Treatment guidance system for hyperkalemia patient

Abstract

The invention discloses a treatment guidance system for a hyperkalemia patient, and the system comprises a data detection unit which obtains the medical history, symptom signs and inspection data of the patient through the butt joint of a hospital information system and a laboratory information system, and carries out the data cleaning and structural processing; the decision analysis unit is used for generating a first treatment scheme based on a pre-stored treatment guide rule base and the real-time data; the scheme guidance unit is used for generating a second treatment scheme according to the feedback of the auditing end and pushing the second treatment scheme to the execution end; the dynamic monitoring unit is used for monitoring indexes such as blood potassium, blood gas, electrocardiogram, blood sugar and urine volume of the patient in real time and triggering treatment adjustment and reexamination reminding according to a preset rule; and the long-term management unit is used for generating a personalized long-term management scheme in combination with etiological analysis. According to the invention, through standardized treatment process, intelligent dose correction, dynamic risk early warning and multi-department cooperation, precise, continuous and closed-loop management of hyperkalemia treatment is realized, the short-term death rate is reduced, and the long-term prognosis of a patient is improved.

Description

Technical Field

[0001] The present invention belongs to the field of smart medical care and specifically discloses a treatment guidance system for patients with hyperkalemia. Background Art

[0002] Hyperkalemia (serum potassium concentration > 5.0 mmol / L) is a common acute complication in patients with chronic kidney disease (CKD), heart failure, and diabetes. In particular, about 50% of CKD stage 4-5 patients have experienced acute attacks of hyperkalemia. Its pathological mechanism is closely related to the failure of the kidney's potassium excretion function, and is also affected by drugs such as RAAS inhibitors and potassium-sparing diuretics. Hyperkalemia can cause fatal arrhythmias. If not treated in time, the patient's mortality rate increases significantly. The traditional treatment process involves discontinuation of potassium-containing drugs and foods, myocardial electrical stabilization (calcium antagonists to counter potassium toxicity), promotion of potassium ion transfer (insulin-glucose, β2 receptor agonists), potassium excretion treatment (diuretics, cation exchange resins, dialysis), and other links. It is necessary to strictly follow the treatment guidelines and closely monitor multiple indicators. However, the existing technology has the following significant defects in clinical practice:

[0003] 1. Fragmented decision-making and inconsistent processes: Treatment pathways vary significantly across departments (e.g., nephrology, emergency medicine, and cardiology), resulting in a lack of standardization in treatment plans. Key steps can be easily delayed due to human oversight (e.g., failure to discontinue potassium-containing medications or initiate dialysis).

[0004] 2. Monitoring blind spots and lack of continuity: Patients with severe hyperkalemia often lack continuous ECG monitoring, and blood potassium and ECG are not retested in a standardized manner after treatment, making it difficult to dynamically assess the treatment effect and arrhythmia risk.

[0005] 3. Improper use of drugs: For example, calcium supplements need to be slowly injected intravenously (5-10 minutes) and monitored by ECG throughout the process. However, in actual operation, improper operation may lead to insufficient efficacy or side effects. In the insulin-glucose regimen, insulin resistance in patients with diabetic nephropathy is often ignored, and continuous blood glucose monitoring is not performed on sensitive patients, increasing the risk of hypoglycemia.

[0006] 4. Delayed assessment of dialysis indications: Emergency dialysis is required when blood potassium is ≥6.5mmol / L or when there are severe electrocardiogram abnormalities. However, the existing system fails to quickly integrate data from multiple departments (such as vascular access status and hemodialysis resource availability), resulting in delayed decision-making.

[0007] 5. Lack of long-term management: There is a lack of etiology tracing and chronic management plans after acute treatment. The patient's dietary structure is not adjusted in time, and the adjustment of high potassium risk drugs is chaotic, leading to repeated attacks of hyperkalemia.

[0008] While some existing medical decision support systems exist, they lack personalized hyperkalemia management, dynamic risk warnings, and multidisciplinary collaboration capabilities, making them unable to address the aforementioned issues. Therefore, a hyperkalemia treatment system integrating intelligent decision-making, real-time monitoring, and closed-loop management is urgently needed to improve treatment efficiency, reduce iatrogenic risks, and improve patient outcomes. Summary of the Invention

[0009] To address the above-mentioned problems in the prior art, the present invention discloses a treatment guidance system for patients with hyperkalemia. Through standardized treatment processes, intelligent dosage correction, dynamic risk warnings, and multi-department collaboration, it solves problems in the prior art such as decision-making fragmentation, monitoring blind spots, improper drug use, and delayed dialysis indications. It achieves precise, continuous, and closed-loop management of hyperkalemia treatment, significantly reducing short-term mortality and improving long-term patient prognosis.

[0010] The present invention includes the following technical solutions:

[0011] A treatment guidance system for patients with hyperkalemia, comprising:

[0012] Data detection unit, used to obtain the target patient's medical history, symptoms, signs and test-related data;

[0013] a decision analysis unit, configured to generate a corresponding first treatment plan based on the data acquired by the data detection unit and in combination with a rule library of a pre-stored treatment guideline;

[0014] a plan guidance unit, configured to generate a second treatment plan based on the first treatment plan and in response to a review result of the first treatment plan by the review end, and send the second treatment plan to the execution end, wherein the second treatment plan is the same as or different from the first treatment plan;

[0015] a dynamic monitoring unit, configured to respond to an instruction from the execution terminal and, based on the second treatment plan, remind and monitor the target patient's electrocardiogram, blood potassium, blood glucose, blood gas, urine volume, edema level, blood pressure, heart rate, and gastrointestinal reactions;

[0016] The long-term management unit is used to respond to the instruction of the execution end and perform etiology tracing and long-term management on the target patient based on the data of the data detection unit.

[0017] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the data detection unit obtains the symptom-related data, including one or more of vital signs, positive signs and test results, by interconnecting with the hospital information system and the laboratory information system, and cleans and organizes the data to form structured data.

[0018] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the vital signs include body temperature, blood pressure, heart rate, and respiratory rate; the positive signs include neuromuscular system manifestations (muscle weakness, weakened tendon reflexes), cardiovascular system manifestations (arrhythmia), digestive system symptoms (nausea, vomiting), and metabolic acidosis signs (deep and rapid breathing); the test results include blood potassium concentration, arterial blood gas analysis, and electrocardiogram characteristics.

[0019] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the first treatment plan generated by the decision analysis unit is determined based on at least one of the following: the patient's symptoms, physical examination results, test results (including blood potassium, renal function, blood gas analysis, heart rate, blood pressure, urine volume and electrocardiogram), past medical history and current medical history.

[0020] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the program guidance unit performs graded management according to the target patient's electrocardiogram abnormalities and the degree of increased blood potassium, guides the use of antiarrhythmic drugs, and evaluates the indications for emergency dialysis.

[0021] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the dynamic monitoring unit controls the target patient to receive treatment within a preset time based on the second treatment plan, and monitors changes in physiological indicators after treatment in real time.

[0022] Furthermore, the above-mentioned rescue guidance system for patients with hyperkalemia also includes a reminder unit, which is used to prompt at least one of the following operations on the review end or the execution end: monitoring the patient's blood pressure, heart rate, blood sugar, blood potassium and electrocardiogram, correcting acidosis, replacing the infusion bag, adjusting the fluid infusion rate, and recording the patient's urine volume.

[0023] Furthermore, the above-mentioned treatment guidance system for patients with hyperkalemia can automatically update the treatment plan based on the patient's real-time data and synchronize the updated plan to the doctor and nurse terminals.

[0024] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the second treatment plan includes at least one of the following: the time interval for monitoring blood potassium, the dosage and injection rate of insulin and glucose solution, the blood glucose monitoring time, the acid-base balance monitoring interval, the dosage and frequency of diuretics, the amount of bicarbonate supplementation, the frequency of electrocardiogram review, and the urine volume change threshold.

[0025] Furthermore, in the above-mentioned treatment guidance system for patients with hyperkalemia, the long-term management unit generates a personalized long-term management plan based on the etiology analysis of the target patient, including low-potassium diet recommendations, drug adjustment plans (such as the use of RAAS inhibitors, angiotensin receptor neprilysin inhibitors, aldosterone receptor antagonists, and cation exchange resins) and regular blood potassium monitoring reminders.

[0026] The present invention also discloses a device for guiding the treatment of patients with hyperkalemia, comprising:

[0027] Data detection unit: used to obtain symptom-related data of target patients; this unit connects to the hospital HIS system through the hospital's reserved interface, cleans and organizes the acquired patient hyperkalemia data to obtain structured data, and sends it to the decision analysis unit;

[0028] Decision analysis unit: stores a rule base extracted based on various guidelines, expert consensus, etc., and is used to generate a corresponding first treatment plan based on the symptom-related data and compare it with the stored rule base;

[0029] A plan guidance unit is configured to generate a second treatment plan based on the first treatment plan and in response to the review result of the first treatment plan by the review end, and then send the second treatment plan to the execution end, wherein the second treatment plan is the same as or different from the first treatment plan;

[0030] Dynamic monitoring unit: used to respond to the instruction of the execution end and remind the monitoring of the target patient's electrocardiogram, blood potassium, blood sugar, blood gas, urine volume, edema degree, blood pressure, heart rate, and gastrointestinal reaction based on the second treatment plan;

[0031] Long-term management unit: used to respond to instructions from the execution end and trace the cause of disease and conduct long-term management of target patients based on the data detection unit.

[0032] Compared with the prior art, the present invention has the following outstanding beneficial effects:

[0033] The hyperkalemia patient treatment guidance system of the present invention has many significant beneficial effects, mainly reflected in the standardization of treatment and unified processes. By integrating international guidelines and in-hospital clinical pathways, it effectively avoids human operational errors and improves treatment efficiency and quality; dynamic risk warning and real-time monitoring, real-time monitoring of key physiological indicators, timely detection and treatment of high-risk events, and significantly reducing patient mortality; multi-department collaboration and efficient resource scheduling, seamless connection of multi-department resources through Internet of Things technology, shortening dialysis preparation time, and improving treatment efficiency; personalized long-term management and patient education, generating personalized management plans based on the results of etiology analysis, and realizing closed-loop outpatient management through mobile APP and other devices, improving patients' long-term prognosis; intelligent dose correction and dynamic plan adjustment, automatically updating treatment plans and synchronizing them to medical staff, improving treatment targeting and effectiveness; and full-cycle closed-loop management and reduced readmission rates, covering the entire course of disease management from acute to chronic stages, significantly reducing readmission rates through multi-device linkage and patient education, and alleviating the medical burden. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is an architectural diagram of a treatment guidance system for hyperkalemia patients according to the present invention;

[0035] Figure 2 is a schematic diagram of decision analysis based on symptoms, physical examination, and laboratory tests according to the present invention;

[0036] Figure 3 is a schematic diagram of hierarchical management and program delivery based on blood potassium levels according to the present invention;

[0037] Figure 4 is a schematic diagram of a new production solution for dynamic monitoring of relevant indicators and feedback according to the present invention;

[0038] Figure 5 It is a schematic diagram of the etiology tracing and long-term management of target patients according to the present invention. DETAILED DESCRIPTION

[0039] This invention proposes a treatment system for patients with hyperkalemia. Based on individual patient differences, it generates comprehensive, systematic, and continuous intervention measures. This system ensures more standardized and timely treatment for patients, preventing doctors and nurses from neglecting details that can prolong or even worsen the course of hyperkalemia. In summary, the provided treatment guidance system for hyperkalemia integrates multiple components, including data detection, intelligent decision-making, recommended treatment options, and infusion monitoring, enabling efficient, timely, and intelligent treatment of patients.

[0040] Specifically, see Figure 1As shown, the provided rescue guidance system for hyperkalemia patients mainly includes a data detection unit, a decision analysis unit, a program guidance unit, a dynamic monitoring unit, a long-term management unit, etc.

[0041] Data detection unit ( Figure 2 ) Obtain various data related to patients with hyperkalemia: The data detection unit automatically extracts relevant patient data by connecting to the hospital's HIS (hospital information system), cleans and organizes the data to obtain structured data, and sends it to the decision analysis unit. The extracted data includes but is not limited to the patient's chief complaint, symptoms and signs, and test indicators. For example, the symptoms include neuromuscular system manifestations (early limb abnormalities, numbness, fatigue, muscle aches, followed by muscle weakness, difficulty walking, gradual flaccid paralysis, severe swallowing, pronunciation, breathing difficulties, irritability, confusion, syncope, etc.), cardiovascular system manifestations (arrhythmia: including bradycardia, ventricular premature beats, ventricular fibrillation or cardiac arrest, etc.), digestive system symptoms (nausea, vomiting, abdominal pain and diarrhea, etc.), accompanied by metabolic acidosis (deep breathing, etc.), accompanied by renal insufficiency manifestations (decreased urine volume, edema, etc.); physical examination includes arrhythmia, decreased tendon reflexes, and lower limb edema; test results include renal function, blood potassium, arterial blood gas analysis, and electrocardiogram.

[0042] Decision Analysis Unit ( Figure 3 ): Compare the above sorted data with the stored rule base to generate a corresponding first treatment plan;

[0043] The rule base of the present invention is a rule base obtained after mining and analyzing various guidelines, clinical treatment pathways, expert consensus, textbooks, papers, works, scientific inferences, experimental reports, test reports, relevant laws and regulations, and relevant literature materials for hyperkalemia.

[0044] The decision analysis unit is used to receive the data sent by the data detection unit and compare it with the rule base stored in the system. It will intelligently generate a treatment plan based on the comparison results and then send the treatment plan to the doctor's HIS for review. The doctor can further modify the treatment plan as needed. Figure 3 As shown,

[0045] The decision analysis unit can perform graded management based on blood potassium levels and recommend antiarrhythmic treatment based on whether the electrocardiogram is abnormal. If the patient develops characteristic electrocardiographic changes, calcium therapy should be initiated immediately to antagonize myocardial toxicity. Under the condition of electrocardiographic monitoring, 10 ml of 10% calcium gluconate is injected intravenously. The HIS system synchronizes the patient's data to the nephrologist's workstation, reports critical blood potassium values, and asks the nephrologist for consultation. First, adjust the diet and medication, stop exogenous potassium intake, and secondly, eliminate medication contraindications. Finally, it is possible to promote the transfer of potassium ions into cells (glucose + insulin), promote the excretion of potassium by the kidneys (diuretics), promote the excretion of potassium by the intestines (oral potassium ion binders), and correct acidosis (bicarbonate).

[0046] After the treatment plan is reviewed by the doctor, the plan guidance unit will send it to the nurse (or execution) side. The nurse side will display the medication, tests, and other measures that need to be completed for the patient in each time period to ensure the accurate implementation of the treatment plan.

[0047] Dynamic Monitoring Unit ( Figure 4 ): Used to respond to instructions from the execution end, and to remind the monitoring of the target patient's electrocardiogram, blood potassium, blood sugar, blood gas, urine volume, degree of edema, blood pressure, heart rate, and gastrointestinal reactions based on the second treatment plan. If the patient still has an abnormal electrocardiogram and intravenous calcium gluconate is given, the electrocardiogram needs to be rechecked within 5-10 minutes. If it is ineffective, calcium can be given again to prevent myocardial toxicity. If the patient's electrocardiogram returns to normal, recheck the blood potassium after 2-4 hours. If the blood potassium is still ≥6.5mmol / L, emergency dialysis is required. If the blood potassium level shows a downward trend but has not returned to normal, potassium-lowering treatment can be continued. The calcium gluconate + insulin treatment plan will take effect within 30 minutes, and blood sugar needs to be closely monitored. Bicarbonate can treat hyperkalemia caused by metabolic acidosis. Usually 150-250ml of sodium bicarbonate is given slowly by intravenous drip, which can last for about 2 hours. Due to excessive Na + Diuretics can increase cardiac volume load and exacerbate heart failure symptoms. Therefore, they are only recommended for patients with hyperkalemia who have achieved adequate fluid control and severe metabolic acidosis, and blood gas monitoring is necessary. Diuretics include loop diuretics (such as furosemide, torsemide, and bumetanide) and thiazide diuretics (such as hydrochlorothiazide). Intravenous administration is more effective than oral administration. Diuretics are only effective if the patient has good renal function and is free of oliguria and hypovolemia. Otherwise, efficacy is poor and the condition may worsen. Excessive use of diuretics can cause adverse reactions such as orthostatic hypotension, shock, hyponatremia, hypochloremia, hypokalemia, hypochloremic alkalosis, thirst, fatigue, and arrhythmias. Therefore, blood pressure, heart rate, urine output, and edema should be monitored. Potassium ion binders include cation exchange resins and newer potassium ion binders. Adverse reactions include gastrointestinal side effects, which can lead to intestinal necrosis in severe cases, necessitating close monitoring for gastrointestinal effects.

[0048] It's important to note that the dynamic monitoring unit continuously monitors patients' real-time data. When new test results become available, the system automatically retrieves them and sends them to the decision-making analysis unit, which then updates the treatment plan. The updated treatment plan is then synchronized with the doctor and nurse, allowing the system to continue reminding the nurse to follow the new order.

[0049] Long-term management unit ( Figure 5 ): Used to respond to instructions from the execution end and conduct long-term management of the target patient's cause based on the data detection unit. For patients with blood potassium >5.0 mmol / L, physicians should assess their diet, current medications, and comorbidities. They should arrange for regular blood potassium checks, avoid high-potassium foods, improve potassium excretion, and eliminate risk factors for elevated blood potassium. Patients with impaired renal function are divided into hemodialysis and non-hemodialysis patients. Hemodialysis patients maintain electrolyte balance through regular hemodialysis. Non-hemodialysis patients with chronic kidney disease are prone to recurrent hyperkalemia due to decreased renal potassium excretion capacity. Even with short-term correction, there is a risk of recurrence. Therefore, regular blood potassium monitoring and long-term potassium management with potassium binders are necessary. If metabolic acidosis is present, oral sodium bicarbonate therapy is required. Long-term use of medications that are prone to causing high potassium levels (traditional Chinese medicine, NSAIDs, RAASi, ARNI, MRAs) requires regular blood potassium monitoring and, if necessary, reduction or discontinuation of the medication or the addition of oral potassium binders. Hyperkalemia requires the establishment of a multi-department collaborative management information management system, which must be combined with the hospital's follow-up system for specialized diseases and chronic diseases. It is recommended to set up specialized disease follow-up nurses to remind patients to regularly check their blood potassium according to the corresponding risk level and conduct standardized management.

[0050] The hyperkalemia treatment guidance system of the present invention is a system that interacts with other systems (such as HIS, infusion pumps, etc.) through data interfaces. Data and information between the various units of the present invention can be transmitted via data lines, wireless transmission, wired network transmission, etc. Wireless transmission methods include infrared, Bluetooth, Wi-Fi, and wireless communication.

[0051] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0052] Computer-readable storage medium can be a tangible device that can keep and store the instructions used by the instruction execution device.Computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device or any suitable combination thereof.More specific examples (non-exhaustive list) of computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove having instructions stored thereon, and any suitable combination thereof.Computer-readable storage medium used herein is not interpreted as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagated by waveguides or other transmission media (for example, light pulses by fiber optic cables), or electrical signals transmitted by wires.

[0053] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0054] The computer program instructions for carrying out the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, Python, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages.

[0055] The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized using the state information of the computer-readable program instructions, which may execute the computer-readable program instructions to implement various aspects of the present invention.

[0056] Various aspects of the present invention are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0057] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0058] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0059] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a unit, program segment or part of an instruction, and the unit, program segment or part of the instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are all equivalent.

[0060] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0061] Example 1

[0062] Application of the rescue system described in the present invention.

[0063] Acute onset of hyperkalemia

[0064] The hospital admitted a patient with acute hyperkalemia. The treatment process was as follows:

[0065] Step 1: Data detection unit collects patient information

[0066] A 65-year-old male patient with CKD stage 5 presented to the emergency department with complaints of palpitations and muscle weakness.

[0067] The data detection unit automatically obtains the following data through the hospital HIS system:

[0068] Vital signs: heart rate 45 beats / min (bradycardia), blood pressure 160 / 95 mmHg;

[0069] Positive signs: limb muscle strength grade III, weakened tendon reflexes, electrocardiogram showing peaked T waves and widened QRS waves;

[0070] Test results: serum potassium 7.2mmol / L, serum creatinine 650μmol / L, arterial blood gas showed metabolic acidosis (pH7.25, HCO3 - 18mmol / L).

[0071] The data detection unit cleans and structures the above data and pushes it to the decision analysis unit.

[0072] Step 2: The decision analysis unit generates the first treatment plan

[0073] The decision analysis unit compares data based on the rule base (KDIGO guidelines, ERC consensus):

[0074] Serum potassium > 6.0 mmol / L + abnormal electrocardiogram → severe hyperkalemia, requiring emergency intervention;

[0075] Renal failure (eGFR < 15 ml / min / 1.73 m 2 )→ The indication for dialysis is clear;

[0076] Metabolic acidosis → requires correction with sodium bicarbonate.

[0077] Generate the first treatment plan:

[0078] Emergency treatment:

[0079] 10% calcium gluconate 10ml is slowly injected intravenously (5-10 minutes) under ECG monitoring;

[0080] Stop taking all potassium-containing medications and foods;

[0081] Promote potassium transfer:

[0082] 10% glucose 500ml + insulin 10U intravenous drip (completed within 1 hour);

[0083] Potassium depletion therapy:

[0084] Oral administration of cation exchange resin 15 g (patients without intestinal obstruction contraindications);

[0085] Dialysis preparation:

[0086] Synchronize vascular access status (maturation of arteriovenous fistula) to the hemodialysis center and prioritize emergency dialysis;

[0087] Monitoring requirements:

[0088] Recheck the electrocardiogram 10 minutes after calcium administration, and monitor blood potassium and blood glucose every hour.

[0089] Step 3: Review and implementation of the program guidance unit

[0090] A pop-up window will appear on the doctor's end to warn of a critical value, and the doctor will review the first treatment plan and confirm it;

[0091] The program guidance unit pushes the second treatment plan to the nurse execution terminal and synchronizes it to the dynamic monitoring unit;

[0092] The nurse execution terminal displays:

[0093] Immediately connect calcium gluconate injection and control the intravenous injection rate to <5ml / min;

[0094] Insulin-glucose solution was infused at a rate of 500 ml / h via an infusion pump;

[0095] The gastrointestinal reactions of patients were recorded after oral administration of cation exchange resin.

[0096] Step 4: Dynamic monitoring unit real-time feedback and adjustment

[0097] After calcium administration:

[0098] Electrocardiogram reexamination showed that the QRS wave returned to normal, but the T wave was still tall and peaked;

[0099] The system prompts "ECG has partially improved, but blood potassium has not reached the standard, and dialysis needs to be started."

[0100] The hemodialysis center terminal receives the instruction: the patient's vascular access is available, and dialysis will begin within 30 minutes;

[0101] One hour later, the serum potassium level was 4.8 mmol / L and the blood glucose level was 8.2 mmol / L.

[0102] Step 5: Generate a personalized plan for long-term management units

[0103] After the acute phase, the long-term management unit analyzes the cause:

[0104] Main causes: CKD stage 5 + RAAS inhibitor use;

[0105] Risk factors: history of high potassium diet, irregular monitoring of blood potassium.

[0106] Generate long-term management plans:

[0107] Dietary adjustment: Promote low-potassium diet (bananas, potatoes, etc. are prohibited), and daily potassium intake is <2g;

[0108] Medication optimization: suspend or reduce the dose of RAAS inhibitors;

[0109] Monitoring reminder: regular hemodialysis;

[0110] Patient education: Push popular science information about hyperkalemia warning symptoms and emergency treatment through mobile devices.

[0111] From this embodiment, we can see the technical effect of this system

[0112] Standardized treatment: Built-in guidelines enforce key steps (such as the timing of intravenous calcium injection and the determination of dialysis indications) to avoid human operational errors.

[0113] Dynamic risk warning: Real-time ECG analysis combined with blood potassium data can provide timely warning of malignant arrhythmias;

[0114] Multi-department collaboration: Automatically synchronize hemodialysis center resources, shortening dialysis preparation time to 30 minutes (traditional process takes more than 2 hours);

[0115] Closed-loop management: Covering the entire cycle from acute treatment to chronic management, the patient readmission rate within 3 months is reduced by 60%.

[0116] Example 2

[0117] Application of the rescue system described in the present invention.

[0118] Treatment of patients with diabetic nephropathy and hyperkalemia.

[0119] Step 1: Data detection unit collects patient information

[0120] The patient was a 58-year-old female with diabetic nephropathy (eGFR 20 ml / min / 1.73 m 2 ), complaining of fatigue and nausea.

[0121] The data detection unit obtains data through the HIS and LIS systems:

[0122] Vital signs: heart rate 82 beats / min, blood pressure 130 / 80 mmHg;

[0123] Positive signs: mild edema of both lower limbs, no obvious abnormalities in the electrocardiogram;

[0124] Test results: serum potassium 6.7mmol / L, blood glucose 14.5mmol / L, HbA1c 8.5%; arterial blood gas showed mild metabolic acidosis (pH 7.30, HCO3 - 20mmol / L).

[0125] After data cleaning, it is pushed to the decision analysis unit.

[0126] Step 2: The decision analysis unit generates the first treatment plan

[0127] Rule base matching results:

[0128] Serum potassium > 6.0 mmol / L but no malignant changes on the electrocardiogram → potassium shift and potassium excretion therapy are required;

[0129] Diabetic nephropathy + insulin resistance → adjust insulin dose according to blood sugar;

[0130] Mild acidosis → Withhold sodium bicarbonate infusion and give oral sodium bicarbonate (1 g three times a day).

[0131] Generate a plan:

[0132] Promote potassium transfer:

[0133] 50% glucose 50ml + insulin 10U intravenous push;

[0134] Potassium depletion therapy:

[0135] Furosemide 40 mg intravenous injection (patient urine output > 30 ml / h);

[0136] Monitoring requirements:

[0137] Monitor blood glucose every 30 minutes and check serum potassium every 2 hours.

[0138] Step 3: Plan implementation and dynamic monitoring

[0139] The nurse receives the instruction:

[0140] 50% glucose 50ml + insulin 10U intravenous push, and monitor blood sugar

[0141] Urine output was recorded after furosemide injection.

[0142] Dynamic monitoring feedback:

[0143] After 30 minutes, blood glucose dropped to 10.2 mmol / L and blood potassium to 4.9 mmol / L;

[0144] Step 4: Long-term management

[0145] Cause analysis: long-term use of ARNI drugs and renal insufficiency.

[0146] Generate a plan:

[0147] Medication adjustment: halve the ARNI dose or discontinue it, and add oral sodium zirconium cyclosilicate;

[0148] Dietary control: Daily potassium intake <1.5g, no oranges or tomatoes;

[0149] Monitoring reminder: Use a home potassium meter to self-test three times a week, and the data will be automatically uploaded to the system.

[0150] Technical effect: The system dynamically monitors blood sugar based on insulin resistance, adjusts dosage, avoids the risk of hypoglycemia, and reduces the recurrence rate of ARNI-related hyperkalemia through drug optimization.

[0151] Example 3

[0152] Application of the rescue system described in the present invention.

[0153] Hyperkalemia and fluid overload in patients with heart failure

[0154] Step 1: Data detection unit collects patient information

[0155] A 72-year-old male patient with chronic heart failure (NYHA class IV) complained of dyspnea and oliguria.

[0156] The data detection unit obtains data:

[0157] Vital signs: heart rate 110 beats / min (atrial fibrillation), blood pressure 85 / 50 mmHg;

[0158] Positive signs: edema of both lower limbs and distended neck veins;

[0159] Test results: serum potassium 6.9mmol / L, NT-proBNP 5000pg / ml; arterial blood gas showed severe acidosis (pH7.18, HCO3 - 12mmol / L);

[0160] Imaging: Lung CT showed pulmonary edema.

[0161] Step 2: The decision analysis unit generates the first treatment plan

[0162] Rule base matching results:

[0163] Serum potassium > 6.0 mmol / L + acidosis + heart failure → urgent dialysis + fluid restriction required;

[0164] Hypotension → Use diuretics with caution and administer sodium bicarbonate infusion with caution.

[0165] Generate a plan:

[0166] Emergency treatment:

[0167] 10% calcium gluconate 10ml slowly injected intravenously (under ECG monitoring);

[0168] Dialysis preparation:

[0169] Prioritize bedside continuous renal replacement therapy (CRRT);

[0170] Monitoring requirements:

[0171] Blood pressure was monitored every 15 minutes, and the degree of pulmonary edema was assessed hourly.

[0172] Step 3: Plan implementation and multi-departmental collaboration

[0173] The hemodialysis center received the instruction: CRRT equipment should be in place within 30 minutes;

[0174] Nurse side execution:

[0175] After calcium infusion, the electrocardiogram showed a normal QT interval and atrial fibrillation with a ventricular rate reduced to 90 beats / min;

[0176] Blood pressure was stable during CRRT (110 / 65 mmHg).

[0177] Step 4: Dynamic Adjustment and Long-term Management

[0178] 2 hours after CRRT initiation: serum potassium dropped to 4.9 mmol / L, and acidosis corrected (pH 7.36);

[0179] Long-term snap-in generation plan:

[0180] Medication adjustment: spironolactone was discontinued and replaced with oral torsemide;

[0181] Fluid management: daily fluid restriction and daily weight monitoring;

[0182] Patient education: Use smart bracelets to provide real-time warnings of fluid overload (such as daily weight gain >1kg).

[0183] Technical effect: The system avoids worsening of heart failure through rapid CRRT scheduling and fluid restriction strategies, while optimizing medication to reduce readmission rates.

[0184] Example 4

[0185] A device for guiding the treatment of patients with hyperkalemia:

[0186] Hardware equipment composition:

[0187] 1. Data detection unit:

[0188] Hospital interface unit: directly connects to the hospital HIS system through the HL7 protocol, and extracts in real time the patient's vital signs (heart rate, blood pressure), test results (blood potassium, creatinine, blood gas analysis), and medication records (such as the use of RAAS inhibitors and other drugs) from the electronic medical record;

[0189] Data cleaning unit: Built-in AI algorithm automatically filters invalid data (such as repeatedly entered blood potassium values) and converts unstructured text (such as "numbness in the limbs" in the doctor's medical record) into standardized labels (positive signs of the neuromuscular system).

[0190] 2. Decision Analysis Unit:

[0191] Rule base storage unit: Integrates KDIGO guidelines, ERC consensus, and our hospital's clinical pathways, covering rules such as blood potassium classification (5.0-5.5mmol / L is mild, 5.5-6.0mmol / L is moderate, and >6.0mmol / L is severe) and dialysis indications (blood potassium ≥6.5mmol / L + poor drug treatment effect);

[0192] Algorithm processing unit: Using a decision tree model, after inputting patient data, it automatically matches the rule base and outputs the priority of treatment plans (such as "abnormal electrocardiogram requiring intravenous calcium > drug treatment including insulin-glucose, diuretics, potassium ion binders > dialysis").

[0193] 3. Program Guidance Unit:

[0194] Review interactive terminal: The doctor's workstation displays a pop-up window displaying the treatment plan, which supports voice command modification (such as "increase the insulin dose by 2U");

[0195] Execution instruction generator: breaks down the plan into steps that nurses can execute (such as "10% calcium gluconate 10ml, infusion rate 1ml / min, ECG monitoring forced to turn on") and synchronizes it to the smart infusion pump and nurse PDA.

[0196] 4. Dynamic monitoring unit:

[0197] Multi-parameter monitor: integrated with ECG, blood pressure, and blood oxygen monitoring, with data transmitted back in real time via Bluetooth 5.0;

[0198] IoT infusion pump: supports multi-channel infusion and automatically locks the infusion rate after receiving system instructions (such as calcium channel ≤1ml / min);

[0199] Rapid potassium tester: This bedside device tests potassium levels every 30 minutes, with results uploaded via Wi-Fi.

[0200] 5. Long-term management unit:

[0201] Mobile app: Patients install the app on their phones to receive dietary advice (e.g., "Today's potassium intake is 1.2g remaining") and check-up reminders;

[0202] Smart medicine box: Linked with the system, it automatically dispenses potassium-lowering drugs (such as sodium zirconium cyclosilicate) and triggers SMS reminders for family members when doses are missed.

[0203] Example 5

[0204] This embodiment is a practical application case of the device of embodiment 4.

[0205] Patient information: Male, 70 years old, CKD stage 4, long-term valsartan treatment, presented to the emergency department with complaints of palpitations and muscle weakness.

[0206] Step 1: Data detection unit starts

[0207] The hospital's HIS system triggered an alarm: the patient's blood potassium level was critically low at 6.8mmol / L;

[0208] The data detection unit automatically extracts data:

[0209] Vital signs: heart rate 48 beats / min (bradycardia), blood pressure 180 / 100 mmHg;

[0210] Test results: serum creatinine 288 μmol / L, arterial blood gas pH 7.28 (metabolic acidosis);

[0211] Electrocardiogram: T wave is tall and sharp, QRS wave width is 120ms;

[0212] Medication record: Continuously taking valsartan 160mg / d for the past week.

[0213] The data cleaning unit marks key information:

[0214] Structured output: {"blood potassium": 6.8,"ECG_abnormal": ["tall T wave", "widened QRS"],"medication_RAAS inhibitor": "valsartan"}.

[0215] Step 2: The decision analysis unit generates the first treatment plan

[0216] Rule base matching:

[0217] Serum potassium ≥6.5mmol / L + widened QRS → severe hyperkalemia, requiring urgent potassium reduction;

[0218] Renal insufficiency (eGFR 18 ml / min / 1.73 m 2 )→ Dialysis indication takes priority;

[0219] Metabolic acidosis → requires correction with sodium bicarbonate.

[0220] Algorithm processing unit output scheme:

[0221]

[0222] Step 3: Review and implementation of the program guidance unit

[0223] The doctor will display the plan in a pop-up window and confirm "I agree to execute" with voice;

[0224] The execution instruction generator sends instructions to the hardware:

[0225] Smart infusion pump:

[0226] Channel 1 is loaded with calcium gluconate, the speed is locked at 1ml / min, and the ECG monitor is forced to start;

[0227] After the infusion is completed, a window will automatically pop up to prompt the nurse to replace the tubing.

[0228] Nurse PDA:

[0229] It displays "Immediately administer 10g of sodium zirconium cyclosilicate orally and record gastrointestinal reactions";

[0230] After scanning the code to verify the medicine, the task will be automatically marked as completed.

[0231] Hemodialysis center receives instructions:

[0232] The system detects the patient's vascular access (the right internal jugular vein catheter is unobstructed) and automatically schedules a dialysis machine space 30 minutes later;

[0233] The green light on the hemodialysis machine control box lights up, and the dialysis fluid (potassium concentration 2.0mmol / L) is prepared.

[0234] Step 4: Dynamic monitoring unit real-time feedback

[0235] During calcium infusion:

[0236] The ECG monitor detected that the QRS wave width had returned to 100ms, and the system prompted "ECG improvement, continue monitoring";

[0237] If the QRS does not improve after 5 minutes of infusion, a repeat administration instruction (a second intravenous injection of 10 ml) will be automatically triggered.

[0238] Retest blood potassium 1 hour later:

[0239] The bedside monitor showed a blood potassium level of 6.2 mmol / L, and the system determined that the rate of descent was insufficient.

[0240] Dynamic monitoring unit update plan:

[0241] Increase insulin-glucose infusion (50% glucose 50ml + insulin 10U intravenous push); Step 5: Long-term management unit start

[0242] After the acute phase, the cause is systematically analyzed:

[0243] Main causes: unadjusted dose of RAAS inhibitor (valsartan) + high potassium diet (the patient reported eating bananas frequently recently);

[0244] Generate a long-term management plan:

[0245] Medication adjustment: Valsartan dose was reduced to 80 mg / d, and potassium binders were added;

[0246] Dietary control: The app pushes low-potassium recipes (bananas and oranges are prohibited, and apples and cabbage are recommended);

[0247] Monitoring reminder:

[0248] The home potassium meter is used for self-testing three times a week, and the data is automatically uploaded;

[0249] If the blood potassium level is >5.5mmol / L for two consecutive times, the APP will trigger a red alert and recommend an emergency reexamination.

[0250] Smart medicine box linkage:

[0251] Unlock valsartan and potassium ion binders at a fixed time every day;

[0252] If the patient misses a dose, the medicine box will flash red and send a reminder to the family member's mobile phone.

[0253] Summary: From the above examples, it can be seen that the system has built a full-process intelligent management solution for hyperkalemia. Its core advantages are reflected in five dimensions: first, it drives the standardized treatment process with guidelines, integrates international guidelines such as KDIGO and in-hospital pathways, and combines decision tree algorithms to implement mandatory constraints and dynamic priority sorting of key treatment steps (such as calcium infusion rate control and automatic triggering of dialysis indications) to ensure zero-error execution; secondly, it establishes a multi-parameter fusion early warning mechanism, links ECG and blood potassium monitoring to predict the risk of malignant arrhythmias, and introduces an adaptive adjustment algorithm to dynamically optimize treatment parameters (such as real-time control of dialysis ultrafiltration volume); thirdly, in terms of multi-department collaboration, it connects the hemodialysis center directly through the Internet of Things devices The heart and bedside CRRT equipment reduce dialysis preparation time by 66%. At the same time, the intelligent infusion pump forcibly locks the infusion speed, achieving a resource scheduling response within seconds. Fourth, an innovative full-cycle closed-loop management model covers the entire disease process, from emergency potassium reduction in the acute phase to etiology analysis in the chronic phase. Patients are equipped with smart medicine boxes, wearable devices, and mobile apps to achieve a closed-loop outpatient management, significantly reducing readmission rates by 60%. Finally, the hardware level adopts a modular design. The data detection unit supports the HL7 protocol for direct connection to the HIS system and completes AI data cleaning. The decision analysis unit outputs priority solutions, and the dynamic monitoring unit enables automatic adjustment of IoT devices. The overall architecture can be flexibly expanded to multiple scenarios such as diabetic nephropathy and heart failure with hyperkalemia. This system is not only a specialized management tool for hyperkalemia, but also forms a full-cycle medical decision-making platform for acute and chronic diseases, demonstrating its extended value in other acute disease areas.

[0254] The above are only a few preferred embodiments of the present invention, and their description is relatively specific and detailed, but it should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art may make various modifications and improvements without departing from the scope of the present invention, and such modifications and improvements are within the scope of protection of the present invention.

Claims

1. A treatment guidance system for patients with hyperkalemia, characterized in that: include: Data detection unit, used to obtain the target patient's medical history, symptoms, signs and test-related data; a decision analysis unit, configured to generate a corresponding first treatment plan based on the data acquired by the data detection unit and in combination with a rule library of a pre-stored treatment guideline; a plan guidance unit, configured to generate a second treatment plan based on the first treatment plan and in response to a review result of the first treatment plan by the review end, and send the second treatment plan to the execution end, wherein the second treatment plan is the same as or different from the first treatment plan; a dynamic monitoring unit, configured to respond to an instruction from the execution terminal and, based on the second treatment plan, remind and monitor the target patient's electrocardiogram, blood potassium, blood glucose, blood gas, urine volume, edema level, blood pressure, heart rate, and gastrointestinal reactions; The long-term management unit is used to respond to the instruction of the execution end and perform etiology tracing and long-term management on the target patient based on the data of the data detection unit.

2. The system according to claim 1, wherein: The data detection unit obtains the symptom-related data, including one or more of vital signs, positive symptom signs, and test results, by interconnecting with the hospital information system and the laboratory information system, and cleans and organizes the data to form structured data; The vital signs include body temperature, blood pressure, heart rate, and respiratory rate; the positive symptoms and signs include neuromuscular system manifestations, cardiovascular system manifestations, digestive system symptoms, and metabolic acidosis signs; the test results include blood potassium concentration, arterial blood gas analysis, and electrocardiogram characteristics.

3. The system according to claim 1, wherein: The first treatment plan generated by the decision analysis unit is determined based on at least one of the following: the patient's symptoms, physical examination results, test results, past medical history, and current medical history.

4. The system according to claim 1, wherein: The program guidance unit performs graded management based on the target patient's electrocardiogram abnormalities and the degree of elevated blood potassium, guides the use of antiarrhythmic drugs, and evaluates the indications for emergency dialysis.

5. The system according to claim 4, characterized in that The second treatment plan in the plan guidance unit includes at least one of the following: the time interval for monitoring blood potassium, the dosage and injection rate of insulin and glucose solution, the blood glucose monitoring time, the acid-base balance monitoring interval, the dosage and frequency of diuretics, the amount of bicarbonate supplementation, the frequency of electrocardiogram review, and the urine volume change threshold.

6. The system according to claim 1, wherein: The dynamic monitoring unit controls the target patient to receive treatment within a preset time based on the second treatment plan, and monitors changes in physiological indicators after treatment in real time.

7. The system according to claim 1, wherein: The system also includes a reminder unit for prompting the review end or the execution end to perform at least one of the following operations: monitoring the patient's blood pressure, heart rate, blood sugar, blood potassium and electrocardiogram, correcting acidosis, replacing the infusion bag, adjusting the fluid infusion rate, and recording the patient's urine volume.

8. The system according to claim 1, wherein: The system can automatically update the treatment plan based on the patient's real-time data and synchronize the updated plan to the doctor and nurse ends.

9. The system according to claim 1, wherein: The long-term management unit generates a personalized long-term management plan based on the etiology analysis of the target patient, including low-potassium diet recommendations, medication adjustment plans, and regular blood potassium monitoring reminders.

10. A device for guiding the treatment of patients with hyperkalemia, characterized in that: include: Data detection unit: used to obtain symptom-related data of target patients; This unit connects to the hospital's HIS system through the hospital's reserved interface, cleans and organizes the acquired patient hyperkalemia data to obtain structured data, and sends it to the decision analysis unit; Decision analysis unit: stores a rule base extracted based on various guidelines, expert consensus, etc., and is used to generate a corresponding first treatment plan based on the symptom-related data and compare it with the stored rule base; A plan guidance unit is configured to generate a second treatment plan based on the first treatment plan and in response to the review result of the first treatment plan by the review end, and then send the second treatment plan to the execution end, wherein the second treatment plan is the same as or different from the first treatment plan; Dynamic monitoring unit: used to respond to the instruction of the execution end and remind the monitoring of the target patient's electrocardiogram, blood potassium, blood sugar, blood gas, urine volume, edema degree, blood pressure, heart rate, and gastrointestinal reaction based on the second treatment plan; Long-term management unit: used to respond to instructions from the execution end and trace the cause of disease and conduct long-term management of target patients based on the data detection unit.

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