenient for clinical research and medical record organization.

[0053] 6. Safety and Calibration Module

[0054] Connected to a real-time blood glucose monitoring module, it has an automatic calibration function: before daily dialysis, the system automatically draws 0.5mL of venous blood from the patient and compares it with the blood glucose data collected by the sensor. If the difference exceeds ±5%, the sensor parameters are automatically adjusted to complete the calibration. The entire calibration process is recorded and the data is stored in the data management and remote monitoring module for easy traceability.

[0055] The safety and calibration module incorporates multiple safety mechanisms, including:

[0056] Operation permission management mechanism: Three levels of operation permissions are set. Level 1 permissions (chief physician) can modify core system parameters (such as blood glucose target range, dosage limit) and approve treatment plan adjustments; Level 2 permissions (head nurse) can execute treatment plans and view complete patient data; Level 3 permissions (interns) can only view real-time blood glucose data and system operation status. Permission settings are implemented through password + fingerprint dual verification.

[0057] Dosage limit mechanism: The maximum single infusion volume of the insulin pump is preset to 10U and the maximum 24-hour infusion volume is 60U. The maximum single infusion volume of the high glucose solution injection pump is 20mL. When the calculated infusion volume exceeds the above limits, the system will automatically prohibit the infusion operation, issue an audible and visual alarm, and lock the operation interface. Only after a person with Level 1 authorization can the operation be restarted.

[0058] Anomaly detection mechanism: Real-time monitoring of blood glucose data transmitted by the sensor; when an anomaly is detected, the system will detect it.

[0059] When the blood glucose level is 5 mmol / L, or below 2.8 mmol / L or above 22.2 mmol / L (outside the normal physiological range), the system will automatically pause the intervention operation and display the message "Data abnormal, please check the sensor" on the human-computer interaction module. At the same time, it will notify medical staff to check and recalibrate the sensor.

[0060] Equipment fault alarm mechanism: The operating status of insulin pump, high glucose solution injection pump, sensor and wireless communication module is monitored in real time (monitoring frequency is 1 time / second). When the equipment is detected to be blocked (insulin pump pressure > 300kPa), low power (remaining power < 10%) or communication interrupted (data transmission interruption for more than 30 seconds), a fault alarm signal is immediately issued (audible and visual alarm + text prompt), and the fault module, fault type and troubleshooting suggestions are displayed in the data management and remote monitoring module.

[0061] 7. Human-Computer Interaction Module

[0062] It features a 10-inch high-definition touchscreen (1920×1080 resolution) that supports multi-touch. The interface adopts a layered design. The main interface displays the patient's name, hospital number, real-time blood glucose value, blood glucose trend curve (last hour), current treatment plan summary, and system operating status. The secondary interface allows users to view the patient's basic information, complete historical blood glucose data (last 72 hours), treatment plan details, and warning / fault records.

[0063] The human-computer interaction module supports voice input (supporting Mandarin Chinese recognition). Medical staff can input basic patient information, modify dialysis parameters (such as "adjust blood flow rate to 250mL / min"), or confirm treatment plans (such as "confirm insulin dosage adjustment plan") via voice commands, making it convenient to operate when hands are busy. At the same time, the touch screen surface is equipped with an antibacterial coating (such as silver ion antibacterial coating), which can effectively inhibit bacterial growth and meet hospital infection control requirements.

[0064] 8. Wireless communication module

[0065] It adopts dual-mode 5G and Wi-Fi communication technology. 5G communication supports downlink speeds of ≥100Mbps and uplink speeds of ≥50Mbps to ensure rapid transmission of real-time blood glucose data and early warning information. Wi-Fi communication supports the IEEE 802.11ac standard and is suitable for Wi-Fi coverage areas within hospitals, reducing communication costs.

[0066] The wireless communication module has an automatic switching function for communication failures. When the 5G signal is interrupted, it automatically switches to Wi-Fi communication. If the Wi-Fi signal is also interrupted, the system temporarily stores the data in the local storage unit and automatically retransmits it after the communication is restored, ensuring that the data is not lost. At the same time, the module adopts the encrypted communication protocol (TLS1.3) to encrypt the transmitted data end-to-end, preventing the data from being stolen or tampered with, and protecting patient privacy and data security.

[0067] The specific implementation process of the glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring in this invention is as follows:

[0068] Ten hemodialysis machines were selected, and each machine was equipped with a hemodialysis patient glucose metabolism management system based on real-time blood glucose monitoring as described in this invention. The modules of the system are connected as follows:

[0069] The electrochemical sensor of the real-time blood glucose monitoring module is connected to the arterial end of the hemodialysis tubing (for collecting blood samples) or the dialysate outlet end (for collecting dialysate samples) via a dedicated interface;

[0070] The wireless communication module is connected to the real-time blood glucose monitoring module, glucose metabolism data analysis module, personalized treatment plan generation module, automatic intervention module, data management and remote monitoring module, safety and calibration module and human-computer interaction module via wireless signals, with the communication frequencies set to 2.4GHz (Wi-Fi) and 5GHz (5G);

[0071] The data management and remote monitoring module connects with the HIS and EMR systems through the hospital's intranet to achieve data sharing.

[0072] Activate the automatic calibration function of the safety and calibration module 30 minutes before the start of each daily dialysis session:

[0073] The system automatically draws 0.5 mL of venous blood from the patient and uses a matching blood glucose analyzer to detect the venous blood glucose level (as a standard value);

[0074] The real-time blood glucose monitoring module collects blood glucose data (as detection values) from the patient's blood or dialysate and transmits it to the safety and calibration module;

[0075] The safety and calibration module calculates the difference between the standard value and the detected value. If the difference is ≤ ±5%, the calibration is passed; if the difference is > ±5%, the sensor's sensitivity parameters are automatically adjusted, the detected value is re-acquired and compared, until the difference is ≤ ±5%.

[0076] The calibration results are recorded in the data management and remote monitoring module, generating a "calibration report" which includes calibration time, standard value, test value, difference, and adjustment parameters.

[0077] One hemodialysis patient with type 2 diabetes (male, 65 years old, weight 60 kg, 10-year history of diabetes, glycated hemoglobin 7.5%, no other underlying diseases) was selected for 4-hour hemodialysis treatment. The system operation process is as follows:

[0078] At the start of dialysis, medical staff input the patient's basic information (age, weight, history of diabetes, etc.) and dialysis parameters (dialysis electrolyte concentration: sodium 138 mmol / L, potassium 2.0 mmol / L, calcium 1.5 mmol / L, dialysate temperature 36.5℃, blood flow rate 250 mL / min, dialysis time 4 hours, dialyzer model Fresenius F6, dialysate flow rate 500 mL / min) through the human-computer interaction module;

[0079] The real-time blood glucose monitoring module collects the patient's blood glucose data every minute, transmits it to the central processing system via the wireless communication module, and then forwards it to the glucose metabolism data analysis module;

[0080] The glucose metabolism data analysis module combines patient basic information, dialysis parameters, and real-time blood glucose data. It uses a built-in machine learning algorithm to predict the blood glucose trend for the next 30 minutes. At the same time, it calculates the blood glucose fluctuation range (pre-dialysis blood glucose 7.2 mmol / L, 1-hour dialysis blood glucose 6.5 mmol / L, 2-hour dialysis blood glucose 5.8 mmol / L, fluctuation range 1.4 mmol / L) and the percentage of time when blood glucose is within the target range (up to 2 hours of dialysis, the percentage of time when blood glucose is between 4.4-10.0 mmol / L is 100%), and assesses the patient's glucose metabolism status as "good".

[0081] The personalized treatment plan generation module generates treatment plans based on the analysis results of glucose metabolism data.

[0082] Insulin dose adjustment plan: target blood glucose range 4.4-10.0 mmol / L, patient's real-time blood glucose 5.8 mmol / L (within the target range), insulin sensitivity coefficient = 1500 ÷ (weight kg × 18) = 1500 ÷ (60 × 18) ≈ 1.39, basal insulin dose 4 U / hour, calculation shows that no insulin dose adjustment is needed, maintain basal infusion;

[0083] Optimization plan for dialysate glucose concentration: The patient's real-time blood glucose was 5.8 mmol / L. Combined with the dialysate flow rate of 500 mL / min and the dialysis time of 4 hours, the appropriate dialysate glucose concentration was calculated to be 5.6 mmol / L.

[0084] Nutritional intervention recommendations: Daily carbohydrate intake = 60kg × 4g / kg = 240g, protein intake = 60kg × 1.3g / kg = 78g, fat intake accounts for 28% of total calories. It is recommended to eat 1 hour before dialysis (50g of staple food and 20g of protein), have a snack 2 hours during dialysis (25g of staple food and 10g of protein), and eat 1 hour after dialysis (75g of staple food and 20g of protein).

[0085] The automatic intervention module receives the treatment plan and controls the insulin pump to infuse insulin at a dose of 4U / hour, while the high glucose solution infusion pump is in standby mode.

[0086] Three hours into dialysis, the glucose metabolism data analysis module predicted that the patient's blood glucose might drop to 4.2 mmol / L (below the lower limit of the target range) in the next 30 minutes. The blood glucose risk warning unit immediately issued an audible and visual warning and transmitted the warning information to the data management and remote monitoring module. Medical staff received the warning information through mobile terminals.

[0087] The individualized treatment plan generation module adjusts the treatment plan in real time, raising the glucose concentration of the dialysate to 7.8 mmol / L, and recommending that medical staff supplement the patient with 25g of carbohydrates (such as biscuits);

[0088] According to the adjusted plan, the automatic intervention module controlled the dialysate supply system to switch to dialysate with a glucose concentration of 7.8 mmol / L. After 30 minutes, the patient's blood glucose rose back to 4.8 mmol / L, and the warning was lifted.

[0089] The data management and remote monitoring module records the patient's blood glucose data (a total of 240 records), treatment plan (initial plan and adjustment plan) and treatment effect (blood glucose 4.2 mmol / L before intervention, blood glucose 4.8 mmol / L after intervention, blood glucose rise of 0.6 mmol / L) in real time during the dialysis process. The data is stored using the AES-256 algorithm for encryption.

[0090] After dialysis, medical staff can use the data query and statistics unit to query the patient's blood glucose data for this dialysis session. The system automatically calculates the average blood glucose level (5.5 mmol / L), blood glucose fluctuation range (4.2-7.2 mmol / L), number of hypoglycemic events (0 times), and number of hyperglycemic events (0 times), and generates a "blood glucose statistics report" which can be exported as an Excel file.

[0091] The system automatically uploads the patient's blood glucose data, treatment plan, and statistical reports for this dialysis session to the HIS and EMR systems, facilitating subsequent medical record organization and clinical follow-up.

[0092] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring, characterized in that: It includes a real-time blood glucose monitoring module, a glucose metabolism data analysis module, a personalized treatment plan generation module, an automatic intervention module, a data management and remote monitoring module, and a safety and calibration module; The real-time blood glucose monitoring module uses an electrochemical sensor to collect patients' blood glucose level data in real time through dialysis fluid or blood, and transmits the collected blood glucose data to the central processing system in real time. The glucose metabolism data analysis module is connected to the central processing system to obtain real-time blood glucose data from the central processing system, and at the same time collect patient basic information and dialysis parameters. It performs comprehensive analysis on the obtained real-time blood glucose data, patient basic information and dialysis parameters. The glucose metabolism data analysis module has a built-in intelligent algorithm to predict the patient's blood glucose change trend based on the comprehensive analysis results and to assess the patient's glucose metabolism status. The individualized treatment plan generation module is connected to the glucose metabolism data analysis module and is used to generate an individualized treatment plan for the patient based on the real-time blood glucose data and glucose metabolism analysis results output by the glucose metabolism data analysis module. The individualized treatment plan includes an insulin dose adjustment plan, a dialysate glucose concentration optimization plan, and nutritional intervention recommendations. The automatic intervention module is equipped with an insulin pump and a high-glucose solution injection pump. The automatic intervention module is connected to the individualized treatment plan generation module and is used to automatically adjust the insulin infusion volume of the insulin pump or the high-glucose solution infusion volume of the high-glucose solution injection pump according to the treatment plan generated by the individualized treatment plan generation module. When the patient is detected to have a risk of hypoglycemia, the module automatically controls the high-glucose solution injection pump to push the high-glucose solution. When the patient is detected to have a risk of hyperglycemia, the module automatically controls the insulin pump to adjust the insulin dose. The data management and remote monitoring module integrates a data storage unit to record the patient's historical blood glucose data, generated treatment plans, and treatment effect data. At the same time, the data management and remote monitoring module supports uploading the recorded data to the hospital information system to enable doctors to remotely monitor the patient's condition and remotely adjust the treatment plan. The safety and calibration module is connected to the real-time blood glucose monitoring module and is used to provide automatic calibration function for the real-time blood glucose monitoring module. The safety and calibration module has multiple built-in safety mechanisms to prevent system misoperation or excessive intervention to patients.

2. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 1, characterized in that: The patient's basic information includes the patient's age, weight, height, gender, duration of diabetes history, type of diabetes, previous blood glucose control, presence of other underlying diseases, and medication history; the dialysis parameters include the electrolyte concentration of the dialysate, dialysate temperature, blood flow rate, dialysis time, dialyzer model, and dialysate flow rate.

3. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 2, characterized in that: The intelligent algorithm built into the glucose metabolism data analysis module adopts a machine learning-based prediction model. The prediction model uses historical blood glucose data, patient basic information, and dialysis parameters as training samples to continuously learn and update the model parameters. Furthermore, when assessing the patient's glucose metabolism status, the intelligent algorithm combines the amplitude of blood glucose fluctuations, the percentage of time that blood glucose reaches the target level, and the glycated hemoglobin level for a comprehensive evaluation.

4. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 3, characterized in that: When generating an insulin dosage adjustment plan, the individualized treatment plan generation module calculates the adjustment range based on the difference between the patient's real-time blood glucose level and the target blood glucose range, the rate of blood glucose change, and the patient's sensitivity coefficient to insulin. When generating an optimized dialysate glucose concentration plan, the module calculates the appropriate dialysate glucose concentration by considering the patient's blood glucose level, dialysate flow rate, and dialysis time. The nutritional intervention recommendations include daily carbohydrate intake, protein intake, fat intake, and recommendations for meal times and frequencies, and these recommendations are dynamically adjusted based on the patient's weight change trends and blood glucose control.

5. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 4, characterized in that: The automatic intervention module also includes a blood glucose risk warning unit, which is connected to the glucose metabolism data analysis module. It is used to receive the blood glucose change trend and glucose metabolism status assessment results output by the glucose metabolism data analysis module. When it is predicted that the patient is likely to experience hypoglycemia or hyperglycemia within the next 30 minutes, it issues a warning signal in advance. The warning signal includes an audible warning and a visual warning. At the same time, the warning information is transmitted to the data management and remote monitoring module.

6. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 5, characterized in that: The data management and remote monitoring module also includes a data query and statistics unit. The data query and statistics unit is used by medical staff to query the patient's blood glucose history data, treatment plan and treatment effect data according to the patient's name, hospitalization number or dialysis time range. It can also perform statistical analysis on the patient's average blood glucose, blood glucose fluctuation range, number of hypoglycemia and number of hyperglycemia within a selected time period, and generate corresponding statistical reports. The statistical reports can be exported to Excel or PDF format.

7. The glucose metabolism management system for hemodialysis patients based on real-time blood glucose monitoring according to claim 6, characterized in that: The security and calibration module incorporates multiple security mechanisms, including: (1) Operation permission management mechanism: different levels of operation permissions are set. Only medical staff with the corresponding permissions can modify system parameters and adjust treatment plans. Ordinary operators can only view patient data and system operation status. (2) Dosage limit mechanism: Limit the maximum single insulin infusion volume of the insulin pump and the maximum single high glucose solution infusion volume of the high glucose solution injection pump. When the calculated insulin or high glucose solution infusion volume exceeds the set limit, the infusion operation is automatically prohibited and an alarm signal is issued. (3) Abnormal data detection mechanism: Real-time monitoring of blood glucose data transmitted by the sensor. When abnormal fluctuations or deviations from the normal physiological range are detected in the blood glucose data, the intervention operation is automatically paused and medical staff are prompted to check and calibrate the sensor. (4) Equipment fault alarm mechanism: The operating status of each module of the system is monitored in real time. When a fault is detected in the insulin pump, high sugar solution injection pump or sensor, a fault alarm signal is immediately issued and the fault module and fault type are displayed in the data management and remote monitoring module.

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